Build Great Backlinks has posted a new item, 'Handling User-Generated &
Manufacturer-Required Duplicate Content Across Large Numbers of URLs'
Posted by randfish
We know that Google tends to penalize duplicate content, especially when it's
something that's found in exactly the same form on thousands of URLs across the
web. So how, then, do we deal with things like product descriptions, when the
manufacturers require us to display things in exactly the same way as other
companies?
In today's Whiteboard Friday, Rand offers three ways for marketers to include
that content while minimizing the risk of a penalty.
Manufacturer-Required Duplicate Content Across Large Numbers of URLs -
Whiteboard Friday
For reference, here's a still of this week's whiteboard!
Video Transcription
Howdy Moz fans, and welcome to another edition of Whiteboard Friday. Today
I'm going to be chatting a little bit about a very specific particular problem
that a lot of e-commerce shops, travel kinds of websites, places that host
user-generated and user-review types of content experience with regards to
duplicate content.
So what happens, basically, is you get a page like this. I'm at BMO's Travel
Gadgets. It's a great website where I can pick up all sorts of travel supplies
and gear. The BMO camera 9000 is an interesting one because the camera's
manufacturer requires that all websites which display the camera contain a lot
of the same information. They want the manufacturer's description. They have
specific photographs that they'd like you to use of the product. They might even
have user reviews that come with those.
Because of this, a lot of the folks, a lot of the e-commerce sites who post
this content find that they're getting trapped in duplicate content filters.
Google is not identifying their content as being particularly unique. So they're
sort of getting relegated to the back of the index, not ranking particularly
well. They may even experience problems like Google Panda, which identifies a
lot of this content and says, "Gosh, we've seen this all over the web and
thousands of their pages, because they have thousands of products, are all
exactly the same as thousands of other websites' other products."
So the challenge becomes: How do they stay unique? How do they stand out from
this crowd, and how can they deal with these duplicate content issues?
Of course, this doesn't just apply to a travel gadget shop. It applies broadly
to the e-commerce category, but also to categories where content licensing
happens a lot. So you could imagine that user reviews of, for example, things
like rental properties or hotels or car rentals or flights or all sorts of
things related to many, many different kinds of verticals could have this same
type of issue.
But there are some ways around it. It's not a huge list of options, but there
are some. Number one, you can essentially say, "Hey, I'm going to create so much
unique content, all of this stuff that I've marked here in green. I'm going to
do some test results with the camera, different photographs. I'm going to do a
comparison between this one and other ones. I'm going to do some specs that
maybe aren't included by the manufacturer. I'll have my own BMO's editorial
review and maybe some reviews that come from BMO customers in particular." That
could work great in order to differentiate that page.
Some of the time you don't need that much unique content in order to be
considered valuable and unique enough to get out of a Panda problem or a
duplicate content issue. However, do be careful not to go way overboard with
this. I've seen a lot of SEOs do this where they essentially say, "Okay, you
know what? We're just going to hire some relatively low quality, cheap writers."
Maybe English isn't even their first language or the country of whatever country
you're trying to target, that language is not their first language, and they
write a lot of content that just all sits below the fold here. It's really
junky. It's not useful to anyone. The only reason they're doing it is to try and
get around a duplicate content filter. I definitely don't recommend this. Panda
is built even more to handle that type of problem than this one, from Google's
perspective anyway.
Number two, if you have some unique content, but you have a significant
amount of content that you know is duplicate and you feel is still useful to the
user, you want to put it on that page, you can use iframes to keep it kind of
out of the engine's index, or at least not associated with this particular URL.
If I've got this page here and I say, "Gosh, you know, I do want to put these
user reviews, but they're the same as a bunch of other places on the web, or
maybe they're duplicates of stuff that happened on other pages of my site." I'm
going to take this, and I'm going to build a little iframe, put it around here,
embed the iframe on the page, but that doesn't mean that this content is
perceived to be a part of this URL. It's coming from it's own separate URL,
maybe over here, and that can also work.
Number three, you can take content which is largely duplicative and apply
aggregation, visualization, or modifications to that duplicate content in order
to build something unique and valuable and new that can rank well. My favorite
example of this is what a lot of movie review sites, or review sites of all
kinds, like Metacritic and Rotten Tomatoes do, where they're essentially
aggregating up review data, and all of the snippets, all of the quotes are
coming from all of these different places on the web. So it's essentially a
bunch of different duplicates, but because they're the aggregator of all of
these unique, useful pieces of content and because they provide their own things
like a metascore or a Rotten Tomatoes rating, or an editorial review of their
own, it becomes something more. The combination of these duplicative pieces of
content becomes more than the sum of its parts, and Google recognizes that and
wants to keep it in their index.
These are all options. Then the last recommendation that I have is when
you're going through this process, especially if you have a large amount of
content that you're already launching with, start with those pages that matter
the most. So you could go down a list of the most popular items in your
database, the things that you know people are searching for the most, the things
that you know you have sold the most of or the internal searches have led to
those pages the most; great, start with those pages. Try and take care of them
from a uniqueness and value standpoint, and you can even, if you want,
especially if you're launching with a large amount of new content all at once,
you can take these duplicative pages and keep them out of the index until you've
gone through that modification process. Now you sort of go, "All right, this
week we got these 10 pages done. Boom, let's make them indexable. Then next week
we're going to do 20, and then the week after that we'll get faster. We'll do
50, 100, and soon we'll have our entire 10,000 product page catalog finish and
completed, all with unique, useful, valuable information that will get us into
Google's index and stop us from being considered duplicate content."
All right everyone, hope you've enjoyed this edition of Whiteboard Friday.
We'll see you again next week. Take care.
Video transcription by Speechpad.com
Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten
hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think
of it as your exclusive digest of stuff you don't have time to hunt down but
want to read!
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/rn_D_v8MLyA/handling-duplicate-content-across-large-numbers-of-urls
You received this e-mail because you asked to be notified when new updates are
posted.
Best regards,
Build Great Backlinks
peter.clarke@designed-for-success.com
Friday 31 January 2014
Thursday 30 January 2014
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Moz's 2013 Year in Review: More
Than You Ever Wanted to Know About Moz, and Then Even More'
Posted by SarahBird
Time for the 2013 end-of-year wrap-up. You can read Rand's 2012 wrap-up here.
The "T" in TAGFEE is for "Transparency," so let's get this show started.
This is a long post. Here are some convenient links to whatever tickles your
fancy:
Four Big Investments in 2013
Community & Customers
Inside Moz HQ
Technical Achievements
Looking Forward
If long-form blog posts aren't your thing, I invite you to check out our Moz
2013 Year In Review Infographic extravaganza!
Four Big Investments
1. The rebrand from SEOmoz to Moz
We'd been planning the rebrand from SEOmoz to Moz for about 18 months before
we executed. The original plan was to launch the rebrand simultaneously with the
release of Moz Analytics. Ah, yes. What a lovely dream!
When it became clear that Moz Analytics wasn't going to be ready before May,
we decided to decouple the rebrand from the product launch.
The rebrand went amazingly well. Better than we anticipated. Most people
weren't surprised, which I think is a good thing; we had been seeding the idea
of "Moz" for a long time. Recently, Search Engine Land released study results
indicating that Moz is the second-most recognized marketing technology brand.
Happily, 85% of people who listed us correctly used "Moz" instead of "SEOmoz."
Whoa!
We suffered a slight dip in traffic after the switch from seomoz.org to
moz.com, but managed to recover quickly. <high five> You can see our
traffic stats in the Community and Customers section below.
2. The epic nine-month launch of Moz Analytics
We began launching Moz Analytics in May and are only now wrapping up the final
phase of launch. Rebuilding the old PRO application from back to front was the
biggest and highest-risk endeavor we'd ever undertaken. Including product
planning, we worked on it for two+ years, and a team of engineers spent 18+
months building it.
The Moz Analytics launch deserves a thoughtful blog post on its own. I tried
to capture the complexity, disappointment, and excitement when drafting this
post, but it's just not possible.
So I'll just say this: Launch diverged dramatically from the plan. Some of it
was forgivable naivet© about the complexity of the project, and some of it
was just plain old stupid mistakes. All of the factors were valuable lessons.
I'm relieved and happy to say that we're wrapping up the "launch phase" of Moz
Analytics very soon. We've almost solved the the critical bugs, and soon we'll
be launching some critical features (like monthly timeframes) that weren't quite
critical enough to block public release.
3. Building data centers in Virginia, Washington, and Texas
We create a lot of our own data at Moz, and it takes a lot of computing power.
Over the years, we've spent many small fortunes at Amazon Web Services. It was
killing our margins and adding to product instability. Adding insult to injury,
we've found the service... lacking.
We spent part of 2012 and all of 2013 building a private cloud in Virginia,
Washington, and mostly Texas.
This was a big bet with over $4 million in capital lease obligations on the
line, and the good news is that it's starting to pay off. On a cash basis, we
spent $6.2 million at Amazon Web Services, and a mere $2.8 million on our own
data centers. The business impact is profound. We're spending less and have
improved reliability and efficiency.
Our gross profit margin had eroded to ~64%, and as of December, it's
approaching 74%. We're shooting for 80+%, and I know we'll get there in 2014.
4. Growing the Moz team
We ended the year with 134 people on the team. In 2013, we brought in 47 new
people, nearly a person each week. We also saw 16 people move on. That's a
tremendous amount of change and growth on top of a high-headcount growth year in
2012. It's invigorating and humbling when I think of the talent we've brought
together at Moz. Check out our Annual Report Infographic for lots fun extras on
the team.
Financial Performance
Revenue grew 33% last year and ended at $29.3 million.
That is off-plan performance. It could have been even worse. Quarters 1 and 2
were actually really strong, and in a subscription business, the year is made by
Q1 and Q2 net adds. In the second half of the year, though, we lost momentum
while in launch mode.
What happened? Many books will be written by many historians on what happened
at Moz in 2013. (Okay, maybe not.)
Here is a list of contributing factors, in no particular order (like I said,
this is really a much bigger topic than we can squeeze into this post):
Delayed launches of the rebrand and Moz Analytics (MA)
Customer unhappiness from some nasty bugs at launch
Customer unhappiness from some high-priority features not included at launch
Lower-quality leads than hoped through the invite list for MA
Compromised marketing funnel during the transition time from the legacy PRO app
to MA
Mismatch between marketing materials and launch offering
It feels really good to have this launch nearly behind us. I'm looking forward
to the next phase of the product development cycle: iterate, iterate, iterate.
And we'll take the lessons of this launch with us into all of our future
projects.
Our Cost of Goods Sold came in at approximately $10.8 million.
The vast majority of this spend is Amazon Web Services, listed here as "Cloud
Services" (see the section above on data centers for more context). While
building our data centers and moving our systems over, we paid for both the data
centers and Amazon. In 2014, we should see a substantial reduction in Cloud
Services because we'll have moved almost entirely off Amazon.
Our Gross Profit Margin for the year came in at 63% overall, but it was up to
70% and climbing in December. Data centers FTW!
For those of you curious about what we spend money on, feast your eyes:
I've included the expense as a percentage of revenue to better express how the
business scales. Notice the growth in Personnel (headcount- and
benefits-driven), Professional Contractors (the fleet to help us get Moz
Analytics out the door), Office Expenses (doubling our square footage means more
supplies and snacks!), and the arrival of the Data Center Depreciation line.
Yes, you're reading that right. The percentage of revenue is greater than 100%
when you add it up. We're not profitable this year. We're ending the year with a
$5,754,925 EBITDA loss (that's fancy accounting-speak for how much money was
left over after you paid the bills).
We knew we were going to burn in 2013. That's why we took the $18m Series B.
This is a bigger loss than we planned on, though, and we're disappointed we
missed our goals.
The good news is that we have enough capital to keep growing the business, and
we're really excited to have the hairy launch behind us and a clean platform on
which we can start iterating. We expect to be profitable in Q3 of this year.
Community & Customers
At the end of the year, over 25,000 people had Pro subscriptions.
Over 21,000 of those accounts are paying subscribers.
On the one hand, I'm disappointed because I don't think we met our potential.
We have the skills, resources and passion to build the best Inbound Marketing
Analytics software on the planet. We're on the path, but we're not there yet.
The whole team is picking up the pace. The destination keeps moving too, which
is part of the fun.
It was a pretty amazing year for web traffic. We're seeing a little dip here
at the end of the year, but we averaged 2.9 million uniques per month. Wow.
Our organic search traffic rose by 28% this year, even with the little hit we
took during the transition from SEOmoz.org to Moz.com.
Our community engagement metrics increased really nicely this year. (Thanks if
y'all are still reading this!) Also, people LOVE Whiteboard Friday. Can you
believe folks watched over 35,000 hours!?
Inside Moz HQ
I already mentioned the team growth in my Big Four above. What I didn't talk
about is how awesome it is to be a part of this team.
Can you believe that combined we donated over $100k to charity in 2013?!
Mozzers gave $41k+ to their favorite charities. Moz contributed $63k+ as part of
our 150% Moz Match program. That's an average of ~$783 per Mozzer.
I'm really proud of this number. It shows me that I work with people who
believe the world can be a better place and are willing to do something about
it. It excludes the time Mozzers have donated; We should start tracking that,
too.
The Annual Report has a complete list of the organizations we've helped.
It's hard to capture what it feels like to work at Moz. This list helps:
Technical Achievements
We've already talked about building Moz Analytics and the new data centers.
Those are major achievements, but they aren't the only things we've been busy
with. Au contraire.
Moz is an increasingly complicated business. We have loads of tools. Even if
you're a long-time Moz fan, I bet we have tools you've never seen. We've been
making investments in some of our key tools and the back-end infrastructure to
support complex web properties.
Launched Fresh Web Explorer in April 2013
We're really excited to offer a simple, high quality mentions-tracking tool.
This is one of our most powerful features, but is still a relatively hidden gem.
Do yourself a favor and go check it out. It's better than Google Alerts, and way
cheaper than enterprise-y mention trackers.
Relaunch GetListed in May 2013
We acquired GetListed in 2012 and did a complete back-to-front rebuild in
early 2013. The rebuild improved scalability, reliability, speed, and allowed
folks to log in to GetListed with their Moz accounts. The improvements laid the
groundwork for an upcoming launch that we can't wait to share with you! The new
release will be a major step forward in listing management.
Followerwonk Improvements
Check out Social Authority Score and our Partnership with Buffer.
Open Site Explorer Improvements
We added Just Discovered Links to Open Site Explorer in May 2013. We're
working hard to get you fresh link data. There will be more to come in 2014.
Sexy Behind-The-Scenes Stuff
Well, we think it's sexy. We rebuilt our billing system (rapture!), updated
our email management back-end (joy!), and created a unified authentication
system to tie all our different web properties together (hallelujah!).
Looking Forward
Things are starting to move fast around here, and that's a good thing. There
is a renewed sense of energy. Launch is behind us, and we can focus on bug
squashing, tuning, and adding some critical MA features like monthly timeframes,
a keyword-not-provided solution, and a content section. We're getting a little
bit closer each month to our goal of 80+% gross profit margin (GPM). The launch
of our Moz Local v.1 is in alpha testing as I write.
For the next several months the company is focused on (1) Increasing retention
by making happier customers, (2) Acquiring new customers by improving the funnel
and driving high-quality traffic to the site, (3) Getting to 80% GPM, and (4)
Launching and learning from our v.1 Local product.
Rand and I are settling into our new roles, and the whole team is starting to
rock a faster, more iterative approach to building software. We're also learning
our way around our brand spanking new digs. If you're in Seattle, you should
come say "hi."
Did I mention the Annual Report?
Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten
hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think
of it as your exclusive digest of stuff you don't have time to hunt down but
want to read!
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/dMJKWdOw49I/mozs-2013-year-in-review
You received this e-mail because you asked to be notified when new updates are
posted.
Best regards,
Build Great Backlinks
peter.clarke@designed-for-success.com
Than You Ever Wanted to Know About Moz, and Then Even More'
Posted by SarahBird
Time for the 2013 end-of-year wrap-up. You can read Rand's 2012 wrap-up here.
The "T" in TAGFEE is for "Transparency," so let's get this show started.
This is a long post. Here are some convenient links to whatever tickles your
fancy:
Four Big Investments in 2013
Community & Customers
Inside Moz HQ
Technical Achievements
Looking Forward
If long-form blog posts aren't your thing, I invite you to check out our Moz
2013 Year In Review Infographic extravaganza!
Four Big Investments
1. The rebrand from SEOmoz to Moz
We'd been planning the rebrand from SEOmoz to Moz for about 18 months before
we executed. The original plan was to launch the rebrand simultaneously with the
release of Moz Analytics. Ah, yes. What a lovely dream!
When it became clear that Moz Analytics wasn't going to be ready before May,
we decided to decouple the rebrand from the product launch.
The rebrand went amazingly well. Better than we anticipated. Most people
weren't surprised, which I think is a good thing; we had been seeding the idea
of "Moz" for a long time. Recently, Search Engine Land released study results
indicating that Moz is the second-most recognized marketing technology brand.
Happily, 85% of people who listed us correctly used "Moz" instead of "SEOmoz."
Whoa!
We suffered a slight dip in traffic after the switch from seomoz.org to
moz.com, but managed to recover quickly. <high five> You can see our
traffic stats in the Community and Customers section below.
2. The epic nine-month launch of Moz Analytics
We began launching Moz Analytics in May and are only now wrapping up the final
phase of launch. Rebuilding the old PRO application from back to front was the
biggest and highest-risk endeavor we'd ever undertaken. Including product
planning, we worked on it for two+ years, and a team of engineers spent 18+
months building it.
The Moz Analytics launch deserves a thoughtful blog post on its own. I tried
to capture the complexity, disappointment, and excitement when drafting this
post, but it's just not possible.
So I'll just say this: Launch diverged dramatically from the plan. Some of it
was forgivable naivet© about the complexity of the project, and some of it
was just plain old stupid mistakes. All of the factors were valuable lessons.
I'm relieved and happy to say that we're wrapping up the "launch phase" of Moz
Analytics very soon. We've almost solved the the critical bugs, and soon we'll
be launching some critical features (like monthly timeframes) that weren't quite
critical enough to block public release.
3. Building data centers in Virginia, Washington, and Texas
We create a lot of our own data at Moz, and it takes a lot of computing power.
Over the years, we've spent many small fortunes at Amazon Web Services. It was
killing our margins and adding to product instability. Adding insult to injury,
we've found the service... lacking.
We spent part of 2012 and all of 2013 building a private cloud in Virginia,
Washington, and mostly Texas.
This was a big bet with over $4 million in capital lease obligations on the
line, and the good news is that it's starting to pay off. On a cash basis, we
spent $6.2 million at Amazon Web Services, and a mere $2.8 million on our own
data centers. The business impact is profound. We're spending less and have
improved reliability and efficiency.
Our gross profit margin had eroded to ~64%, and as of December, it's
approaching 74%. We're shooting for 80+%, and I know we'll get there in 2014.
4. Growing the Moz team
We ended the year with 134 people on the team. In 2013, we brought in 47 new
people, nearly a person each week. We also saw 16 people move on. That's a
tremendous amount of change and growth on top of a high-headcount growth year in
2012. It's invigorating and humbling when I think of the talent we've brought
together at Moz. Check out our Annual Report Infographic for lots fun extras on
the team.
Financial Performance
Revenue grew 33% last year and ended at $29.3 million.
That is off-plan performance. It could have been even worse. Quarters 1 and 2
were actually really strong, and in a subscription business, the year is made by
Q1 and Q2 net adds. In the second half of the year, though, we lost momentum
while in launch mode.
What happened? Many books will be written by many historians on what happened
at Moz in 2013. (Okay, maybe not.)
Here is a list of contributing factors, in no particular order (like I said,
this is really a much bigger topic than we can squeeze into this post):
Delayed launches of the rebrand and Moz Analytics (MA)
Customer unhappiness from some nasty bugs at launch
Customer unhappiness from some high-priority features not included at launch
Lower-quality leads than hoped through the invite list for MA
Compromised marketing funnel during the transition time from the legacy PRO app
to MA
Mismatch between marketing materials and launch offering
It feels really good to have this launch nearly behind us. I'm looking forward
to the next phase of the product development cycle: iterate, iterate, iterate.
And we'll take the lessons of this launch with us into all of our future
projects.
Our Cost of Goods Sold came in at approximately $10.8 million.
The vast majority of this spend is Amazon Web Services, listed here as "Cloud
Services" (see the section above on data centers for more context). While
building our data centers and moving our systems over, we paid for both the data
centers and Amazon. In 2014, we should see a substantial reduction in Cloud
Services because we'll have moved almost entirely off Amazon.
Our Gross Profit Margin for the year came in at 63% overall, but it was up to
70% and climbing in December. Data centers FTW!
For those of you curious about what we spend money on, feast your eyes:
I've included the expense as a percentage of revenue to better express how the
business scales. Notice the growth in Personnel (headcount- and
benefits-driven), Professional Contractors (the fleet to help us get Moz
Analytics out the door), Office Expenses (doubling our square footage means more
supplies and snacks!), and the arrival of the Data Center Depreciation line.
Yes, you're reading that right. The percentage of revenue is greater than 100%
when you add it up. We're not profitable this year. We're ending the year with a
$5,754,925 EBITDA loss (that's fancy accounting-speak for how much money was
left over after you paid the bills).
We knew we were going to burn in 2013. That's why we took the $18m Series B.
This is a bigger loss than we planned on, though, and we're disappointed we
missed our goals.
The good news is that we have enough capital to keep growing the business, and
we're really excited to have the hairy launch behind us and a clean platform on
which we can start iterating. We expect to be profitable in Q3 of this year.
Community & Customers
At the end of the year, over 25,000 people had Pro subscriptions.
Over 21,000 of those accounts are paying subscribers.
On the one hand, I'm disappointed because I don't think we met our potential.
We have the skills, resources and passion to build the best Inbound Marketing
Analytics software on the planet. We're on the path, but we're not there yet.
The whole team is picking up the pace. The destination keeps moving too, which
is part of the fun.
It was a pretty amazing year for web traffic. We're seeing a little dip here
at the end of the year, but we averaged 2.9 million uniques per month. Wow.
Our organic search traffic rose by 28% this year, even with the little hit we
took during the transition from SEOmoz.org to Moz.com.
Our community engagement metrics increased really nicely this year. (Thanks if
y'all are still reading this!) Also, people LOVE Whiteboard Friday. Can you
believe folks watched over 35,000 hours!?
Inside Moz HQ
I already mentioned the team growth in my Big Four above. What I didn't talk
about is how awesome it is to be a part of this team.
Can you believe that combined we donated over $100k to charity in 2013?!
Mozzers gave $41k+ to their favorite charities. Moz contributed $63k+ as part of
our 150% Moz Match program. That's an average of ~$783 per Mozzer.
I'm really proud of this number. It shows me that I work with people who
believe the world can be a better place and are willing to do something about
it. It excludes the time Mozzers have donated; We should start tracking that,
too.
The Annual Report has a complete list of the organizations we've helped.
It's hard to capture what it feels like to work at Moz. This list helps:
Technical Achievements
We've already talked about building Moz Analytics and the new data centers.
Those are major achievements, but they aren't the only things we've been busy
with. Au contraire.
Moz is an increasingly complicated business. We have loads of tools. Even if
you're a long-time Moz fan, I bet we have tools you've never seen. We've been
making investments in some of our key tools and the back-end infrastructure to
support complex web properties.
Launched Fresh Web Explorer in April 2013
We're really excited to offer a simple, high quality mentions-tracking tool.
This is one of our most powerful features, but is still a relatively hidden gem.
Do yourself a favor and go check it out. It's better than Google Alerts, and way
cheaper than enterprise-y mention trackers.
Relaunch GetListed in May 2013
We acquired GetListed in 2012 and did a complete back-to-front rebuild in
early 2013. The rebuild improved scalability, reliability, speed, and allowed
folks to log in to GetListed with their Moz accounts. The improvements laid the
groundwork for an upcoming launch that we can't wait to share with you! The new
release will be a major step forward in listing management.
Followerwonk Improvements
Check out Social Authority Score and our Partnership with Buffer.
Open Site Explorer Improvements
We added Just Discovered Links to Open Site Explorer in May 2013. We're
working hard to get you fresh link data. There will be more to come in 2014.
Sexy Behind-The-Scenes Stuff
Well, we think it's sexy. We rebuilt our billing system (rapture!), updated
our email management back-end (joy!), and created a unified authentication
system to tie all our different web properties together (hallelujah!).
Looking Forward
Things are starting to move fast around here, and that's a good thing. There
is a renewed sense of energy. Launch is behind us, and we can focus on bug
squashing, tuning, and adding some critical MA features like monthly timeframes,
a keyword-not-provided solution, and a content section. We're getting a little
bit closer each month to our goal of 80+% gross profit margin (GPM). The launch
of our Moz Local v.1 is in alpha testing as I write.
For the next several months the company is focused on (1) Increasing retention
by making happier customers, (2) Acquiring new customers by improving the funnel
and driving high-quality traffic to the site, (3) Getting to 80% GPM, and (4)
Launching and learning from our v.1 Local product.
Rand and I are settling into our new roles, and the whole team is starting to
rock a faster, more iterative approach to building software. We're also learning
our way around our brand spanking new digs. If you're in Seattle, you should
come say "hi."
Did I mention the Annual Report?
Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten
hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think
of it as your exclusive digest of stuff you don't have time to hunt down but
want to read!
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/dMJKWdOw49I/mozs-2013-year-in-review
You received this e-mail because you asked to be notified when new updates are
posted.
Best regards,
Build Great Backlinks
peter.clarke@designed-for-success.com
Wednesday 29 January 2014
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Personas: The Art and Science of
Understanding the Person Behind the Visit'
Posted by iPullRank
Market segmentation is a basic tenet of marketing that has long been ignored
by SEOs. And that's okay, because for a long time working on the keyword-level
of abstraction was enough. In fact, you can still do SEO and marketing in any
other channel without ever having the idea of market segmentation cross your
mind despite (not provided), Hummingbird, and a whole host of changes Google is
forcing as of late.
That isâ if you enjoy 0.04% conversion rates. Right.
There have been many posts about personas in the wake of the methods I've
popularized for SEO, but nothing that truly walks through the process with data
or gives context into how measurement has matured. In this post I'll go into
detail about these approaches, giving frameworks and step-by-step instructions
on how to build and use personas.
There's something in this post for everyone from beginners to advanced
marketers. I feel that it's important to give context to the discussion to
clarify why developing and using data-driven personas is critical to the future
of search and digital marketing in general. Use this table of contents as a way
to navigate to precisely what you want to know. You'll also find "Back to table
of contents" links at the end of every section.
Waitâwhat are personas?
What is the difference between segments, cohorts, and personas?
Segments
Cohorts
Personas
Google is pushing all channels in this direction
Affinity segments/categories
Building personas
Layering data
Qualitative research
Quantitative research
Building Mozzy Smurf
User journeys
Use cases
Further applications
Frequently asked questions
Resources
First, personas are a method of market segmentation wherein we collect a
combination of qualitative and quantitative data to build archetypes of the
members of our target audience. In other words we take data to tell a predictive
story about our users based on past behaviors and attributes.
I mentioned keywords as a level of "abstraction;" Google has obscured that
type of abstraction with (not provided), taking an otherwise perfect
direct-response dataset and turning up the opacity. Nonetheless, it was always a
representation of a person taking an action to fulfill a need. However, that
abstraction removed us completely from those people and placed our focus clearly
on the keyword and the Boolean idea of whether or not their visit on that
keyword led to the completion of a task.
If the keyword-level of abstraction is a stick figure a persona is an action
figure.
Over the past few years I've built methodologies in a land of marketing make
believe to develop personas and apply them to the intersection of Search and
Social Media helping us understand the person behind the search. Much like the
cartoons that action figures are modeled after personas have a set of attributes
that they are to (ahem) personify. Dictated by the business goals and the data
that can be collected and analyzed these attributes are typically a picture,
demographics, psychographics, user needs and a user story, but can be as
in-depth or as vague as you want - as long it's actionable. For example, some
people like to give each persona a "quote" that sums them up. Personas also come
with a user journey which is a collection of steps a user takes in fulfilling
those needs.
Ultimately, though, you're trying to tell the most actionable story with your
data. Think of it as another layer to your analytics. The most important layer.
The people layer.
People often ask me why they need to use personas. In my previous role of
selling SEO services to people that talk about SEO and marketing as separate
things I've experienced a lot of pushback. Fortunately there were far more
instances where a CMO or VP was in the room and speaking in terms of segments
and market opportunity rather than just keywords, meta tags and guest posts
helped us win the business.
But I digress.
One of the main reasons for using personas is that when you target everyone
you actually target no one. The art of segmentation is about narrowing your
focus in on people in the market more likely to become your users/customers so
you can better serve them. This applies not only to your product and/or service,
but your content as well.
Donald A. Norman of the Nielsen Norman Group explained it best when he
declared "A major virtue of personas is the establishment of empathy and
understanding the individual who uses the product."
In the Content Strategy world one of the major concepts they push is
"empathy." How can we understand and then fight for the user to create the best
possible content experience to fulfill their needs? Not just the right words,
but the right structure, the right metadata, the right presentation.
User Experience professionals use that idea of empathy with personas to plan
and build things that work for the target audience. For example, if our audience
is people over 50 then it may make sense to design a site with the larger text.
In the world of marketing this is all a means to specific end of course, but
ultimately we just want to know who we're talking to so we can improve our rate
of persuasion - or conversion.
Organic Search as a marketing channel is about just that - persuading people
who have a specific intent to believe you can fulfill their needs. Building
personas allows you to speak directly to their needs from as early as the page
title and meta description. This applies to not only your product and/or
service, but your content as well.
Back to table of contents
The terms are often used interchangeably, but they can mean slightly different
things. All of these concepts are abstractions of people, but the basic
difference between the three lies in their specificity. A segment is the
broadest concept of a person while a persona is the most specific snapshot of a
user archetype.
For the purposes of this discussion the Smurfs will act as a way to make these
ideas a little more real (whoa, meta). I tried to get G.I. Joe, but, they were
busy fighting wars and stuffâ yeah, anywayâ
Segments
Segments are groupings of similar entities. You can (and should) quite
literally segment by any set of rules in your data as I've discussed in my last
Moz post. On the cartoon the Smurfs you had humans, animals and Smurfs. Each of
those could be a segment. You could segment just the Smurfs themselves by color
of their mushroom homes. You can segment them based on things that happened on
the show. Two segments could be "Those that Gargamel Has Captured" and "Those
that Gargamel Has Not Captured." You could segment by where they live in the
Village. North Smurfs, West Smurfs, Southeast Smurfs. You could sub-segment any
of these groups with any granularity that you see fit or combine criteria just
like you would with standard clickstream data in Google Analytics.
The point is, although you can segment by anything you can track, will it be
actionable? Popular actionable segments that are used every day are geographic,
behavioral, seasonal, and benefit segments.
Nielsen PRIZM is a popular market segmentation system that is based on zip
codes where people are chunked into subsets regarding their location, income and
behavior. Nielsen builds this system on top of US Census data and sends out
surveys to a large sample of people to create 66 segments throughout the United
States. Experian Simmons is similar, and maybe more interesting to inbound
marketers with its connection to Hitwise, but Google has recently brought
segmentation purely online and has the potential to supplant them all. More on
that later.
Cohorts
Cohorts are groupings based on similar experience. Common vernacular for
cohorts would be generations. In the Smurf Village you had three generations of
Smurfs. The baby Smurfs (which for whatever reason had the only other female
Smurf). Let's call them Generation Next. You had the adult Smurfs like Jokey,
Vanity, Brainy, and Smurfette's cohort. Let's call them Generation Now. A cohort
that walked around believing shirts were optional.
And you had Papa Smurf and a few of his buddies. Let's call them the Elder
Smurfs.
Obviously, each individual in any of these groups is different from the next,
but they are grouped by their shared temporally attitudes, cultural interests
(ex. fashion sense, music), and life experiences (Gargamel captures, first
appearance of Smurfette).
In the real world we have Baby Boomers, Generation X, and the ever elusive
Millenials. Baby Boomers were a generation defined in the post-World War II era
of increasing affluence, Civil Rights movements and the death of JFK. Generation
X was a people defined by rebellion, MTV, baggy pants, the dot Com Bubble, the
rise of Grunge, Microsoft, and the death of Kurt Cobain. Millenials are defined
by 9/11, job-hopping, Apple, Google, Facebook, free music, nerd glasses, tight
jeans, everybody having a startup and the death of Michael Jackson.
Right now every big product-driven company is asking how do we get Millenials
to care about us?
Personas
Personas are specific archetypes of people in the target audience. The
attributes identified across the group are collected to give birth to a single
entity that represents these users. A persona has a descriptive name and is
meant to be thought of like someone that actually exists. They are generally a
composite of people that do exist.
In this case we will use individual Smurfs themselves as our personas. While
some people in the 80s viewed the cartoon as communist it can also be seen as an
exercise in behavioral segmentation. Each character was clearly differentiated
by what they specifically did or how they acted within the Smurf Village.
You had Brainy Smurf, the original hipster. He's a bit of an introvert and
likely to be found at a Barnes & Noble sipping a macchiatto latte and discussing
Sartre, injecting barbs of sardonic wit. He spends a lot of time updating his
blog, and he's a freelance copywriter for a multinational ad agency, but he only
shops at the mall. Brainy prefers Facebook over Twitter as he would rather have
a long-form discussion where he can definitively disprove what you believe. He
listens to NPR and of course is a Mac rather than a PC.
You had Smurfette. Well, you had two Smurfettes, each of which could be a
persona.
The first Smurfette was a tom boy who just wanted to hang with the homies.
After all she was created by Gargamel as a way to distract and trap the Smurfs.
She shopped at second hand stores before it was in style. No, really.
Old Smurfette goes to open mics and loves to be around music. She enjoys
vintage vinyl records and playing with her rescue cat. The Old Smurfette is a
bit of a couch surfer who frequents SmurfBNB and eats at Baker Smurf's
restaurant rather than the big chains. You guessed it; Old Smurfette is a
persona based on the female hipster Millenial cohort.
Later, after Papa Smurf turned her into a real Smurf she got all high-end
fashion on us, dying her hair blonde, wearing Diane von Smurfstenburg dresses
and Christian Smurfboutin shoes. She's more likely to be found at high-end
establishments, but only goes out when invited. Smurfette would rather be
shopping than go to a music night spot. She's all about convenience over
supporting her local community. Smurfette likes to see and be seen.
Then you had Jokey Smurf. His persona name would probably be Terrorist Tom
because he loves to hand people presents that explode. In the context of
marketing Jokey is the type of user who loves extreme sports, sites like
Break.com, and the type of content that Red Bull creates. He's highly likely to
buy Ed Hardy clothing. Only the jeans, though, because males in his cohort don't
wear shirts. Jokey loves craft beer, Xbox One and action movies.
In the above cases I've taken what I know about the millennial cohort and
layered it into a story about the different Smurf characters based on things
that could be observed on the show. As marketers building personas we do this
with regard to the context of our marketing programs. That is to say we focus on
elements of the story that is relevant to our goals rather than including every
data point we can find.
A key distinction to be made in the context of inbound marketing programs is
that between the buyer person and the audience persona. The audience persona is
typically someone looking to consume content for education or entertainment.
These people are not actively looking to purchase a good or service and are
better measured via KPIs having to do with the spread or the building of
authority for that content or the building of community.
Conversely, buyer personas may also be looking to consume content, but only as
a means to make the specific transaction to support their needs. There is
frequently overlap between the two types of personas and a given user can also
transition between the two types. Keep this in mind as you develop your
personas.
Once this in-depth profile of the audience is created smart marketers ask
questions and take actions with regard to how these personas would best be
served to meet the business objective.
At Amazon, Jeff Bezos leaves a chair empty at meetings to signify the customer
persona is in the room listening to the decisions they are making. At Experian
they have developed the character and placed her on banners throughout the
office and in the company newsletter to keep the customer top of mind. When I
worked on LG they sent a poster of their home appliances persona Wendy and she
came up often in our strategy meetings. At AirBNB they have a section of the
office with the personas in storyboards on the wall along with illustrations of
those of personas going through the user journey.
No matter what method you use, it is important to keep the consumer, customer,
user at the center of the marketing initiative. Don't just build personas and
forget they exist.
Back to table of contents
"Why should I care," you say? Well for some time I have touted this idea of
the intersection of search and social media to take intent to match it up with
the person. This and some of Google's actions towards the end of 2011 (remember
the consolidation of the privacy policies ?) led me into the idea that they
are using G+ to model users to apply a sliding scale of authority based on
topical relevance for better search quality and to provide the Holy Grail of
advertising opportunities. In fact I believed the whole purpose was modeling
beyond the keyword to make every dollar worth a lot more by marrying multiple
data sets. It turns out this is exactly where Google wants to go with their
marketing products and I'm basically just ahead of my time. ;]
Ian Lurie has also been talking about this extensively for the past few years
as well through a concept he calls "random affinities" which is similar to
something I was (perhaps mistakenly) calling "co-relevance" when I built a tool
for getting ahead of search demand with social media.
Forgive the quality of these screenshots, but in a recent video from Google
featuring Forrester Research's VP/Principal Analyst Nate Elliot they discussed
the concept of affinity and market segmentation. What he describes as Smart
Affinity is what a methodology like Keyword-Level Demographics is looking to
harness. This is a capability that marketers in general have yet to embrace
because it's simply too complicated for most. Google is taking us there kicking
and screaming.
Diya Jolly from Google gives some of the insight into why Google is obviously
the best suited for the job in her discussion of the data signals available
across the Google ecosystem. The amount of data combined with the sample size
allows Google to have probably the most robust and accurate model of user
behavior which potentially render other modes of advertising and market research
nearly obsolete or at least less effective.
I dug a little deeper into the process and found the "Inferring User
Interests" patent where they discuss more in-depth how they figure out user
interests. For example:
"In the situation where a first user lacks information in his profile,
profiles of other users that are related to the first user can be used to
generate online ads for display with the first user's profile. For example, a
first user Isaac may not have any information in his profile except that he has
two friends-Jacob and Esau. The server system 104 can use information from Jacob
and Esau's profiles to infer information for Isaac's profile. The inferred
information can be used to generate online ads that are displayed when Isaac's
profile is viewed."
How's the saying go? When it's free, you're the product.
Affinity segments/categories
All the data we give Google for free has allowed them to roll out this new
Affinity Segments product which is Google's own new segmentation system.
In their own words :
"We use the main topics and themes from the page as well as data from
third-party companies to associate interests with a visitor's anonymous cookie
ID, taking into account how often people visit sites of those categories, among
other factors.
Google may use information that people provide to these partner websites about
their gender, age, and other demographic or interest information. We may also
use the websites people visit and third-party data to infer this information.
For example, if the sites a person visits have a majority of female visitors
(based on aggregated survey data on site visitation), we may associate the
person's cookie with the female demographic category."
In typical Google fashion, aside from the video and a few articles in the
Adwords Support site, the detailed information about these segments is pretty
sparse. Luckily, I was able to get my hands on a deck with short user stories
and targeting ideas for each segment. I'm sure your Adwords account manager
would be able to furnish something like the below if you asked them nicely.
Affinity Segments is the broad name for these targeting types, but in practice
Google offers "Affinity Categories," "In-market Buyers," and "Other Categories"
as targeting types in AdWords. Affinity Segments are users in a broad sense,
In-market segments are people that are actively looking to purchase and other
categories are a variety of things. You're likely to see other categories the
most if you're not in the US.
I appreciate that Google makes the distinction between "Affinity Categories"
and "In-market Buyers" as this directly mirrors the approach I take in creating
both "Audience Personas" and "Buyer Personas." More on that later.
As an end user you can see which demographics and interests Google has
associated with you in your Ad Settings. You can also opt-out or change your
features as seen below.
However, the most important point for this persona discussion is that you can
now measure everything in Google Analytics based on these segments.
Let that sink in for a second. Google has Google+ as an "identity platform"
which is pretty much a front end for data collection and modeling of people.
They have Google Consumer Surveys so marketers can poll the audience and I
imagine at some point you'll be able to ask questions by affinity segment. And
now you have Google Analytics showing website actions in context of those
affinity segments. Google has just set itself up to disrupt the entire market
research industry with end to end people modeling. If that doesn't sell you at
least on the power of segmentation nothing will. This is completely
unprecedented.
Back to table of contents
Ok, enough with the background; let's get you building personas. There are
many methods for developing personas and I will discuss several of them, but you
should choose your approach based on the data and resources at your disposal.
Again, what we will be doing is collecting data, segmenting it and telling a
story about that segment. First I'll outline different processes then we'll walk
through the creation of a persona for Moz leveraging data from the scraping
post, Twtrland, Followerwonk,the community Q&A forum, and feature requests.
In my experience a combination of approaches yields the best personas.
Otherwise you'll end up relying too much on your own assumptions. Also I
typically build four personas with Googlebot, which AJ Kohn has aptly named the
Blind Five Year Old, acting as the fifth, but you can build as many as you see
fit.
Layering data
If you've seen me speak in the past year or so you've probably seen this
image. When I was at my previous agency my market research lead Norris Rowley
and I developed a methodology wherein we layered data from Nielsen Prizm and
Experian Simmons to collect data on segments at scale.
When I say layering I mean that we look for commonality between datasets and
if there is enough commonality or overlap we consider all features potentially
valid for sub-segments. That is to say if enough attributes of a Prizm Code and
a MOSAIC Type are shared we consider any data in one to be potentially valid for
the other and we applied this approach across all the available datasets.
Whether or not that is scientifically sound can be debated, but remember that
personas are hypotheses that will ultimately be validated or invalidated through
measurement.
Since the Prizm and Simmons surveys deal mostly in offline behaviors we'd plug
those data points into Social PPC inventories (Facebook Ads, Twitter Ads,
LinkedIn Ads) to ensure that those segments were valid online. If they proved to
be valid then we'd take that segment and build a persona.
I still believe this to be a solid approach especially if you can leverage
this data in context with some of Simmons' other products measure online usage
behavior as well as Google's Affinity Segments.
No matter which method you use you should start by determining the business
objectives which will then help to determine the goals of your research. Then
define how these personas will be used. Are you just looking to focus on your
buyer personas or will you be thinking about audience personas as well?
Qualitative research
With Qualitative Research you're asking open-ended questions to small sample
sizes to get a sense of the "how"s and the "why"s behind a specific problem.
You're typically looking at unstructured data to inform commonality amongst your
user group and any insights are then validated for scale throughout quantitative
research processes. Qualitative research within our context is often user
interviews, focus groups, content analysis, text-mining, ethnography and
affinity mapping.
(image source)
Affinity mapping / affinity diagramming
When most people think of a persona-building exercise they think of this.
Affinity mapping or affinity diagramming is the process of collecting everyone's
thoughts and segmenting them into meaningful groups. In the context of personas
this is typically done in a several hour session of everyone writing their ideas
of their customers on post-it notes with Sharpies, discussing them as a team and
then grouping them.
This process is great for putting the consumer back in focus for the team and
also for getting executive buy-in. However it's mostly based on assumptions so I
would not suggest doing only this when building personas as your research may be
attacked and biased by HIPPOs.
When you do this you want to get all the key stakeholders involved, especially
the upper management team but most importantly the people that deal with your
customers or users on a regular basis like your Sales or Help teams. The former
helps with internal adoption. The latter helps get closest to the right answer.
Many people building personas stop here to save time and resources, but when you
do these profiles are typically known as "proto-personas."
Affinity Mapping is typically done in the following 90 minute rounds:
Assumption round one (Needs) - Each person spends 5-20 minutes jotting down a
goal, activity, need, or problem for any user. This is to be exclusive of any
attributes of the user, rather it's about what the user is trying to accomplish.
An example assumption could be "User needing to make a confident decision on
which LSAT prep course to enroll in."
Once everyone has comfortably collected their ideas you go around the room and
each person introduces one of their post-its. The entire team weighs in on how
valid they believe the assumption to be. Those that are valid are placed on the
board. Those that are not are discarded. You continue until all post-its are on
the boards or in the trash. Throughout the process groups start to emerge as
assumptions begin to fit together. You can give the groups names if you'd like,
but at this point it's not that important as names can be given later in the
analysis phase.
Assumption Round Two (Attributes) - Each person again spends 5-20 minutes
jotting down information about the target audience, but this time they present
attributes of the user groupings from the first round. Again, you'll go around
the room and everyone will share and discuss their assumptions. The ones that
the group agrees are valid will then get added to the wall.
To continue the example from above an assumption could be "College graduate
25-34 who is unhappy with their career." Starting with the needs in the first
round helps to really zero on the demographics and psychographics of the people
in this round. If you go the other way around the parameters of the people may
be too broad.
Factoid Round - The final round of the exercise involves everyone in the group
spending 15-30 minutes finding data points to back up the groups of assumptions.
This data can come from any number of other relevant sources including
analytics, sales data, internal and external research. Again, the team discusses
the data points and decides their validity and adds it them to the groups.
An example fact could be "20% of all signups for our LSAT prep course
graduated college 4-11 years ago and reported in their registration that they
want to make more money."
The factoid round helps perfect the user story based on quantifiable realities
instead of just assumptions. It also allows you to potentially dump segments if
there's no data to back them up.ProTip: Although it sounds like a daunting
procedure that requires in-person interaction it can be done very effectively
remote by using Mural.ly and Google+ Hangouts.
The screenshot above is from a recent session I did with a startup called
Trip.Me in Berlin. We got members of the marketing team, the CEO and the
Operations team together on G+. We color-coded each round of assumptions and
factoids with the virtual post-it notes and then the tool makes it easy to bring
in links and content that supports any assumptions anyone on the team had. The
Google+ effects made it a fun time for all.
Build Personas - At this point you have all the data to build out the skeletal
personas. Your goal should be to whittle all of these insights into 3-5
actionable personas. While you can make as many as you'd like, it's difficult
for teams to stay mindful of too many. We'll go into more of how to formulate
stories based on the data when I actually walk through the process, but at this
point that is what you'll do.
These are often referred to as skeletons or proto-personas because they don't
have direct user research or a large wealth of quantitative data behind them.
However for many people this is just fine because the team may be most invested
in this type of persona, and that will help with adoption.
Focus groups
Focus groups are formal meetings with people of the target segment wherein a
moderator asks research questions to understand users and their needs. I've
personally never run one of these, but the ones that clients have conducted and
shared with us have made useful inputs in the creation of personas. They help
with determining questions and need states of users. However I often find that
moderators lead the group on some of the questions thereby invalidating their
responses to draw bias conclusions.
The quality of the output from a focus group has entirely to do with the
experience and biases of the moderator, the quality of the questions, and most
importantly the selection and attentiveness of the panelists. Another thing to
be leery of is the dominance of one opinion in group settings as people are
often swayed by the loudest participant. Furthermore the incentive the people
set for being involved may be their only reason to participate and they won't
give thoughtful answers.
We're about halfway through the post so I encourage you to take a break and
watch Conan O'Brien go undercover and moderate a focus group about himself:
User/customer interviews
These are similar to focus groups except they involve a one-on-one or small
one-on-two group environment where you directly speak to a user or customer. For
design, products or CRO this can be usability testing and eye-tracking or it can
just be direct Q&A as in the case of personas. All of the insights on how
customers user the product can be valuable to both the personas and the
determining the user journey.
Ethnographic research
Ad-Hoc data collection is what I've been calling the method of using social
listening, forum searches and keyword research to build personas , but I've
come to learn that research such as this when you watch users act in their
natural habitats is called "ethnography" or when it's on the web "netnography."
This is a great way to build personas when you have few resources because you
can easily identify online communities or watch hashtags and specific
representatives of your users on Twitter. Great tools for this include Topsy,
Sysomos, Radian6, Google Discussion Search, Keyword Planner, and the Display
Planner, Twtrland and Followerwonk.
The Display Planner, Quantcast, Compete, Twtrland and Followerwonk will all
give you demographic data that helps you frame your personas. Where Twtrland
bests Followerwonk is in its ability to infer interests from tweets and not just
user bios. The Keyword Planner gives you the keywords associated with the site
for use as the vocabulary to find your users in discussion search and eavesdrop
on their conversations with Social Listening tools like R6, Topsy and Sysomos.
Naturally, you'll need to do several iterations of looking at keywords and
conversations to identify trends across your users. You can also uses sites like
Quora and Reddit by going as far as to pose questions to kickstart the
conversation.
While the screenshot above is a good framework to work within there's no
defined structure to ethnographic research. You'll have to judge for yourself
when you feel your research questions have been answered. However you should
generally expect to do the following:
Collect examples of what you see users doing in their natural environments
called "field notes"
Analyze notes to discover new questions and reiterate
Look for shared patterns of belief, language and behavior
Write the ethnography which in this case is the persona
Ethnographic research is both the easiest and hardest of approaches because it
just requires observation, but the approach is completely subjective so it's
hard to convince people that the insights should stick in and of themselves
without quantitative research to back it up.
Quantitative research
If you're reading Moz you're probably a data-driven marketer so this end of
the research spectrum will appeal to your sensibilities. Quantitative research
is about using numbers and statistics to understand behaviors of users
empirically. The sample sizes are often quite large so that the insights can be
applied to broad populations of people.
Multiple-choice surveys
Polling your target audience allows you to ask precise questions. There are
many options for this, but I prefer SurveyMonkey Audience for this type of work
simply due to the fact that they collect of demographic data explicitly from
users while Google has is inferring it from user behavior. Survio is also a good
choice for surveying non-US markets. Survey Design is a science in itself and
SurveyMonkey has great resources on it , but the key thing to note here is that
at this point you want your surveys to not be exploratory or open-ended in
nature. You want your surveys to give users well-defined choices that you've
defined based on your qualitative research. The results will need to be
cross-tabbed until insights are wrangled out and personas begin to appear.
Market segmentation tools
As I mentioned before Experian Simmons, Nielsen as well as tools like MRI and
ComScore provide market segmentation based on surveyed panels and usage data.
These tools are incredibly helpful with scaling the persona building process by
providing prebuilt segments as well as a wealth of data in context of those
segments.
These tools fail when there if a specific question has not been included.
These providers are eager to take feedback and insights to add to their
quarterly surveys, but even when they do you are at least 3 months away from
seeing your questions answered and input into the system.
Analytics
Even without demographic tracking your analytics can have a wealth of
knowledge especially internal search, paid search and historical organic search
keywords in context of site actions. Also looking at location demographic data
as well as the times your users are visiting can be helpful determinations of
their attributes. Really what you can pull from analytics is completely
dependent upon your setup.
User profiles
If your site has user profiles, especially those that have collected data from
Social logins or other identity data providers there is a wealth of data that
users have explicitly set.
Internal data
Data on sales, calls, returns, reviews, users and transactions of all types
can be leveraged to give parameters and color during the persona development
process.
Publicly available studies
Every industry has public research and data that can be leveraged when
building personas. For example Google has the Consumer Barometer where you can
pull various data points.
I tend to use a combination of these approaches in my persona building
depending on what resources are available. In my client work experience I've
found it best to start with an affinity mapping session and then to prove or
disprove those assumptions and gain additional insights with data from the other
sources.
Back to table of contents
For this exercise we will be using data I've scraped from Moz in context with
some social analysis and listening tools to build Mozzy Smurf. I'm calling this
persona Mozzy Smurf just to keep with the theme of the post, but I generally
like to give personas an alliterated name in the form of [adjective] [name]. For
example, this persona might normally be called "Busy Bob."
Naming is incredibly important because the adjective helps all the people that
will use the personas to recall their attributes much easier and the name
portion helps us imagine them as a real person.
State our goal
One of Moz's key business goals is to increase the number of users that signup
for free services that become monthly subscribers. Therefore the goal of this
persona exercise will be to discover a key segment of Moz's audience that is
very likely to share and link to content, but hasn't purchased a Moz Analytics
pro membership yet. Let's get to the bottom line of how we can show Moz is
valuable enough to pay for. The ultimate output will be the user story, user
needs, psychographics, demographics and engagement insights.
Additionally, we'll have all the values required to set up a segment to
measure this persona in Google Analytics including which Affinity Segment best
represents the persona in the data that we've collected. We'll be using data
from the Google Display Planner, Twtrland, Followerwonk, Moz Q&A, and data I
scraped from Moz user profiles almost a year ago.
Demographic data
First, I'll start by pulling demographic data from the Google Display Planner.
If you remember the DoubleClick Adplanner this has replaced it. Starting from
the demographic data allows me to determine what parameters of features are
valid for the user segments that I'm looking to discover. While the Display
Planner will be the most relevant we could have also pulled this data from sites
like Compete and Quantcast. If there's no data for your site pull data on a
high-performing competitor site.
Based on this data most of the people that visit Moz are between 25 and 34,
Male, and use Mobile devices. They are interested in SEO, Marketing,
Advertising, and Loyalty Programs. By the same token based on this data it's
also valid to build a segment that is 65+, female, is a heavy tablet user and is
interested in Loyalty Programs, but not SEO. While this segment is valid it's
not actionable to Moz so we wouldn't create a persona based on that combination.
As we collect more data the attributes we'll zero in on who are persona is.
There's one big caveat to this data, I've noticed that when comparing this to
client analytics that the devices data is typically way off. You must keep in
mind that every analytics program measures differently and ultimately your
analytics is the proving ground for any assumptions.
Another caveat is that since I'm so close to the Moz brand and the 25-34,
Male, mobile devices segment is me it's easy for me to lean on my assumptions.
This is the very reason that I'll need to pull data from a variety of sources in
order to validate any hypotheses and get the most value out of this exercise.
User needs
Normally user needs are best surfaced qualitatively through user interviews,
but as digital marketers we can discover the user needs that we aren't currently
serving through internal search analytics and social listening. Before (not
provided) we could also look at Organic keywords, but now only PPC will work for
that data.
Once needs are determined we'll be able to identify "need states" which are
the specific goal the user is looking to fulfill with their search and/or visit.
An example need state could be "How do I found out the best software for
rankings?" and this could be mapped to the awareness phase of the consumer
decision journey. We'll speak more about this when we get to the user journey.
In this case we already have a quantified user needs data set from the user
profile data that Jiafeng Li already analyzed. While this information was pulled
in early 2013, it'll still work to illustrate the process. From the screenshot
we see that the biggest segment of users with Basic accounts is the Business
Owner which we can assume means Small Business Owner in the case of Moz.
Some more key data points from the report are:
The largest single group of Basic users has been using Moz for less than a year
though there are many that have been users for 2-7 years.
There is a large group of Business Owners that spend more than 50 hours a week
on SEO and are Basic users.
Super Heavy Basic Users that are Business Owners are mostly interested in
on-page optimization, link building, content & blogging, intermediate & advanced
SEO, analytics, SEO technical issues, social media, keyword research, and
entrepreneurship and web design - in that order.
Business Owners make up 22% of the entire sample of users.
Next, I'll switch to netnographic research. I'll take a random sampling of
Moz Q&A threads looking at popular questions in each of the categories that fits
my audience to identify what their needs are. I'll also look at the feature
requests section of the site and finally do some social identification and
listening.
In Moz Q&A there are filters that help with this process allowing me to pull
the questions with the most responses of each of the topics. Unfortunately this
is a relatively time-consuming process because I'll need to double check the
profiles of the contributors to ensure they fit within my basic user / small
business segment. In interest of time I'll only review the first page of results
for each topic looking at only the past 30 days because I'm not sure whether or
not the old private Q&A was merged into public Q&A when Moz made the change.
Next we'll look at the explicitly requested user needs with regard to the Moz
product. The issues and features request section of the site provides just that.
I'm sorting by the most popular feature requests and looking at the top 10.
Again, this may not be completely scientifically sound because I'm looking at
different windows of time for each dataset. Unfortunately, this is a hazard of
netnography, but it's worth keeping track of the dates of posts when you collect
your data so you can decide the range you'll be looking at after data collection
is complete. A lot of this data will be captured in the form of screenshots and
if you're using a tool like SnagIt it will keep track of the URL so you can
refer back.
Then I review the people asking and contributing to the questions to see what
they are specifically talking about.
Since the feature request app is on Zendesk I have to search for people's Moz
profiles for verification.
After this process I've found that the small business owner segment is largely
underrepresented in the feature requests section of the site. Those that do give
feedback are mostly agency, followed by in-house, and followed by independent
consultants or agency owners. Naturally, Moz does proactively reach out to users
for feedback, but the mom and pops that the getListed.org acquisition was likely
to be target are definitely underrepresented in the online conversation I was
able to find.
Roughly, in the order of pain points that had the most business owners, we
have:
Multi-seat accounts - Users have been incredibly vocal for the last couple of
years about wanting to be able to associate multiple email addresses with an
account so multiple users can login. The conversation has gotten a bit heated
because the team hasn't been able to deliver on the timelines due to other more
pressing features, updates and the rollout of Moz Analytics. This was the
biggest issue across all account types, but it was definitely dominated by
agencies. This makes sense because business owners typically will not require
multiple parties to login to their account.
The Value of Moz - Based on the insights I got from the segmentation I went
into this exercise I assumed the biggest pain point would be in a small business
owner not understanding the value of Moz.
These users seem to understand that there is some value in the Moz toolset,
but they can't quite justify the expense when they are a small fry.
Moz iPhone App - Some People want at least top line metrics from Moz
Analytics and Whiteboard Friday in a native phone app.
Cloning / Altering Campaigns - Users need to be able to make changes to the
domain name in accounts and not lose their historical data
Analysis of More Competitors - Users need to compare more than 5 competitors.
Some are asking for as many as 15
Moz Link Manager - Some users appear to be big fans of the toolset, but wish
it had features of other tools so they could just use Moz for everything
From this I've found some specific user needs and validated that there are
indeed users within the demographic that the Display Planner reported.
The next step is social listening. I'll be leveraging free tools with keywords
identified in the user needs collection phase for this, namely Twtrland and
Twitter Search. Normally, I would have used Discussion Search, but it seems like
Google killed it recently. Luckily Twitter Search allows us to search by
sentiment and return tweets that have questions. The negative sentiment filter
is a bit of a joke though because it just looks for a frown smiley face rather
than performing sentiment analysis.
I'll keep it simple and search for tweets with questions.
Immediately I find a user within our target group is asking for feature. It's
good old Justin Briggs asking for improvements to the workflow. Justin is no
longer a small business owner, but was until recently so I'd consider his
feedback valid. However this reveals my bias and context so I will dump it.
Further searches through the tweet with question marks reveal more ephemeral
questions regarding the status and uptime of Moz. However that's an insight in
and of itself, Moz should do a better job of making the Application Status
experience more visible. It took me 10 minutes to remember where it was and I
couldn't find it by searching.
My next step is to review the users that fit my demographic data to look for
commonalities. In this case I can use Twtrland to look at that specific subset
of Followers. Twtrland has filters that allow me to set the gender, the age
range and whether or not the user is an entrepreneur.
I'll also take a quick peek at Graph Search on Facebook to see what type of
people it returns when I look for Men who are not my friends and li
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/KoYbrPtkO4Y/personas-understanding-the-person-behind-the-visit
You received this e-mail because you asked to be notified when new updates are
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Best regards,
Build Great Backlinks
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Understanding the Person Behind the Visit'
Posted by iPullRank
Market segmentation is a basic tenet of marketing that has long been ignored
by SEOs. And that's okay, because for a long time working on the keyword-level
of abstraction was enough. In fact, you can still do SEO and marketing in any
other channel without ever having the idea of market segmentation cross your
mind despite (not provided), Hummingbird, and a whole host of changes Google is
forcing as of late.
That isâ if you enjoy 0.04% conversion rates. Right.
There have been many posts about personas in the wake of the methods I've
popularized for SEO, but nothing that truly walks through the process with data
or gives context into how measurement has matured. In this post I'll go into
detail about these approaches, giving frameworks and step-by-step instructions
on how to build and use personas.
There's something in this post for everyone from beginners to advanced
marketers. I feel that it's important to give context to the discussion to
clarify why developing and using data-driven personas is critical to the future
of search and digital marketing in general. Use this table of contents as a way
to navigate to precisely what you want to know. You'll also find "Back to table
of contents" links at the end of every section.
Waitâwhat are personas?
What is the difference between segments, cohorts, and personas?
Segments
Cohorts
Personas
Google is pushing all channels in this direction
Affinity segments/categories
Building personas
Layering data
Qualitative research
Quantitative research
Building Mozzy Smurf
User journeys
Use cases
Further applications
Frequently asked questions
Resources
First, personas are a method of market segmentation wherein we collect a
combination of qualitative and quantitative data to build archetypes of the
members of our target audience. In other words we take data to tell a predictive
story about our users based on past behaviors and attributes.
I mentioned keywords as a level of "abstraction;" Google has obscured that
type of abstraction with (not provided), taking an otherwise perfect
direct-response dataset and turning up the opacity. Nonetheless, it was always a
representation of a person taking an action to fulfill a need. However, that
abstraction removed us completely from those people and placed our focus clearly
on the keyword and the Boolean idea of whether or not their visit on that
keyword led to the completion of a task.
If the keyword-level of abstraction is a stick figure a persona is an action
figure.
Over the past few years I've built methodologies in a land of marketing make
believe to develop personas and apply them to the intersection of Search and
Social Media helping us understand the person behind the search. Much like the
cartoons that action figures are modeled after personas have a set of attributes
that they are to (ahem) personify. Dictated by the business goals and the data
that can be collected and analyzed these attributes are typically a picture,
demographics, psychographics, user needs and a user story, but can be as
in-depth or as vague as you want - as long it's actionable. For example, some
people like to give each persona a "quote" that sums them up. Personas also come
with a user journey which is a collection of steps a user takes in fulfilling
those needs.
Ultimately, though, you're trying to tell the most actionable story with your
data. Think of it as another layer to your analytics. The most important layer.
The people layer.
People often ask me why they need to use personas. In my previous role of
selling SEO services to people that talk about SEO and marketing as separate
things I've experienced a lot of pushback. Fortunately there were far more
instances where a CMO or VP was in the room and speaking in terms of segments
and market opportunity rather than just keywords, meta tags and guest posts
helped us win the business.
But I digress.
One of the main reasons for using personas is that when you target everyone
you actually target no one. The art of segmentation is about narrowing your
focus in on people in the market more likely to become your users/customers so
you can better serve them. This applies not only to your product and/or service,
but your content as well.
Donald A. Norman of the Nielsen Norman Group explained it best when he
declared "A major virtue of personas is the establishment of empathy and
understanding the individual who uses the product."
In the Content Strategy world one of the major concepts they push is
"empathy." How can we understand and then fight for the user to create the best
possible content experience to fulfill their needs? Not just the right words,
but the right structure, the right metadata, the right presentation.
User Experience professionals use that idea of empathy with personas to plan
and build things that work for the target audience. For example, if our audience
is people over 50 then it may make sense to design a site with the larger text.
In the world of marketing this is all a means to specific end of course, but
ultimately we just want to know who we're talking to so we can improve our rate
of persuasion - or conversion.
Organic Search as a marketing channel is about just that - persuading people
who have a specific intent to believe you can fulfill their needs. Building
personas allows you to speak directly to their needs from as early as the page
title and meta description. This applies to not only your product and/or
service, but your content as well.
Back to table of contents
The terms are often used interchangeably, but they can mean slightly different
things. All of these concepts are abstractions of people, but the basic
difference between the three lies in their specificity. A segment is the
broadest concept of a person while a persona is the most specific snapshot of a
user archetype.
For the purposes of this discussion the Smurfs will act as a way to make these
ideas a little more real (whoa, meta). I tried to get G.I. Joe, but, they were
busy fighting wars and stuffâ yeah, anywayâ
Segments
Segments are groupings of similar entities. You can (and should) quite
literally segment by any set of rules in your data as I've discussed in my last
Moz post. On the cartoon the Smurfs you had humans, animals and Smurfs. Each of
those could be a segment. You could segment just the Smurfs themselves by color
of their mushroom homes. You can segment them based on things that happened on
the show. Two segments could be "Those that Gargamel Has Captured" and "Those
that Gargamel Has Not Captured." You could segment by where they live in the
Village. North Smurfs, West Smurfs, Southeast Smurfs. You could sub-segment any
of these groups with any granularity that you see fit or combine criteria just
like you would with standard clickstream data in Google Analytics.
The point is, although you can segment by anything you can track, will it be
actionable? Popular actionable segments that are used every day are geographic,
behavioral, seasonal, and benefit segments.
Nielsen PRIZM is a popular market segmentation system that is based on zip
codes where people are chunked into subsets regarding their location, income and
behavior. Nielsen builds this system on top of US Census data and sends out
surveys to a large sample of people to create 66 segments throughout the United
States. Experian Simmons is similar, and maybe more interesting to inbound
marketers with its connection to Hitwise, but Google has recently brought
segmentation purely online and has the potential to supplant them all. More on
that later.
Cohorts
Cohorts are groupings based on similar experience. Common vernacular for
cohorts would be generations. In the Smurf Village you had three generations of
Smurfs. The baby Smurfs (which for whatever reason had the only other female
Smurf). Let's call them Generation Next. You had the adult Smurfs like Jokey,
Vanity, Brainy, and Smurfette's cohort. Let's call them Generation Now. A cohort
that walked around believing shirts were optional.
And you had Papa Smurf and a few of his buddies. Let's call them the Elder
Smurfs.
Obviously, each individual in any of these groups is different from the next,
but they are grouped by their shared temporally attitudes, cultural interests
(ex. fashion sense, music), and life experiences (Gargamel captures, first
appearance of Smurfette).
In the real world we have Baby Boomers, Generation X, and the ever elusive
Millenials. Baby Boomers were a generation defined in the post-World War II era
of increasing affluence, Civil Rights movements and the death of JFK. Generation
X was a people defined by rebellion, MTV, baggy pants, the dot Com Bubble, the
rise of Grunge, Microsoft, and the death of Kurt Cobain. Millenials are defined
by 9/11, job-hopping, Apple, Google, Facebook, free music, nerd glasses, tight
jeans, everybody having a startup and the death of Michael Jackson.
Right now every big product-driven company is asking how do we get Millenials
to care about us?
Personas
Personas are specific archetypes of people in the target audience. The
attributes identified across the group are collected to give birth to a single
entity that represents these users. A persona has a descriptive name and is
meant to be thought of like someone that actually exists. They are generally a
composite of people that do exist.
In this case we will use individual Smurfs themselves as our personas. While
some people in the 80s viewed the cartoon as communist it can also be seen as an
exercise in behavioral segmentation. Each character was clearly differentiated
by what they specifically did or how they acted within the Smurf Village.
You had Brainy Smurf, the original hipster. He's a bit of an introvert and
likely to be found at a Barnes & Noble sipping a macchiatto latte and discussing
Sartre, injecting barbs of sardonic wit. He spends a lot of time updating his
blog, and he's a freelance copywriter for a multinational ad agency, but he only
shops at the mall. Brainy prefers Facebook over Twitter as he would rather have
a long-form discussion where he can definitively disprove what you believe. He
listens to NPR and of course is a Mac rather than a PC.
You had Smurfette. Well, you had two Smurfettes, each of which could be a
persona.
The first Smurfette was a tom boy who just wanted to hang with the homies.
After all she was created by Gargamel as a way to distract and trap the Smurfs.
She shopped at second hand stores before it was in style. No, really.
Old Smurfette goes to open mics and loves to be around music. She enjoys
vintage vinyl records and playing with her rescue cat. The Old Smurfette is a
bit of a couch surfer who frequents SmurfBNB and eats at Baker Smurf's
restaurant rather than the big chains. You guessed it; Old Smurfette is a
persona based on the female hipster Millenial cohort.
Later, after Papa Smurf turned her into a real Smurf she got all high-end
fashion on us, dying her hair blonde, wearing Diane von Smurfstenburg dresses
and Christian Smurfboutin shoes. She's more likely to be found at high-end
establishments, but only goes out when invited. Smurfette would rather be
shopping than go to a music night spot. She's all about convenience over
supporting her local community. Smurfette likes to see and be seen.
Then you had Jokey Smurf. His persona name would probably be Terrorist Tom
because he loves to hand people presents that explode. In the context of
marketing Jokey is the type of user who loves extreme sports, sites like
Break.com, and the type of content that Red Bull creates. He's highly likely to
buy Ed Hardy clothing. Only the jeans, though, because males in his cohort don't
wear shirts. Jokey loves craft beer, Xbox One and action movies.
In the above cases I've taken what I know about the millennial cohort and
layered it into a story about the different Smurf characters based on things
that could be observed on the show. As marketers building personas we do this
with regard to the context of our marketing programs. That is to say we focus on
elements of the story that is relevant to our goals rather than including every
data point we can find.
A key distinction to be made in the context of inbound marketing programs is
that between the buyer person and the audience persona. The audience persona is
typically someone looking to consume content for education or entertainment.
These people are not actively looking to purchase a good or service and are
better measured via KPIs having to do with the spread or the building of
authority for that content or the building of community.
Conversely, buyer personas may also be looking to consume content, but only as
a means to make the specific transaction to support their needs. There is
frequently overlap between the two types of personas and a given user can also
transition between the two types. Keep this in mind as you develop your
personas.
Once this in-depth profile of the audience is created smart marketers ask
questions and take actions with regard to how these personas would best be
served to meet the business objective.
At Amazon, Jeff Bezos leaves a chair empty at meetings to signify the customer
persona is in the room listening to the decisions they are making. At Experian
they have developed the character and placed her on banners throughout the
office and in the company newsletter to keep the customer top of mind. When I
worked on LG they sent a poster of their home appliances persona Wendy and she
came up often in our strategy meetings. At AirBNB they have a section of the
office with the personas in storyboards on the wall along with illustrations of
those of personas going through the user journey.
No matter what method you use, it is important to keep the consumer, customer,
user at the center of the marketing initiative. Don't just build personas and
forget they exist.
Back to table of contents
"Why should I care," you say? Well for some time I have touted this idea of
the intersection of search and social media to take intent to match it up with
the person. This and some of Google's actions towards the end of 2011 (remember
the consolidation of the privacy policies ?) led me into the idea that they
are using G+ to model users to apply a sliding scale of authority based on
topical relevance for better search quality and to provide the Holy Grail of
advertising opportunities. In fact I believed the whole purpose was modeling
beyond the keyword to make every dollar worth a lot more by marrying multiple
data sets. It turns out this is exactly where Google wants to go with their
marketing products and I'm basically just ahead of my time. ;]
Ian Lurie has also been talking about this extensively for the past few years
as well through a concept he calls "random affinities" which is similar to
something I was (perhaps mistakenly) calling "co-relevance" when I built a tool
for getting ahead of search demand with social media.
Forgive the quality of these screenshots, but in a recent video from Google
featuring Forrester Research's VP/Principal Analyst Nate Elliot they discussed
the concept of affinity and market segmentation. What he describes as Smart
Affinity is what a methodology like Keyword-Level Demographics is looking to
harness. This is a capability that marketers in general have yet to embrace
because it's simply too complicated for most. Google is taking us there kicking
and screaming.
Diya Jolly from Google gives some of the insight into why Google is obviously
the best suited for the job in her discussion of the data signals available
across the Google ecosystem. The amount of data combined with the sample size
allows Google to have probably the most robust and accurate model of user
behavior which potentially render other modes of advertising and market research
nearly obsolete or at least less effective.
I dug a little deeper into the process and found the "Inferring User
Interests" patent where they discuss more in-depth how they figure out user
interests. For example:
"In the situation where a first user lacks information in his profile,
profiles of other users that are related to the first user can be used to
generate online ads for display with the first user's profile. For example, a
first user Isaac may not have any information in his profile except that he has
two friends-Jacob and Esau. The server system 104 can use information from Jacob
and Esau's profiles to infer information for Isaac's profile. The inferred
information can be used to generate online ads that are displayed when Isaac's
profile is viewed."
How's the saying go? When it's free, you're the product.
Affinity segments/categories
All the data we give Google for free has allowed them to roll out this new
Affinity Segments product which is Google's own new segmentation system.
In their own words :
"We use the main topics and themes from the page as well as data from
third-party companies to associate interests with a visitor's anonymous cookie
ID, taking into account how often people visit sites of those categories, among
other factors.
Google may use information that people provide to these partner websites about
their gender, age, and other demographic or interest information. We may also
use the websites people visit and third-party data to infer this information.
For example, if the sites a person visits have a majority of female visitors
(based on aggregated survey data on site visitation), we may associate the
person's cookie with the female demographic category."
In typical Google fashion, aside from the video and a few articles in the
Adwords Support site, the detailed information about these segments is pretty
sparse. Luckily, I was able to get my hands on a deck with short user stories
and targeting ideas for each segment. I'm sure your Adwords account manager
would be able to furnish something like the below if you asked them nicely.
Affinity Segments is the broad name for these targeting types, but in practice
Google offers "Affinity Categories," "In-market Buyers," and "Other Categories"
as targeting types in AdWords. Affinity Segments are users in a broad sense,
In-market segments are people that are actively looking to purchase and other
categories are a variety of things. You're likely to see other categories the
most if you're not in the US.
I appreciate that Google makes the distinction between "Affinity Categories"
and "In-market Buyers" as this directly mirrors the approach I take in creating
both "Audience Personas" and "Buyer Personas." More on that later.
As an end user you can see which demographics and interests Google has
associated with you in your Ad Settings. You can also opt-out or change your
features as seen below.
However, the most important point for this persona discussion is that you can
now measure everything in Google Analytics based on these segments.
Let that sink in for a second. Google has Google+ as an "identity platform"
which is pretty much a front end for data collection and modeling of people.
They have Google Consumer Surveys so marketers can poll the audience and I
imagine at some point you'll be able to ask questions by affinity segment. And
now you have Google Analytics showing website actions in context of those
affinity segments. Google has just set itself up to disrupt the entire market
research industry with end to end people modeling. If that doesn't sell you at
least on the power of segmentation nothing will. This is completely
unprecedented.
Back to table of contents
Ok, enough with the background; let's get you building personas. There are
many methods for developing personas and I will discuss several of them, but you
should choose your approach based on the data and resources at your disposal.
Again, what we will be doing is collecting data, segmenting it and telling a
story about that segment. First I'll outline different processes then we'll walk
through the creation of a persona for Moz leveraging data from the scraping
post, Twtrland, Followerwonk,the community Q&A forum, and feature requests.
In my experience a combination of approaches yields the best personas.
Otherwise you'll end up relying too much on your own assumptions. Also I
typically build four personas with Googlebot, which AJ Kohn has aptly named the
Blind Five Year Old, acting as the fifth, but you can build as many as you see
fit.
Layering data
If you've seen me speak in the past year or so you've probably seen this
image. When I was at my previous agency my market research lead Norris Rowley
and I developed a methodology wherein we layered data from Nielsen Prizm and
Experian Simmons to collect data on segments at scale.
When I say layering I mean that we look for commonality between datasets and
if there is enough commonality or overlap we consider all features potentially
valid for sub-segments. That is to say if enough attributes of a Prizm Code and
a MOSAIC Type are shared we consider any data in one to be potentially valid for
the other and we applied this approach across all the available datasets.
Whether or not that is scientifically sound can be debated, but remember that
personas are hypotheses that will ultimately be validated or invalidated through
measurement.
Since the Prizm and Simmons surveys deal mostly in offline behaviors we'd plug
those data points into Social PPC inventories (Facebook Ads, Twitter Ads,
LinkedIn Ads) to ensure that those segments were valid online. If they proved to
be valid then we'd take that segment and build a persona.
I still believe this to be a solid approach especially if you can leverage
this data in context with some of Simmons' other products measure online usage
behavior as well as Google's Affinity Segments.
No matter which method you use you should start by determining the business
objectives which will then help to determine the goals of your research. Then
define how these personas will be used. Are you just looking to focus on your
buyer personas or will you be thinking about audience personas as well?
Qualitative research
With Qualitative Research you're asking open-ended questions to small sample
sizes to get a sense of the "how"s and the "why"s behind a specific problem.
You're typically looking at unstructured data to inform commonality amongst your
user group and any insights are then validated for scale throughout quantitative
research processes. Qualitative research within our context is often user
interviews, focus groups, content analysis, text-mining, ethnography and
affinity mapping.
(image source)
Affinity mapping / affinity diagramming
When most people think of a persona-building exercise they think of this.
Affinity mapping or affinity diagramming is the process of collecting everyone's
thoughts and segmenting them into meaningful groups. In the context of personas
this is typically done in a several hour session of everyone writing their ideas
of their customers on post-it notes with Sharpies, discussing them as a team and
then grouping them.
This process is great for putting the consumer back in focus for the team and
also for getting executive buy-in. However it's mostly based on assumptions so I
would not suggest doing only this when building personas as your research may be
attacked and biased by HIPPOs.
When you do this you want to get all the key stakeholders involved, especially
the upper management team but most importantly the people that deal with your
customers or users on a regular basis like your Sales or Help teams. The former
helps with internal adoption. The latter helps get closest to the right answer.
Many people building personas stop here to save time and resources, but when you
do these profiles are typically known as "proto-personas."
Affinity Mapping is typically done in the following 90 minute rounds:
Assumption round one (Needs) - Each person spends 5-20 minutes jotting down a
goal, activity, need, or problem for any user. This is to be exclusive of any
attributes of the user, rather it's about what the user is trying to accomplish.
An example assumption could be "User needing to make a confident decision on
which LSAT prep course to enroll in."
Once everyone has comfortably collected their ideas you go around the room and
each person introduces one of their post-its. The entire team weighs in on how
valid they believe the assumption to be. Those that are valid are placed on the
board. Those that are not are discarded. You continue until all post-its are on
the boards or in the trash. Throughout the process groups start to emerge as
assumptions begin to fit together. You can give the groups names if you'd like,
but at this point it's not that important as names can be given later in the
analysis phase.
Assumption Round Two (Attributes) - Each person again spends 5-20 minutes
jotting down information about the target audience, but this time they present
attributes of the user groupings from the first round. Again, you'll go around
the room and everyone will share and discuss their assumptions. The ones that
the group agrees are valid will then get added to the wall.
To continue the example from above an assumption could be "College graduate
25-34 who is unhappy with their career." Starting with the needs in the first
round helps to really zero on the demographics and psychographics of the people
in this round. If you go the other way around the parameters of the people may
be too broad.
Factoid Round - The final round of the exercise involves everyone in the group
spending 15-30 minutes finding data points to back up the groups of assumptions.
This data can come from any number of other relevant sources including
analytics, sales data, internal and external research. Again, the team discusses
the data points and decides their validity and adds it them to the groups.
An example fact could be "20% of all signups for our LSAT prep course
graduated college 4-11 years ago and reported in their registration that they
want to make more money."
The factoid round helps perfect the user story based on quantifiable realities
instead of just assumptions. It also allows you to potentially dump segments if
there's no data to back them up.ProTip: Although it sounds like a daunting
procedure that requires in-person interaction it can be done very effectively
remote by using Mural.ly and Google+ Hangouts.
The screenshot above is from a recent session I did with a startup called
Trip.Me in Berlin. We got members of the marketing team, the CEO and the
Operations team together on G+. We color-coded each round of assumptions and
factoids with the virtual post-it notes and then the tool makes it easy to bring
in links and content that supports any assumptions anyone on the team had. The
Google+ effects made it a fun time for all.
Build Personas - At this point you have all the data to build out the skeletal
personas. Your goal should be to whittle all of these insights into 3-5
actionable personas. While you can make as many as you'd like, it's difficult
for teams to stay mindful of too many. We'll go into more of how to formulate
stories based on the data when I actually walk through the process, but at this
point that is what you'll do.
These are often referred to as skeletons or proto-personas because they don't
have direct user research or a large wealth of quantitative data behind them.
However for many people this is just fine because the team may be most invested
in this type of persona, and that will help with adoption.
Focus groups
Focus groups are formal meetings with people of the target segment wherein a
moderator asks research questions to understand users and their needs. I've
personally never run one of these, but the ones that clients have conducted and
shared with us have made useful inputs in the creation of personas. They help
with determining questions and need states of users. However I often find that
moderators lead the group on some of the questions thereby invalidating their
responses to draw bias conclusions.
The quality of the output from a focus group has entirely to do with the
experience and biases of the moderator, the quality of the questions, and most
importantly the selection and attentiveness of the panelists. Another thing to
be leery of is the dominance of one opinion in group settings as people are
often swayed by the loudest participant. Furthermore the incentive the people
set for being involved may be their only reason to participate and they won't
give thoughtful answers.
We're about halfway through the post so I encourage you to take a break and
watch Conan O'Brien go undercover and moderate a focus group about himself:
User/customer interviews
These are similar to focus groups except they involve a one-on-one or small
one-on-two group environment where you directly speak to a user or customer. For
design, products or CRO this can be usability testing and eye-tracking or it can
just be direct Q&A as in the case of personas. All of the insights on how
customers user the product can be valuable to both the personas and the
determining the user journey.
Ethnographic research
Ad-Hoc data collection is what I've been calling the method of using social
listening, forum searches and keyword research to build personas , but I've
come to learn that research such as this when you watch users act in their
natural habitats is called "ethnography" or when it's on the web "netnography."
This is a great way to build personas when you have few resources because you
can easily identify online communities or watch hashtags and specific
representatives of your users on Twitter. Great tools for this include Topsy,
Sysomos, Radian6, Google Discussion Search, Keyword Planner, and the Display
Planner, Twtrland and Followerwonk.
The Display Planner, Quantcast, Compete, Twtrland and Followerwonk will all
give you demographic data that helps you frame your personas. Where Twtrland
bests Followerwonk is in its ability to infer interests from tweets and not just
user bios. The Keyword Planner gives you the keywords associated with the site
for use as the vocabulary to find your users in discussion search and eavesdrop
on their conversations with Social Listening tools like R6, Topsy and Sysomos.
Naturally, you'll need to do several iterations of looking at keywords and
conversations to identify trends across your users. You can also uses sites like
Quora and Reddit by going as far as to pose questions to kickstart the
conversation.
While the screenshot above is a good framework to work within there's no
defined structure to ethnographic research. You'll have to judge for yourself
when you feel your research questions have been answered. However you should
generally expect to do the following:
Collect examples of what you see users doing in their natural environments
called "field notes"
Analyze notes to discover new questions and reiterate
Look for shared patterns of belief, language and behavior
Write the ethnography which in this case is the persona
Ethnographic research is both the easiest and hardest of approaches because it
just requires observation, but the approach is completely subjective so it's
hard to convince people that the insights should stick in and of themselves
without quantitative research to back it up.
Quantitative research
If you're reading Moz you're probably a data-driven marketer so this end of
the research spectrum will appeal to your sensibilities. Quantitative research
is about using numbers and statistics to understand behaviors of users
empirically. The sample sizes are often quite large so that the insights can be
applied to broad populations of people.
Multiple-choice surveys
Polling your target audience allows you to ask precise questions. There are
many options for this, but I prefer SurveyMonkey Audience for this type of work
simply due to the fact that they collect of demographic data explicitly from
users while Google has is inferring it from user behavior. Survio is also a good
choice for surveying non-US markets. Survey Design is a science in itself and
SurveyMonkey has great resources on it , but the key thing to note here is that
at this point you want your surveys to not be exploratory or open-ended in
nature. You want your surveys to give users well-defined choices that you've
defined based on your qualitative research. The results will need to be
cross-tabbed until insights are wrangled out and personas begin to appear.
Market segmentation tools
As I mentioned before Experian Simmons, Nielsen as well as tools like MRI and
ComScore provide market segmentation based on surveyed panels and usage data.
These tools are incredibly helpful with scaling the persona building process by
providing prebuilt segments as well as a wealth of data in context of those
segments.
These tools fail when there if a specific question has not been included.
These providers are eager to take feedback and insights to add to their
quarterly surveys, but even when they do you are at least 3 months away from
seeing your questions answered and input into the system.
Analytics
Even without demographic tracking your analytics can have a wealth of
knowledge especially internal search, paid search and historical organic search
keywords in context of site actions. Also looking at location demographic data
as well as the times your users are visiting can be helpful determinations of
their attributes. Really what you can pull from analytics is completely
dependent upon your setup.
User profiles
If your site has user profiles, especially those that have collected data from
Social logins or other identity data providers there is a wealth of data that
users have explicitly set.
Internal data
Data on sales, calls, returns, reviews, users and transactions of all types
can be leveraged to give parameters and color during the persona development
process.
Publicly available studies
Every industry has public research and data that can be leveraged when
building personas. For example Google has the Consumer Barometer where you can
pull various data points.
I tend to use a combination of these approaches in my persona building
depending on what resources are available. In my client work experience I've
found it best to start with an affinity mapping session and then to prove or
disprove those assumptions and gain additional insights with data from the other
sources.
Back to table of contents
For this exercise we will be using data I've scraped from Moz in context with
some social analysis and listening tools to build Mozzy Smurf. I'm calling this
persona Mozzy Smurf just to keep with the theme of the post, but I generally
like to give personas an alliterated name in the form of [adjective] [name]. For
example, this persona might normally be called "Busy Bob."
Naming is incredibly important because the adjective helps all the people that
will use the personas to recall their attributes much easier and the name
portion helps us imagine them as a real person.
State our goal
One of Moz's key business goals is to increase the number of users that signup
for free services that become monthly subscribers. Therefore the goal of this
persona exercise will be to discover a key segment of Moz's audience that is
very likely to share and link to content, but hasn't purchased a Moz Analytics
pro membership yet. Let's get to the bottom line of how we can show Moz is
valuable enough to pay for. The ultimate output will be the user story, user
needs, psychographics, demographics and engagement insights.
Additionally, we'll have all the values required to set up a segment to
measure this persona in Google Analytics including which Affinity Segment best
represents the persona in the data that we've collected. We'll be using data
from the Google Display Planner, Twtrland, Followerwonk, Moz Q&A, and data I
scraped from Moz user profiles almost a year ago.
Demographic data
First, I'll start by pulling demographic data from the Google Display Planner.
If you remember the DoubleClick Adplanner this has replaced it. Starting from
the demographic data allows me to determine what parameters of features are
valid for the user segments that I'm looking to discover. While the Display
Planner will be the most relevant we could have also pulled this data from sites
like Compete and Quantcast. If there's no data for your site pull data on a
high-performing competitor site.
Based on this data most of the people that visit Moz are between 25 and 34,
Male, and use Mobile devices. They are interested in SEO, Marketing,
Advertising, and Loyalty Programs. By the same token based on this data it's
also valid to build a segment that is 65+, female, is a heavy tablet user and is
interested in Loyalty Programs, but not SEO. While this segment is valid it's
not actionable to Moz so we wouldn't create a persona based on that combination.
As we collect more data the attributes we'll zero in on who are persona is.
There's one big caveat to this data, I've noticed that when comparing this to
client analytics that the devices data is typically way off. You must keep in
mind that every analytics program measures differently and ultimately your
analytics is the proving ground for any assumptions.
Another caveat is that since I'm so close to the Moz brand and the 25-34,
Male, mobile devices segment is me it's easy for me to lean on my assumptions.
This is the very reason that I'll need to pull data from a variety of sources in
order to validate any hypotheses and get the most value out of this exercise.
User needs
Normally user needs are best surfaced qualitatively through user interviews,
but as digital marketers we can discover the user needs that we aren't currently
serving through internal search analytics and social listening. Before (not
provided) we could also look at Organic keywords, but now only PPC will work for
that data.
Once needs are determined we'll be able to identify "need states" which are
the specific goal the user is looking to fulfill with their search and/or visit.
An example need state could be "How do I found out the best software for
rankings?" and this could be mapped to the awareness phase of the consumer
decision journey. We'll speak more about this when we get to the user journey.
In this case we already have a quantified user needs data set from the user
profile data that Jiafeng Li already analyzed. While this information was pulled
in early 2013, it'll still work to illustrate the process. From the screenshot
we see that the biggest segment of users with Basic accounts is the Business
Owner which we can assume means Small Business Owner in the case of Moz.
Some more key data points from the report are:
The largest single group of Basic users has been using Moz for less than a year
though there are many that have been users for 2-7 years.
There is a large group of Business Owners that spend more than 50 hours a week
on SEO and are Basic users.
Super Heavy Basic Users that are Business Owners are mostly interested in
on-page optimization, link building, content & blogging, intermediate & advanced
SEO, analytics, SEO technical issues, social media, keyword research, and
entrepreneurship and web design - in that order.
Business Owners make up 22% of the entire sample of users.
Next, I'll switch to netnographic research. I'll take a random sampling of
Moz Q&A threads looking at popular questions in each of the categories that fits
my audience to identify what their needs are. I'll also look at the feature
requests section of the site and finally do some social identification and
listening.
In Moz Q&A there are filters that help with this process allowing me to pull
the questions with the most responses of each of the topics. Unfortunately this
is a relatively time-consuming process because I'll need to double check the
profiles of the contributors to ensure they fit within my basic user / small
business segment. In interest of time I'll only review the first page of results
for each topic looking at only the past 30 days because I'm not sure whether or
not the old private Q&A was merged into public Q&A when Moz made the change.
Next we'll look at the explicitly requested user needs with regard to the Moz
product. The issues and features request section of the site provides just that.
I'm sorting by the most popular feature requests and looking at the top 10.
Again, this may not be completely scientifically sound because I'm looking at
different windows of time for each dataset. Unfortunately, this is a hazard of
netnography, but it's worth keeping track of the dates of posts when you collect
your data so you can decide the range you'll be looking at after data collection
is complete. A lot of this data will be captured in the form of screenshots and
if you're using a tool like SnagIt it will keep track of the URL so you can
refer back.
Then I review the people asking and contributing to the questions to see what
they are specifically talking about.
Since the feature request app is on Zendesk I have to search for people's Moz
profiles for verification.
After this process I've found that the small business owner segment is largely
underrepresented in the feature requests section of the site. Those that do give
feedback are mostly agency, followed by in-house, and followed by independent
consultants or agency owners. Naturally, Moz does proactively reach out to users
for feedback, but the mom and pops that the getListed.org acquisition was likely
to be target are definitely underrepresented in the online conversation I was
able to find.
Roughly, in the order of pain points that had the most business owners, we
have:
Multi-seat accounts - Users have been incredibly vocal for the last couple of
years about wanting to be able to associate multiple email addresses with an
account so multiple users can login. The conversation has gotten a bit heated
because the team hasn't been able to deliver on the timelines due to other more
pressing features, updates and the rollout of Moz Analytics. This was the
biggest issue across all account types, but it was definitely dominated by
agencies. This makes sense because business owners typically will not require
multiple parties to login to their account.
The Value of Moz - Based on the insights I got from the segmentation I went
into this exercise I assumed the biggest pain point would be in a small business
owner not understanding the value of Moz.
These users seem to understand that there is some value in the Moz toolset,
but they can't quite justify the expense when they are a small fry.
Moz iPhone App - Some People want at least top line metrics from Moz
Analytics and Whiteboard Friday in a native phone app.
Cloning / Altering Campaigns - Users need to be able to make changes to the
domain name in accounts and not lose their historical data
Analysis of More Competitors - Users need to compare more than 5 competitors.
Some are asking for as many as 15
Moz Link Manager - Some users appear to be big fans of the toolset, but wish
it had features of other tools so they could just use Moz for everything
From this I've found some specific user needs and validated that there are
indeed users within the demographic that the Display Planner reported.
The next step is social listening. I'll be leveraging free tools with keywords
identified in the user needs collection phase for this, namely Twtrland and
Twitter Search. Normally, I would have used Discussion Search, but it seems like
Google killed it recently. Luckily Twitter Search allows us to search by
sentiment and return tweets that have questions. The negative sentiment filter
is a bit of a joke though because it just looks for a frown smiley face rather
than performing sentiment analysis.
I'll keep it simple and search for tweets with questions.
Immediately I find a user within our target group is asking for feature. It's
good old Justin Briggs asking for improvements to the workflow. Justin is no
longer a small business owner, but was until recently so I'd consider his
feedback valid. However this reveals my bias and context so I will dump it.
Further searches through the tweet with question marks reveal more ephemeral
questions regarding the status and uptime of Moz. However that's an insight in
and of itself, Moz should do a better job of making the Application Status
experience more visible. It took me 10 minutes to remember where it was and I
couldn't find it by searching.
My next step is to review the users that fit my demographic data to look for
commonalities. In this case I can use Twtrland to look at that specific subset
of Followers. Twtrland has filters that allow me to set the gender, the age
range and whether or not the user is an entrepreneur.
I'll also take a quick peek at Graph Search on Facebook to see what type of
people it returns when I look for Men who are not my friends and li
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Tuesday 28 January 2014
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'New Top Strategies, Salaries and
Tools: Announcing the 2014 Industry Survey Results'
Posted by Cyrus-Shepard
Late last year we set out to discover the top tools, tactics, and trends of
the online marketing world. With the help of our partners, over 3700
participated in this year's Industry Survey.
Today...
You may view the latest post at
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Tools: Announcing the 2014 Industry Survey Results'
Posted by Cyrus-Shepard
Late last year we set out to discover the top tools, tactics, and trends of
the online marketing world. With the help of our partners, over 3700
participated in this year's Industry Survey.
Today...
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/baU16mVZh-E/marketing-trends-2014
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Build Great Backlinks has posted a new item, 'Why Google Pushed Me to Build a
(Bigger) Link Network'
In 1865, Fredik Idestam built a pulp mill on the banks of the Tammerkoski River
in southwestern Finland. He soon added a papermaking machine. As with any
papermaking company at the time, much of what the company produced was used for
stationery, newsprint, and books the primary means of communication before the
age of []
You may view the latest post at
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(Bigger) Link Network'
In 1865, Fredik Idestam built a pulp mill on the banks of the Tammerkoski River
in southwestern Finland. He soon added a papermaking machine. As with any
papermaking company at the time, much of what the company produced was used for
stationery, newsprint, and books the primary means of communication before the
age of []
You may view the latest post at
http://www.viperchill.com/blog-network/
You received this e-mail because you asked to be notified when new updates are
posted.
Best regards,
Build Great Backlinks
peter.clarke@designed-for-success.com
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Top Strategies, Salaries and Tools
Revealed: Industry Survey Results 2014'
Posted by Cyrus-Shepard
Late last year we set out to discover the top tools, tactics, and trends of
the online marketing world. With the help of our partners, over 3700
participated in this year's Industry Survey.
Today, Moz is proud...
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/baU16mVZh-E/marketing-trends-2014
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Revealed: Industry Survey Results 2014'
Posted by Cyrus-Shepard
Late last year we set out to discover the top tools, tactics, and trends of
the online marketing world. With the help of our partners, over 3700
participated in this year's Industry Survey.
Today, Moz is proud...
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/baU16mVZh-E/marketing-trends-2014
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Monday 27 January 2014
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Applying Lessons from the
Publishing Industry to SEO Consulting'
Posted by SarahKershaw
"Search has been less and less relevant since Facebook released News Feed. Now
we get the vast majority of our traffic via social, and about 1-2% from search"
â Chris Dannen from Fast Co Labs
"We benefited a ton from an early SEO audit thanks to IAC's SEO pros, but once
the right framework was in place, it's been up to us as content creators to
really dig deep into Google Analytics to determine where the opportunities
lieâ"
â Jordan Shakeshaft, editorial director of Life by DailyBurn
"None" was another person's response to my question about the role of SEO
within her company. "There's very little of actual value in it for us." This
from a respected British magazine.
In preparation for this post, I started thinking about publishers and their
plans for 2014, specifically their growth strategies for the coming year. My
thought was that as the publishing industry usually leads the way when it comes
to new content techniques and products, it is at the forefront of publishing
initiatives. As publishers blaze new trails, we as consultants have the
opportunity to learn by proxy, observing what has worked and what has not. These
observations can then be applied to our own clients' content creation. In this
post-panda arena, the scramble to produce high-quality, compelling content is as
real as ever, and lessons need to be learned fast. Let the publishing industry
be your guide; come, walk with me.
In researching this post, I spoke to a combination of editors, industry
analysts and publishing company employees. The quotes are representative of my
contacts and their responses, but it is in no way comprehensive for the
publishing industry as whole.
As per the quotes above, the sobering reality is that, at best, publishers see
SEO as just one small part of their marketing strategy. Moz's very own legend,
Dr. Pete, has been trying to tell us this for a while, encouraging the search
community to look beyond rankings. Our goal as consultants is to continue to add
value in this altogether more varied landscape. The good news is that we can if
we leverage our technical knowledge and use this to present some of the newer
ideas, beyond our usual scope, to our clients.
This post is an examination of some of the other opportunities publishers are
pursuing this year, along with my dreams for what they could be doing and some
tips on how to present these ideas to clients.
What are publishers doing for growth?
1) Investing in site redesigns
The internet was all aflutter earlier this month, when The New York Times
launched its site redesign. That project, in addition to generating buzz,
traffic, and links, was the site's first major redesign since 2006. The main
visual changes include:
Changing of fonts and font colours so it more closely resembles the print
edition. The links from the home page to the categories page are now black, not
blue for example.
Article comments now appear on the right-hand side of the article, allowing
comments to receive the same level of visibility as the article.
Infinite scroll, rather than pagination.
A much more minimal look on article pages with more white space.
This redesign freshens up the look of the page as a whole and the cleaner,
sparer UI is more in keeping with what other publications are doing. This video
from Fi talks us through its process for redesigning USAToday.com, which has
several design features in common with the Times' update.
The insight: Good design matters.
Your access point: When presenting ideas of this ilk to your clients, it is
important to be in cahoots with the designers. Your aim is to collaborate in
these projects, ideally from initial conception. The advantage of being an
outsider weighing in on a site redesign is that you are invariably not bound by
the limitations of a CMS or the like; you are free to see the site and where it
stands in relation to industry competitors with a detached view. You can
represent SEO and call on your experiences with redesigns to offer suggestions.
2) Embracing social
You probably already know that social networks are an increasingly important
means of discovery, and amongst the under-45s, they are the most popular method
of finding content. Social becomes more and more important as user groups get
younger. For example, 44% of 18- to 24-year-olds rely on social, versus just 19%
of users over 55. This is illustrated by this graph from the Reuters Institute's
Digital News Report 2013:
Clearly, if you wish to build long term trust with your users, social networks
are critical for getting your content in front of younger users. It goes without
saying that social networks are also now critical for engagement among all age
groups.
What is surprising is the extent to which publishers are still missing this
opportunity, whilst newer companies such as Upworthy and Buzzfeed are swooping
in and winning traffic. This recent article from the Media Briefing visualizes
how some of the media players are doing on Facebook, and the newsworthy part is
that none of the more established players feature at all. In short, they are not
getting it right. The winners in this particular data set are companies that
have been formed within the last eight years (Buzzfeed was formed in 2006,
Upworthy in 2012); the Huffington Post is the old guard here, and that is only
nine years old.
The results are clear Upworthy and Buzzfeed have mastered the sort of content
that gets people sharing. Whilst the audience may eventually tire of cats in
unlikely situations, photoshop-shaming, and listicles, you can be sure that both
companies are investing time and effort to evolve from their current strategy.
Mark Suster expanded on this idea in a recent post, saying "I think companies
like Upworthy can build really compelling businesses in the future â but
I'm willing to bet serious cash ... that it won't be by sticking to the playbook
[that is, writing content to generate as many social shares as possible] that
has worked tremendously well to date."
The insight: For all of the chatter about social networks, publishers are
still not getting it right.
Your access point: Present working in social networks as a series of
easy-to-implement A/B tests.
Using the Upworthy premise, as outlined below, clients have a quick, clean
testing method that should give them confidence to test their social network
content.
Upworthy produced a wildly popular slide deck back in 2012 that outlines some
of their tactics, which makes for an interesting read. The key takeaway,
regardless of the sort of content your client might produce, is the idea of
testing multiple headlines. Upworthy writes 25 different headlines for a post,
and then tests the headlines in two demographically similar cities within
Facebook for an hour or so. They then push the headline with more shares.
This is both agile and data-driven; keep this example in mind, as it's
deliciously simple and reasonably easy to implement. It can also be applied to
subheadings, images, and more. As consultants, A/B Testing is very much within
the traditional scope of your work. By using this experience (and the client's
trust in this experience) you are moving into new terrain via a familiar method.
Let social embrace you back
To approach the opportunities of social networks from another angle, Facebook
and Twitter are both making a concerted effort to woo publishers. Facebook's
algorithm tweak in August 2013 has increased the amount of traffic sent to news
sites. Buzzfeed saw a 69% jump during this time, and they were not the only
ones. In December 2013, Facebook gave us more insight.
"We've noticed that people enjoy seeing articles ... and so we're now paying
closer attention to what makes for high-quality content and how often articles
are clicked on ...
"Starting soon, we'll be doing a better job of distinguishing between a
high-quality article on a website versus a meme photo hosted somewhere other
than Facebook ... this means that high-quality articles you or others read may
show up a bit more prominently in your News Feed, and meme photos may show up a
bit less prominently."
(Is this the end of memes? Maybe so if Facebook gets its way)
The insight: Facebook is working to keep its users entertained with your
content
Your access: Leverage your Analytics prowess; you are an Analytics tiger!
Analyse your Facebook referral traffic comparing August-December 2013 with the
previous six-month period and the same period in 2012, and assess how much
impact the algorithm update had on your site. In the same article quoted above,
Facebook claims that they have increased the amount of traffic to media sites by
an average of 170%. If you did not see a significant jump it suggests that the
site is not sufficiently integrated into Facebook. The sort of numbers
referenced by Facebook (the 170%) are considerable, all publishers would love to
see traffic increases in this range, let this be your approach to re-evaluate
your Facebook strategy.
But wait, there's more
Beyond sending more traffic to publishers, Facebook is also working with
publishers to share the vast trove of data about what is trending so publishers
can incorporate it into their stories. Facebook's Public Feed API shares public
data and is open to anyone with the functionality. A second API, the Keyword
Insights API, is only available to a select number of news organisations. The
Keyword Insights API allows news organisations like CNN, Today Show, and BSkyB
access to programmatically search through Facebook's public data for anonymous
keyword data. This data can be sliced by gender, current city, and age range.
There are no plans yet to release it to a wider audience, but it seems
inevitable that (if successful) it will be rolled out in the future. (Note, an
email to Facebook about this has not yet been answered. I will update in the
comments if I hear more.)
The insight: other publishers are working with Facebook, if only in the sense
that they are incorporating new data sources for their users.
Your access: Shaming (gently!). Depending on the size of your client. The
Keyword Insights API isn't publicly available yet, but you can present
opportunities for anyone consistently producing content to get access to similar
data. For example, try Mass Relevance, a Facebook Preferred Marketing Developer,
which can provide insights and trends from Facebook slicing data by a variety of
metrics, including device.
What publishers could be doing
Now we have a general sense of how some publishers are trying to grow, I've
also compiled a short list of some of the opportunities or ideas that have not
been mentioned thus far. This list is based on stealing ideas from other
industries, general common sense, and no small amount of wishful thinking.
1) Embracing Google products
Google's range of products is staggering. For publishers this can lead to
confusion about how to use the products available. To address this, Google has
created Google Media Tools, a valuable hub designed to demystify many of the
products in the roster, explaining everything from hot searches and trends to
Google Earth to Google Crisis Response, and references examples of how
publishers are using these products. For example, NBC Today uses Google Trends
each Monday to give viewers a sense of what was popular over the weekend. At the
Google For Media Summit, hosted earlier in January, attendees tweeted about BBC
News' integration with Hangouts.
Quick note: Make sure you get it right. This screengrab of a Google search
for "bbc news" is from 22nd August 2013, not 2001...
Clearly, it can be difficult to implement, but do not give up. Again,
referring to Dr Pete's slide deck, as Google products increasingly appear in the
search results, pure organic search results will be forced lower down the page.
Embrace Google's products to maximise your client's chances of staying on the
first page.
The insight: Competing for organic rankings is only ever going to get you so
far. (Again, Dr Pete said so!) Encourage clients to embrace the suite of Google
products out there, in the spirit of trying new things and also offering new
products to the end users.
Your access point: Your expertise. Most people do not differentiate between
Google Search, Google News, Google Local, Google Trends, etc. Anything to do
with an internet search engine is your domain.
Your second access point: Training.
Offer your clients and their writers training in using these new products. As
an experienced consultant, there will inevitably be a few training slide decks
or "best practices" guides in your past. Use this didactic approach to showcase
your knowledge and support the clients when they start to use them. As with the
BBC example above, it might not be perfect immediately, but persevere.
2) Planning for change
"The pace of technological change will not abate, and to think of our current
time as a transition between two eras, rather than a continuum of change is a
mistake."
â Richard Gingras, Senior Director of News and Social Products at Google
The New York Times appears to have taken this advice seriously, for amidst the
redesign fanfare, the most important feature is the Times' decision to change
the back end. I interpret this as a commitment to the future; this fluidity is
admirable. As referenced in this Fast Co Labs summary of the redesign:
"The new system, however, is more dynamic. "We can continually iterate on the
site and take advantages of the trends as we see them happening, rather than
having to do a big unveil."
Insight: Change is the only constant. (this is probably true of more than just
technology used in the publishing industry)
Your access point: this will be the toughest sell of anything else recommended
in this post. Persuading clients that it is important to invest money in the
backend system without any proven ROI is difficult. I'd welcome any ideas in the
comments, but know this: It still has to be done. The best method I have so far
is to use sites like the New York Times as a case study. The theory being that
as they can present new ideas quickly, they get more press (possibly with
links), and maybe even more readers. By monitoring new products on The New York
Times and monitoring their search visibility using a tool like Searchmetrics,
you should hopefully see traffic growth. You can then present this data to your
clients. The good news is that you don't have to manually check the Times' site
everyday; instead, sign up for the free email digests from Mediagazer, as they
monitor new product developments.
3) Understanding paywall models
Paywalls are starting to work, and you can be certain that your clients will be
watching how competitors are starting to use them. As a consultant, it is
important that you understand the variety of paywalls out there and how to
implement them. These articles from SEO Book and Mashable are excellent
resources to get you started. Google also has some limited information about
using First Click Free, their solution for publishers wanting to charge for
their content whilst still appearing in the search results. The goal in this
instance is to develop an opinion on paywalls as well as an up-to-date idea of
how your competitors are using them (and if they are successful).
The insight: As paywalls are beginning to pay off, you will be asked about
them
Your access point: Forward planning. By researching ahead of time, you will be
ready with an opinion when asked (and you will be asked).
4) Putting their content to work
Publishers are in the enviable position of having plenty of content to play
with, however now it's a question of putting that content to work. Here are a
few ideas, some riskier than others.
i) Creating new page types
Creating new page types is a classic tactic to get more traffic. If this is
what your client is looking for, look at different ways of categorizing your
content.
As referenced in Sara Wachter-Boettcher's Content Everywhere, the BBC Food
pages tried this approach in 2011 by introducing pages organizing their content
by recipe and also by ingredient. This led to an increase of 150,000 in organic
traffic, and overall traffic doubled to 1.3 million visitors.
The insight: New page types lead to more traffic
Your access point: Grounding the creative task of thinking of new page types
within standard information architecture best practices. Abby Covert,
Information Architect extraordinaire, explains it well: there are 5 methods of
categorizing. Use these as a starting point for inspiration when thinking about
how to group your client's content:
On this theme, I would love to see news publishers in particular tagging their
content with zip-codes. I think it would prove a useful resource for tourists,
anyone looking to rent or buy in an area, historians, and even schools. This
could become even more useful on portable devices if there was an opportunity to
tie news stories of particular importance into existing map products. But I'm
getting carried away.
Some news organisations are already trying new page types, the AP has,
frankly, had some fun experimenting with Archive page types to commemorate
pivotal moments in history, and has used its own images and stories to add to
the narrative.
ii) Partnering with new businesses
Partnering up with other businesses can be seen as risky because success
cannot be guaranteed. One option would be to partner up with some of the newer
content creation services on the market. LinkedIn has just bought Pulse, a
service that pulls in news it believes will be of interest to you based on your
LinkedIn profile.There is also the wistful Kennedy app, which automatically
supplies iPhone users with context when taking notes and writing deep thoughts.
Insight: Your client's content can live on in different formats.
Your access point: Introducing this and other like ideas to your client. In
terms of publishers, the opportunity lies in being part of the potential
newsfeed as it is a valuable branding opportunity. You might be able to generate
revenue from supplying products like this with your content.
5) Looking to other niches within publishing and adapting their best ideas.
The academic eBook publishing industry is in a stage of rapid change as it
moves beyond the basic eBooks into much more exciting enhanced eBook territory.
The broader industry themes are:
Interactivity
Socially-connected groups
Adaptive eBooks
Interactivity
Bookry, a Welsh company, is just one of the many companies out there building
interactive components for eBook. The company specializes in building widgets
that allow eBook users to play with data tables. This allows users to see how
positive coefficient correlation looks and how the data points, when changed,
change the graph. By allowing users to play around with the data, you make them
think about the material itself. The most obvious use is to improve educational
resources, but there's no reason why it couldn't be applied in a broader sense
for all publishers.
Socially-connected groups
The idea behind this is that eBook publishers are trying to encourage
commentary and interaction with the course material. Most publishers are already
offering social sharing as a matter of form, however some eBook publishers are
going one step further and developing products that allow all the comments,
notes and questions to be stored in the cloud, all in one place. This allows the
user to keep track of where she has interacted but also is useful for professors
looking to grade a student on the quantity and quality of her interactions. It
would be incredibly useful for users to track all comments and interactions in
one place, other than on the site of the comment.
Adaptive technology
McGraw Hill launched what they call Smartbooks last year, designed to assess
the reader's understanding of the material and then adapt it based on her
knowledge of the subject.
Another company, Knewton, based in New York, specialize in adaptive technology
and offer education publishers the opportunity to personalise the reading
experience. The effect on students' pass rates has been impressive, which
supports the idea that tailoring content to the user's comprehension boosts
retention. Any publisher or content-producing site looking to launch a body of
work for a large audience of differing ages might find these developments
interesting.
This is an extremely top-level summary of some of the developments in the
eBook publishing sphere, as documented in the Digital Book World Conference held
last week in New York.
The insight: use developments in a related industry to inspire your clients,
in ebook publishing as per my example, the industry leaders are pushing ebook
content in new, exciting, immersive directions, adapt these ideas to suit your
customer's content.
Your access point: Your expert curation skills. By taking the time to
understand the broader industry trends, you can skim the very best ideas and
present them as opportunities to your client. If you assume responsibility for
industry developments, you save your clients time and headspace whilst also
expanding your sphere of influence.
Have you seen new publishing products, or been involved in building them? Do
you have any strong opinions about where content creation is heading next?
Please share in the comments below. In terms of reading around on this subject,
I've included a limited list of resources that I have found helpful.
Resources
Ebook Publishing - useful for quickly gleaming ebook industry trends
Future of StoryTelling - the best thing I watch; it covers the new ways to
tell stories
Understanding Media by Understand Google - a free and useful Coursera course
(sign up for the next semester!)
People
Tim O'Reilly - an ebook pioneer. He's thinking at least two years ahead.
Charlie Melcher - of Melcher media, founder of the Future of StoryTelling
mentioned above and also involved in Al Gore's Our Choice app, as referenced in
this Tedtalk.
Frank Rose - Frank Rose writes beautifully on immersive content, he will
inspire you to think about the role the audience plays in telling a story.
Tim Pool - now at Vice magazine. Tim's livestream of NY's Occupy Wall Street
has changed the perception of citizen journalism.
Jeff Jarvis - this post from 2008 has some thought provoking ideas.
Chris Danen - Fast Co Labs, tends to write about the future of media and often
brings in Fast Co examples.
Products
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Publishing Industry to SEO Consulting'
Posted by SarahKershaw
"Search has been less and less relevant since Facebook released News Feed. Now
we get the vast majority of our traffic via social, and about 1-2% from search"
â Chris Dannen from Fast Co Labs
"We benefited a ton from an early SEO audit thanks to IAC's SEO pros, but once
the right framework was in place, it's been up to us as content creators to
really dig deep into Google Analytics to determine where the opportunities
lieâ"
â Jordan Shakeshaft, editorial director of Life by DailyBurn
"None" was another person's response to my question about the role of SEO
within her company. "There's very little of actual value in it for us." This
from a respected British magazine.
In preparation for this post, I started thinking about publishers and their
plans for 2014, specifically their growth strategies for the coming year. My
thought was that as the publishing industry usually leads the way when it comes
to new content techniques and products, it is at the forefront of publishing
initiatives. As publishers blaze new trails, we as consultants have the
opportunity to learn by proxy, observing what has worked and what has not. These
observations can then be applied to our own clients' content creation. In this
post-panda arena, the scramble to produce high-quality, compelling content is as
real as ever, and lessons need to be learned fast. Let the publishing industry
be your guide; come, walk with me.
In researching this post, I spoke to a combination of editors, industry
analysts and publishing company employees. The quotes are representative of my
contacts and their responses, but it is in no way comprehensive for the
publishing industry as whole.
As per the quotes above, the sobering reality is that, at best, publishers see
SEO as just one small part of their marketing strategy. Moz's very own legend,
Dr. Pete, has been trying to tell us this for a while, encouraging the search
community to look beyond rankings. Our goal as consultants is to continue to add
value in this altogether more varied landscape. The good news is that we can if
we leverage our technical knowledge and use this to present some of the newer
ideas, beyond our usual scope, to our clients.
This post is an examination of some of the other opportunities publishers are
pursuing this year, along with my dreams for what they could be doing and some
tips on how to present these ideas to clients.
What are publishers doing for growth?
1) Investing in site redesigns
The internet was all aflutter earlier this month, when The New York Times
launched its site redesign. That project, in addition to generating buzz,
traffic, and links, was the site's first major redesign since 2006. The main
visual changes include:
Changing of fonts and font colours so it more closely resembles the print
edition. The links from the home page to the categories page are now black, not
blue for example.
Article comments now appear on the right-hand side of the article, allowing
comments to receive the same level of visibility as the article.
Infinite scroll, rather than pagination.
A much more minimal look on article pages with more white space.
This redesign freshens up the look of the page as a whole and the cleaner,
sparer UI is more in keeping with what other publications are doing. This video
from Fi talks us through its process for redesigning USAToday.com, which has
several design features in common with the Times' update.
The insight: Good design matters.
Your access point: When presenting ideas of this ilk to your clients, it is
important to be in cahoots with the designers. Your aim is to collaborate in
these projects, ideally from initial conception. The advantage of being an
outsider weighing in on a site redesign is that you are invariably not bound by
the limitations of a CMS or the like; you are free to see the site and where it
stands in relation to industry competitors with a detached view. You can
represent SEO and call on your experiences with redesigns to offer suggestions.
2) Embracing social
You probably already know that social networks are an increasingly important
means of discovery, and amongst the under-45s, they are the most popular method
of finding content. Social becomes more and more important as user groups get
younger. For example, 44% of 18- to 24-year-olds rely on social, versus just 19%
of users over 55. This is illustrated by this graph from the Reuters Institute's
Digital News Report 2013:
Clearly, if you wish to build long term trust with your users, social networks
are critical for getting your content in front of younger users. It goes without
saying that social networks are also now critical for engagement among all age
groups.
What is surprising is the extent to which publishers are still missing this
opportunity, whilst newer companies such as Upworthy and Buzzfeed are swooping
in and winning traffic. This recent article from the Media Briefing visualizes
how some of the media players are doing on Facebook, and the newsworthy part is
that none of the more established players feature at all. In short, they are not
getting it right. The winners in this particular data set are companies that
have been formed within the last eight years (Buzzfeed was formed in 2006,
Upworthy in 2012); the Huffington Post is the old guard here, and that is only
nine years old.
The results are clear Upworthy and Buzzfeed have mastered the sort of content
that gets people sharing. Whilst the audience may eventually tire of cats in
unlikely situations, photoshop-shaming, and listicles, you can be sure that both
companies are investing time and effort to evolve from their current strategy.
Mark Suster expanded on this idea in a recent post, saying "I think companies
like Upworthy can build really compelling businesses in the future â but
I'm willing to bet serious cash ... that it won't be by sticking to the playbook
[that is, writing content to generate as many social shares as possible] that
has worked tremendously well to date."
The insight: For all of the chatter about social networks, publishers are
still not getting it right.
Your access point: Present working in social networks as a series of
easy-to-implement A/B tests.
Using the Upworthy premise, as outlined below, clients have a quick, clean
testing method that should give them confidence to test their social network
content.
Upworthy produced a wildly popular slide deck back in 2012 that outlines some
of their tactics, which makes for an interesting read. The key takeaway,
regardless of the sort of content your client might produce, is the idea of
testing multiple headlines. Upworthy writes 25 different headlines for a post,
and then tests the headlines in two demographically similar cities within
Facebook for an hour or so. They then push the headline with more shares.
This is both agile and data-driven; keep this example in mind, as it's
deliciously simple and reasonably easy to implement. It can also be applied to
subheadings, images, and more. As consultants, A/B Testing is very much within
the traditional scope of your work. By using this experience (and the client's
trust in this experience) you are moving into new terrain via a familiar method.
Let social embrace you back
To approach the opportunities of social networks from another angle, Facebook
and Twitter are both making a concerted effort to woo publishers. Facebook's
algorithm tweak in August 2013 has increased the amount of traffic sent to news
sites. Buzzfeed saw a 69% jump during this time, and they were not the only
ones. In December 2013, Facebook gave us more insight.
"We've noticed that people enjoy seeing articles ... and so we're now paying
closer attention to what makes for high-quality content and how often articles
are clicked on ...
"Starting soon, we'll be doing a better job of distinguishing between a
high-quality article on a website versus a meme photo hosted somewhere other
than Facebook ... this means that high-quality articles you or others read may
show up a bit more prominently in your News Feed, and meme photos may show up a
bit less prominently."
(Is this the end of memes? Maybe so if Facebook gets its way)
The insight: Facebook is working to keep its users entertained with your
content
Your access: Leverage your Analytics prowess; you are an Analytics tiger!
Analyse your Facebook referral traffic comparing August-December 2013 with the
previous six-month period and the same period in 2012, and assess how much
impact the algorithm update had on your site. In the same article quoted above,
Facebook claims that they have increased the amount of traffic to media sites by
an average of 170%. If you did not see a significant jump it suggests that the
site is not sufficiently integrated into Facebook. The sort of numbers
referenced by Facebook (the 170%) are considerable, all publishers would love to
see traffic increases in this range, let this be your approach to re-evaluate
your Facebook strategy.
But wait, there's more
Beyond sending more traffic to publishers, Facebook is also working with
publishers to share the vast trove of data about what is trending so publishers
can incorporate it into their stories. Facebook's Public Feed API shares public
data and is open to anyone with the functionality. A second API, the Keyword
Insights API, is only available to a select number of news organisations. The
Keyword Insights API allows news organisations like CNN, Today Show, and BSkyB
access to programmatically search through Facebook's public data for anonymous
keyword data. This data can be sliced by gender, current city, and age range.
There are no plans yet to release it to a wider audience, but it seems
inevitable that (if successful) it will be rolled out in the future. (Note, an
email to Facebook about this has not yet been answered. I will update in the
comments if I hear more.)
The insight: other publishers are working with Facebook, if only in the sense
that they are incorporating new data sources for their users.
Your access: Shaming (gently!). Depending on the size of your client. The
Keyword Insights API isn't publicly available yet, but you can present
opportunities for anyone consistently producing content to get access to similar
data. For example, try Mass Relevance, a Facebook Preferred Marketing Developer,
which can provide insights and trends from Facebook slicing data by a variety of
metrics, including device.
What publishers could be doing
Now we have a general sense of how some publishers are trying to grow, I've
also compiled a short list of some of the opportunities or ideas that have not
been mentioned thus far. This list is based on stealing ideas from other
industries, general common sense, and no small amount of wishful thinking.
1) Embracing Google products
Google's range of products is staggering. For publishers this can lead to
confusion about how to use the products available. To address this, Google has
created Google Media Tools, a valuable hub designed to demystify many of the
products in the roster, explaining everything from hot searches and trends to
Google Earth to Google Crisis Response, and references examples of how
publishers are using these products. For example, NBC Today uses Google Trends
each Monday to give viewers a sense of what was popular over the weekend. At the
Google For Media Summit, hosted earlier in January, attendees tweeted about BBC
News' integration with Hangouts.
Quick note: Make sure you get it right. This screengrab of a Google search
for "bbc news" is from 22nd August 2013, not 2001...
Clearly, it can be difficult to implement, but do not give up. Again,
referring to Dr Pete's slide deck, as Google products increasingly appear in the
search results, pure organic search results will be forced lower down the page.
Embrace Google's products to maximise your client's chances of staying on the
first page.
The insight: Competing for organic rankings is only ever going to get you so
far. (Again, Dr Pete said so!) Encourage clients to embrace the suite of Google
products out there, in the spirit of trying new things and also offering new
products to the end users.
Your access point: Your expertise. Most people do not differentiate between
Google Search, Google News, Google Local, Google Trends, etc. Anything to do
with an internet search engine is your domain.
Your second access point: Training.
Offer your clients and their writers training in using these new products. As
an experienced consultant, there will inevitably be a few training slide decks
or "best practices" guides in your past. Use this didactic approach to showcase
your knowledge and support the clients when they start to use them. As with the
BBC example above, it might not be perfect immediately, but persevere.
2) Planning for change
"The pace of technological change will not abate, and to think of our current
time as a transition between two eras, rather than a continuum of change is a
mistake."
â Richard Gingras, Senior Director of News and Social Products at Google
The New York Times appears to have taken this advice seriously, for amidst the
redesign fanfare, the most important feature is the Times' decision to change
the back end. I interpret this as a commitment to the future; this fluidity is
admirable. As referenced in this Fast Co Labs summary of the redesign:
"The new system, however, is more dynamic. "We can continually iterate on the
site and take advantages of the trends as we see them happening, rather than
having to do a big unveil."
Insight: Change is the only constant. (this is probably true of more than just
technology used in the publishing industry)
Your access point: this will be the toughest sell of anything else recommended
in this post. Persuading clients that it is important to invest money in the
backend system without any proven ROI is difficult. I'd welcome any ideas in the
comments, but know this: It still has to be done. The best method I have so far
is to use sites like the New York Times as a case study. The theory being that
as they can present new ideas quickly, they get more press (possibly with
links), and maybe even more readers. By monitoring new products on The New York
Times and monitoring their search visibility using a tool like Searchmetrics,
you should hopefully see traffic growth. You can then present this data to your
clients. The good news is that you don't have to manually check the Times' site
everyday; instead, sign up for the free email digests from Mediagazer, as they
monitor new product developments.
3) Understanding paywall models
Paywalls are starting to work, and you can be certain that your clients will be
watching how competitors are starting to use them. As a consultant, it is
important that you understand the variety of paywalls out there and how to
implement them. These articles from SEO Book and Mashable are excellent
resources to get you started. Google also has some limited information about
using First Click Free, their solution for publishers wanting to charge for
their content whilst still appearing in the search results. The goal in this
instance is to develop an opinion on paywalls as well as an up-to-date idea of
how your competitors are using them (and if they are successful).
The insight: As paywalls are beginning to pay off, you will be asked about
them
Your access point: Forward planning. By researching ahead of time, you will be
ready with an opinion when asked (and you will be asked).
4) Putting their content to work
Publishers are in the enviable position of having plenty of content to play
with, however now it's a question of putting that content to work. Here are a
few ideas, some riskier than others.
i) Creating new page types
Creating new page types is a classic tactic to get more traffic. If this is
what your client is looking for, look at different ways of categorizing your
content.
As referenced in Sara Wachter-Boettcher's Content Everywhere, the BBC Food
pages tried this approach in 2011 by introducing pages organizing their content
by recipe and also by ingredient. This led to an increase of 150,000 in organic
traffic, and overall traffic doubled to 1.3 million visitors.
The insight: New page types lead to more traffic
Your access point: Grounding the creative task of thinking of new page types
within standard information architecture best practices. Abby Covert,
Information Architect extraordinaire, explains it well: there are 5 methods of
categorizing. Use these as a starting point for inspiration when thinking about
how to group your client's content:
On this theme, I would love to see news publishers in particular tagging their
content with zip-codes. I think it would prove a useful resource for tourists,
anyone looking to rent or buy in an area, historians, and even schools. This
could become even more useful on portable devices if there was an opportunity to
tie news stories of particular importance into existing map products. But I'm
getting carried away.
Some news organisations are already trying new page types, the AP has,
frankly, had some fun experimenting with Archive page types to commemorate
pivotal moments in history, and has used its own images and stories to add to
the narrative.
ii) Partnering with new businesses
Partnering up with other businesses can be seen as risky because success
cannot be guaranteed. One option would be to partner up with some of the newer
content creation services on the market. LinkedIn has just bought Pulse, a
service that pulls in news it believes will be of interest to you based on your
LinkedIn profile.There is also the wistful Kennedy app, which automatically
supplies iPhone users with context when taking notes and writing deep thoughts.
Insight: Your client's content can live on in different formats.
Your access point: Introducing this and other like ideas to your client. In
terms of publishers, the opportunity lies in being part of the potential
newsfeed as it is a valuable branding opportunity. You might be able to generate
revenue from supplying products like this with your content.
5) Looking to other niches within publishing and adapting their best ideas.
The academic eBook publishing industry is in a stage of rapid change as it
moves beyond the basic eBooks into much more exciting enhanced eBook territory.
The broader industry themes are:
Interactivity
Socially-connected groups
Adaptive eBooks
Interactivity
Bookry, a Welsh company, is just one of the many companies out there building
interactive components for eBook. The company specializes in building widgets
that allow eBook users to play with data tables. This allows users to see how
positive coefficient correlation looks and how the data points, when changed,
change the graph. By allowing users to play around with the data, you make them
think about the material itself. The most obvious use is to improve educational
resources, but there's no reason why it couldn't be applied in a broader sense
for all publishers.
Socially-connected groups
The idea behind this is that eBook publishers are trying to encourage
commentary and interaction with the course material. Most publishers are already
offering social sharing as a matter of form, however some eBook publishers are
going one step further and developing products that allow all the comments,
notes and questions to be stored in the cloud, all in one place. This allows the
user to keep track of where she has interacted but also is useful for professors
looking to grade a student on the quantity and quality of her interactions. It
would be incredibly useful for users to track all comments and interactions in
one place, other than on the site of the comment.
Adaptive technology
McGraw Hill launched what they call Smartbooks last year, designed to assess
the reader's understanding of the material and then adapt it based on her
knowledge of the subject.
Another company, Knewton, based in New York, specialize in adaptive technology
and offer education publishers the opportunity to personalise the reading
experience. The effect on students' pass rates has been impressive, which
supports the idea that tailoring content to the user's comprehension boosts
retention. Any publisher or content-producing site looking to launch a body of
work for a large audience of differing ages might find these developments
interesting.
This is an extremely top-level summary of some of the developments in the
eBook publishing sphere, as documented in the Digital Book World Conference held
last week in New York.
The insight: use developments in a related industry to inspire your clients,
in ebook publishing as per my example, the industry leaders are pushing ebook
content in new, exciting, immersive directions, adapt these ideas to suit your
customer's content.
Your access point: Your expert curation skills. By taking the time to
understand the broader industry trends, you can skim the very best ideas and
present them as opportunities to your client. If you assume responsibility for
industry developments, you save your clients time and headspace whilst also
expanding your sphere of influence.
Have you seen new publishing products, or been involved in building them? Do
you have any strong opinions about where content creation is heading next?
Please share in the comments below. In terms of reading around on this subject,
I've included a limited list of resources that I have found helpful.
Resources
Ebook Publishing - useful for quickly gleaming ebook industry trends
Future of StoryTelling - the best thing I watch; it covers the new ways to
tell stories
Understanding Media by Understand Google - a free and useful Coursera course
(sign up for the next semester!)
People
Tim O'Reilly - an ebook pioneer. He's thinking at least two years ahead.
Charlie Melcher - of Melcher media, founder of the Future of StoryTelling
mentioned above and also involved in Al Gore's Our Choice app, as referenced in
this Tedtalk.
Frank Rose - Frank Rose writes beautifully on immersive content, he will
inspire you to think about the role the audience plays in telling a story.
Tim Pool - now at Vice magazine. Tim's livestream of NY's Occupy Wall Street
has changed the perception of citizen journalism.
Jeff Jarvis - this post from 2008 has some thought provoking ideas.
Chris Danen - Fast Co Labs, tends to write about the future of media and often
brings in Fast Co examples.
Products
Circa
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