Build Great Backlinks has posted a new item, 'The Best of 2013: The Top Posts
and People on the Moz Blog'
Posted by Trevor-Klein
Continuing what has become an annual tradition at Moz, on the last day of 2013
we're excited to bring you a roundup of the very best of this year's posts on
the Moz Blog and YouMoz.
After asking Roger to work overtime to crunch these numbers, we've whittled
the posts down to the cream of the crop, and have organized them in several
different ways:
The top Moz Blog posts by unique pageviews
The top YouMoz Blog posts by unique pageviews
The top Moz Blog posts by number of thumbs up
The top Moz Blog posts by number of comments
The top Moz Blog posts by number of linking root domains
The top comments from our community by number of thumbs up
The most active community members by number of comments posted
This year's data was more difficult to collect, as we migrated to our new
domain in May. My eternal gratitude goes to Cyrus Shepard for helping make sure
the right numbers were pulled.
Top posts by unique pageviews
One of the quintessential metrics for a piece of content is its number of
unique pageviews. Reflecting our audience's thirst for advanced SEO, content
marketing, and data analysis, these posts were winners from the very beginning.
1. 10 Tools for Creating Infographics and VisualizationsFebruary 6 - Posted by
Miranda Rensch
Communicating visually is one of the most effective ways to explain complex
concepts and relationships, both internally with your teammates and externally
with your clients. Our very own Product Manager, Miranda Rensch, offers a list
of tools you can use to create beautiful visualizations and let your visual
communication skills shine!
2. A Visual Guide to Keyword Targeting and On-Page OptimizationAugust 6 -
Posted by randfish
As the "O" in SEO has broadened in scope, the most effective elements of
on-page optimization have changed. While there is arguably no "perfectly
optimized page," this update to a 2009 post provides a comprehensive guide to
steer you in the right direction.
3. The Web Developer's SEO Cheat Sheet 2.0August 29 - Posted by DannyDover
It is my honor and privilege today to introduce the brand new version of The
Web Developer's SEO Cheat Sheet. This free and downloadable cheat sheet covers
all of the important SEO code and best practices that are needed by online
marketers and developers.
4. How to Rank: 25 Step SEO Master BlueprintMay 14 - Posted by Cyrus-Shepard
If youâre like most SEOs, you spend hours each week reading the latest
SEO tactics and search engine tidbits. We spend hours learning, but does 90% of
it change what we actually do - that is, the basic work of ranking a web page
for search? To lend a hand, let me introduce the 25 Step SEO Master Blueprint.
5. Amazing Correlation Between Google +1s and Higher Search RankingsAugust 20 -
Posted by Cyrus-Shepard
This year's Search Ranking Factors Study showed a very strong correlation
between Google +1s and higher rankings, and there's a compelling reason why.
Google+ was built for SEO, and is far better optimized for search than other
platforms.
6. Holy Grail of eCommerce Conversion Optimization - 91 Point Checklist and
InfographicJanuary 24 - Posted by CueBlocks.com
Invest in building filthy rich user experience, consistently and throughout
your store. That is what stores with deeper pockets (like ASOS, Zappos, and
JCPenney) do to achieve better conversion rate than your store. This article
will take you away from usual Search Engine Optimization stuff to where the real
money lies - Conversion Rate Optimization. What you do with the visitors you
bring to your website?
7. 2013 Search Engine Ranking FactorsJuly 9 - Posted by Matt Peters
The results are in! Come check out Moz's 2013 Ranking Factors as Matt Peters
presents a preview of the results from the survey and correlation study.
8. Goodbye SEOmoz. Hello Moz!May 29 - Posted by randfish
For the last two years, the 130+ Mozzers across product, engineering,
marketing, and operations have been working to transform this company to the
next stage of our evolution. Today, that incredibly demanding, intense, but
ultimately rewarding process has reached its first goal. I'm excited to announce
that as of today, SEOmoz is formally transitioning our brand, our products, our
company name, and all of our efforts to Moz.
9. The 100 Best Free SEO Tools & Resources for Every Challenge -
InteractiveJuly 31 - Posted by Cyrus-Shepard
At Moz, we love using premium SEO Tools. Paid tools are essential when you
need advanced features, increased limits, historical features, or professional
support. For other tasks, a free tool does the trick. Here you'll find a
collection of the 100 best completely free tools, tools with both free and paid
options, and free trials.
10. When Keyword (not provided) is 100 Percent of Organic Referrals, What
Should Marketers Do? - Whiteboard FridaySeptember 24 - Posted by randfish
The rate at which Google is lumping keywords into "(not provided)" has
skyrocketed in the last month, leading to a huge drop in referral data and
speculation that 100% of keywords will soon be masked. In this special
Whiteboard Tuesday, Rand covers what marketers can do to make up for this
drastic change.
Top YouMoz posts by unique pageviews
We saw some real gems come through the YouMoz queue this year. Most of these
posts were promoted to the Moz Blog shortly after they were published, as their
resonance with the Moz community was readily apparent.
1. Holy Grail of eCommerce Conversion Optimization - 91 Point Checklist and
InfographicJanuary 24 - Posted by CueBlocks.com
Invest in building filthy rich user experience, consistently and throughout
your store. That is what stores with deeper pockets (like ASOS, Zappos, and
JCPenney) do to achieve better conversion rate than your store. This article
will take you away from usual Search Engine Optimization stuff to where the real
money lies - Conversion Rate Optimization. What you do with the visitors you
bring to your website?
2. 96 Quick SEO Wins - What Can You Do With an Hour?January 31 - Posted by
kevingibbons
If you want to win at SEO in 2013, you must commit to a solid long-term
strategy. However, that's not to say you can't build small wins into your
long-term strategy to strengthen it along the way. Here are 96 quick wins you
can implement in an hour or less to see tremendous results.
3. The Ultimate Guide to Advanced Guest BloggingJanuary 21 - Posted by
Pratik.Dholakiya
With "content marketing" being the indisputable SEO buzzword of 2012, we can
expect 2013 to see an onslaught of marketers trying to build links with guest
posts. The growth in this market will cause some sites to lower their guest
posting standards, others to raise them, and still more to stop accepting them
altogether. We're going to help you combat this by sharing how we got posts up
on ProBlogger and Search Engine Journal, and by introducing you to our strategy
for success with our clients.
4. 33 Link Building Questions AnsweredApril 4 - Posted by Rhea Drysdale
When it comes to link building idea generation, the sky's the limit! In
today's post, Rhea Drysdale offers her tips for best practices and a
philosophical approach to link building that will help bring your ideas to life.
5. Post-Penguin Anchor Text Case StudyJanuary 15 - Posted by Court Tuttle
It's no secret that Google's Panda and Penguin updates caused a lot of panic.
Although I'm pretty turned off to information about these updates, I've been
really interested in the anchor text issues surrounding the Penguin update. If
sites that have over-optimized anchors lost traffic due to the update, it seems
to make sense that sites can move up with relatively few (or without any)
anchored links. I wanted to test that idea and decided that it was time for a
good, old fashioned case study.
6. 5 Lessons Learned from 100,000 Usability StudiesAugust 28 - Posted by Phil
Sharp
As helpful as analytics can be, they simply can't give as complete a picture
as usability studies. This post walks through five of the most important lessons
we've learned after performing hundreds of thousands of those studies.
7. How to Build Links to Your Blog - A Case StudyJune 4 - Posted by
MatthewBarby
After a month or so of development, my site was finally ready and I wanted to
start thinking about how to get some traffic going on the website. Whilst paid
advertising and social media were a huge part of the strategy, I knew that
appearing in the search engines for a wide selection of long-tail phrases was
going to be instrumental to the blog's success. This is when I began developing
my link building strategy and, after trialing out some very successful
approaches, I've decided to now share my link building tactics with you all.
8. How to Build a Great Online Fashion Brand - 34 Things that Really Amazing
Fashion Retailers DoMay 30 - Posted by ILoveFashionRetail.com
Despite the title, we believe this article can also benefit and inspire
retailers in industries outside fashion and help them find their way to success
in online retail business in this new social commerce environment. The Online
Fashion Retail Industry, particularly at the luxury end, seems to be doing well.
Over the past few years, lot of money has been invested into fashion retail
businesses. Valuations of these companies might seem inflated, but these
companies are growing fast with the help of clear revenue stream and a value
proposition thatâs beyond price advantage. But while some companies in
Fashion technology are successfully raising more money and growing, there is
another segment thatâs struggling to survive. These businesses are
stalling because of their ability to adopt to the shift in the media consumption
behavior of the consumer.
9. How To Blog Successfully About AnythingJanuary 9 - Posted by TannerC
In order to create a successful blog, you must be passionately curious about
the topic you're covering. Learn how to turn even the most uninteresting blog
post topics into goldmines with these tips for successful bloggers.
10. Semantic Web and Link Building without Links > The Future for
SEO?January 10 - Posted by simonpenson
Randâs recent WBF about co-occurrence was a real wake up call for those
still transfixed with link building practices of old. While anchor text based
links may still have some effect, there is little arguing the fact that the
factorâs importance is dwindling. In its place are things like social
signals, link age, and, most importantly, a growing reliance on relevancy and
how that is deciphered.
Top Moz Blog posts by number of thumbs up
While something of a controversial metric, there's nothing more satisfying for
an author (or, I admit, for a publisher!) than seeing a bunch of thumbs up.
These posts went far beyond satisfying, though, garnering jaw-dropping numbers
of thumbs up.
1. How to Rank: 25 Step SEO Master BlueprintMay 14 - Posted by Cyrus-Shepard
If youâre like most SEOs, you spend hours each week reading the latest
SEO tactics and search engine tidbits. We spend hours learning, but does 90% of
it change what we actually do - that is, the basic work of ranking a web page
for search? To lend a hand, let me introduce the 25 Step SEO Master Blueprint.
2. Goodbye SEOmoz. Hello Moz!May 29 - Posted by randfish
For the last two years, the 130+ Mozzers across product, engineering,
marketing, and operations have been working to transform this company to the
next stage of our evolution. Today, that incredibly demanding, intense, but
ultimately rewarding process has reached its first goal. I'm excited to announce
that as of today, SEOmoz is formally transitioning our brand, our products, our
company name, and all of our efforts to Moz.
3. The Web Developer's SEO Cheat Sheet 2.0August 29 - Posted by DannyDover
It is my honor and privilege today to introduce the brand new version of The
Web Developer's SEO Cheat Sheet. This free and downloadable cheat sheet covers
all of the important SEO code and best practices that are needed by online
marketers and developers.
4. A Visual Guide to Keyword Targeting and On-Page OptimizationAugust 6 -
Posted by randfish
As the "O" in SEO has broadened in scope, the most effective elements of
on-page optimization have changed. While there is arguably no "perfectly
optimized page," this update to a 2009 post provides a comprehensive guide to
steer you in the right direction.
5. Amazing Correlation Between Google +1s and Higher Search RankingsAugust 20
- Posted by Cyrus-Shepard
This year's Search Ranking Factors Study showed a very strong correlation
between Google +1s and higher rankings, and there's a compelling reason why.
Google+ was built for SEO, and is far better optimized for search than other
platforms.
6. 2013 Search Engine Ranking FactorsJuly 9 - Posted by Matt Peters
The results are in! Come check out Moz's 2013 Ranking Factors as Matt Peters
presents a preview of the results from the survey and correlation study.
7. The 100 Best Free SEO Tools & Resources for Every Challenge -
InteractiveJuly 31 - Posted by Cyrus-Shepard
At Moz, we love using premium SEO Tools. Paid tools are essential when you
need advanced features, increased limits, historical features, or professional
support. For other tasks, a free tool does the trick. Here you'll find a
collection of the 100 best completely free tools, tools with both free and paid
options, and free trials.
8. From Zero to a Million: 20 Lessons for Starting an Internet Marketing
AgencySeptember 19 - Posted by NiftyMarketing
This post is a combination of stories and thoughts about what I have gone
through building Nifty Marketing. My hope is that a few of you who are out there
hustling will benefit from doing some of the things that I did, and most of the
things that I didn't.
9. Post-Penguin Anchor Text Case StudyJanuary 15 - Posted by Court Tuttle
It's no secret that Google's Panda and Penguin updates caused a lot of panic.
Although I'm pretty turned off to information about these updates, I've been
really interested in the anchor text issues surrounding the Penguin update. If
sites that have over-optimized anchors lost traffic due to the update, it seems
to make sense that sites can move up with relatively few (or without any)
anchored links. I wanted to test that idea and decided that it was time for a
good, old fashioned case study.
10. Holy Grail of eCommerce Conversion Optimization - 91 Point Checklist and
InfographicJanuary 24 - Posted by CueBlocks.com
Invest in building filthy rich user experience, consistently and throughout
your store. That is what stores with deeper pockets (like ASOS, Zappos, and
JCPenney) do to achieve better conversion rate than your store. This article
will take you away from usual Search Engine Optimization stuff to where the real
money lies - Conversion Rate Optimization. What you do with the visitors you
bring to your website?
Top Moz Blog posts by number of comments
Some posts, whether due to truly inspired content or a touch of controversy
(sometimes a little of both), generate significantly more discussion in the
comments than others. Many of these have comment sections that dwarf the
original post! We expected our announcement of the shift from SEOmoz to Moz
would drum up some conversation, but we were interested to take a look at the
rest of this list.
1. Goodbye SEOmoz. Hello Moz!May 29 - Posted by randfish
For the last two years, the 130+ Mozzers across product, engineering,
marketing, and operations have been working to transform this company to the
next stage of our evolution. Today, that incredibly demanding, intense, but
ultimately rewarding process has reached its first goal. I'm excited to announce
that as of today, SEOmoz is formally transitioning our brand, our products, our
company name, and all of our efforts to Moz.
2. Post-Penguin Anchor Text Case StudyJanuary 15 - Posted by Court Tuttle
It's no secret that Google's Panda and Penguin updates caused a lot of panic.
Although I'm pretty turned off to information about these updates, I've been
really interested in the anchor text issues surrounding the Penguin update. If
sites that have over-optimized anchors lost traffic due to the update, it seems
to make sense that sites can move up with relatively few (or without any)
anchored links. I wanted to test that idea and decided that it was time for a
good, old fashioned case study.
3. The Ultimate Guide to Advanced Guest BloggingJanuary 21 - Posted by
Pratik.Dholakiya
With âcontent marketingâ being the indisputable SEO buzzword of
2012, we can expect 2013 to see an onslaught of marketers trying to build links
with guest posts. The growth in this market will cause some sites to lower their
guest posting standards, others to raise them, and still more to stop accepting
them altogether. We're going to help you combat this by sharing how we got posts
up on ProBlogger and Search Engine Journal, and by introducing you to our
strategy for success with our clients.
4. Why We Can't Just Be SEOs Anymore - Whiteboard FridayMay 2 - Posted by
randfish
There's a movement happening in our industry where many SEOs are changing
their titles and practices to "inbound marketing." Where did this shift
originate, and how is it shaping our industry at large? In today's Whiteboard
Friday, Rand shares his thoughts on why we can't just be SEOs anymore if we're
aiming for the bigger picture.
5. The 100 Best Free SEO Tools & Resources for Every Challenge -
InteractiveJuly 31 - Posted by Cyrus-Shepard
At Moz, we love using premium SEO Tools. Paid tools are essential when you
need advanced features, increased limits, historical features, or professional
support. For other tasks, a free tool does the trick. Here you'll find a
collection of the 100 best completely free tools, tools with both free and paid
options, and free trials.
6. Ultimate Guide to Google Penalty RemovalOctober 14 - Posted by
PinpointDesigns
A few months back, I wrote an article on Moz all about a penalty our web
agency received for unnatural links pointing to our website. At first, this was
a bit of a shock to the system, but since then, we've learned so much about
Google's webmaster guidelines and we've helped lots of companies get their
businesses back on track and remove manual penalties associated with their
websites.
7. From Zero to a Million: 20 Lessons for Starting an Internet Marketing
AgencySeptember 19 - Posted by NiftyMarketing
This post is a combination of stories and thoughts about what I have gone
through building Nifty Marketing. My hope is that a few of you who are out there
hustling will benefit from doing some of the things that I did, and most of the
things that I didn't.
8. When Keyword (not provided) is 100 Percent of Organic Referrals, What
Should Marketers Do? - Whiteboard TuesdaySeptember 24 - Posted by randfish
The rate at which Google is lumping keywords into "(not provided)" has
skyrocketed in the last month, leading to a huge drop in referral data and
speculation that 100% of keywords will soon be masked. In this special
Whiteboard Tuesday, Rand covers what marketers can do to make up for this
drastic change.
9. How to Rank: 25 Step SEO Master BlueprintMay 14 - Posted by Cyrus-Shepard
If youâre like most SEOs, you spend hours each week reading the latest
SEO tactics and search engine tidbits. We spend hours learning, but does 90% of
it change what we actually do - that is, the basic work of ranking a web page
for search? To lend a hand, let me introduce the 25 Step SEO Master Blueprint.
10. Why Google Analytics Tagging Matters - Whiteboard FridayMarch 15 - Posted
by RachaelGerson
In today's Whiteboard Friday, Rachael Gerson sheds some light on "dark social"
and explains why tagging in Google Analytics improves the accuracy of your
referrals. Take credit for the work that you're doing, and tag your links!
Top Moz Blog posts by number of linking root domains
It just wouldn't seem right to use unique pageviews, thumbs, and comments to
judge an SEO-focused blog without throwing in linking root domains as well.
Using data from Open Site Explorer, here are the 10 posts that garnered the most
attention from unique domains across the web.
1. Amazing Correlation Between Google +1s and Higher Search RankingsAugust 20
- Posted by Cyrus-Shepard
This year's Search Ranking Factors Study showed a very strong correlation
between Google +1s and higher rankings, and there's a compelling reason why.
Google+ was built for SEO, and is far better optimized for search than other
platforms.
2. 2013 Search Engine Ranking FactorsJuly 9 - Posted by Matt Peters
The results are in! Come check out Moz's 2013 Ranking Factors as Matt Peters
presents a preview of the results from the survey and correlation study.
3. When Keyword (not provided) is 100 Percent of Organic Referrals, What
Should Marketers Do? â Whiteboard TuesdaySeptember 24 - Posted by randfish
The rate at which Google is lumping keywords into "(not provided)" has
skyrocketed in the last month, leading to a huge drop in referral data and
speculation that 100% of keywords will soon be masked. In this special
Whiteboard Tuesday, Rand covers what marketers can do to make up for this
drastic change.
4. Goodbye SEOmoz. Hello Moz!May 29 - Posted by randfish
For the last two years, the 130+ Mozzers across product, engineering,
marketing, and operations have been working to transform this company to the
next stage of our evolution. Today, that incredibly demanding, intense, but
ultimately rewarding process has reached its first goal. I'm excited to announce
that as of today, SEOmoz is formally transitioning our brand, our products, our
company name, and all of our efforts to Moz.
5. The Web Developer's SEO Cheat Sheet 2.0August 29 - Posted by DannyDover
It is my honor and privilege today to introduce the brand new version of The
Web Developer's SEO Cheat Sheet. This free and downloadable cheat sheet covers
all of the important SEO code and best practices that are needed by online
marketers and developers.
6. A Visual Guide to Keyword Targeting and On-Page OptimizationAugust 6 -
Posted by randfish
As the "O" in SEO has broadened in scope, the most effective elements of
on-page optimization have changed. While there is arguably no "perfectly
optimized page," this update to a 2009 post provides a comprehensive guide to
steer you in the right direction.
7. How Website Speed Actually Impacts Search RankingAugust 1 - Posted by
Zoompf
Google has long stated website performance will impact search ranking, but
what exactly does this mean? In this article, Zoompf researches over 40
different speed metrics to determine the most impactful performance changes you
can make to your website to improve search ranking.
8. 10 Tools for Creating Infographics and VisualizationsFebruary 6 - Posted by
Miranda.Rensch
Communicating visually is one of the most effective ways to explain complex
concepts and relationships, both internally with your teammates and externally
with your clients. Our very own Product Manager, Miranda Rensch, offers a list
of tools you can use to create beautiful visualizations and let your visual
communication skills shine!
9. The SEO of Responsive Web DesignJanuary 28 - Posted by Kristina Kledzik
Will Critchlow announced back in November that Distilled's blog was updated
with a new responsive design, but it occurred to me recently that we never went
into the specifics of why responsive web design is so great. It's been a hot
topic in online marketing for the past few months, but is it really going to
become an industry standard? Short answer: yep.
10. How to Rank: 25 Step SEO Master BlueprintMay 14 - Posted by Cyrus-Shepard
If youâre like most SEOs, you spend hours each week reading the latest
SEO tactics and search engine tidbits. We spend hours learning, but does 90% of
it change what we actually do - that is, the basic work of ranking a web page
for search? To lend a hand, let me introduce the 25 Step SEO Master Blueprint.
Top comments by number of thumbs up
We're always impressed by the discussions we see in the comments below blog
posts. In addition to the great many insightful points that add to what the
authors say, one of our favorite parts is the support our community members show
for one another. Here are the most thumbed-up comments from 2013.
1. Stephan_Boehringer | September 24 When Keyword (not provided) is 100 Percent
of Organic Referrals, What Should Marketers Do? - Whiteboard Tuesday
2. gfiorelli1 | July 19 Heart to Heart About Link Building - Whiteboard Friday
3. MarkTraphagen | August 20 Amazing Correlation Between Google +1s and Higher
Search Rankings
4. jcolman | May 29 Goodbye SEOmoz. Hello Moz!
5. randfish | August 29 The Web Developer's SEO Cheat Sheet 2.0
6. Dr-Pete | April 15 The Difference Between Penguin and an Unnatural Links
Penalty (and some info on Panda too)
7. Bill Sebald | July 16 9 Experts and a Summary: What Makes an Ideal SEO
Employee?
8. KeriMorgret | February 7 Going Beyond Moz Metrics to Answer: "Why is this
Site Outranking Me?"
9. evolvingSEO | February 12 Stop Clicking Here! 7 Superior SEO Alternatives to
Generic Links
10. KeriMorgret | March 8 6 Ways to Use Fresh Links & Mentions to Improve Your
Marketing Efforts - Whiteboard Friday
Most active users by number of comments
While quality certainly trumps quantity in most cases, we're continuously
impressed by the ability of our community members to cover both bases. On
average, the folks on this list (which intentionally omits our own staff and
associates) have left a comment on every second or third post we've published,
and we couldn't appreciate their contributions more.
1. Charles_SEO
mozPoints: 516 | Rank: 161
2. Spook SEO
mozPoints: 259 | Rank: 350
3. Brahmadas
mozPoints: 341 | Rank: 248
4. Dubs
mozPoints: 946 | Rank: 85
5. steviephil
mozPoints: 1,030 | Rank: 77
6. paints-n-design
mozPoints: 224 | Rank: 435
7. danatanseo
mozPoints: 3,298 | Rank: 10
8. manishbhalla
mozPoints: 230 | Rank: 422
9. skifr
mozPoints: 234 | Rank: 407
10. Matt-Antonino
mozPoints: 1,681 | Rank: 36
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/dRfKcCRiK3I/the-best-of-2013
You received this e-mail because you asked to be notified when new updates are
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Best regards,
Build Great Backlinks
peter.clarke@designed-for-success.com
Tuesday 31 December 2013
Monday 30 December 2013
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Foursquare Quietly Unlocks Its Own
Local Data Aggregator Badge'
Posted by David-Mihm
I was wrong about Foursquare.
While five of my 2013 local search prognostications came to fruition, my sixth
predictionâthat Foursquare would be boughtâdoesn't look like it will
(unless Apple has silently acquired Foursquare in the last couple of days).
In fact, Foursquare has been turning away from an acquisition path, setting
off on a fundraising spree in 2013. While this quest for cash has struck some
analysts as a desperate tactic, PR from the company indicates that it remains
focused on growing its userbase and its revenues for the foreseeable future.
It's one of the few companies in tech to successfully address both sides of the
merchant and consumer marketplace, and as a result, might even have a chance at
an IPO.
As the company matures, we hear less and less about mayorships, badges, and
social gamificationâperhaps a tacit admission that checkins are indeed
dying as the motivational factor underlying usage of Foursquare.
Foursquare: the data aggregator
Instead, the company is pivoting into a self-described position as "the
location layer for the Internet."
Google, Bing, Nokia, and other mapping companies have built their own much
broader location layers to varying degrees of success, but it's the human
activity associated with location data that makes Foursquare unique. Its growing
database of keyword-rich tips and comments and widening network of social
interactions even make predictive recommendations possible.
But I'm considerably less excited about these consumer-facing recommendations
than I am about Foursquare's data play. If "location layer for the internet" is
not a synonym for "data aggregator," I'm not sure what would be.
In the last several months, Foursquare has been prompting its users to provide
business details about the places they check-in at, like whether a business has
wi-fi, its relative price range, delivery and payment options, and more. It's
also accumulating one of the biggest photo libraries in all of local search. For
companies that have not yet built their own services like StreetView and
Mapmaker, Foursquare "ground truth" position is enviable.
So from my standpoint, Foursquare's already achieved the status of a major
data aggregator, and seems to have its sights set on becoming the data
aggregator.
Foursquare: The Data Aggregator?
That statement would have sounded preposterous 18 months ago, with "only" 15
million users and 250,000 claimed venues.
But while many of us in the local search space have been distracted by the
shiny objects of Google+ Local and Facebook Graph Search, Foursquare has struck
deals with the two largest up-and-coming social apps (Instagram and Pinterest)
to provide the location backbone for their geolocation features. Not to mention
Uber, WhatsApp, and a host of other conversational and transactional apps.
And buried in the December 5th TechCrunch article about Foursquare's latest
iOS release was this throwaway line:
"Foursquare has a sharing deal with Apple already â it's one of over a
dozen contributors to Apple's Maps data."
So, doing some quick math, we have
Foursquare's ~20 million users (U.S.)
Apple Maps' 35 million users (U.S.)
Instagram's 50 million users (U.S.)
Pinterest's 55 million users (U.S.)
All of a sudden that's a substantial number of people contributing location
information to Foursquare. Granted, there's considerable overlap in those users,
but even a conservative 80-100 million would be a pretty large number of
touchpoints.
In fact, one thing that Wil Reynolds and I realized at a recent get-together
in San Diego is that for many people outside the tech world, Foursquare and
Instagram are basically the same app (see screenshots below). I'm seeing more
and more of my decidedly non-techie Instagram friends tagging their photos with
location. And avid Foursquare users like Matthew Brown have always made
photography their primary network activity.
Providing the geographic foundation for two appsâPinterest and
Instagramâthat are far more popular than Foursquare gives it a strong
running start on laying the location foundation for the Internet.
What's next for Foursquare?
While Facebook is undoubtedly building its own location layer, Zuckerberg and
company have long ignored local search. And they've got plenty of other short-
and mid-term priorities. Exposing Facebook check-in data to the extent
Foursquare has, and forcing Instagram to update a very successful API
integration, would seem to be pretty far down the list.
As I suggested in my Local Search Ecosystem update in August, to challenge
established players like Infogroup, Neustar, and Acxiom, in the long run
Foursquare does need to build out its index considerably beyond the current
sweetspots of food, drink, and entertainment.
But in the short run, the quality and depth of Foursquare's popular venue
information in major cities gives start-up app developers everything they need
to launch and attract users to their apps. And Foursquare's independence from
Google, Facebook, and Apple is appealing for many of themâparticularly for
non-U.S. app developers who have a hard time finding publicly-available location
databases outside of Google or Facebook.
Foursquare's success with Instagram and Pinterest has created a
self-perpetuating growth strategy: it will continue to be the location API of
choice for most "hot" local startups.
TL;DR
Foursquare venues have been contributing to a business's citation profile for
years, so hopefully most of you have included venue creation and management in
your local SEO service packages already. Even if you optimize non-retail
locations like insurance agencies, accounting offices, and the like, make one of
your 2014 New Year's resolutions be a higher level of engagement with
Foursquare.
The bottom line is that irrespective of its user growth and beyond just SEO,
Foursquare is going to get more important to the SoLoMo ecosystem in the coming
year.
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/i3dukj-i1HA/foursquare-as-data-aggregator
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
Local Data Aggregator Badge'
Posted by David-Mihm
I was wrong about Foursquare.
While five of my 2013 local search prognostications came to fruition, my sixth
predictionâthat Foursquare would be boughtâdoesn't look like it will
(unless Apple has silently acquired Foursquare in the last couple of days).
In fact, Foursquare has been turning away from an acquisition path, setting
off on a fundraising spree in 2013. While this quest for cash has struck some
analysts as a desperate tactic, PR from the company indicates that it remains
focused on growing its userbase and its revenues for the foreseeable future.
It's one of the few companies in tech to successfully address both sides of the
merchant and consumer marketplace, and as a result, might even have a chance at
an IPO.
As the company matures, we hear less and less about mayorships, badges, and
social gamificationâperhaps a tacit admission that checkins are indeed
dying as the motivational factor underlying usage of Foursquare.
Foursquare: the data aggregator
Instead, the company is pivoting into a self-described position as "the
location layer for the Internet."
Google, Bing, Nokia, and other mapping companies have built their own much
broader location layers to varying degrees of success, but it's the human
activity associated with location data that makes Foursquare unique. Its growing
database of keyword-rich tips and comments and widening network of social
interactions even make predictive recommendations possible.
But I'm considerably less excited about these consumer-facing recommendations
than I am about Foursquare's data play. If "location layer for the internet" is
not a synonym for "data aggregator," I'm not sure what would be.
In the last several months, Foursquare has been prompting its users to provide
business details about the places they check-in at, like whether a business has
wi-fi, its relative price range, delivery and payment options, and more. It's
also accumulating one of the biggest photo libraries in all of local search. For
companies that have not yet built their own services like StreetView and
Mapmaker, Foursquare "ground truth" position is enviable.
So from my standpoint, Foursquare's already achieved the status of a major
data aggregator, and seems to have its sights set on becoming the data
aggregator.
Foursquare: The Data Aggregator?
That statement would have sounded preposterous 18 months ago, with "only" 15
million users and 250,000 claimed venues.
But while many of us in the local search space have been distracted by the
shiny objects of Google+ Local and Facebook Graph Search, Foursquare has struck
deals with the two largest up-and-coming social apps (Instagram and Pinterest)
to provide the location backbone for their geolocation features. Not to mention
Uber, WhatsApp, and a host of other conversational and transactional apps.
And buried in the December 5th TechCrunch article about Foursquare's latest
iOS release was this throwaway line:
"Foursquare has a sharing deal with Apple already â it's one of over a
dozen contributors to Apple's Maps data."
So, doing some quick math, we have
Foursquare's ~20 million users (U.S.)
Apple Maps' 35 million users (U.S.)
Instagram's 50 million users (U.S.)
Pinterest's 55 million users (U.S.)
All of a sudden that's a substantial number of people contributing location
information to Foursquare. Granted, there's considerable overlap in those users,
but even a conservative 80-100 million would be a pretty large number of
touchpoints.
In fact, one thing that Wil Reynolds and I realized at a recent get-together
in San Diego is that for many people outside the tech world, Foursquare and
Instagram are basically the same app (see screenshots below). I'm seeing more
and more of my decidedly non-techie Instagram friends tagging their photos with
location. And avid Foursquare users like Matthew Brown have always made
photography their primary network activity.
Providing the geographic foundation for two appsâPinterest and
Instagramâthat are far more popular than Foursquare gives it a strong
running start on laying the location foundation for the Internet.
What's next for Foursquare?
While Facebook is undoubtedly building its own location layer, Zuckerberg and
company have long ignored local search. And they've got plenty of other short-
and mid-term priorities. Exposing Facebook check-in data to the extent
Foursquare has, and forcing Instagram to update a very successful API
integration, would seem to be pretty far down the list.
As I suggested in my Local Search Ecosystem update in August, to challenge
established players like Infogroup, Neustar, and Acxiom, in the long run
Foursquare does need to build out its index considerably beyond the current
sweetspots of food, drink, and entertainment.
But in the short run, the quality and depth of Foursquare's popular venue
information in major cities gives start-up app developers everything they need
to launch and attract users to their apps. And Foursquare's independence from
Google, Facebook, and Apple is appealing for many of themâparticularly for
non-U.S. app developers who have a hard time finding publicly-available location
databases outside of Google or Facebook.
Foursquare's success with Instagram and Pinterest has created a
self-perpetuating growth strategy: it will continue to be the location API of
choice for most "hot" local startups.
TL;DR
Foursquare venues have been contributing to a business's citation profile for
years, so hopefully most of you have included venue creation and management in
your local SEO service packages already. Even if you optimize non-retail
locations like insurance agencies, accounting offices, and the like, make one of
your 2014 New Year's resolutions be a higher level of engagement with
Foursquare.
The bottom line is that irrespective of its user growth and beyond just SEO,
Foursquare is going to get more important to the SoLoMo ecosystem in the coming
year.
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/i3dukj-i1HA/foursquare-as-data-aggregator
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, 'When 2 Become 1: How Merging Two
Domains Made Us an SEO Killing'
Posted by WPMU DEVThis post was originally in YouMoz, and was promoted to the
main blog because it provides great value and interest to our community. The
author's views are entirely his or her own and may not reflect the views of Moz,
Inc.
This is a ...
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/rCxzxvsg74A/2-become-1-merging-two-domains-made-us-an-seo-killing
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
Domains Made Us an SEO Killing'
Posted by WPMU DEVThis post was originally in YouMoz, and was promoted to the
main blog because it provides great value and interest to our community. The
author's views are entirely his or her own and may not reflect the views of Moz,
Inc.
This is a ...
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/rCxzxvsg74A/2-become-1-merging-two-domains-made-us-an-seo-killing
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 27 December 2013
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'The IdeaGraph - Whiteboard Friday'
Posted by wrttnwrd
There can be important links between topics that seem completely unrelated at
first glance. These random affinities are factoring into search results more and
more, and in today's Whiteboard Friday, Ian Lurie of Portent, Inc. shows us how
we can find and benefit from those otherwise-hidden links.
Whiteboard Friday - Ian Lurie - The Ideagraph
For reference, here's a still of this week's whiteboard!
Video Transcription
Howdy Moz fans. Today we're going to talk about the IdeaGraph. My name's Ian
Lurie, and I want to talk about some critical evolution that's happening in the
world of search right now.
Google and other search engines have existed in a world of words and links.
Words establish relevance. Links establish connections and authority. The
problem with that is Google takes a look at this world of links and words and
has a very hard time with what I call random affinities.
Let's say all cyclists like eggplant, or some cyclists like eggplant. Google
can't figure that out. There is no way to make that connection. Maybe if every
eggplant site on the planet linked to every cycling site on the planet, there
would be something there for them, but there really isn't.
So Google exists purely on words and links, which means there's a lot of
things that it doesn't pick up on. The things it doesn't pick up on are what I
call the IdeaGraph.
The IdeaGraph is something that's always existed. It's not something new.
It's this thing that creates these connections that are formed only by people.
So things that are totally unrelated, like eggplant and cyclists, and by the way
that's not true as far as I know. I'm a cyclist and I hate eggplant. But all
these things that randomly connect are part of the IdeaGraph.
The IdeaGraph has been used by marketers for years and years and years. If
you walk into a grocery store, and you're going from one aisle to the next and
you see these products in semi-random order, there's some research there where
they test different configurations and see, if someone's walking to the dairy
section way at the back of the store, what products can we put along their walk
that they're most likely to pick up? Those products, even if the marketers don't
know it, are part of the IdeaGraph, because you could put chocolate there, and
maybe the chocolate is what people want, but maybe you should put cleaning
supplies there and nobody wants it, because the IdeaGraph doesn't connect them
tightly enough.
The other place that you run into issues with the IdeaGraph on search and on
the Internet is with authorship and credibility and authority.
Right now, if you write an article, and it gets posted on a third-party site,
like The New York Times, and it's a huge hit, and it gets thousands and
thousands and thousands of links, you might get a little authority sent back to
your site, and your site is sad. See? Sad face website. Because it's not getting
all the authority it could. Your post is getting tons. It's happy. But your site
is not.
With the IdeaGraph it will be easier because the thing that connects your
site to your article is you. So just like you can connect widely varying ideas
and concepts, you can also connect everything you contribute to a single central
source, which then redistributes that authority.
Now Google is starting to work on this. They're starting to work on how to
make this work for them in search results. What they've started to do is build
these random affinities. So if you take cyclists and eggplant, theoretically
some of the things Google is doing could eventually create this place, this
space, where you would be able to tell from Google, and Google would be able to
tell you that there is this overlap.
The place that they're starting to do it, I think, remember Google doesn't
come and tell us these things, but I think it's Google+. With authorship and
publisher, rel=author and rel=publisher, they're actually tying these different
things together into a single receptacle into your Google+ profile. Remember,
anyone who has Gmail, has a Google+ profile. They may not know it, but they do.
Now Google's gathering all sorts of demographic data with that as well.
So what they're doing is, let's say you're using rel=author and you publish
posts all over the Internet, good posts. If you're just doing crappy guest
blogging, this probably won't work. You'll just send yourself all the lousy
credit. You want the good credit. So you write all these posts, and you have the
rel=author on the post, and they link back to your Google+ profile.
So your Google+ profile gets more and more authoritative. As it gets more and
more authoritative, it redistributes that authority, that connection to all the
places you publish. What you end up with is a much more robust way of connecting
content to people and ideas to people, and ideas to each other. If you write
about cycling on one site and eggplant on another, and they both link back to
your Google+ profile, and a lot of other people do that, Google can start to
say, "Huh, there might be a connection here. Maybe, with my new enhanced query
results, I should think about how I can put these two pieces of information
together to provide better search results." And your site ends up happier. See?
Happy site. Total limit of my artistic ability.
So that becomes a very powerful tool for creating exactly the right kind of
results that we, as human beings, really want, because people create the
IdeaGraph. Search engines create the world of words and links, and that's why
some people have so much trouble with queries, because they're having to convert
their thinking from just ideas to words and links.
So what powers the IdeaGraph is this concept of random affinities. You, as a
marketer, can take advantage of that, because as Google figures this out through
Google+, you're going to be able to find these affinities, and just like all
those aisles in the grocery store, or when you walk into a Starbucks and there's
a CD thereâyou're buying coffee and there's a CD? How do those relate?
When you find those random affinities, you can capitalize on them and make your
marketing message that much more compelling, because you can find where to put
that message in places you might never expect.
An example I like is I went on Amazon once and I searched for "lonely
planet," and in the "people who bought this also bought," I found a book on
making really great smoothies, which tells me there's this random affinity
between people who travel lonely planet style and people who like smoothies. It
might be a tiny attachment. It might be a tiny relationship, but it's a great
place to do some cross marketing and to target content.
So if you take a look here, if you want to find random affinities and build
on them, take a look at the Facebook Ad Planner. When you're building a Facebook
ad, you can put in a precise interest, and it'll show you other related precise
interests. Those relationships are built almost purely on the people who have
them in common. So sometimes there is no match, there's no relationship between
those two different concepts or interests, other than the fact that lots of
people like them both. So that's a good place to start.
Any site that uses collaborative filtering. So, Amazon, for example. Any site
that has "people who bought this also bought that" is a great place to go try
this. Go on Amazon and try it and look at "people who bought also bought."
You'll find all sorts of cool relationships.
Followerwonk is a fantastic tool for this. This one takes a little more work,
but the data you can find is incredible. Let's say you know that Rand is one of
your customers. He's a perfect customer, and he's typical of your perfect
customer. You can go on Followerwonk and find all the people who follow him and
then pull all of their bios, do a little research into the bios and find what
other interests those people express.
So they're following Randfish, but maybe a whole bunch of them express an
interest in comic books, and it's more than just one or two. It's a big number
of them. You just found a random affinity. People who like Rand also like comic
books. You can then find this area, and it's always easier to sell and get
interest in this area.
Again, you can use that to drive content strategy. You can use that to drive
keyword selection in a world where we don't really know what keywords are
driving traffic anymore, but we can find out what ideas are. You can use it to
target specific messages to people.
The ways you capitalize on this, on your own site you want to make sure that
you have rel=author and publisher set up, because that's the most obvious
IdeaGraph implementation we have right now, is rel=author and publisher.
Make sure you're using schemas from Schema.org whenever you can. For example,
make sure you use the article mark-up on your site because Google's enhanced
articles, results that are showing up at the bottom of search results right now,
those are powered, in part, by pages that have the article mark-up, or at least
there's a very high correlation between them. We don't know if it's causal, but
it seems to be.
Use product mark-up and review mark-up. I've seen a few instances and some of
my colleagues have seen instances where schema mark-up on a page allows content
to show up in search results attributed to that page, even if they're being
populated to the page by JavaScript or something else.
Get yourself set up with Google Analytics Demographics, as Google rolls it
out. You'll be able to get demographic data and categorical data in Google
Analytics based on visitors to your site. Then again, if you have a demographic
profile, you can look at the things that that demographic profile is interested
in and find those random affinities.
So just to summarize all of this, links and words have worked for a long
time, but we're starting to see the limitations of it, particularly with mobile
devices and other kinds of search. Google has been trying to find a way to fix
this, as has Bing, and they're both working very hard at this. They're trying to
build on this thing that has always existed that I call the IdeaGraph, and
they're building on it using random affinities. Selling to random affinities is
much, much easier. You can find them using lots of tools out on the web like
collaborative filtering, Facebook, and Followerwonk. You can take advantage and
position your site for it by just making sure that you have these basic mark-up
elements in place, and you're already collecting data.
I hope that was helpful to all Moz fans out there, and I look forward to
talking to you online. Thanks.
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/EKkUlffTEfU/the-ideagraph-whiteboard-friday
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
Posted by wrttnwrd
There can be important links between topics that seem completely unrelated at
first glance. These random affinities are factoring into search results more and
more, and in today's Whiteboard Friday, Ian Lurie of Portent, Inc. shows us how
we can find and benefit from those otherwise-hidden links.
Whiteboard Friday - Ian Lurie - The Ideagraph
For reference, here's a still of this week's whiteboard!
Video Transcription
Howdy Moz fans. Today we're going to talk about the IdeaGraph. My name's Ian
Lurie, and I want to talk about some critical evolution that's happening in the
world of search right now.
Google and other search engines have existed in a world of words and links.
Words establish relevance. Links establish connections and authority. The
problem with that is Google takes a look at this world of links and words and
has a very hard time with what I call random affinities.
Let's say all cyclists like eggplant, or some cyclists like eggplant. Google
can't figure that out. There is no way to make that connection. Maybe if every
eggplant site on the planet linked to every cycling site on the planet, there
would be something there for them, but there really isn't.
So Google exists purely on words and links, which means there's a lot of
things that it doesn't pick up on. The things it doesn't pick up on are what I
call the IdeaGraph.
The IdeaGraph is something that's always existed. It's not something new.
It's this thing that creates these connections that are formed only by people.
So things that are totally unrelated, like eggplant and cyclists, and by the way
that's not true as far as I know. I'm a cyclist and I hate eggplant. But all
these things that randomly connect are part of the IdeaGraph.
The IdeaGraph has been used by marketers for years and years and years. If
you walk into a grocery store, and you're going from one aisle to the next and
you see these products in semi-random order, there's some research there where
they test different configurations and see, if someone's walking to the dairy
section way at the back of the store, what products can we put along their walk
that they're most likely to pick up? Those products, even if the marketers don't
know it, are part of the IdeaGraph, because you could put chocolate there, and
maybe the chocolate is what people want, but maybe you should put cleaning
supplies there and nobody wants it, because the IdeaGraph doesn't connect them
tightly enough.
The other place that you run into issues with the IdeaGraph on search and on
the Internet is with authorship and credibility and authority.
Right now, if you write an article, and it gets posted on a third-party site,
like The New York Times, and it's a huge hit, and it gets thousands and
thousands and thousands of links, you might get a little authority sent back to
your site, and your site is sad. See? Sad face website. Because it's not getting
all the authority it could. Your post is getting tons. It's happy. But your site
is not.
With the IdeaGraph it will be easier because the thing that connects your
site to your article is you. So just like you can connect widely varying ideas
and concepts, you can also connect everything you contribute to a single central
source, which then redistributes that authority.
Now Google is starting to work on this. They're starting to work on how to
make this work for them in search results. What they've started to do is build
these random affinities. So if you take cyclists and eggplant, theoretically
some of the things Google is doing could eventually create this place, this
space, where you would be able to tell from Google, and Google would be able to
tell you that there is this overlap.
The place that they're starting to do it, I think, remember Google doesn't
come and tell us these things, but I think it's Google+. With authorship and
publisher, rel=author and rel=publisher, they're actually tying these different
things together into a single receptacle into your Google+ profile. Remember,
anyone who has Gmail, has a Google+ profile. They may not know it, but they do.
Now Google's gathering all sorts of demographic data with that as well.
So what they're doing is, let's say you're using rel=author and you publish
posts all over the Internet, good posts. If you're just doing crappy guest
blogging, this probably won't work. You'll just send yourself all the lousy
credit. You want the good credit. So you write all these posts, and you have the
rel=author on the post, and they link back to your Google+ profile.
So your Google+ profile gets more and more authoritative. As it gets more and
more authoritative, it redistributes that authority, that connection to all the
places you publish. What you end up with is a much more robust way of connecting
content to people and ideas to people, and ideas to each other. If you write
about cycling on one site and eggplant on another, and they both link back to
your Google+ profile, and a lot of other people do that, Google can start to
say, "Huh, there might be a connection here. Maybe, with my new enhanced query
results, I should think about how I can put these two pieces of information
together to provide better search results." And your site ends up happier. See?
Happy site. Total limit of my artistic ability.
So that becomes a very powerful tool for creating exactly the right kind of
results that we, as human beings, really want, because people create the
IdeaGraph. Search engines create the world of words and links, and that's why
some people have so much trouble with queries, because they're having to convert
their thinking from just ideas to words and links.
So what powers the IdeaGraph is this concept of random affinities. You, as a
marketer, can take advantage of that, because as Google figures this out through
Google+, you're going to be able to find these affinities, and just like all
those aisles in the grocery store, or when you walk into a Starbucks and there's
a CD thereâyou're buying coffee and there's a CD? How do those relate?
When you find those random affinities, you can capitalize on them and make your
marketing message that much more compelling, because you can find where to put
that message in places you might never expect.
An example I like is I went on Amazon once and I searched for "lonely
planet," and in the "people who bought this also bought," I found a book on
making really great smoothies, which tells me there's this random affinity
between people who travel lonely planet style and people who like smoothies. It
might be a tiny attachment. It might be a tiny relationship, but it's a great
place to do some cross marketing and to target content.
So if you take a look here, if you want to find random affinities and build
on them, take a look at the Facebook Ad Planner. When you're building a Facebook
ad, you can put in a precise interest, and it'll show you other related precise
interests. Those relationships are built almost purely on the people who have
them in common. So sometimes there is no match, there's no relationship between
those two different concepts or interests, other than the fact that lots of
people like them both. So that's a good place to start.
Any site that uses collaborative filtering. So, Amazon, for example. Any site
that has "people who bought this also bought that" is a great place to go try
this. Go on Amazon and try it and look at "people who bought also bought."
You'll find all sorts of cool relationships.
Followerwonk is a fantastic tool for this. This one takes a little more work,
but the data you can find is incredible. Let's say you know that Rand is one of
your customers. He's a perfect customer, and he's typical of your perfect
customer. You can go on Followerwonk and find all the people who follow him and
then pull all of their bios, do a little research into the bios and find what
other interests those people express.
So they're following Randfish, but maybe a whole bunch of them express an
interest in comic books, and it's more than just one or two. It's a big number
of them. You just found a random affinity. People who like Rand also like comic
books. You can then find this area, and it's always easier to sell and get
interest in this area.
Again, you can use that to drive content strategy. You can use that to drive
keyword selection in a world where we don't really know what keywords are
driving traffic anymore, but we can find out what ideas are. You can use it to
target specific messages to people.
The ways you capitalize on this, on your own site you want to make sure that
you have rel=author and publisher set up, because that's the most obvious
IdeaGraph implementation we have right now, is rel=author and publisher.
Make sure you're using schemas from Schema.org whenever you can. For example,
make sure you use the article mark-up on your site because Google's enhanced
articles, results that are showing up at the bottom of search results right now,
those are powered, in part, by pages that have the article mark-up, or at least
there's a very high correlation between them. We don't know if it's causal, but
it seems to be.
Use product mark-up and review mark-up. I've seen a few instances and some of
my colleagues have seen instances where schema mark-up on a page allows content
to show up in search results attributed to that page, even if they're being
populated to the page by JavaScript or something else.
Get yourself set up with Google Analytics Demographics, as Google rolls it
out. You'll be able to get demographic data and categorical data in Google
Analytics based on visitors to your site. Then again, if you have a demographic
profile, you can look at the things that that demographic profile is interested
in and find those random affinities.
So just to summarize all of this, links and words have worked for a long
time, but we're starting to see the limitations of it, particularly with mobile
devices and other kinds of search. Google has been trying to find a way to fix
this, as has Bing, and they're both working very hard at this. They're trying to
build on this thing that has always existed that I call the IdeaGraph, and
they're building on it using random affinities. Selling to random affinities is
much, much easier. You can find them using lots of tools out on the web like
collaborative filtering, Facebook, and Followerwonk. You can take advantage and
position your site for it by just making sure that you have these basic mark-up
elements in place, and you're already collecting data.
I hope that was helpful to all Moz fans out there, and I look forward to
talking to you online. Thanks.
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/EKkUlffTEfU/the-ideagraph-whiteboard-friday
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
Thursday 26 December 2013
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Mission ImposSERPble 2: User
Intent and Click Through Rates'
Posted by CatalystSEMThis post was originally in YouMoz, and was promoted to the
main blog because it provides great value and interest to our community. The
author's views are entirely his or her own and may not reflect the views of Moz,
Inc.
Itâs been quite a while since I first read (and bookmarked) Slingshot
SEOâs YouMoz blog post, Mission ImposSERPble: Establishing Click-through
Rates, which showcased their study examining organic click-through rates (CTR)
across search engine result pages. The Slingshot study is an excellent example
of how one can use data to uncover trends and insights. However, that study is
over two and a half years old now, and the Google search results have evolved
significantly since then.
Using the Slingshot CTR study (and a few others) as inspiration, Catalyst
thought it would be beneficial to take a fresh look at some of our own
click-through rate data and dive into the mindset of searchers and their
proclivity for clicking on the different types of modern organic Google search
results.
Swing on over to Catalystâs website and download the free Google CTR
Study: How User Intent Impacts Google Click-Through Rates
**TANGENT: I'm really hoping that the Moz community's reception of this
'sequel' post follows the path of some of the all-time great movie sequels
(think Terminator 2, The Godfather: Part II) and not that of Jaws 2.
How is the 2013 Catalyst CTR study unique?
RECENT DATA: This CTR study is the most current large-scale US study available.
It contains data ranging from Oct. 2012 â June 2013. Google is constantly
tweaking its SERP UI, which can influence organic CTR behavior.
MORE DATA: This study contains more keyword data, too. The keyword set for this
study spans 17,500 unique queries across 59 different websites. More data can
lead to more accurate representations of the true population.
MORE SEGMENTS: This study segments queries into categories not covered in
previous studies which allows us to compared CTR behavior attributed to
different keyword types. For example, branded v. unbranded queries, and question
v. non-question based queries.
How have organic CTRs changed over time?
The most significant changes since the 2011 Slingshot study is the higher CTRs
for positions 3, 4, and 5.
Ranking on the first page of search results is great for achieving visibility;
however, the search result for your website must be compelling enough to make
searchers want to click through to your website. In fact, this study shows that
having the most compelling listing in the SERPs could be more important than
âranking #1â (provided you are still ranking within the top five
listings, anyway).
Read on to learn more.
Since Slingshotâs 2011 study, click-through rates have not dramatically
shifted, with the total average CTR for first page organic results dropping by
just 4%.
While seemingly minor, these downward shifts could be a result of
Googleâs ever-evolving user interface. For example, with elements such as
Product Listing Ads, Knowledge Graph information, G+ authorship snippets, and
other microdata becoming more and more common in a Google SERP, usersâ
eyes may tend to stray further from the historical âF shapeâ
pattern, impacting the CTR by ranking position.
Positions 3-5 showed slightly higher average CTRs than what Slingshot
presented in 2011. A possible explanation for this shift is that users could be
more aware of Paid Search listing located at the top of the results page, so in
an attempt to âbypassâ these results, they may have modified their
browsing behavior to quickly scan/wheel-scroll past a few listings down the
page.
What is the distribution of clicks across a Google SERP?
Business owners need to understand that even if your website ranks in the
first organic position for your target keyword, your site will almost certainly
never receive traffic from every one of those users/searchers.
On average, the top organic SERP listing (#1) drives visits from around 17% of
Google searches.
The top four positions, or typical rankings âabove the foldâ for
many desktop users, receive 83% of first page organic clicks.
The Catalyst data also reveals that only 48% of Google searches result in a
page one organic click (meaning any click on listings ranging 1-10). So what is
the other 52% doing? Two things, the user either clicks on a Paid Search
listing, or they âabandonâ the search, which we define as:
Query Refinement â based on the displayed results, the user alters their
search
Instant Satisfaction â based on the displayed results, the user gets the
answer they were interested in without having to click
2nd Page Organic SERP â the user navigates to other SERPs
Leave Search Engine â the user exits the Google search engine
How do branded query CTRs differ from unbranded queries?
Branded CTRs for top ranking terms are lower than unbranded CTRs, likely due to
both user intent and the way Google presents results.
These numbers shocked us a bit. At the surface, you might assume that listings
with top rankings for branded queries would have higher CTRs than unbranded
queries. But, when you take a closer look at the current Google UI and place
yourself in the mindset of a searcher, our data actually seems more likely.
Consumers who search unbranded queries are often times higher in the
purchasing funnel: looking for information, without a specific answer or action
in mind. As a result, they may be more likely to click on the first result,
particularly when the listing belongs to a strong brand that they trust.
Additionally, take a look at the example below, notice how many organic
results are presented âabove the foldâ for a unbranded query
compared to an branded query (note: these SERP screenshots were taken from
1366x768 screen resolution). There are far fewer potential organic click paths
for a user to take when presented with the branded query's result page (1
organic result v. 4.5 results). It really boils down to 'transactional' v.
'informational' queries. Typically, keywords that are more transactional (e.g.
purchase intent) and/or drive higher ROI are more competitive in the PPC space
and as a result will have more paid search ads encroaching on valuable SERP real
estate.
We all know the makeup of every search result page is different and the number
of organic results above the fold can be influenced by a number of factors,
including, device type, screen size/resolution, paid search competiveness, and
so on.
You can use your website analytics platform to see what screen resolutions
your visitors are using and predict how many organic listings your target
audience would typically see for different search types and devices. In our
example, you can see that my desktop visitors most commonly use screen
resolutions higher than 1280x800, so I can be fairly certain that my current
audience typically sees up to 5 organic results from a desktop Google search.
Does query length/word count impact organic CTR?
As a userâs query length approaches the long tail, the average CTR for
page one rankings increases.
The organic click percentage totals represented in this graph suggest that as
a userâs query becomes more refined they are more likely to click on a
first page organic result (~56% for four+ word queries v. ~30% for one-word
queries).
Furthermore, as a query approaches the long tail, click distributions across
the top ten results begin to spread more evenly down the fold. Meaning, when a
consumerâs search becomes more refined/specific, they likely spend more
time scanning the SERPs looking for the best possible listing to answer their
search inquiry. This is where compelling calls-to-action and eye-catching page
titles/meta descriptions can really make or break your organic click through
rates.
As previously stated, only about 30% of one-word queries result in a first
page organic click. Why so low? Well, one potential reason for this is that
searchers use one-word queries simply to refine their search based on their
initial impression of the SERP. This means that the single word query would
become a multiple word query. If the user does not find what they are looking
for within the first result, they modify their search to be more specific, often
resulting in the query to contain multiple words.
Additionally, one-word queries resulted in 60% of the total first page organic
clicks (17.68%) being attributed to the first ranking. Maybe, by nature,
one-word queries are very similar to navigational queries (as the keywords are
oftentimes very broad or a specific brand name).
Potential business uses
Leveraging click-through rate data enables us to further understand user
behavior on a search result and how it can differ depending on search intent.
These learnings can play an integral role in defining a companyâs digital
strategy, as well as forecasting website traffic and even ROI. For instance:
Forecasting Website Performance and Traffic Given a keywordâs monthly
search volume, we can predict the number of visits a website could expect to
receive by each ranking position. This becomes increasingly valuable when we
have conversion rate data attributed to specific keywords.
Identifying Search Keyword Targets With Google Webmaster Toolsâ
CTR/search query data we can easily determine the keywords that are
âlow-hanging fruitâ. We consider low hanging fruit to be keywords
that a brand ranks fairly well on, but are just outside of achieving high
visibility/high organic traffic because the site currently ranks âbelow
the foldâ on page 1 of the SERPs or rank somewhere within pages 2-3 of the
results.). Once targeted and integrated into the brandâs keyphrase
strategy, SEOs can then work to improve the siteâs rankings for that
particular query.
Identifying Under-performing Top Visible Keywords By comparing a brandâs
specific search query CTR against the industry average as identified in this
report, we can identify under-performing keyphrases. Next, an SEO can perform an
audit to determine if the low CTR is due to factors within the brandâs
control, or if it is caused by external factors.
Data set, criteria, and methodology
Some information about our data set and methodology. If youâre like me,
and want to follow along using your own data, you can review our complete
process in our whitepaper. All websites included in the study are Consumer
Packaged Goods (CPG) brands. As such, the associated CTRs, and hypothesized user
behaviors reflect only those brands and users.
Data was collected via each brandâs respective Google Webmaster Tools
account, which was then processed and analyzed using a powerful BI and data
visualization tool.
Catalyst analyzed close to 17,500 unique search queries (with an average
ranking between 1â10, and a minimum of 50 search impressions per month)
across 59 unique brands over a 9 month timeframe (Oct. 2012 â Jun 2013).
Here are a few definitions so weâre all on the same page (we mirrored
definitions as provided by Google for their Google Webmaster Tools)â
Click-Through Rate (CTR) - the percentage of impressions that resulted in a
click for a website.
Average Position â the average top position of a website on the search
results page for that query. To calculate average position, Google takes into
account the top ranking URL from the website for a particular query.
Final word
I have learned a great deal from the studies and blog posts shared by Moz and
other industry experts throughout my career, and I felt I had an opportunity to
meaningfully contribute back to the SEO community by providing an updated, more
in-depth Google CTR study for SEOs to use as a resource when benchmarking and
measuring their campaigns and progress.
For more data and analysis relating to coupon-based queries, question based
queries, desktop v. mobile user devices, and more download our complete CTR
study.
Have any questions or comments on our study? Did anyone actually enjoy Jaws 2?
Please let us know and join the discussion below!
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/WvIGffHi4Vw/mission-imposserpble-2-user-intent-click-through-rates
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
Intent and Click Through Rates'
Posted by CatalystSEMThis post was originally in YouMoz, and was promoted to the
main blog because it provides great value and interest to our community. The
author's views are entirely his or her own and may not reflect the views of Moz,
Inc.
Itâs been quite a while since I first read (and bookmarked) Slingshot
SEOâs YouMoz blog post, Mission ImposSERPble: Establishing Click-through
Rates, which showcased their study examining organic click-through rates (CTR)
across search engine result pages. The Slingshot study is an excellent example
of how one can use data to uncover trends and insights. However, that study is
over two and a half years old now, and the Google search results have evolved
significantly since then.
Using the Slingshot CTR study (and a few others) as inspiration, Catalyst
thought it would be beneficial to take a fresh look at some of our own
click-through rate data and dive into the mindset of searchers and their
proclivity for clicking on the different types of modern organic Google search
results.
Swing on over to Catalystâs website and download the free Google CTR
Study: How User Intent Impacts Google Click-Through Rates
**TANGENT: I'm really hoping that the Moz community's reception of this
'sequel' post follows the path of some of the all-time great movie sequels
(think Terminator 2, The Godfather: Part II) and not that of Jaws 2.
How is the 2013 Catalyst CTR study unique?
RECENT DATA: This CTR study is the most current large-scale US study available.
It contains data ranging from Oct. 2012 â June 2013. Google is constantly
tweaking its SERP UI, which can influence organic CTR behavior.
MORE DATA: This study contains more keyword data, too. The keyword set for this
study spans 17,500 unique queries across 59 different websites. More data can
lead to more accurate representations of the true population.
MORE SEGMENTS: This study segments queries into categories not covered in
previous studies which allows us to compared CTR behavior attributed to
different keyword types. For example, branded v. unbranded queries, and question
v. non-question based queries.
How have organic CTRs changed over time?
The most significant changes since the 2011 Slingshot study is the higher CTRs
for positions 3, 4, and 5.
Ranking on the first page of search results is great for achieving visibility;
however, the search result for your website must be compelling enough to make
searchers want to click through to your website. In fact, this study shows that
having the most compelling listing in the SERPs could be more important than
âranking #1â (provided you are still ranking within the top five
listings, anyway).
Read on to learn more.
Since Slingshotâs 2011 study, click-through rates have not dramatically
shifted, with the total average CTR for first page organic results dropping by
just 4%.
While seemingly minor, these downward shifts could be a result of
Googleâs ever-evolving user interface. For example, with elements such as
Product Listing Ads, Knowledge Graph information, G+ authorship snippets, and
other microdata becoming more and more common in a Google SERP, usersâ
eyes may tend to stray further from the historical âF shapeâ
pattern, impacting the CTR by ranking position.
Positions 3-5 showed slightly higher average CTRs than what Slingshot
presented in 2011. A possible explanation for this shift is that users could be
more aware of Paid Search listing located at the top of the results page, so in
an attempt to âbypassâ these results, they may have modified their
browsing behavior to quickly scan/wheel-scroll past a few listings down the
page.
What is the distribution of clicks across a Google SERP?
Business owners need to understand that even if your website ranks in the
first organic position for your target keyword, your site will almost certainly
never receive traffic from every one of those users/searchers.
On average, the top organic SERP listing (#1) drives visits from around 17% of
Google searches.
The top four positions, or typical rankings âabove the foldâ for
many desktop users, receive 83% of first page organic clicks.
The Catalyst data also reveals that only 48% of Google searches result in a
page one organic click (meaning any click on listings ranging 1-10). So what is
the other 52% doing? Two things, the user either clicks on a Paid Search
listing, or they âabandonâ the search, which we define as:
Query Refinement â based on the displayed results, the user alters their
search
Instant Satisfaction â based on the displayed results, the user gets the
answer they were interested in without having to click
2nd Page Organic SERP â the user navigates to other SERPs
Leave Search Engine â the user exits the Google search engine
How do branded query CTRs differ from unbranded queries?
Branded CTRs for top ranking terms are lower than unbranded CTRs, likely due to
both user intent and the way Google presents results.
These numbers shocked us a bit. At the surface, you might assume that listings
with top rankings for branded queries would have higher CTRs than unbranded
queries. But, when you take a closer look at the current Google UI and place
yourself in the mindset of a searcher, our data actually seems more likely.
Consumers who search unbranded queries are often times higher in the
purchasing funnel: looking for information, without a specific answer or action
in mind. As a result, they may be more likely to click on the first result,
particularly when the listing belongs to a strong brand that they trust.
Additionally, take a look at the example below, notice how many organic
results are presented âabove the foldâ for a unbranded query
compared to an branded query (note: these SERP screenshots were taken from
1366x768 screen resolution). There are far fewer potential organic click paths
for a user to take when presented with the branded query's result page (1
organic result v. 4.5 results). It really boils down to 'transactional' v.
'informational' queries. Typically, keywords that are more transactional (e.g.
purchase intent) and/or drive higher ROI are more competitive in the PPC space
and as a result will have more paid search ads encroaching on valuable SERP real
estate.
We all know the makeup of every search result page is different and the number
of organic results above the fold can be influenced by a number of factors,
including, device type, screen size/resolution, paid search competiveness, and
so on.
You can use your website analytics platform to see what screen resolutions
your visitors are using and predict how many organic listings your target
audience would typically see for different search types and devices. In our
example, you can see that my desktop visitors most commonly use screen
resolutions higher than 1280x800, so I can be fairly certain that my current
audience typically sees up to 5 organic results from a desktop Google search.
Does query length/word count impact organic CTR?
As a userâs query length approaches the long tail, the average CTR for
page one rankings increases.
The organic click percentage totals represented in this graph suggest that as
a userâs query becomes more refined they are more likely to click on a
first page organic result (~56% for four+ word queries v. ~30% for one-word
queries).
Furthermore, as a query approaches the long tail, click distributions across
the top ten results begin to spread more evenly down the fold. Meaning, when a
consumerâs search becomes more refined/specific, they likely spend more
time scanning the SERPs looking for the best possible listing to answer their
search inquiry. This is where compelling calls-to-action and eye-catching page
titles/meta descriptions can really make or break your organic click through
rates.
As previously stated, only about 30% of one-word queries result in a first
page organic click. Why so low? Well, one potential reason for this is that
searchers use one-word queries simply to refine their search based on their
initial impression of the SERP. This means that the single word query would
become a multiple word query. If the user does not find what they are looking
for within the first result, they modify their search to be more specific, often
resulting in the query to contain multiple words.
Additionally, one-word queries resulted in 60% of the total first page organic
clicks (17.68%) being attributed to the first ranking. Maybe, by nature,
one-word queries are very similar to navigational queries (as the keywords are
oftentimes very broad or a specific brand name).
Potential business uses
Leveraging click-through rate data enables us to further understand user
behavior on a search result and how it can differ depending on search intent.
These learnings can play an integral role in defining a companyâs digital
strategy, as well as forecasting website traffic and even ROI. For instance:
Forecasting Website Performance and Traffic Given a keywordâs monthly
search volume, we can predict the number of visits a website could expect to
receive by each ranking position. This becomes increasingly valuable when we
have conversion rate data attributed to specific keywords.
Identifying Search Keyword Targets With Google Webmaster Toolsâ
CTR/search query data we can easily determine the keywords that are
âlow-hanging fruitâ. We consider low hanging fruit to be keywords
that a brand ranks fairly well on, but are just outside of achieving high
visibility/high organic traffic because the site currently ranks âbelow
the foldâ on page 1 of the SERPs or rank somewhere within pages 2-3 of the
results.). Once targeted and integrated into the brandâs keyphrase
strategy, SEOs can then work to improve the siteâs rankings for that
particular query.
Identifying Under-performing Top Visible Keywords By comparing a brandâs
specific search query CTR against the industry average as identified in this
report, we can identify under-performing keyphrases. Next, an SEO can perform an
audit to determine if the low CTR is due to factors within the brandâs
control, or if it is caused by external factors.
Data set, criteria, and methodology
Some information about our data set and methodology. If youâre like me,
and want to follow along using your own data, you can review our complete
process in our whitepaper. All websites included in the study are Consumer
Packaged Goods (CPG) brands. As such, the associated CTRs, and hypothesized user
behaviors reflect only those brands and users.
Data was collected via each brandâs respective Google Webmaster Tools
account, which was then processed and analyzed using a powerful BI and data
visualization tool.
Catalyst analyzed close to 17,500 unique search queries (with an average
ranking between 1â10, and a minimum of 50 search impressions per month)
across 59 unique brands over a 9 month timeframe (Oct. 2012 â Jun 2013).
Here are a few definitions so weâre all on the same page (we mirrored
definitions as provided by Google for their Google Webmaster Tools)â
Click-Through Rate (CTR) - the percentage of impressions that resulted in a
click for a website.
Average Position â the average top position of a website on the search
results page for that query. To calculate average position, Google takes into
account the top ranking URL from the website for a particular query.
Final word
I have learned a great deal from the studies and blog posts shared by Moz and
other industry experts throughout my career, and I felt I had an opportunity to
meaningfully contribute back to the SEO community by providing an updated, more
in-depth Google CTR study for SEOs to use as a resource when benchmarking and
measuring their campaigns and progress.
For more data and analysis relating to coupon-based queries, question based
queries, desktop v. mobile user devices, and more download our complete CTR
study.
Have any questions or comments on our study? Did anyone actually enjoy Jaws 2?
Please let us know and join the discussion below!
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/WvIGffHi4Vw/mission-imposserpble-2-user-intent-click-through-rates
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
Tuesday 24 December 2013
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Moz Holiday Traditions'
Posted by ssnsestak
Here at Moz, we often feel like a big family. Just like any other family, over
the years we've developed an eclectic set of traditions to celebrate the holiday
season. We'd like to share a few of our favorites and welcome you to join us in
these most joyous of festivities. ;)
Seasons Greetings!
Moz Holiday Traditions 2013 _regular out
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/a0_k0LQm6jo/moz-holiday-traditions
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
Posted by ssnsestak
Here at Moz, we often feel like a big family. Just like any other family, over
the years we've developed an eclectic set of traditions to celebrate the holiday
season. We'd like to share a few of our favorites and welcome you to join us in
these most joyous of festivities. ;)
Seasons Greetings!
Moz Holiday Traditions 2013 _regular out
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/a0_k0LQm6jo/moz-holiday-traditions
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
Monday 23 December 2013
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Machine Learning for SEOs'
Posted by Tom-Anthony
Since the Panda and Penguin updates, the SEO community has been talking more
and more about machine learning, and yet often the term still isn't well
understood. We know that it is the "magic" behind Panda and Pengui...
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/MTyr7xmqVmE/machine-learning-for-seos
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
Posted by Tom-Anthony
Since the Panda and Penguin updates, the SEO community has been talking more
and more about machine learning, and yet often the term still isn't well
understood. We know that it is the "magic" behind Panda and Pengui...
You may view the latest post at
http://feedproxy.google.com/~r/seomoz/~3/MTyr7xmqVmE/machine-learning-for-seos
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 20 December 2013
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Building SEO-Focused Pages to
Serve Topics & People Rather than Keywords & Rankings - Whiteboard Friday'
Posted by randfish
With updates like Hummingbird, Google is getting better and better at
determining what's relevant to you and what you're looking for. This can
actually help our work in SEO, as it means we don't have to focus quite so
intently on specific keywords.
In today's Whiteboard Friday, Rand explains how focusing on specific kinds of
people and the topics they're interested in can be even more effective in
driving valuable traffic than ranking for specific keywords.
Whiteboard Friday - Building SEO focused pages to serve topics and people
rather than keywords and rankings
For reference, here's a still of this week's whiteboard:
Video Transcription
Howdy, Moz fans and welcome to another edition of "Whiteboard Friday." This
week, I want to talk to you a little bit about the classic technique of building
SEO pages for keywords and rankings versus the more modern technique of trying
to do this with people and topics in mind. So, let me walk you through the
classic model and show you why we've needed to evolve.
So, historically, SEO has really been about keyword rankings. It's "I want to
rank well for this keyword because that particular keyword sends me traffic that
is of high quality. The value of the people visiting my site from that is high."
The problem is, this doesn't account for other types of traffic, channels, and
sources, right? We're just focused on SEO.
This can be a little bit problematic because it can mean that we ignore
things like social and content marketing opportunities and email marketing
opportunities. But, okay. Let's stick with it. In order to do this, we do some
keyword research. We figure out which terms and phrases are popular, which ones
are high and low competition, which ones we expect to drive high-quality
traffic.
We create some landing pages for each of these terms and phrases. We get
links. And we optimize that content so that hopefully, it performs well in the
search engines. And then we measure the success of this process based on both
the ranking itself. But also, the keywords that drive traffic to those pages.
And whether people who visit coming from those keywords are high-quality
visitors.
And then we decide "Yeah, I'm not ranking so well for this keyword. But gosh,
it's sending great traffic. Let me focus more on this one." Or "Oh, I am ranking
well for this. But the keyword is not sending me high-quality traffic. So, it
doesn't matter that much. I'm going to ignore it because of the problems."
So, a lot of times, creating these landing pages with each particular term
and phrase is doing a lot of unnecessary overlapping work, right? Even if you're
not doing this sort of hyper, slight modifications of each phrase. "Brown
bowling shoes," "red bowling shoes," "blue bowling shoes." Maybe you could just
have a bowling shoes page and then have a list of colors to choose from. Okay.
But even still, you might have "bowling shoes" and "shoes for going bowling."
And "shoes for indoor sports," all of these different kinds of things that could
have a considerable amount of overlap. And many different topic areas do this.
The problem with getting links and optimizing these individual pages is that
you're only getting a page to rank for one particular term or maybe a couple of
different terms, versus a group of keywords in a topic that might all be very
well-served by the same content, by the same landing page.
And by the way, because you're doing this, you're not putting in the same
level of effort, energy, quality and improvement, right? Because it's an
improvement into making this content better and better. You're just trying to
churn out landing page after landing page.
And then, if you're measuring success based on the traffic that the keyword
is sending, this isn't even possible anymore. Because Google has taken away
keyword referral data and given us (not provided) instead.
And this is why we're seeing this big shift to this new model, this more
modern model, where SEO is really about the broad performance of search traffic
across a website, and about the broad performance of the pages receiving search
visits. So, this means that I look at a given set of pages, I look at a section
of my site, I look at content areas that I'm investing in, and I say "Gosh, the
visits that come from Google, that come from Bing, that come from Image Search,
whatever they are, these are performing at a high quality, therefore, I want to
invest more in SEO." Not necessarily "Oh, look. This keyword sent me this good
traffic."
I'm still doing keyword research. I'm still using that same process, right?
Where I go and I try to figure out "Okay, how many people are searching for this
term? Do I think they're going to be high-quality visitors? And is the
competition low enough to where I think my website can compete?"
I'm going to then define groups of terms and phrases that can be well-served
by that content. This is very different. Instead of saying "Blue bowling shoes"
and "Brown bowling shoes," I'm saying, "I think I can have one great page around
bowling shoes, in general, that's going to serve me really well. I'm going to
have all different kinds, custom bowling shoes and all these different things."
And maybe some of them deserve their own individual landing pages, but
together, this group of keywords can be served by this page. And then these
individual ones have their own targeted pages.
From there, I'm going to optimize for two things that are a little bit
different than what I've done in the past. Both keyword targeting and being able
to earn some links. But also, an opportunity for amplification.
That amplification can come from links. It could come from email marketing,
it could come from social media. It could come from word-of-mouth. But,
regardless, this is the new fantastic way to earn those signals that seem to
correlate with things ranking well.
Links are certainly one of them. But we don't need the same types of direct
anchor text that we used to need. Broad links to a website can now help increase
our domain authority, meaning that all of our content ranks well.
Google certainly seems to be getting very good at recognizing relevancy of
particular websites around topic areas. Meaning that if I've done a good job in
the past of showing Google that I'm relevant for a particular topic like bowling
shoes. When I put together custom, graphic-printed, leather bowling shoes pages,
that page might rank right away. Even if I haven't done very much work to
specifically earn links to it and get anchor text and those kinds of things,
because of the relevancy signals I've built up in the past. And that's what this
process does.
And now, I can measure success based on how the search traffic to given
landing pages is performing. Let me show you an example of this.
And here, I've got my example. So, I'm focusing beyond bowling shoes. I'm
going to go with "Comparing mobile phone plans," right? So, let's say that
you're putting together a site and you want to try and help consumers who are
looking at different mobile phone plans, figure out which one they should go
with, great.
So, "Compare mobile phone plans" is where you're starting. And you're also
thinking about 'Well, okay. Let me expand beyond that. I want to get broad
performance." And so, I'm trying to get this broad audience to target. Everyone
who is interested in this topic. All these consumers.
And so, what are things that they also might be interested in? And I'll do
some keyword research and some subject matter research. Maybe I'll talk to some
experts, I'll talk to some consumers. And I'll see providers, they're looking
for different phone providers. They might use synonyms of these different terms.
They might have some concept expansion that I go through as I'm doing my keyword
research.
Maybe I'm looking for queries that people search for before and after. So,
after they make the determination if they like this particular provider, then
they go look at phones. Or after they determine they like this phone, they want
to see which provider offers that phone. Fine, fair.
So, now, I'm going to do this definition of the groups of keywords that I
care about. I have comparison in my providers. Verizon, T-Mobile, Sprint, AT&T.
Comparison of phones, the Galaxy, iPhone, Nexus, by price or features. What
about people who are really heavy into international calling or family plans or
travel a lot? Need data-heavy stuff or doing lots of tethering to their laptops.
So, this type of thing is what's defining the pages that I might build by the
searcher's intent. When they search for keywords around these topics, I'm not
necessarily sure that I'm going to be able to capture all of the keywords that
they might search for and that's okay.
I'm going to take these specific phrases that I do put in my keyword
research. And then, I'm going to expand out to, "All right, I want to try and
have a page that reaches all the people who are looking for stuff like this."
And Google's actually really helping you with search algorithms like
Hummingbird, where they're expanding the definition of what keyword relevancy
and keyword matching is really meaning.
So, now, I'm going to go and I'm going to try and build out these pages. So,
I've got my phone plans compared. Verizon versus T-Mobile versus AT&T versus
Sprint. The showdown.
And that page is going to feature things like "I want to show the price of
the services relative to time over time. I want to show which phones they have
available." And maybe pull in some expert ratings and reviews for those
particular phones. Maybe I'll toss in CNET's rating on each of the phones and
link over to that.
What add-ons do they have? What included services? Do I maybe want to link
out to some expert reviews? Can I have sorting so that I can say "Oh, I only
want this particular phone. So, show me only the providers that have got that
phone" or those types of things.
And then, I'm going to take this and I'm going to launch it. All this stuff,
all these features are not just there to help be relevant to the search query.
They're to help the searcher and to make this worthy of amplification.
And then, I can use the performance of all the search traffic that lands on
any version of this page. So, this page might have lots of different URLs based
on the sorting or what features I select or whatever that is. Maybe I rel
canonical them or maybe I don't, because I think it can be expanded out and
serve a lot of these different needs. And that's fine, too.
But this, this is a great way to effectively determine the ROI that I've
gotten from producing this content, targeting these searchers. And then, I can
look at the value from other channels in how search impacts social and social
impacts search by looking at multi-channel and multi-touch. It's really, really
cool.
So, yes. SEO has gotten more complex. It's gotten harder. There's a little
bit of disassociation away from just the keyword and the ranking. But this
process still really works and it's still very powerful. And I think SEOs are
going to be using this for a long time to come. We just have to have a switch in
our mentality.
All right, everyone. I look forward to the comments. And we'll see you again
next week for another edition of "Whiteboard Friday." 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/id0FsOPvyvw/topics-people-over-keywords-rankings-whiteboard-friday
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
Serve Topics & People Rather than Keywords & Rankings - Whiteboard Friday'
Posted by randfish
With updates like Hummingbird, Google is getting better and better at
determining what's relevant to you and what you're looking for. This can
actually help our work in SEO, as it means we don't have to focus quite so
intently on specific keywords.
In today's Whiteboard Friday, Rand explains how focusing on specific kinds of
people and the topics they're interested in can be even more effective in
driving valuable traffic than ranking for specific keywords.
Whiteboard Friday - Building SEO focused pages to serve topics and people
rather than keywords and rankings
For reference, here's a still of this week's whiteboard:
Video Transcription
Howdy, Moz fans and welcome to another edition of "Whiteboard Friday." This
week, I want to talk to you a little bit about the classic technique of building
SEO pages for keywords and rankings versus the more modern technique of trying
to do this with people and topics in mind. So, let me walk you through the
classic model and show you why we've needed to evolve.
So, historically, SEO has really been about keyword rankings. It's "I want to
rank well for this keyword because that particular keyword sends me traffic that
is of high quality. The value of the people visiting my site from that is high."
The problem is, this doesn't account for other types of traffic, channels, and
sources, right? We're just focused on SEO.
This can be a little bit problematic because it can mean that we ignore
things like social and content marketing opportunities and email marketing
opportunities. But, okay. Let's stick with it. In order to do this, we do some
keyword research. We figure out which terms and phrases are popular, which ones
are high and low competition, which ones we expect to drive high-quality
traffic.
We create some landing pages for each of these terms and phrases. We get
links. And we optimize that content so that hopefully, it performs well in the
search engines. And then we measure the success of this process based on both
the ranking itself. But also, the keywords that drive traffic to those pages.
And whether people who visit coming from those keywords are high-quality
visitors.
And then we decide "Yeah, I'm not ranking so well for this keyword. But gosh,
it's sending great traffic. Let me focus more on this one." Or "Oh, I am ranking
well for this. But the keyword is not sending me high-quality traffic. So, it
doesn't matter that much. I'm going to ignore it because of the problems."
So, a lot of times, creating these landing pages with each particular term
and phrase is doing a lot of unnecessary overlapping work, right? Even if you're
not doing this sort of hyper, slight modifications of each phrase. "Brown
bowling shoes," "red bowling shoes," "blue bowling shoes." Maybe you could just
have a bowling shoes page and then have a list of colors to choose from. Okay.
But even still, you might have "bowling shoes" and "shoes for going bowling."
And "shoes for indoor sports," all of these different kinds of things that could
have a considerable amount of overlap. And many different topic areas do this.
The problem with getting links and optimizing these individual pages is that
you're only getting a page to rank for one particular term or maybe a couple of
different terms, versus a group of keywords in a topic that might all be very
well-served by the same content, by the same landing page.
And by the way, because you're doing this, you're not putting in the same
level of effort, energy, quality and improvement, right? Because it's an
improvement into making this content better and better. You're just trying to
churn out landing page after landing page.
And then, if you're measuring success based on the traffic that the keyword
is sending, this isn't even possible anymore. Because Google has taken away
keyword referral data and given us (not provided) instead.
And this is why we're seeing this big shift to this new model, this more
modern model, where SEO is really about the broad performance of search traffic
across a website, and about the broad performance of the pages receiving search
visits. So, this means that I look at a given set of pages, I look at a section
of my site, I look at content areas that I'm investing in, and I say "Gosh, the
visits that come from Google, that come from Bing, that come from Image Search,
whatever they are, these are performing at a high quality, therefore, I want to
invest more in SEO." Not necessarily "Oh, look. This keyword sent me this good
traffic."
I'm still doing keyword research. I'm still using that same process, right?
Where I go and I try to figure out "Okay, how many people are searching for this
term? Do I think they're going to be high-quality visitors? And is the
competition low enough to where I think my website can compete?"
I'm going to then define groups of terms and phrases that can be well-served
by that content. This is very different. Instead of saying "Blue bowling shoes"
and "Brown bowling shoes," I'm saying, "I think I can have one great page around
bowling shoes, in general, that's going to serve me really well. I'm going to
have all different kinds, custom bowling shoes and all these different things."
And maybe some of them deserve their own individual landing pages, but
together, this group of keywords can be served by this page. And then these
individual ones have their own targeted pages.
From there, I'm going to optimize for two things that are a little bit
different than what I've done in the past. Both keyword targeting and being able
to earn some links. But also, an opportunity for amplification.
That amplification can come from links. It could come from email marketing,
it could come from social media. It could come from word-of-mouth. But,
regardless, this is the new fantastic way to earn those signals that seem to
correlate with things ranking well.
Links are certainly one of them. But we don't need the same types of direct
anchor text that we used to need. Broad links to a website can now help increase
our domain authority, meaning that all of our content ranks well.
Google certainly seems to be getting very good at recognizing relevancy of
particular websites around topic areas. Meaning that if I've done a good job in
the past of showing Google that I'm relevant for a particular topic like bowling
shoes. When I put together custom, graphic-printed, leather bowling shoes pages,
that page might rank right away. Even if I haven't done very much work to
specifically earn links to it and get anchor text and those kinds of things,
because of the relevancy signals I've built up in the past. And that's what this
process does.
And now, I can measure success based on how the search traffic to given
landing pages is performing. Let me show you an example of this.
And here, I've got my example. So, I'm focusing beyond bowling shoes. I'm
going to go with "Comparing mobile phone plans," right? So, let's say that
you're putting together a site and you want to try and help consumers who are
looking at different mobile phone plans, figure out which one they should go
with, great.
So, "Compare mobile phone plans" is where you're starting. And you're also
thinking about 'Well, okay. Let me expand beyond that. I want to get broad
performance." And so, I'm trying to get this broad audience to target. Everyone
who is interested in this topic. All these consumers.
And so, what are things that they also might be interested in? And I'll do
some keyword research and some subject matter research. Maybe I'll talk to some
experts, I'll talk to some consumers. And I'll see providers, they're looking
for different phone providers. They might use synonyms of these different terms.
They might have some concept expansion that I go through as I'm doing my keyword
research.
Maybe I'm looking for queries that people search for before and after. So,
after they make the determination if they like this particular provider, then
they go look at phones. Or after they determine they like this phone, they want
to see which provider offers that phone. Fine, fair.
So, now, I'm going to do this definition of the groups of keywords that I
care about. I have comparison in my providers. Verizon, T-Mobile, Sprint, AT&T.
Comparison of phones, the Galaxy, iPhone, Nexus, by price or features. What
about people who are really heavy into international calling or family plans or
travel a lot? Need data-heavy stuff or doing lots of tethering to their laptops.
So, this type of thing is what's defining the pages that I might build by the
searcher's intent. When they search for keywords around these topics, I'm not
necessarily sure that I'm going to be able to capture all of the keywords that
they might search for and that's okay.
I'm going to take these specific phrases that I do put in my keyword
research. And then, I'm going to expand out to, "All right, I want to try and
have a page that reaches all the people who are looking for stuff like this."
And Google's actually really helping you with search algorithms like
Hummingbird, where they're expanding the definition of what keyword relevancy
and keyword matching is really meaning.
So, now, I'm going to go and I'm going to try and build out these pages. So,
I've got my phone plans compared. Verizon versus T-Mobile versus AT&T versus
Sprint. The showdown.
And that page is going to feature things like "I want to show the price of
the services relative to time over time. I want to show which phones they have
available." And maybe pull in some expert ratings and reviews for those
particular phones. Maybe I'll toss in CNET's rating on each of the phones and
link over to that.
What add-ons do they have? What included services? Do I maybe want to link
out to some expert reviews? Can I have sorting so that I can say "Oh, I only
want this particular phone. So, show me only the providers that have got that
phone" or those types of things.
And then, I'm going to take this and I'm going to launch it. All this stuff,
all these features are not just there to help be relevant to the search query.
They're to help the searcher and to make this worthy of amplification.
And then, I can use the performance of all the search traffic that lands on
any version of this page. So, this page might have lots of different URLs based
on the sorting or what features I select or whatever that is. Maybe I rel
canonical them or maybe I don't, because I think it can be expanded out and
serve a lot of these different needs. And that's fine, too.
But this, this is a great way to effectively determine the ROI that I've
gotten from producing this content, targeting these searchers. And then, I can
look at the value from other channels in how search impacts social and social
impacts search by looking at multi-channel and multi-touch. It's really, really
cool.
So, yes. SEO has gotten more complex. It's gotten harder. There's a little
bit of disassociation away from just the keyword and the ranking. But this
process still really works and it's still very powerful. And I think SEOs are
going to be using this for a long time to come. We just have to have a switch in
our mentality.
All right, everyone. I look forward to the comments. And we'll see you again
next week for another edition of "Whiteboard Friday." 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/id0FsOPvyvw/topics-people-over-keywords-rankings-whiteboard-friday
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
Thursday 19 December 2013
[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'I Am an Entity: Hacking the
Knowledge Graph'
Posted by Andrew_IsidoroThis post was originally in YouMoz, and was promoted to
the main blog because it provides great value and interest to our community. The
author's views are entirely his or her own and may not reflect the views of Moz,
Inc.
For a long time Google has algorithmically led users towards web pages based
on search strings, yet over the past few years, we've seen many changes which
are leading to a more data-driven model of semantic search.
In 2010 Google hit a milestone with its acquisition of Metaweb and its
semantic database now known as Freebase. This database helps to make up the
Knowledge Graph; an archive of over 570 million of the most searched-for people,
places and things (entities), including around 18 billion cross-references. A
truly impressive demonstration of what a semantic search engine with structured
data can bring to the everyday user.
What has changed?
The surge of Knowledge Graph entries picked up by Dr Pete a few weeks ago
indicates a huge change in the algorithm. Google has been attempting to
establish a deep associative context around the entities to try and understand
the query rather than just regurgitate what it believes is the closest result
for some time, but this has been focused on a very tight dataset reserved for
high profile people, places and things.
It seems that has changed.
Over the past few weeks, while looking into how the Knowledge Graph pulls data
for certain sources, I have made a few general observations and have been
tracking what, if any, impact certain practices have on the display of
information panels.
If I'm being brutally honest, this experiment was to scratch a personal
"itch." I was interested in the constructs of the Knowledge Graph over anything
else, which is why I was so surprised that a few weeks ago I began to see this:
It seems that anyone now wishing to find out "Andrew Isidoro's Age" could now
be greeted with not only my age but also my date of birth in an information
panel. After a few well-planned boasts to my girlfriend about my new found fame
(all of which were dismissed as "slightly sad and geeky"), I began to probe
further and found that this was by no means the only piece of information that
Google could supply users about me.
It also displayed data such as my place of birth and my Job. It could even
answer natural language queries and connect me to other entities like in queries
such as: "Where did Andrew Isidoro go to school?"
and somewhat creepily, "Who are Andrew Isidoro's parents?".
Many of you may now be a little scared about your own personal privacy, but I
have a confession to make. Though I am by no means a celebrity, I do have a
Freebase profile. The information that I have inputted into this is now
available for all to see as a part of Google's search product.
I've already written about the implications of privacy so I'll gloss over the
ethics for a moment and get right into the mechanics.
How are entities born?
Disclaimer: I'm a long-time user of and contributor to Freebase, I've written
about its potential uses in search many times and the below represents my
opinion based on externally-visible interactions with Freebase and other Google
products.
After taking some time to study the subject, there seems to be a structure
around how entities are initiated within the Knowledge Graph:
Affinity
As anyone who works with external data will tell you, one of the most
challenging tasks is identifying the levels of trust within a data-set. Google
is not different here; to be able to offer a definitive answer to a query, they
must be confident of its reliability.
After a few experiments with Freebase data, it seems clear that Google are
pretty damn sure the string "Andrew Isidoro" is me. There are a few potential
reasons for this:
Provenance
To take a definition from W3C:
"Provenance is information about entities, activities, and people involved in
producing a piece of data or thing, which can be used to form assessments about
its quality, reliability or trustworthiness."
In summary, provenance is the 'who'. It's about finding the original author,
editor and maintainer of data; and through that information Google can begin to
make judgements about their data's credibility.
Google has been very smart with their structuring of Freebase user accounts.
To login to your account you are asked to sign in via Google; which of course
gives the search giant access to your personal details, and may offer a source
of data provenance from a user's Google+ profile.
Freebase Topic pages also allow us to link a Freebase user profile through the
"Users Who Say They Are This Person" property. This begins to add provenance to
the inputted data and, depending on the source, could add further trust.
External structured data
Recently an area of tremendous growth in material for SEOs has been structured
data. Understanding the schema.org vocabulary has become a big part of our roles
within search but there is still much that isn't being experimented with.
Once Google crawls web pages with structured markup, it can easily extract and
understand structured data based on the markup tags and add it to the Knowledge
Graph.
No property has been more overlooked in the last few months than the sameAs
relationship. Google has long used two-way verification to authenticate web
properties, and even explicitly recommends using sameAs with Freebase within its
documentation; so why wouldn't I try and link my personal webpage (complete with
person and location markup) to my Freebase profile? I used a simple itemprop to
exhibit the relationship on my personal blog:
<link itemprop="sameAs" href="<a href="http://www.freebase.com/m/0py84hb"
>http://www.freebase.com/m/0py84hb</a>">Andrew Isidoro</a>
Finally, my name is by no means common; according to howmanyofme.com there are
just 2 people in the U.S. named Andrew Isidoro. What's more, I am the only
person with my name in the Freebase database, which massively reduces the amount
of noise when looking for an entity related to a query for my name.
Data sources
Over the past few months, I have written many times about the Knowledge Graph
and have had conversations with some fantastic people around how Google decides
which queries to show information panels for.
Google uses a number of data sources and it seems that each panel template
requires a number of separate data sources to initiate. However, I believe that
it is less an information retrieval exercise and more of a verification of data.
Take my age panel example; this information is in the Freebase database yet in
order to have the necessary trust in the result, Google must verify it against a
secondary source. In their patent for the Knowledge Graph, they constantly make
reference to multiple sources of panel data:
"Content including at least one content item obtained from a first resource and
at least one second content item obtained from a second resource different than
the first resource"
These resources could include any entity provided to Google's crawlers as
structured data, including code marked up with microformats, microdata or RDFa;
all of which, when used to their full potential, are particularly good at making
relationships between themselves and other resources.
The Knowledge Graph panels access several databases dynamically to identify
content items, and it is important to understand that I have only been looking
at initiating the Knowledge Graph for a person, not for any other type of panel
template. As always, correlation â causation; however it does seem that
Freebase is a major player in a number of trusted sources that Google uses to
form Knowledge Graph panels.
Search behaviour
As for influencing what might appear in a knowledge panel, there are a lot of
different potential sources that information might come from that go beyond just
what we might think of when we think of knowledge bases.
Bill Slawski has written on what may affect data within panels; most notably
that Google query and click logs are likely being used to see what people are
interested in when they perform searches related to an entity. Google search
results might also be used to unveil aspects and attributes that might be
related to an entity as well.
For example, search for "David Beckham", and scan through the titles and
descriptions for the top 100 search results, and you may see certain terms and
phrases appearing frequently. It's probably not a coincidence that his salary is
shown within the Knowledge Graph panel when "David Beckham Net Worth" is the top
auto suggest result for his name.
Why now?
Dr Pete wrote a fantastic post a few weeks ago on "The Day the Knowledge Graph
Exploded" which highlights what I am beginning to believe was a major turning
point in the way Google displays data within panels.
However, where Dr Pete's "gut feeling is that Google has bumped up the volume
on the Knowledge Graph, letting KG entries appear more frequently," I believe
that there was a change in the way they determine the quality of their data. A
reduction in affinity threshold needed to display information.
For example, not only did we see an increase in the number of panels displayed
but we began to see a few errors in the data:
This error can be traced back to a rogue Freebase entry added in December 2012
(almost a year ago) that sat unnoticed until this "update" put it into the
public domain. This suggests that some sort of editorial control was relaxed to
allow this information to show, and that Freebase can be used as a single source
of data.
For person-based panels, my inclusion seems to show a new era of Knowledge
Graph that Dr Pete reported a few weeks ago. We can see that new "things" are
being discovered as strings then, using data, free text extraction and natural
language processing tools, Google is able to aggregate, clean, normalize and
structure information from Freebase and the search index, with the appropriate
schema and relational graphs, to create entities.
Despite the brash headline, this post is a single experiment and should not be
treated as gospel. Instead, let's use this as a chance to generate discussion
around the changes to the Knowledge Graph, for us to start thinking about our
own hypotheses and begin to test them. Please leave any thoughts or comments
below.
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/~3/9wwqJPILyTc/i-am-an-entity-hacking-the-knowledge-graph
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
Knowledge Graph'
Posted by Andrew_IsidoroThis post was originally in YouMoz, and was promoted to
the main blog because it provides great value and interest to our community. The
author's views are entirely his or her own and may not reflect the views of Moz,
Inc.
For a long time Google has algorithmically led users towards web pages based
on search strings, yet over the past few years, we've seen many changes which
are leading to a more data-driven model of semantic search.
In 2010 Google hit a milestone with its acquisition of Metaweb and its
semantic database now known as Freebase. This database helps to make up the
Knowledge Graph; an archive of over 570 million of the most searched-for people,
places and things (entities), including around 18 billion cross-references. A
truly impressive demonstration of what a semantic search engine with structured
data can bring to the everyday user.
What has changed?
The surge of Knowledge Graph entries picked up by Dr Pete a few weeks ago
indicates a huge change in the algorithm. Google has been attempting to
establish a deep associative context around the entities to try and understand
the query rather than just regurgitate what it believes is the closest result
for some time, but this has been focused on a very tight dataset reserved for
high profile people, places and things.
It seems that has changed.
Over the past few weeks, while looking into how the Knowledge Graph pulls data
for certain sources, I have made a few general observations and have been
tracking what, if any, impact certain practices have on the display of
information panels.
If I'm being brutally honest, this experiment was to scratch a personal
"itch." I was interested in the constructs of the Knowledge Graph over anything
else, which is why I was so surprised that a few weeks ago I began to see this:
It seems that anyone now wishing to find out "Andrew Isidoro's Age" could now
be greeted with not only my age but also my date of birth in an information
panel. After a few well-planned boasts to my girlfriend about my new found fame
(all of which were dismissed as "slightly sad and geeky"), I began to probe
further and found that this was by no means the only piece of information that
Google could supply users about me.
It also displayed data such as my place of birth and my Job. It could even
answer natural language queries and connect me to other entities like in queries
such as: "Where did Andrew Isidoro go to school?"
and somewhat creepily, "Who are Andrew Isidoro's parents?".
Many of you may now be a little scared about your own personal privacy, but I
have a confession to make. Though I am by no means a celebrity, I do have a
Freebase profile. The information that I have inputted into this is now
available for all to see as a part of Google's search product.
I've already written about the implications of privacy so I'll gloss over the
ethics for a moment and get right into the mechanics.
How are entities born?
Disclaimer: I'm a long-time user of and contributor to Freebase, I've written
about its potential uses in search many times and the below represents my
opinion based on externally-visible interactions with Freebase and other Google
products.
After taking some time to study the subject, there seems to be a structure
around how entities are initiated within the Knowledge Graph:
Affinity
As anyone who works with external data will tell you, one of the most
challenging tasks is identifying the levels of trust within a data-set. Google
is not different here; to be able to offer a definitive answer to a query, they
must be confident of its reliability.
After a few experiments with Freebase data, it seems clear that Google are
pretty damn sure the string "Andrew Isidoro" is me. There are a few potential
reasons for this:
Provenance
To take a definition from W3C:
"Provenance is information about entities, activities, and people involved in
producing a piece of data or thing, which can be used to form assessments about
its quality, reliability or trustworthiness."
In summary, provenance is the 'who'. It's about finding the original author,
editor and maintainer of data; and through that information Google can begin to
make judgements about their data's credibility.
Google has been very smart with their structuring of Freebase user accounts.
To login to your account you are asked to sign in via Google; which of course
gives the search giant access to your personal details, and may offer a source
of data provenance from a user's Google+ profile.
Freebase Topic pages also allow us to link a Freebase user profile through the
"Users Who Say They Are This Person" property. This begins to add provenance to
the inputted data and, depending on the source, could add further trust.
External structured data
Recently an area of tremendous growth in material for SEOs has been structured
data. Understanding the schema.org vocabulary has become a big part of our roles
within search but there is still much that isn't being experimented with.
Once Google crawls web pages with structured markup, it can easily extract and
understand structured data based on the markup tags and add it to the Knowledge
Graph.
No property has been more overlooked in the last few months than the sameAs
relationship. Google has long used two-way verification to authenticate web
properties, and even explicitly recommends using sameAs with Freebase within its
documentation; so why wouldn't I try and link my personal webpage (complete with
person and location markup) to my Freebase profile? I used a simple itemprop to
exhibit the relationship on my personal blog:
<link itemprop="sameAs" href="<a href="http://www.freebase.com/m/0py84hb"
>http://www.freebase.com/m/0py84hb</a>">Andrew Isidoro</a>
Finally, my name is by no means common; according to howmanyofme.com there are
just 2 people in the U.S. named Andrew Isidoro. What's more, I am the only
person with my name in the Freebase database, which massively reduces the amount
of noise when looking for an entity related to a query for my name.
Data sources
Over the past few months, I have written many times about the Knowledge Graph
and have had conversations with some fantastic people around how Google decides
which queries to show information panels for.
Google uses a number of data sources and it seems that each panel template
requires a number of separate data sources to initiate. However, I believe that
it is less an information retrieval exercise and more of a verification of data.
Take my age panel example; this information is in the Freebase database yet in
order to have the necessary trust in the result, Google must verify it against a
secondary source. In their patent for the Knowledge Graph, they constantly make
reference to multiple sources of panel data:
"Content including at least one content item obtained from a first resource and
at least one second content item obtained from a second resource different than
the first resource"
These resources could include any entity provided to Google's crawlers as
structured data, including code marked up with microformats, microdata or RDFa;
all of which, when used to their full potential, are particularly good at making
relationships between themselves and other resources.
The Knowledge Graph panels access several databases dynamically to identify
content items, and it is important to understand that I have only been looking
at initiating the Knowledge Graph for a person, not for any other type of panel
template. As always, correlation â causation; however it does seem that
Freebase is a major player in a number of trusted sources that Google uses to
form Knowledge Graph panels.
Search behaviour
As for influencing what might appear in a knowledge panel, there are a lot of
different potential sources that information might come from that go beyond just
what we might think of when we think of knowledge bases.
Bill Slawski has written on what may affect data within panels; most notably
that Google query and click logs are likely being used to see what people are
interested in when they perform searches related to an entity. Google search
results might also be used to unveil aspects and attributes that might be
related to an entity as well.
For example, search for "David Beckham", and scan through the titles and
descriptions for the top 100 search results, and you may see certain terms and
phrases appearing frequently. It's probably not a coincidence that his salary is
shown within the Knowledge Graph panel when "David Beckham Net Worth" is the top
auto suggest result for his name.
Why now?
Dr Pete wrote a fantastic post a few weeks ago on "The Day the Knowledge Graph
Exploded" which highlights what I am beginning to believe was a major turning
point in the way Google displays data within panels.
However, where Dr Pete's "gut feeling is that Google has bumped up the volume
on the Knowledge Graph, letting KG entries appear more frequently," I believe
that there was a change in the way they determine the quality of their data. A
reduction in affinity threshold needed to display information.
For example, not only did we see an increase in the number of panels displayed
but we began to see a few errors in the data:
This error can be traced back to a rogue Freebase entry added in December 2012
(almost a year ago) that sat unnoticed until this "update" put it into the
public domain. This suggests that some sort of editorial control was relaxed to
allow this information to show, and that Freebase can be used as a single source
of data.
For person-based panels, my inclusion seems to show a new era of Knowledge
Graph that Dr Pete reported a few weeks ago. We can see that new "things" are
being discovered as strings then, using data, free text extraction and natural
language processing tools, Google is able to aggregate, clean, normalize and
structure information from Freebase and the search index, with the appropriate
schema and relational graphs, to create entities.
Despite the brash headline, this post is a single experiment and should not be
treated as gospel. Instead, let's use this as a chance to generate discussion
around the changes to the Knowledge Graph, for us to start thinking about our
own hypotheses and begin to test them. Please leave any thoughts or comments
below.
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
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[Build Great Backlinks] TITLE
Build Great Backlinks has posted a new item, 'Triple X Niche Case Study Update:
Expenses Report'
Last month we mentioned that the Triple X Niche Case Study was now live on
ViperChill. If you missed the launch then a quick summary is that three people
will be tackling the same industry with three different approaches. I (Glen) am
only allowed to focus on social media. Diggy (my SEO business partner) is []
You may view the latest post at
http://www.viperchill.com/triple-x-expenses/
You received this e-mail because you asked to be notified when new updates are
posted.
Best regards,
Build Great Backlinks
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Expenses Report'
Last month we mentioned that the Triple X Niche Case Study was now live on
ViperChill. If you missed the launch then a quick summary is that three people
will be tackling the same industry with three different approaches. I (Glen) am
only allowed to focus on social media. Diggy (my SEO business partner) is []
You may view the latest post at
http://www.viperchill.com/triple-x-expenses/
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, 'The Shape of Things to Come:
Google in 2014'
Posted by gfiorelli1
We can't imagine the future without first understanding the past.
In this post, I will present what I consider the most relevant events we
experienced this year in search, and will try to paint a picture of things to
come by answering this question: How will Google evolve now that it has acquired
Wavii, Behav.io, PostRank, and Grapple, along with machine learning and neural
computing technology?
The future of Google will be based on entity search, semantic search, and
¼ber-personalization, and all the technologies it acquired will interact
with one another in order to shape the Google we will experience in 2014. I'll
show you how to deal with it.
The past
Last year, in my "preview" post The Cassandra Memorandum, besides presenting
my predictions on what would have been the search marketing landscape during
this 2013, I presented a funny prophecy from a friend of mine: the "Balrog
Update," an algorithm that, wrapped in fire, would have crawled the web,
penalizing and incinerating sites which do not include the anchor text "click
here" at least seven times and do not include a picture of a kitten asleep in a
basket.
Thinking back, though, that hilarious preview wasn't incorrect at all.
In the past three years, we've had all sorts of updates from Google: Panda,
Penguin, Venice, Top-Heavy, EMD, (Not Provided) and Hummingbird (and that's just
its organic search facet).
Bing, Facebook, Twitter, and other inbound marketing outlets also had their
share of meaningful updates.
For many SEOs (and not just for them), organic search especially has become a
sort of Land of Mordor...
For this reason, and because I see so often in the Q&A, in tweets sent to me,
or in requests for help popping up in my inbox, how many SEOs feel discouraged
in their daily work by all these frenzied changes, before presenting my vision
of what we need to expect in Search in 2014, I thought it was better to have our
own war speech.
Somehow we need it:
(Clip from the "The Lord of the Rings: The Return of the King" by Peter
Jackson, distributed by Warner Bros)
A day may come when the courage of SEOs fails. But it is not this day.
A methodology
"I give you the light of Earendil ... May it be a light for you in dark
places,
when all other lights go out."
Even if I'm interested in large-scale correlation tests like the Moz Search
Engine Ranking Factors, in reality I am convinced that the science in which we
best excel is that of hindsight.
For example, when Caffeine was introduced, almost no one imagined that that
magnification of the SERPs would have meant its deterioration too.
Probably not even Google had calculated the side effects of that epochal
infrastructural change, and only the obvious decline in the quality of the SERPs
(who remembers this post by Rand) led to Panda, Penguin, and EMD.
But we understood just after they rolled out that Panda and Co. were needed
consequences of Caffeine (and of spammers' greed).
And despite my thinking that every technical marketer (as SEOs and social
media marketers are) should devote part of their time to conducting experiments
that test their theories, actually the best science we tend to apply is the
science of inference.
AuthorRank is a good example of that. Give us a Patent, give us some new
mark-up and new social-based user profiling, and we will create a new theory
from scratch that may include some fundamentals but is not proven by the facts.
Hindsight and deduction, however, are not to blame. On the contrary; if
done wisely, reading into the news (albeit avoiding paranoid theories) can help
us perceive with some degree of accuracy what the future of our industry may be,
and can prepare us for the changes that will come.
While we were distracted...
While we were distractedâfirst by the increasingly spammy nature of
Google and, secondly, by the updates Google rolled out to fight those same
spammy SERPsâBig G was silently working on its evolution.
Our (justified) obsession with the Google zoo made us underestimate what
were actually the most relevant Google "updates:" the Knowledge Graph, Google
Now, and MyAnswers.
The firstâwhich has become a sort of new obsession for us
SEOsâwas telling us that Google didn't need an explicit query for showing
us relevant information, and even more importantly, that people could stay
inside Google to find that information.
The second was a clear declaration of which field Google is focusing its
complete interest on: mobile.
The third, MyAnswers, tells us that Personalizationâor, better,
¼ber-personalizationâis the present and future of Google.
MyAnswers, recently rolled out in the regional Googles, is a good example
of just how much we were distracted. Tell me: How many of you still talk about
SPYW? And how many of you know that its page now redirects to the MyAnswers one?
Try it: www.google.com/insidesearch/features/plus/â.
What about Hummingbird?
Yes, Hummingbird, the update no SEO noticed was rolled out.
Hummingbird, as I described in my latest post here on Moz, is an
infrastructural update that essentially governs how Google understands a query,
applying to all the existing "ranking factors" (sigh) that draw the SERPs.
From the very few things we know, it is based over the synonym dictionaries
Google was already using, but applies a concept based analysis over them where
entities (both named and search) and "word coupling" play a very important role.
But, still, Google is attending primary school and must learn a lot, for
instance not confusing Spain with France when analyzing the word "tapas" (or
Italy with the USA for "pizza"):
But we also know that Google has bought DNNresearch Inc. and its deep
neural networks, which had gained great experience in machine learning with
Panda, and that people like Andrew Ng moved from the Google X team to the
Knowledge Team (the same of Amit Singhal and Matt Cutts), so it is quite
probable that Google will be a very disciplined student and will learn very
fast.
The missing pieces of the "future" puzzle
As with any other infrastructural change, Hummingbird will lead to visible
changes. Some might already be here (the turmoil in the Local Search as
described by David Mihm), but the most interesting ones are still to come.
Do you want to know what they are? Then watch and listen to what Oren
Etzioni of Wavii (bought by Google last April 2013) says in this video:
As well described by Bill Slawski here:
The [open information] extraction approach identifies nouns and how they
might be related to each other by the verbs that create a relationship between
them, and rates the quality of those relationships. A âclassifierâ
determines how trustworthy each relationship might be, and retains only the
trustworthy relationships.
These terms within these relationships (each considered a
âtupleâ) are stored in an inverted index that can be used to respond
to queries.
So, it can improve the usage of the immense Knowledge Base of Google, along
with the predictive answers to queries based on context. Doesn't all this remind
you what we already see in the SERPs?
Moreover, do you see the connection with Hummingbird and how it can link
together the Knowledge Graph, Google Now, and MyAnswers; and ultimately also
determine how classic organic results (and ads) will be shown to the users over
a pure entity-based and semantic analysis, where links will still play a role,
but not be so overly determinant?
So, if I have to preview the news that will shake our industry in 2014, I
would look to the path Wavii has shown us, but also especially to the solutions
that Google finds for answering the questions Etzioni himself was presenting in
the video above as the challenges Wavii still needed to solve.
But another acquisition may hide the key to those questions: the team from
Behav.io.
I say team, because Google did not buy Behav.io as a society, but the
entire team, which became part of the Google Now area.
What was the objective of Behav.io? It was looking at how peoplesâ
locations, networks of phone contacts, physical proximity, and movement
throughout the day could help in predicting a range of behaviors.
More over, Behav.io was based over the smart analysis of the all the data
the sensors in our smartphones could tell about us. Not only GPS data (have you
ever looked at your Location History?), but also the speakers/microphones, the
proximity detection between two or more sensors, which apps we use and which we
download and discard, the lighting sensors, browser history (no matter which
search engines we use), the accelerometer, SMS...
You can imagine how Google could use all this information: Again, for
enhancing the predictive solution of any query that could matter to us. The
repercussions of this technology will be obvious for Google Now, but also for
MyAnswers, which substantially is very similar to Google Now in its purposes.
The ability to understand app usage could allow Google to create an
interest graph for each one of us, which could enhance the "simple"
personalization offered by our web history. For instance, I usually read the
news directly from the official apps of the newspapers and magazines I like, not
from Google News or a browser. I also read 70% of the posts I'm interested in
from my Feedly app. All that information would normally not be accessible by
Google, but now that it owns the Behav.io technology, it could access it.
But the Behav.io technology could also be very important for helping Google
understand what the real social graph of every single person is. The social
graph is not just the connection between profiles in Facebook or Twitter or
Google Plus or any other social network, nor is it the sum of all the
connections of every social network. The "real life social graph" (this
definition is mine) is also composed of the relations between people that we
don't have in our circles/followers/fans, people we contact only by phone, short
text messages or WhatsApp.
Finally, we should remember that back in 2011 Google acquired two other
interesting startups: PostRank and Social Grapple. It is quite sure that Google
has already used their technology, especially for Google Plus Analytics, but I
have the feeling that it (or its evolution) will be used to analyze the quality
of the connections we have in our own "real life social graph," hence helping
Google distinguish who our real influencers are, and therefore to personalize
our searches in any facet (predictive or not predictive).
Image credit: Niemanlab.org
Another aspect that we probably will see introduced once and for all will
be sentiment analysis as a pre-rendering phase of the SERPs (something that
Google could easily do with the science behind its Prediction API). Sentiment
Analysis is needed, not just because it could help distinguishing between
documents that are appreciated by its users and those that are not. If we agree
that semantic search is key in Hummingbird; if we agree that Semantic is not
just about the triptych subject, verb, and object; and if we agree that natural
language understanding is becoming essential for Google due to Voice Search,
then sentiment analysis is needed in order to understand rhetoric figures (i.e.
the use of metaphors and allegories) and emotional inflections of the voice (the
ironic and sarcastic tones, for instance).
Maybe it is also for these reasons that Google is so interested in buying
companies like Boston Dynamics? No, I am not thinking of Skynet; I am thinking
of HAL 9000, which could be the ideal objective of Google in the years to come,
even more so than the often-cited "Star Trek Computer."
What about us?
Sincerely, I don't think that our daily lives as SEOs and inbound marketers
will radically change in 2014 from what they are now.
Websites will still need to be crawled, parsed, and indexed; hence
technical SEO will still maintain a huge role in the future.
Maybe from a technical point of view, those ones who still have not
embraced structured data will need to do so, even though structured data by
itself is not enough to say that we are doing semantic SEO.
Updates like Panda and Penguin will still be rolled out, with Penguin
possibly introduced as a layer in the Link Graph in order to automate it, as it
happens now with Panda.
And Matt Cutts will still announce to us that some link network has been
"retired."
What I can predict with some sort of clarityâand for the simple
reason that people and not search engines definitely are our targetsâis
that real audience analysis and cohort analysis, not just keywords and
competitor research, will become even more important as SEO tasks.
But if we already were putting people at the center of our jobsâif we
already were considering SEO as Search Experience Optimizationâthen we
won't change the they we work that much.
We will still create digital assets that will help our sites be considered
useful by the users, and we will organize our jobs in synergy with social,
content, and email marketing in order to earn the status of thought leaders in
our niche, and in doing so will enter into the "real life social graph" of our
audience members, hence being visible in their private SERPs.
The future I painted is telling us that is the route to follow. The only
thing it is urging us to do better is integrate our internet marketing strategy
with our "offline" marketing strategy, because that distinction makes no sense
anymore for the users, nor does it make sense to our clients. Because marketing,
not just analytics, is universal.
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/N3sD0R4aDBQ/search-marketing-in-2014
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
Google in 2014'
Posted by gfiorelli1
We can't imagine the future without first understanding the past.
In this post, I will present what I consider the most relevant events we
experienced this year in search, and will try to paint a picture of things to
come by answering this question: How will Google evolve now that it has acquired
Wavii, Behav.io, PostRank, and Grapple, along with machine learning and neural
computing technology?
The future of Google will be based on entity search, semantic search, and
¼ber-personalization, and all the technologies it acquired will interact
with one another in order to shape the Google we will experience in 2014. I'll
show you how to deal with it.
The past
Last year, in my "preview" post The Cassandra Memorandum, besides presenting
my predictions on what would have been the search marketing landscape during
this 2013, I presented a funny prophecy from a friend of mine: the "Balrog
Update," an algorithm that, wrapped in fire, would have crawled the web,
penalizing and incinerating sites which do not include the anchor text "click
here" at least seven times and do not include a picture of a kitten asleep in a
basket.
Thinking back, though, that hilarious preview wasn't incorrect at all.
In the past three years, we've had all sorts of updates from Google: Panda,
Penguin, Venice, Top-Heavy, EMD, (Not Provided) and Hummingbird (and that's just
its organic search facet).
Bing, Facebook, Twitter, and other inbound marketing outlets also had their
share of meaningful updates.
For many SEOs (and not just for them), organic search especially has become a
sort of Land of Mordor...
For this reason, and because I see so often in the Q&A, in tweets sent to me,
or in requests for help popping up in my inbox, how many SEOs feel discouraged
in their daily work by all these frenzied changes, before presenting my vision
of what we need to expect in Search in 2014, I thought it was better to have our
own war speech.
Somehow we need it:
(Clip from the "The Lord of the Rings: The Return of the King" by Peter
Jackson, distributed by Warner Bros)
A day may come when the courage of SEOs fails. But it is not this day.
A methodology
"I give you the light of Earendil ... May it be a light for you in dark
places,
when all other lights go out."
Even if I'm interested in large-scale correlation tests like the Moz Search
Engine Ranking Factors, in reality I am convinced that the science in which we
best excel is that of hindsight.
For example, when Caffeine was introduced, almost no one imagined that that
magnification of the SERPs would have meant its deterioration too.
Probably not even Google had calculated the side effects of that epochal
infrastructural change, and only the obvious decline in the quality of the SERPs
(who remembers this post by Rand) led to Panda, Penguin, and EMD.
But we understood just after they rolled out that Panda and Co. were needed
consequences of Caffeine (and of spammers' greed).
And despite my thinking that every technical marketer (as SEOs and social
media marketers are) should devote part of their time to conducting experiments
that test their theories, actually the best science we tend to apply is the
science of inference.
AuthorRank is a good example of that. Give us a Patent, give us some new
mark-up and new social-based user profiling, and we will create a new theory
from scratch that may include some fundamentals but is not proven by the facts.
Hindsight and deduction, however, are not to blame. On the contrary; if
done wisely, reading into the news (albeit avoiding paranoid theories) can help
us perceive with some degree of accuracy what the future of our industry may be,
and can prepare us for the changes that will come.
While we were distracted...
While we were distractedâfirst by the increasingly spammy nature of
Google and, secondly, by the updates Google rolled out to fight those same
spammy SERPsâBig G was silently working on its evolution.
Our (justified) obsession with the Google zoo made us underestimate what
were actually the most relevant Google "updates:" the Knowledge Graph, Google
Now, and MyAnswers.
The firstâwhich has become a sort of new obsession for us
SEOsâwas telling us that Google didn't need an explicit query for showing
us relevant information, and even more importantly, that people could stay
inside Google to find that information.
The second was a clear declaration of which field Google is focusing its
complete interest on: mobile.
The third, MyAnswers, tells us that Personalizationâor, better,
¼ber-personalizationâis the present and future of Google.
MyAnswers, recently rolled out in the regional Googles, is a good example
of just how much we were distracted. Tell me: How many of you still talk about
SPYW? And how many of you know that its page now redirects to the MyAnswers one?
Try it: www.google.com/insidesearch/features/plus/â.
What about Hummingbird?
Yes, Hummingbird, the update no SEO noticed was rolled out.
Hummingbird, as I described in my latest post here on Moz, is an
infrastructural update that essentially governs how Google understands a query,
applying to all the existing "ranking factors" (sigh) that draw the SERPs.
From the very few things we know, it is based over the synonym dictionaries
Google was already using, but applies a concept based analysis over them where
entities (both named and search) and "word coupling" play a very important role.
But, still, Google is attending primary school and must learn a lot, for
instance not confusing Spain with France when analyzing the word "tapas" (or
Italy with the USA for "pizza"):
But we also know that Google has bought DNNresearch Inc. and its deep
neural networks, which had gained great experience in machine learning with
Panda, and that people like Andrew Ng moved from the Google X team to the
Knowledge Team (the same of Amit Singhal and Matt Cutts), so it is quite
probable that Google will be a very disciplined student and will learn very
fast.
The missing pieces of the "future" puzzle
As with any other infrastructural change, Hummingbird will lead to visible
changes. Some might already be here (the turmoil in the Local Search as
described by David Mihm), but the most interesting ones are still to come.
Do you want to know what they are? Then watch and listen to what Oren
Etzioni of Wavii (bought by Google last April 2013) says in this video:
As well described by Bill Slawski here:
The [open information] extraction approach identifies nouns and how they
might be related to each other by the verbs that create a relationship between
them, and rates the quality of those relationships. A âclassifierâ
determines how trustworthy each relationship might be, and retains only the
trustworthy relationships.
These terms within these relationships (each considered a
âtupleâ) are stored in an inverted index that can be used to respond
to queries.
So, it can improve the usage of the immense Knowledge Base of Google, along
with the predictive answers to queries based on context. Doesn't all this remind
you what we already see in the SERPs?
Moreover, do you see the connection with Hummingbird and how it can link
together the Knowledge Graph, Google Now, and MyAnswers; and ultimately also
determine how classic organic results (and ads) will be shown to the users over
a pure entity-based and semantic analysis, where links will still play a role,
but not be so overly determinant?
So, if I have to preview the news that will shake our industry in 2014, I
would look to the path Wavii has shown us, but also especially to the solutions
that Google finds for answering the questions Etzioni himself was presenting in
the video above as the challenges Wavii still needed to solve.
But another acquisition may hide the key to those questions: the team from
Behav.io.
I say team, because Google did not buy Behav.io as a society, but the
entire team, which became part of the Google Now area.
What was the objective of Behav.io? It was looking at how peoplesâ
locations, networks of phone contacts, physical proximity, and movement
throughout the day could help in predicting a range of behaviors.
More over, Behav.io was based over the smart analysis of the all the data
the sensors in our smartphones could tell about us. Not only GPS data (have you
ever looked at your Location History?), but also the speakers/microphones, the
proximity detection between two or more sensors, which apps we use and which we
download and discard, the lighting sensors, browser history (no matter which
search engines we use), the accelerometer, SMS...
You can imagine how Google could use all this information: Again, for
enhancing the predictive solution of any query that could matter to us. The
repercussions of this technology will be obvious for Google Now, but also for
MyAnswers, which substantially is very similar to Google Now in its purposes.
The ability to understand app usage could allow Google to create an
interest graph for each one of us, which could enhance the "simple"
personalization offered by our web history. For instance, I usually read the
news directly from the official apps of the newspapers and magazines I like, not
from Google News or a browser. I also read 70% of the posts I'm interested in
from my Feedly app. All that information would normally not be accessible by
Google, but now that it owns the Behav.io technology, it could access it.
But the Behav.io technology could also be very important for helping Google
understand what the real social graph of every single person is. The social
graph is not just the connection between profiles in Facebook or Twitter or
Google Plus or any other social network, nor is it the sum of all the
connections of every social network. The "real life social graph" (this
definition is mine) is also composed of the relations between people that we
don't have in our circles/followers/fans, people we contact only by phone, short
text messages or WhatsApp.
Finally, we should remember that back in 2011 Google acquired two other
interesting startups: PostRank and Social Grapple. It is quite sure that Google
has already used their technology, especially for Google Plus Analytics, but I
have the feeling that it (or its evolution) will be used to analyze the quality
of the connections we have in our own "real life social graph," hence helping
Google distinguish who our real influencers are, and therefore to personalize
our searches in any facet (predictive or not predictive).
Image credit: Niemanlab.org
Another aspect that we probably will see introduced once and for all will
be sentiment analysis as a pre-rendering phase of the SERPs (something that
Google could easily do with the science behind its Prediction API). Sentiment
Analysis is needed, not just because it could help distinguishing between
documents that are appreciated by its users and those that are not. If we agree
that semantic search is key in Hummingbird; if we agree that Semantic is not
just about the triptych subject, verb, and object; and if we agree that natural
language understanding is becoming essential for Google due to Voice Search,
then sentiment analysis is needed in order to understand rhetoric figures (i.e.
the use of metaphors and allegories) and emotional inflections of the voice (the
ironic and sarcastic tones, for instance).
Maybe it is also for these reasons that Google is so interested in buying
companies like Boston Dynamics? No, I am not thinking of Skynet; I am thinking
of HAL 9000, which could be the ideal objective of Google in the years to come,
even more so than the often-cited "Star Trek Computer."
What about us?
Sincerely, I don't think that our daily lives as SEOs and inbound marketers
will radically change in 2014 from what they are now.
Websites will still need to be crawled, parsed, and indexed; hence
technical SEO will still maintain a huge role in the future.
Maybe from a technical point of view, those ones who still have not
embraced structured data will need to do so, even though structured data by
itself is not enough to say that we are doing semantic SEO.
Updates like Panda and Penguin will still be rolled out, with Penguin
possibly introduced as a layer in the Link Graph in order to automate it, as it
happens now with Panda.
And Matt Cutts will still announce to us that some link network has been
"retired."
What I can predict with some sort of clarityâand for the simple
reason that people and not search engines definitely are our targetsâis
that real audience analysis and cohort analysis, not just keywords and
competitor research, will become even more important as SEO tasks.
But if we already were putting people at the center of our jobsâif we
already were considering SEO as Search Experience Optimizationâthen we
won't change the they we work that much.
We will still create digital assets that will help our sites be considered
useful by the users, and we will organize our jobs in synergy with social,
content, and email marketing in order to earn the status of thought leaders in
our niche, and in doing so will enter into the "real life social graph" of our
audience members, hence being visible in their private SERPs.
The future I painted is telling us that is the route to follow. The only
thing it is urging us to do better is integrate our internet marketing strategy
with our "offline" marketing strategy, because that distinction makes no sense
anymore for the users, nor does it make sense to our clients. Because marketing,
not just analytics, is universal.
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peter.clarke@designed-for-success.com
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