What’s the Real Relationship Between Organic Rankings & Social Shares? (Hint: They’re Related, But Not the Way You Think)
One of the biggest areas of speculation, contention, and confusion within the SEO universe over the past six years or so has been whether (or how much) social media signals impact organic search rankings.
But even if Google isn’t directly using social share counts in their search algorithms, there ought to be some other explanation about why high share counts correlate with high organic search rankings.
That is exactly what we’re going to research in this post.
Are social shares a ranking signal?
People have noticed the connection between social shares and ranking going back to 2010. But correlating rankings and social signals has been a bit of a cat-and-mouse game.
If you’ve done any SEO, you’ve probably noticed the stories that rank well tend to have high social share counts.
These are your unicorns — the extremely popular magical pieces of content that drive a ridiculous amount of traffic to your site. These elite “unicorn” content drive 10–1000x better results than all your other content (the donkeys).
Why do top-performing posts often also have a high number of shares? What exactly is causing these observable correlations?
Some SEOs believed that Google was somehow factoring social share counts into the algorithm like links (though not with nearly the same amount of weight).
Social shares figured into Moz’s Search Engine Ranking Factors 2015, albeit as a low factor:
“Always controversial, the number of social shares a page accumulates tends to show a positive correlation with rankings. Although there is strong reason to believe Google doesn’t use social share counts directly in its algorithm, there are many secondary SEO benefits to be gained through successful social sharing.”
Indeed, there is a strong reason to believe Google doesn’t use share counts as a direct ranking factor.Google has said so.
Google doesn’t use Facebook, Twitter, or any other social share counts as a direct ranking factor.
It’s not shares, it’s engagement
We need a new approach to answer these questions. Maybe we’re looking at the wrong social metrics. Maybe we should be looking at social engagement rates rather than just the total number of social shares.
What percentage of total unique people who saw your update clicked on it and/or shared it?
Perhaps the relationship is that the social posts that get very high engagement rates (which leads to high numbers of shares) come from the same content that get above-average click-through rates in organic search results pages, which we know tends to result in better organic rankings.
But how can we test this theory?
A crazy new correlation study: Social engagement, organic search CTR, & rankings
So here’s my crazy idea: to compare social engagement rates with normalized organic click-through rates for 1,000 pages.
Previous studies have only looked at external-facing number of shares. But bots and other factors can easily taint share counts. Plus, studies have shown that many social media users share content without actually reading it.
How did I do this? I:
- Downloaded post engagement data from Facebook Insights (sharing and engagement data).
- Downloaded query data from Google Search Console (CTR and ranking data).
- Matched up the data. This was somewhat difficult because neither Facebook nor Google provided me with the destination URLs, so some custom programming was required.
Important note: You have to normalize your CTR for search based on position. Obviously higher average positions have higher CTRs than lower positions, so I’ve used my Donkey detection algorithm to compute the expected CTR by position to help determine whether the CTR is above or below expectations.
The results: Organic search CTR vs. Facebook post engagement
Here’s what I’d consider a pretty strong link between higher social post engagement and higher organic CTR (and vice-versa):
Here, a 100% Relative Search CTR corresponds to a keyword/page achieving the expected CTR for organic search for a given ranking; 200% percent is double the expected search CTR; 50% is half the expected CTR, and so on.
What I found was that Facebook posts with extraordinarily high engagement rates — anywhere from 6 to 13 percent — also tended to have above expected organic search CTR.
Why? My theory: The same emotions that make people share things also make people click on those things in the SERPs. This is particularly true for headlines with unusually high CTRs.
The correlations were much stronger with unicorn content. The R-squared values were well above 0.5 — the model is stronger the more of an outlier you’re pushing. Unicorns with high social engagement rates almost always had high organic CTR, and vice versa.
The correlations were substantially weaker with donkey content. The R-squared values were pretty noisy, around .1 to .4. Donkeys sometimes had high engagement rates, sometimes low engagement rates. The same was true with CTR, some high, some low.
So this research illustrates how high social engagement rates correlate with high CTR, and vice versa.
Really, the argument isn’t whether social sharing causes organic search rankings or organic rankings cause social sharing.
It’s about how engaging your content is.
Theory is great. But let’s see if the theory matches by looking at some top-performing content.
Here are just three examples of posts from my company that have top organic rankings on Google and above-expected organic CTR. What was the engagement rate on Facebook?
This post has brought in nearly 500,000 visits from organic search. It had a 7.4 engagement rate on Facebook.
OK. Once is just a fluke.
This post brought in more than 250,000 visits from organic search. It got an 8.5 engagement rate on Facebook.
Two times? Could just be a coincidence.
This piece brought in 100,000 organic visits. It had a 7.1 percent engagement rate when shared on Facebook.
Guys, now we have a trend! All of these posts that rank well had 3x or 4x higher engagement than my average Facebook post.
I could keep posting more examples like these, but it would be more of the same.
Correlation or causation?
What is causing the correlation? There is one thing that makes me certain that the relationship between social engagement and organic click through rates is a co-dependent, causal relationship.
Machine learning systems actually reward high engagement with higher visibility.
Higher visibility means higher organic rankings and more social shares.
To determine success, an algorithm looks at whether users engaged. If more people engage, that’s a clear sign that their algorithm is showing this right content; if not, their systems will audition other content instead to find something that does generate that interest.
Here’s a greatly simplified look at the role machine learning systems play in the Facebook news feed and Google search results. Basically, it’s all about rewarding content that has above-expected engagement:
When a piece of content fails to beat the expected engagement, it won’t get that same visibility, whether it’s on Google, Facebook, or any other system that measures user engagement.
Whenever someone searches on Google for something, Google wants to return the best result. Out of all the potential results Google could show for any given query, Google must find what’s most useful and relevant.
One way Google checks itself is to look at organic click-through rate (but not the only way!). Did users click on the result in Position 1, or did more people click on the Position 2 or 3 result?
Even though all three of these pages may answer a user’s need, click-through rate is a huge clue about whether Google is providing the best answers in the right order for users.
Now let’s think about Facebook. Whenever a piece of content gets hot, it means lots of people are talking about it relative to the number of people who see it, in a short period of time. Are tons of people liking, commenting, and sharing a post?
When this happens, Facebook’s machine learning algorithm gives these posts or topics greater visibility. It becomes a virtuous cycle:
- Post gets lots of user engagement (shares, likes, comments).
- Facebook rewards the engagement by showing it to more users.
- Higher visibility results in the post getting lots more user engagement.
- Facebook rewards the engagement by showing it to more users.
- And so on, until the the social post is no longer new and engagement dwindles.
What to do?
Turn your best social stuff into organic content and vice-versa.
Since stuff that does well on organic social tends to also do great in paid social, it follows that your content that gets top organic rankings will make great content for paid and organic social.
Conversely, your content that gets tons of engagement on social media platforms (paid and organic) will likely rank highly organically for the topics that they cover.
These unicorns I’ve been obsessing about forever matter. Big time. Is your content a sparkly majestic unicorn or a boring old donkey?
At the heart of a unicorn is a truly remarkable, inspiring idea. Truly exciting ideas (not just ideas you think are awesome). Content with remarkably high engagement rates has high conversion rates and does incredibly well in paid and organic search and social media, because of machine learning systems that greatly reward remarkably high user engagement.
The old theory was that high social shares correlates with high organic rankings.
But really it’s not the number of shares that matters. It’s the engagement rate.
Remarkably high social engagement rates correlate strongly with high organic search CTR, which correlates with high rankings. Meaning, click-through rate matters a great deal. Think of it like an invisible hand that helps determine whether your content succeeds (thumbs up) or fails (thumbs down).
What’s happening here is Facebook Ads, Facebook’s news feed algorithm, Google AdWords, and increasingly Google organic search are all systems governed by machine learning systems that reward remarkable engagement with greater visibility.
High engagement rates and machine learning systems are the common factor that explains the correlation between SEO and social metrics.
Originally posted on the Moz Blog.
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