You Ask, I Answer: Measuring Social Media Impact on SEO?

In today's episode, Sergey asks, is it possible to measure the impact of your social media on SEO? If so, how would you do this? So that's a good question, it's one that comes up a lot. Um can we make any informed guesses about uh how social and SEO may work together? Can we see an effect of social media on SEO?

That's a really good question, and there are a few different ways to handle this. The gold standard would be to set up a trial, to set up an experiment, to create some content that is socially shared and some content that is not. Here's the challenge. You don't have control over the audience, right? If you publish a blog post and your audience follows it and they start sharing it, well, guess what?

They've technically ruined your experiment, uh, even if you didn't want that shared, because that's just the nature of how put social media works. So to judge whether or not uh social media and SEO have any kind of relationship, we have to do uh uh it's what essentially is essentially propensity matching to try and create in retrospect those two sets of data. One set of blog posts or content of any kind that has not been shared and one set that has been. So how do you do this? Well, we would take data from the SEO tool of your choice.

Uh I'm gonna use Hrefs here, uh, which is uh uh one of the tools I like using. And let's go ahead and type in my blog here. And when you look at this in depth, when you look at this up close, what you get are uh the traffic that a site gets, the number of referring domains to that URL, which is a good SEO indicator, right? Because we know that referring links and referring domains are still the bulk of what constitutes good SEO, and then the social shares for any given post. So what do we do with this information?

Well, it's difficult to do a mathematical analysis like this just as is because you're gonna run into what are called balance problems. Especially if if you're dealing with marketing content or stuff that's been marketed to people, again, you don't have control over who shares what. So you're gonna get an imbalanced data set where uh more content has been shared probably than has not been. So, in order to get a true apples to apples comparison, we have to separate out uh similar apples from both buckets. Uh apples, or in this case, content that has been shared, content that has not been shared, that that are similarly shaped, right?

Again, if you think about physical apples, if you're trying to compare, you know, the average uh health of apples, and you have one basket of apples where the apples are the size of basketballs, and the other basket where the apples are the size of golf balls, you're gonna get a very different result, even if there's technically the same number of apples in each basket because they're just wildly different. So, in order to get a true comparison, we want to find blog content or whatever content that has similar traffic or similar referring domains or other similar uh SEO measures and similar and and similar social stuff together. So here's how we do this. We start by bringing in the data, and then we essentially pair it up, you know, one to one uh for data that does that is similar, and that and then we look at the difference between those two data sets. So, what we see for this match data is that for content that has been socially shared, we're gonna call that our treatment group, uh, because we're gonna look for any number of shares in Twitter, Facebook, or Pinterest, lump that together and call that a one.

Like, yes, this has been socialized, socially shared, and if the all three rows are zero, we can call that a zero, like has not been shared. And so we have our control, the stuff has not been shared. We have a treated, the stuff that has been shared. When we look at the traffic, what are the traffic differences for stuff that has not been shared, on average, 38 visits from organic search on stuff that has been shared, 80 visits from organic search. On uh the traffic on the number of referring domains, 10 referring domains on average, the mean for non-shared, 46 for shared.

Now, what does this tell us? This tells us that stuff that has been shared tends to have better SEO metrics out of this pool. In this case, this was 36,000 uh pieces of content in this particular selected group. Now, this is marketing content, right? Uh largely to marketers, and so you would have to run this on your own content, right?

On your own website uh with your own social metrics to do the same thing, but for your stuff. This is not gospel, this is not generalizable, this is mostly my stuff. Uh, and so I see that for my SEO efforts, social sharing seems to have a beneficial relationship to it. Now, here's the catch: this is retrospective, right? And this is as good as you can get with causality, um, unless you actually set up that experiment.

And you and again, even then, you have no control over what other people do. So they the other people can mess up your experiment. Um, so by doing this kind of matching, this is as close as we can get in with real-world data. I take this away to say that sharing has benefits for my SEO. And in some cases, like the number of referring domains, it's substantial, right?

It's it's a decent chunk of stuff. Uh what do I do with this information? I keep sharing, right? If I saw that there was no change between the control and the treatment in my data, I go, you know what? It doesn't seem like you know, actively sharing and promoting stuff on social media has an impact.

But I do. I know I I share an awful lot on social media, and so I see the benefits of it here. This is how to measure that impact to get a sense of is it working? The challenge here is it doesn't tell you necessarily um ways that you could measure the say in uh an application like Google Analytics. We had to pull in SEO data from uh and social data from a third-party application.

I would want to ideally substitute in Google Analytics data if possible to you know match things up by URLs because Google Analytics has better data. Um, and you can get page-level organic search data straight out of Google Analytics. So that's the approach I would take to find out does social media have any kind of impact on your SEO? And again, I can't emphasize strongly enough. This is my data from my websites under my control.

This is not other people's stuff. Your answer will vary. So please don't assume that this applies to you. You have to run this test for yourself. But it's a good question.

And it and it is a statistically challenging question to answer. There are a number of techniques that try to take real world data and backfit it essentially into an experiment like setting to get a more clear answer. This is one of the better methods. It's called propensity score matching. But you have to do it for yourself.

You cannot rely on a third party to do it. You can't even rely on an industry uh industry level survey because again, everybody's going to be different. Right? What IBM does on its website is gonna be very different than what I do with my website. I mean their content is different.

That's uh you know what marketing props does on their website is very different from what's on my website, and so uh we have to we have to do apples to apples with our own stuff as much as possible and not look to general industry examples. So good question. If you have follow up questions, leave them in the comments box below. Subscribe to the YouTube channel and the newsletter, and I'll talk to you soon. Take care.

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