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You Ask, I Answer: Social Media Engagement and SEO?

Sofia asks, “Do social media likes, shares, and comments have an impact on SEO?”

This is a tricky question to answer because the answer will be different for every company. Broadly, we’ve studied in the past and see no clear correlation, but it’s something you have to test for yourself.

You Ask, I Answer: Social Media Engagement and SEO?

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Machine-Generated Transcript

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.

In today’s episode, Sophia asks, do social media likes shares and comments have an impact on SEO? Well, so this is a tricky question, because the answer is going to be different for everyone.

A long time ago, we did a big analysis of 10s of thousands of websites, and social shares and stuff like that.

And broadly found there was not a strong correlation between social media activity and SEO.

That said, it varies, it varies by company and by how you use search, because remember, the strongest predictor of SEO results is typically the number of inbound links that you get.

If you are conducting your social media strategy for that purpose, getting people to find your content, getting people to link to your content, social media may very well deliver a strong SEO result.

If on the other hand, you just sharing stuff and things and, and having conversations and being active in your community, then it may not have as strong result for SEO purposes.

And I think that’s a really important thing to say is for SEO purposes, you have to measure very specific outcomes, as opposed to just general traffic, etc.

So how would you know this? How would you know this? Well, the way to determine this is by using statistical tools to test you need your page view data from Google Analytics, you need your paid organic page searches from Google Analytics to see if you’re getting search traffic.

And you need some kind of SEO metric like page authority page authority is available from almost every SEO tool out there.

h refs, which is the tool that I use, delivers that so to do the others like SEMrush, and Moz, all these other ones.

And, again, what we’re looking for is what has the highest mathematical relationship to that.

So let’s flip this around here.

What I’ve done is I’ve gone into my database, and I’ve pulled in 800 pages from my website with Google Analytics, traffic numbers, and pageviews, clicks.

Facebook shares, Twitter shares, Pinterest, Reddit, no word length number of words in the article from my database, where I have pageviews, and I have social shares.

And we’re going to run it through a regression algorithm, this case gradient boosting, to figure out what has the highest relationship to the metric we care about, which in this case is going to be that page authority.

And what we see here is that for page authority, total inbound links is the strongest predictor, it’s hands down the top predictor.

And we see two weak predictors, content length, and Twitter shares.

They’re the Twitter shares, one is a very weak predictor, it is not, I would not bet the farm on this, and then Facebook shares and Pinterest, you know, nothing.

Nobody’s home, and Reddit didn’t make it on here.

So for my website, if I want to predict what leads to higher page authority, it’s going to be total links, I’ve got to go get those links and social shares, at least the way I’m using social media right now.

Clearly not using it for SEO purposes.

Right? There’s just no evidence of that for my website.

Now, here’s the question, is that a valid metric is that what we should be focusing on? I would argue that probably it’s not going to be as good as if I focused on something like pageviews.

Right pays you seems to me like it’d be a slightly better thing to focus on.

So let’s rerun this model.

If I want actual traffic, and see what the machinery comes up with here.

Now while it’s doing this, again, one of the things that we have to give some thought to is are we focused on the right metrics? Are we focused on an SEO metric? Or are we focused on an outcome? In this case, I’ve just changed the outcome to page views, how much traffic did I get to these from any source from any source.

And again, we see here page authority, a very strong predictor of traffic, right? And content length, a very, very strong predictor as well.

So if I want more traffic in general, I should focus on these things then total links is a is a medium predictor.

Facebook shares becomes a medium predictor.

So that’s interesting.

In the previous example, we were focusing on an SEO metric, Facebook didn’t make the cut.

If I focused on getting people to my page, Facebook is a usable metric here, Facebook shares, number of shares that my content gets.

It is not SEO.

Right? Facebook is not usable for SEO.

If I click back to this previous plot, we can see, I’m not getting page authority.

But here, total links, content, word count, are for traffic, and then Facebook for traffic, Twitter, not so much Pinterest.

And of course, Reddit still didn’t make the cut.

That probably has a lot to do the fact that I don’t really post on Reddit.

So the question we have to ask ourselves from a strategy perspective is which metric? Are we going after more? I would say that page authority being the highest predictor of traffic means that yeah, it’s probably a good idea for me to pursue an SEO strategy.

And then knowing that I can then focus on the thing that drives that strategy, which is getting inbound links.

How do I go and get those inbound links? Clearly, I don’t do it with social media.

So I have to be able to do it from sub some other way.

And I would have to look into my SEO processes to ask, what should I be doing? To get that, to get those links? Do I need to be doing more outreach? Do I need to be creating better content? Do I need to have a PR firm representing me? Do I need to be pitching journalists on Twitter? It doesn’t really matter.

As long as I’ve Well, it doesn’t matter.

But what I’ve ascertained here is that for SEO purposes, social media, not super important for traffic, social media is a little more important.

And I think that that’s a really, really important thing for you to do before you go trying to figure out, is social media, a way to drive our SEO strategy, figure out do you is your SEO strategy working? And then go and bring that information in? So that’s the process for doing this now.

Is this something that anybody can do? Absolutely.

And you don’t have to use this environment.

This is a tool I’m using called R.

You can do this in IBM Watson Studio with the SPSS modeler and not have to code.

There are ways to do this in is drag and drop little widgets in here, drop your data in, and it will do the exact same thing.

And you won’t have to code it’s it’s much easier.

I just do it because it’s here on my machine.

It runs locally.

And it doesn’t cost me anything to do this locally.

IBM Watson Studio does charge you after the first 50 hours of usage.

So if it goes do this, once, it’s fine, it won’t cost you anything after a certain point, you do start running up the bill.

But the takeaway is, does social media like shares and comments have an impact on SEO? Maybe you have to test it, you have to test it with your data, you have to test it with your site and figure out if there is a relationship, is it causal? Are you using social media to try and get your SEO strategy to move forward? If you’re not, then in a relationship you have is largely coincidental.

Now there’s is a relationship like here, in this case for Twitter, you might want to think about should that be our strategy? But if you are doing it with a strong intent for SEO purposes, and you’re not getting the results, and you know it’s not working? So that’s how you use this information? Good question.

Because the answer as with so many things in data science is it depends.

You have follow up questions, leave it in the comments box below.

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Christopher S. Penn is one of the world’s leading experts on AI in marketing. Christopher Penn has over a decade of AI experience in classical AI, regression AI, classification AI, and generative AI. Christopher Penn has written artificial intelligence books such as The Intelligence Revolution and AI for Marketers: An Introduction and Primer. Christopher Penn is an AI keynote speaker around the world.


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