Analyzing Social Media Sharing with BuzzSumo: B2B Market Research podcast

Episode 78: – Analyzing Social Media Sharing with BuzzSumo – An Interview with Steve Rayson

We cover:

  • The difference between using Google and a tool like BuzzSumo for intelligence collection.
  • How the analysis of Social Sharing data, across platforms such as LinkedIn and Twitter, allows you to blend a form of human intelligence with streams of public data.
  • What happens when you type a competitor’s domain name or keywords that are aligned with a competitor into BuzzSumo.

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Modified transcript:

[Sean]

Welcome to another episode of the B2B Market Research podcast. In this podcast, we’ll be interviewing one of the folks from BuzzSumo, a tool that we have grown to appreciate quite a bit over the last few months.

With that, I want to turn the discussion over to our guest from BuzzSumo. Why don’t you go ahead and introduce yourself and then we’ll get started?

[Steve Rayson]

My name is Steve Rayson, one of the directors at BuzzSumo, and I’m looking forward to the podcast.

[Sean]

In terms of BuzzSumo, there’s a lot of things we could talk about, but the first thing that jumps out is the fact that you guys have wrapped the whole thing, in a lot of ways, around social sharing.

In other words, if you go into BuzzSumo and you put in a URL for a competitor, such as their domain name, or you put in a term, like a product name that a competitor offers, the list of articles and links that are going to come up are going to be indexed by how often they’ve been shared. That simple thing alone, indexing on the sharing versus other metrics that Google or whatever might use is really powerful.

What led you guys to think that the social sharing was really going to be the thing you wanted to focus on for the tool?

[Steve Rayson]

That’s a good question, because I think for us, the social side did look very important, really, because Google indexes and organizes everything by some of authority algorithm, but we were just interested in what are people sharing. What’s engaging enough that people want to share it?

Also you start to see who’s amplifying that content, so we thought it would be really interesting to type in a competitor’s domain name, see how many times it’s been shared and see what was the most shared content?

We’re not looking at their most authoritative content. We’re looking at simply what’s the most shared constant that your competitors got, and you might want to filter that by all of their most shared content today, or their most shared content last week … Then we can show you what was the most shared, but also importantly, who shared that, so it’s a great list of seeing who’s amplifying your competitor’s content, because we live in a competitive world.

You’re not just seeing what’s good content, you’re seeing who are the other people who are actually sharing that content and which platforms are they sharing it on?

As the user, you can re-filter your list by platform. You will get quite different lists, whether you’re sorting by Facebook or by LinkedIn, because different people use different networks, but the centrality of what we’re doing is really looking at that social engagement, in terms of people sharing content.

It just creates really interesting lists, simply what was the most shared content on a topic yesterday, or what was the most shared content from your competitor. In terms of what’s engaging, which might help you with your own content marketing, or help you understand what your competitor’s doing.

For us, the social sharing was absolutely fundamental. It is different from Google’s based on authority, but often that means you just get Wikipedia number one on every search. We’re really looking at what was the most shared on any particular day, and the filtering by time period, we think, really helps as well.

[Sean]

What I find really fascinating about what you’re talking about is, it’s really kind of a fusion of human intelligence and digital intelligence, right? Every Facebook like, every LinkedIn like, and every Twitter re-tweet, is an individual human being saying, ‘I found relevancy in what that competitor is sharing and what they’re doing, whether that’s positive or negative news for the competitor, right? You’re really fusing those two worlds.

[Steve Rayson] 

Whether you agree or disagree, that article that’s being shared most by your competitor is clearly resonating with a particular audience, because they want to share it with their followers. They may want to share it for a number of reasons, but they still want to just share that content.

I think you’re right about the fusion. It’s really bringing out what people are sharing. I think you can then get other intelligence

The most popular button on the site is a little button called “View Shares.” They like to see who’s been sharing that competitor’s content, and you can export that list.

You can click View Shares, see 1000 people who’ve shared that piece of content, and just export that list as well, so that may be who you want to follow and engage with, because they’re clearly amplifying your competitor’s content, and they’re real people. It can produce a list of the people who are actually sharing that content.

[Sean]

What kind of data set are you guys looking at? I realize some of that is secret sauce, so I don’t want you to expose any of that, obviously, and neither do you, but one of the questions I think CI market research professionals have … because a lot of people in this discipline are highly analytical, kind of quant-focused, in a way. They kind of want to understand the data set.

[Steve Rayson]

We avoid some types of content. We avoid all the product pages on Amazon, and things like that, because we’re not so interested in what’s being shared on those. We do ignore certain pages, but generally include most of the content on the Internet. We track the number of shares of that content, and we put that into our own database. We’ve got a database with billions of items now scrolling massively across.

We really have an index of virtually all of the content that has been published on the Internet, how many social shares, and we keep track of who shared that as well.

In essence, you can basically do a search for any topic, we will find you the most-shared content in that topic. We have an algorithm that categorizes the topic, but we will then just produce for you a date that we show these were 100, top 10,000 most-shared articles.

As you say in the export feature, people like to put it into an Excel sheet, partly because they might want to put it into another sort of database, or they might want to use another tool to slice and dice the data. We actually show quite a lot of data on the page, but we provide a lot more data when you export it. For example, you can’t see the date published on the list, but if you export it, we provide you with the date published and all other forms of data as well.

The exports are incredibly popular for people, and if it’s influenced a list, people like to export it just to put them into a CRM system, or into some sort of outreach database that they happen to be using.

In terms of the data set, we just find content on the web, we track the number of times it’s shared, and we stick it into our own database. We’re not real-time. We periodically during the day update the number of social shares, so it’s not actual real-time, but it’s close enough, really, for most people, for the purposes of what we’re doing.

[Sean]

As a closing question, where do you think social sharing is headed? When you look at what’s been talked about, Google seems to be kind of angling more and more that way with recent releases. What do you think is the future of this, because you guys have found a nice little niche, and I don’t think we’re really done, in a lot of ways.

[Steve Rayson]

I think that’s right. I’m surprised really, that more people aren’t doing what we’re doing, looking at this data, because the signals are really important signals.

Some people would argue that people share things, and they don’t really read it. That may be true in part, but people don’t share stuff unless they think it’s reasonable quality, I think.

You wouldn’t want to share something if it was a terrible piece of content, because it reflects badly on you. So I think people do have some quality control about what they share. They may not read the whole of an article, but they may know the author.

I think it is a really important social signal, because it’s not just that people have read the article and gained something from it. They actually want to share that with their followers, or with a particular audience. I think it’s an important indicator.

We also track back links, for example, so along with who shared it, it will also show who linked to it, because both are important. I think social signals are just growing in importance.

I don’t know if you read that article from the New York Times? What that survey showed quite clearly was the number of people finding content through Google search was actually declining, and the number of people getting to that site through social sidewalls was actually increasing.

I can see this for myself increasingly. I find articles through feeds on LinkedIn or on Facebook, etc., that my friends are sharing, I click on it, I go read that article. That’s rising in how I view content, as opposed to going to Google and searching. I’m still doing that, but actually, people finding content through social referrals is just growing.

I thought the report that was leaked from the New York Times showed that very clearly, the rise in people reaching their pages through social referrals, as opposed to people searching on Google for a specific topic. I think there’s no question that’s increasing, I think, the importance of those social signals.

[Sean]

That’s a great way to wrap it. I saw the same New York Times article you mentioned too. Yeah, there’s a huge importance in that. We’ve even seen it in our own analytics over the years, the number of just the inbound links from those platforms, so completely agree.

With that, I want to wrap things up. Thanks for coming on the podcast.

 

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