It’s smart to organize content when you have a core piece of pillar content linked to several smaller pieces covering sub-topics around your main topic. Also, it’s about knowing what to include in a topic cluster and how to organize information within a hub-and-spoke content model.
Today’s guest is Skyler Reeves from Ardent Growth, a content intelligence consultancy. Building out topic clusters can be expensive, especially when mistakes are made. How much time and resources does it take to produce multiple pieces to make something like the hub-and-spoke model work the first time around?
Ben: Hey, Skyler. How's it going this Friday afternoon?
Skyler: It's going pretty well, Ben. How about yourself?
Ben: Not too bad. Just wrapping up another busy week. We were chit-chatting before we actually jumped into the interview here. It sounds like you've had a pretty busy week as well.
Skyler: Yeah. It's been busy. We've been working on some new internal tools to speed up our processes internally. Something we're constantly trying to do is figure out ways to simplify things for everyone with the way they do their work so they can get it done faster and more accurately. That's taking the bulk of the week, working on those tools to make that happen.
Ben: For sure. The internal process sometimes takes a lot of legwork upfront, but once you get things where they need to be, it starts to take care of all those problems.
I'm so glad to have you on the show to talk about content intelligence which I understand is your core focus. I feel like the term content intelligence, if somebody was unfamiliar with it, they might take it to mean multiple different things potentially. They might define it in multiple different ways. In your own words, what do you mean by content intelligence?
Skyler: You can think of content intelligence as this intersection between content strategy and business intelligence. That's the way we look at it. We're applying data and data modeling whether through databases, rendering stuff out in Tableau, or coming up with formulas and algorithms to answer questions that we want to know about the content before we actually go to make those decisions.
You can think of it as a precursor or an overarching theme to content strategy and content marketing.
Ben: Sure. That makes sense. What led you down this path of pursuing content intelligence as a discipline? What really motivated you to niche down in this direction?
Skyler: I'd say a large part of it were the problems that we were facing and the questions that we wanted answers to.
My background is in computer science and engineering. I got into this world of content marketing, SEO, and things like that. There was a lot of talk especially because of HubSpot from 2017 when they talked about this hub-and-spoke model. That all sounded good. It's a nice theoretical framework, but we were always left with trying to answer this question of how do you know what the perfect hub is? How do you know when something needs to be part of hub A or part of hub B especially when you're trying to rank these things on search engines?
I said, all right, let's see if we can figure out the answer to this question. That's what we've been working on and have a solution for now. In a nutshell, it's really just because we had our own problems that we wanted answered and questions that no one else had the answers to, so we went and found them.
Ben: I think it's such an interesting problem to go after too because the topic clusters as a concept are nothing new at this point. Common SEO tools that we're all using will maybe get you a little bit of the way there just by at least identifying some basic relationships between terms and topics.
This is a parent topic. These are some related terms, but they don't really go so far as telling you specifically that if you want to cover this topic, these are all the subpoints that you have to touch on. There's a lot of manual research and subjective analysis that goes into it. Speaking from experience, you never quite feel like you're not getting it right. It's too big, too small, too wide, or too narrow. I think this is really fascinating stuff.
From your perspective, what should marketers care about when they're building topic clusters or when they're focused on—maybe another term people might be familiar with—topic modeling? I feel like that's in the same sphere if you're planning content for a website. Why does it matter? Why worry about it that much?
Skyler: I think that the general way people approach this is because—like you mentioned—it is a very tedious process to try to get it right. That's assuming that you know how to approach the problem to begin with. You do end up left with this feeling of, is it exactly the way that it needs to be? But at the end of the day, we start to take action. We start to move forward. We can't just sit there in analysis paralysis.
The value that comes from it is that if you spend all this time doing the tedious work, it takes too long. If you do use parent keywords—I think Ahrefs has a parent keyword—that's a great way to start.
It's not as accurate because the way the parent keyword works is based off of what's the highest-volume term that those pages rank for things like that. That's assuming that they get it right too, and that's not always the case. The real value that comes from it is that when they plan out a content strategy for the the year or for half a year, if you're going back to refresh existing content, or you're trying to get more value out of what you already have—let's say you're a large site like HubSpot, ActiveCampaign, or CoSchedule even—what you're left with is trying to know what's the fastest way to do this? Where should I prioritize things to get the most value?
If you're creating new content for a brand-new website—let's say you're launching a new feature or a new product—it's knowing what's the easiest and fastest way for me to map out how to create this content in such a way that I'm going to be able to rank for it quicker? Because you always have to account for things like opportunity costs. What do you lose by not doing it the right way to begin with, having to come back after the fact, realizing that you've got pages cannibalizing each other, or you've missed search intent—what people are actually really looking for whenever they search for something?
I think it matters the most because you're dealing with the budget here. We have a model here. There are only two ways to do things—either do them right or you do them again. We prefer to measure twice, cut once. Save budget really is what it comes down to.
Ben: Absolutely. It makes a lot of sense to really tie it back to budget and resource allocation because budget isn't infinite. It can dry up really quickly if the work that you put in doesn't generate the return you're expecting because the data or the strategy was off, and it was going to take too much time to get it on track before you started. It can definitely become a vicious cycle in a lot of ways.
Skyler: Yeah. Depending on the role that you're in with an organization, being able to model this stuff out and begin to sell global financial predictions off of it helps a ton when you try to go and sell that idea to leadership about this is why we want to take this strategy. Here are what our projected upper and lower bounds are on return. Here's what it looks like over time for the return. Here's what the investment resources are going to look like.
You're able to actually come to them with numbers in terms of cost, in terms of revenue, and in terms of projections on ROI. Are they always perfect? No, they're not. But we're always aiming for directionally accurate data. That's all you can really hope for in this world. It's better than coming with no data at all. You're going to have a much better case to be able to argue for your position.
If you're (let's say) in-house somewhere and you're trying to get something done on the blog—you're trying to get content refreshed, trying to get something changed, and you're always having a fight with the developer and getting developer resources for that—being able to come to them and say, here is what the projected return on this is going to be and here's the value that we're losing out by not doing this makes it so much easier to get that greenlight. They'll say yes, the developer resources can be allocated for that. That's a $40,000 return. We can spare two hours to fix that.
Ben: Yeah. I think something that may be picked out there is the term directional data or using data directionally. That's something we talk about internally. It's something that I think about a lot. It's something that comes up in the conversations on the show from time to time. I think it's important to know or just keep in mind that there are limits to how accurate your data is ever going to get, but if you use this as a guide like a weather vane—what way are things moving in—that's great.
Listeners can probably infer what some of the downsides would be just based on some things that we've already touched on here, but if marketers ignore content intelligence or if they ignore even basic data when they're creating a topic cluster or when they're creating content at all, if it's not data-driven, and it's driven purely by gut feeling, intuition, something that's more brand-focused, or whatever it might be, what are the downsides to not having the data that you need to know that you're making a good decision?
Skyler: With most things, I think it depends. I don't think there's a problem with creating content that is more brand-focused. There are going to be benefits from that in the long-term. There's value from sometimes going with your gut. If you can pick your gut instinct and then see if you can validate it with some data, it makes things much easier.
If you completely ignore it altogether though, the main downside is that none of us have perfect data. But if you take two competing organizations—let's say QuickBooks and Xero—and they're head-to-head constantly, every little advantage helps there.
When you ignore data, you risk the opportunity that your competition is not ignoring data. If they're not ignoring data, they're going to take some of your addressable market or your serviceable market. That's at a large scale. That's not a game that I like to roll the dice with.
I would say that's primarily the main downfall of just ignoring it altogether. Again, that's not saying that you can't balance it with being brand-focused, but if it's part of the strategy to build the brand—let's say you're just starting out—you have to get people to trust you and know who you are first. That's best done through branded content.
Sometimes, content intelligence can't answer questions. When we're looking at what I would say is a more very bottom-of-funnel sales enablement type of content, content intelligence isn't always going to help there. You have to rely on data and feedback you're getting from SDRs, from account executives, and things like that to know what's going to resonate with the audience and help them actually be able to close deals.
It really comes down to what are the current constraints that your business is facing? Does it need more awareness? Does it need more sales-enabled material and a more bottom-of-funnel thing?
Ben: It sounds to me like content intelligence has its place in a bigger picture.
Skyler: Yeah. It's all part of business strategy. Everything's a subset of business strategy, so it fits in there.
Ben: Something worth thinking about here that we mentioned in the introduction is if you're wondering why content intelligence is so important or why this topic is so interesting, something to consider might be the potential cost of not using the best data to inform how you structure your topic clusters.
At a minimum, your content might underperform, but worse than that, you might burn the budget on a significant project that doesn't return much on your investment in that content at all. If that happens, that's really going to burn your trust with whoever signed off on you doing that project.
The downsides of ignoring what content intelligence can do are a bit bigger than simply not catering the best stuff possible, and could actually have some significant impacts, not only on how your content performs but potentially on your career.
Now, back to Skyler.
If a marketer or a marketing team is interested in exploring this concept of content intelligence further and they want to use better data to better plan their topic clusters, where would you recommend they start?
Skyler: As with every tool that you ever use, there are always a few things that it can't do that you want it to do. That's why we built ours, but we're not really going to throw ours out to the public.
I would say out there, right now, there are tools like Keyword Insights. I think SE Ranking has one that's somewhat similar. You don't always get all the data that you want. What those will do for you is you'll be able to give it (let's say) a few thousand keywords or something like that, and it will cluster them together for you.
The way it's clustering them is instead of using tools like Ahrefs, SEMrush, Moz, or anything like that—and again, this is under the purview of trying to rank, this is for search traffic—what they'll do is they'll go look at the rankings. They will look for an overlap of similarity between the search results between various keywords.
Whenever they hit a certain threshold of similarity, you can assume based on the way Google works—because Google's trying to give you the best results for the intent that someone has behind their search—that if it's showing very similar results like URLs or a handful of keywords, they're all are following the same intent. They're all essentially the same keyword very close within that topic.
One of them is probably going to have more volume than the rest, and that becomes your main term. The ones that have less volume tend to be your subtopics. Those are going to be your h2s of the page. Those are the questions that people are asking about that topic.
Keyword Insights, Keyword Cupid, and SE Ranking all have ways to do this. The thing they don't do that forced us to go make ours is because it's nice to have everything clustered together, but then you don't know how to prioritize it.
Internally, that's where it may take a little bit more manual work. You have to start to look at what your conversion data looks like. Where is it going to take a minimal amount of effort to get the return?
That's a matter of taking that data. The output they give to you now can be put in the sheet. You can take that sheet and you could probably blend that together with conversion data for analytics, or you can use your gut instinct too if you want to be more ad hoc and say, all right, I know that value is worth a lot to our company. It gets a lot of conversions, so let's go fix that one first.
Ben: Yeah. It's probably worth reiterating that you certainly don't want to disregard what your intuition is telling you, but it tends to be more correct when you have something to validate it against.
Once marketers understand the basics of how topic cluster works, they wrap their minds around how to use these tools—whether it's yours or any other option they might have—they know how to get the data out of those tools, and they have some idea of how to actually apply it, how to prioritize it, how to spot the best opportunities, and how to incorporate it into their content, what are some more advanced tactics that they could consider to really take this to the next level?
Skyler: I was looking at this earlier just as an example. One of the interesting insights to tie this together with the gut instinct conversation is that I think it's always good to listen to your gut because it's usually in some way, shape, or form, influenced—like in this context—by your audience. You know your people, or you should.
What’s interesting if you look at data are the things that you didn't expect. That's when you can really find some interesting opportunities.
Let's say you were to build a topic cluster around a set of keywords. Let's say you're on ActiveCampaign, MailChimp, or Constant Contact. Something in your gut may tell you that email campaign templates and email templates are the same topic, but they're not.
What happens when you go to look at it is you see that for email campaign templates, people are looking for more business templates because of campaigns. For email templates, they're actually still looking for business, but where the intent shifts is they're looking for free templates.
When you go to compare the difference between these, let's say you get an output from one of these tools or if you work on something yourself, what we'll do with ours is we'll take it, we'll look at it, we'll see what the differences are, and then we try to understand why it is different that way.
If you want to get really advanced with it, what we do is we extract data from the title tags, extract data from the meta descriptions, and run some natural language processing on that to figure out what are the similarities amongst these things between each result from Google? That helps us understand what the themes are.
At scale, that's really where this comes in handy. We're trying to set scale because for most of the tools out there, you can put in a couple thousand on them. I think in one of them, they said the other day that they could do about 1000 keywords or 10,000 keywords in about 1 hour or something like that.
We built ours that we could do about 10,000 in about 5 minutes, but when you try to do this over 150,000, 250,000 keywords, trying to figure out intent at scale becomes difficult, trying to figure out theme and scope becomes difficult, and trying to figure out value becomes difficult.
The way you can apply this though is if you go to look through these tools. Let's say you run a [...]. You're going to see in these spreadsheets where there's a variant keyword underneath the main. Perhaps it's something like how to build an email campaign template. You'll see that your website isn't ranking for it.
That's a gap. Go answer that question on that page, and you can begin ranking for it especially if you're already ranking for some of the other topics. Where it becomes really helpful is when you start to compare when you have the same page ranking across different topic clusters. Because usually, one of them is going to be underperforming compared to the other. That means you need to go create a new piece of content for that so you can actually target the main term there with a different intent.
What's really advanced that you can do sometimes when you have two pages competing but very closely—let's say they're positioned 11 or 12—you're trying to solve the cannibalization issue. The easiest way is to google the term. Go to the page (wherever they're both ranking), look at the one that you don't want to rank, look at the meta description—Google rewrites meta descriptions about 80% of the time—take it, and go find where it's at on the page that you don't want to rank.
That's the piece of content that they think is the most relevant to that query. That's why they rewrote that meta description. You can extract that content, add it to the page that you want to rank, and all of a sudden, the one that you don't want to rank will begin dropping off and the one that you do want to rank will begin to come up higher.
That's one of the easiest, quick ways to solve cannibalization without having to rely on your gut. Just go look at what Google's telling you.
Ben: That's a great example because that's such a common problem. A company will be like, okay, this keyword or this topic is super essential for our company to grow. We need to be seen as an authority on this. They'll go, okay, well, we need to create a lot of content on that one thing.
I know that I've definitely been guilty of that to various extents in the past, but it's something that we see frequently. It's a great problem to zero in on and really show how this works and what kinds of problems it can really solve for people.
Skyler: To your point, by the way, too when you mentioned creating a lot of content around that topic. When you said, take a topic modeling approach to it, and you've clustered these things together. It'll also prevent you from wasting time, energy, and budget and creating content that didn't need to be created to begin with.
That's really what it comes down to, just figuring out how do I either save money upfront or how do I get most of it back prior to taking this approach?
Ben: Definitely. Skyler, this has been awesome. Thanks so much for coming on the show. If people want to find you or they want to find Ardent Growth online, where would be the best place for them to go?
Skyler: The best place would probably be LinkedIn. You can search my name, Skyler Reeves. I'm on Twitter, @being_skyler. If you're a fan of the dark social on Slack communities, I'm in Traffic Think Tank. That's a great community.
I'm in Superpath by Jimmy Daly from Animalz. That's a really great community for content marketers. I highly recommend checking that out if you're not already there.
Those are some of the best places to find me and ask questions. I like trying to help people out there and learn from other people as well. Website is ardentgrowth.com.
Ben: Awesome. Very cool. Thanks again, Skyler, for coming on the show and for sharing your insight with our audience. I'm sure that our listeners are really going to get a lot out of this conversation.
Skyler: Appreciate it. Thanks, Ben.
Ben Sailer is the Inbound Marketing Director at Automattic. His specialties include content strategy, SEO, copywriting, and more. When he's not hard at work helping people do better marketing, he can be found cross-country skiing with his wife and their dog.