Nitro-Net.com – Internet Marketing Services – A Global Marketing Group Company

Episode Overview: Search is defined by user intent, and understanding intent through the SERP features created to answer user queries can reveal the nuances of user intent. Join host Ben as he speaks with G2 Vice President of SEO and Content Kevin Indig about how to reverse engineer user intent via SERPs and how to best utilize it in SEO.

Summary

  • An essential principle to follow is, if your content doesn’t meet, or answer, user intent, your content won’t rank. 
  • There are three categories to user intent; informational, transactional and directional.
  • User intent continually modifies and changes over time, including the different ways people interpret and use keywords over time.

GUESTS & RESOURCES

Ben:                   Welcome to the Voices of Search podcast. I’m your host, Benjamin Shapiro and today we’re going to talk to one of my favorite SEOs who every time we talk he’s got a different job. Joining us today is Kevin Indig who is the vice president of SEO and content at G2. G2 is the world’s leading B2B software and services review platform. And until recently selecting businesses software was difficult and inherently risky, but using G2s real verified user reviews, they help you objectively really assess what is best for your business. Now prior to taking his role at G2, Kevin was the head of technical SEO at Atlassian, he was the director of SEO at Dailymotion and once upon a time he was an SEO at the world’s greatest SEO SAAS platform our friends at Searchmetrics.

Ben:                  Yesterday in my conversation with Kevin, we talked about his new role at G2 and how he recommends SEOs take advantage of reviews and review sites. And today we’re going to talk about something that Kevin has been working on outside of his daily job at G2, which is reverse engineering the user intent using the SERP. Okay, here is the second part of my conversation with Kevin Indig VP of SEO and content at G2. Kevin, welcome back to the Voices of Search podcast.

Kevin:            Great to be back as always.

Ben:                Excited to have you here. Hey yesterday I mentioned that every time we talk you have changed your jobs, are you still at G2?

Kevin:            I’m still at G2.

Ben:               All right, good.

Kevin:           Ask me again tomorrow.

Ben:               I will, I will ask you again tomorrow. I’m glad that you’re sitting tight, I love G2 it’s a great company, a service we use all the time. And today we’re going to talk about something that you’ve been thinking about and talking about and speaking about publicly which is how you can reverse engineer user intent through the SERP. Let’s start off by talking about user intent, what do you mean by user intent before we start figuring out how to break it into its pieces?

Kevin:           Great question, thank you for that. And the way that I understand user intent is basically the end goal that the user has in mind when performing a google search. That sounds relatively trivial but it’s a bit more complex for a couple of reasons but the biggest one is that the machine has to understand what that actually is. And we as human beings are very good at understanding implicit meaning, but for search engines it has to be as explicit as possible. But to be fair search engines have, especially Google has gotten much much better at understanding implicit intent over the last couple of years with things like RankBrain or most recently Bird.

Kevin:            But the idea of user intent is interesting and important for marketers and especially SEOs to understand because it’s a ranking enabler. And what that means is that if your content does not meet user intent, you will not rank. It pretty much doesn’t matter what content you have or how many backlinks you have or what brand you have user intent is more or less like a gateway to search results.

Ben:                 So when I think about user intent, I think about something that Jordan Koene told me about SDL a long time ago, which was there’s really three categories for user intent. There’s informational, transactional and directional. Are you thinking about user intent from a more complex segmentation than those three terms? Or is it really just if someone is searching for a given query am I hitting the right bucket with my content?

Kevin:              I think that pretty much hits it on the head and the answer is yes, I do think about user intent from a more sophisticated standpoint of view. It used to be that for a very long time don’t get me wrong, these models are not incorrect. But as search engines have become smarter, they’re also able to detect a much finer user intent that fits into these different buckets. Now, Google publishes these rater guidelines and in the rater guidelines they distinguished between six different user intents but my assumption is that there are actually hundreds of different user intents.

Kevin:              And when we dive a bit deeper into the topic we’ll see that users have learned to use certain modifiers to indicate their user intent. So when users for example, look for something like best software they obviously want a ranking or they want a list. We as humans again we get that of course they want that, they want to pick from something because they want the best. For machines that’s something that they just figured out in the last couple of years. And so this whole kind of idea of reverse engineering user intent is this idea of monitoring closely what layouts or a better said SERP features, Google shows in the search results. To then derive from that how Google understands the search intent for a certain keyword.

Ben:                 So talk me through what you mean by SERP features that help dictate what the user intent is.

Kevin:             Right. So SERP features are all sorts of modules that Google shows in the search results to give people a better answer aside from the organic results. So it could be featured snippets, people also ask boxes, knowledge cards, local pegs, image carousels, just like this-

Ben:                 Reviews.

Kevin:             Yeah. Reviews of course. There’s this whole list of different SERP features I don’t even know how many there are, there must be over 30 by now if not 50 maybe. So this is constantly growing as Google is giving more and more answers itself and it’s very interesting because this whole change took place in 2018. That’s when there was a blog article on the Google webmaster’s blog about the last 20 years of search and in the same context a gentleman named Ben Gomez who was the SVP of news assistant and search. Which is a very interesting title wrote about the next 20 years in search and in that article he touched on three big shifts.

Kevin:           For example, the shift from queries to a query-less search experience. The shift from text to images and the shift from questions to answers. And so within that, they also introduced this technology called the topic layer which sits on top of the knowledge graph which is Google’s database of entities like names, places, people, books and so on. And so now with the topic layer they’re also able to understand topics like opinions or trends, news and all that kind of stuff. And that’s why with the technology advance and these shifts in search they start to show more and more SERP features. Meaning we can get smarter about understanding how Google actually interprets user intent.

Ben:                So you mentioned before that there are modifiers and a term like best indicates that you want to list. And if you have a keyword that says best MarTech tools or best MarTech podcast, or hey best SEO podcasts. Google is probably going to have a list of somebody writing a ranking review showing obviously the Voices of Search podcast is at the top. What are some other modifiers? What are some other sort of common examples you have and how can you reverse engineer that to understand the intent?

Kevin:            Yeah, that’s a great question. A couple of more examples are versus queries. Something like Asana versus Jira or a product one versus product two. Something like cheap in front of an ecommerce term like “Cheap vacuum cleaner,” stuff like that or tutorials at the end of a query or inspiration or images, destination. There’s a whole long list and I think I’ve touched on most of these in this article that I wrote a while ago about reverse engineering user intent. But the interesting thing is, that’s very fascinating that the definition of these things changes over time especially with modifiers like best, cheap and a couple of others.

Kevin:            Because what do you define as best? That’s not always easy to define. For example look for something like best smartphone. Is the best smartphone the most durable one? The cheapest? Is it the one with the most high quality component? It’s subjective and Google gets better at understanding the subjectivity behind these queries and gives you suggestions for what you might actually mean. I call these things query refinement bubbles and you’ve might’ve seen these in search already. These little bubbles, these little buttons that you can click to further refine your search and Google shows that because they understand that best is subjective. And the more you indicate to them what you define as best or fastest or cheapest or whatever, the more they will modify the search results for you.

Ben:                 So let’s try to make this actionable for the SEO listening to this podcast. When I understand that my query has some sort of a modifier or when I go onto the SERP and I see that there is a search element how do I connect the two? How do I actually make it actionable to not only understand the user intent but improve rankings?

Kevin:             Yeah, that’s a good question. So you take a tool like let’s say Searchmetrics for example, which allows you to track keywords but also shows you the SERP features that it found for a specific keyword. From that you would create a spreadsheet and say that whenever Google shows SERP feature X, the user intent equals Y. And so one example could be that whenever Google shows a featured snippet, the user intent is probably to learn something or to understand something better. I think we’ll get a bit more in the nitty gritty later on how to segment that further but once you have that spreadsheet, you have an indicator of not only what formats your content has to come in but also what your content has to be about.

Kevin:            So say for example, you’re a marketplace like ours and you see that people are looking for a lot of lists, then you want to make sure that you have not just the results on G2 like the different products that fit into a category. But you also want to make sure that you have some texts on your category page that indicates those lists. That makes it easy for Google to pull from structured data and show a list. And the same way you could say, if you see that there’s a paragraph featured snippet for your site say you have a blog, then you want to make sure that your content actually has a paragraph that can speak to that featured snippet the same with image carousels or local packs. You want to adapt and adjust your format depending on what SERP features Google actually shows for a query.

Ben:                So I think the key word is formatting, right? When you’re understanding what the query is and you can look at the elements that Google has on the SERP. You can go back and reformat your content and make sure that you have the right elements that give you the highest probability to show up in that knowledge graph type experience whatever it may be.

Kevin:            Yes and let’s take this a step further. What about shorthead keywords? Like let’s say side cuts, right? So you look for the query “Side cuts hairstyle.” Now that’s a relatively ambiguous-

Ben:                Is that a thing?

Kevin:            I guess for undercut or whatever it’s called, gosh I’m not a hair stylist. I’m no barber Ben-

Ben:                It’s the era of the coronavirus, no one is a barber.

Kevin:            Clearly not. Some people do a bit better than others. So say you look for something like that, right? Like “Side cut.” That is an ambiguous query, which means that there are several interpretations of what a person actually wants with that query. Meaning there are several user intents. And so one of them could be just images of a side cut because they want to see what it looks like, maybe they’ve heard about it from a friend. Another one could be a tutorial, so how do you actually do a side cut yourself? Or another one could be a barber that can get you a side cut.

Kevin:            So there are all these different possibilities of what a person actually might want and that’s where we have to look at the search results and the SERP features to understand what’s not just the right format, but also content is. So as a website you then want to make sure that you don’t just describe what a side cut is, in best case you probably show some images as well. And you might have a video tutorial or a written tutorial and that would make sure you cover your basis in terms of user intent. Instead of just assuming what your perception of the user intent is for that keyword.

Ben:                For what it’s worth, anybody that’s driving or on their treadmill a side cut is essentially Miley Cyrus’s haircut.

Kevin:           Yeah.

Ben:               Had to google it. Image graph comes up first.

Kevin:           Hey, here we go. See this is something that I was not prepared for and so if I were to create content for that I better know and I better have a tool that tells me some of these things that images are very important for that user intent or searcher intent. So then you can take the next step and think about like what images to add to your site and maybe what more you could do to make sure that you stand out in an image carousel. That’s kind of the next step from optimizing for these SERP features.

Ben:              I feel like that’s a really important takeaway. Most SEOs are thinking about keywords and on page content and they’re not always connecting the dots to what the search experience is on Google and building around how their content will be shown. And so thinking about the user intent and gauging how Google is interpreting the user intent by what modules they’re putting on the SERP is a really interesting way to start thinking about creating more relevant, targeted searches. And that wraps up this episode of the Voices of Search podcast. Thanks for listening to my conversation with Kevin Indig, the vice president of SEO and content at G2.

Ben:             If you’d like to get in touch with Kevin we’re going to have a link to his LinkedIn profile in our show notes. You can contact him on Twitter, his handle is Kevin_Indig. Or you can visit his personal website, which has Kevin-Indig.com. Just one more link in our show notes I’d like to tell you about. If you didn’t have a chance to take notes while you were listening to this podcast, head over to voicesofsearch.com where we have summaries of all of our episodes, the contact information for our guests. You can send us your topic suggestions, your SEO questions, you can even apply to be a guest speaker on the Voices of Search podcast.

Ben:            Of course you can always reach out on social media. Our handle is Voices of Search on Twitter and my personal handle is BenJShap. And if you haven’t subscribed yet and you want a daily stream of SEO and content marketing insights in your podcast feed, we’re going to publish episodes every day during the work week. So hit the subscribe button in your podcast app and we’ll be back into your feed soon. All right, that’s it for today but until next time remember the answers are always in the data.

Original Source

Advertisement