Mapping the Overlap of SERP Feature Suggestions

Mapping the Overlap of SERP Feature Suggestions

From carousel snippets to related searches to “People also ask” boxes and “People also search for” boxes, the Google SERP is jam-packed with features that not only aid in keyword list creation but can help you better understand the topics your unique search landscape is structured around. We then look at patterns to understand how these subtopics relate to each other, so we can more intelligently surface the type of content you might want to explore next.” But, even before Google came out with its Topic Layer, Cindy Krum, CEO & Founder of MobileMoxie, was all about what she called “entities” as mobile-first indexing was (finally) rolling out. Each PAA suggestion got its own bag, as did each related search, and we removed the search term itself from all of the bags. Other reasons to consider these terms when list-building and content strategizing: Google keeps this snippet right at the top of the SERP and doesn’t require clicking of any kind in order to surface the bubbles, which means they’re one of the first things Google makes sure a searcher sees. The "People also ask" box The “People also ask” box typically contains four questions (before it gets infinite) related to the searcher’s initial query, which then expand to reveal answers that Google has pulled from other websites and links that guide users to a SERP of the PAA question. PAA questions ended up returning the second highest level of duplication, though most of that was tied to terms we pulled from the “People also search for” box — the two had a 10.41 percent overlap. Out of all our comparisons, PASF boxes had the most amount of overlap, particularly with PAAs (which we noted above) and related searches. Given that PASF terms are attached, both physically and topically, to the organic result and not the search query, we actually didn’t expect them to share this much. Even if understanding the topic hierarchies that rule your query space is a little outside of your day-to-day concerns, if people click on search suggestions rather than — or even in addition to — organic results, then it stands to reason that you should at least be trying to rank for these terms as well as the base query. Conversely, since STAT’s got super easy PAA and related searches reports, you could quickly cover about as much ground with those two.

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From carousel snippets to related searches to “People also ask” boxes and “People also search for” boxes, the Google SERP is jam-packed with features that not only aid in keyword list creation but can help you better understand the topics your unique search landscape is structured around.

In fact, the increase of topics and entities as a way of navigating and indexing the web was one of the biggest developments in search in 2018. This is why we took 40,977 SERPS and stripped out every term or phrase from the aforementioned features — a small, first step toward making sense of Google’s organizational skills.

We wanted to see how much overlap might exist across these different SERP features. Does Google give us a lot of new keywords to work with or just suggest the same stuff over and over again? Do we need to pay attention to each SERP feature when building out our SEO strategy or can we overlook a few? We dug into a bunch of data in STAT to find out.

A little bit on topics and entities and SERP features

In September 2018, Google announced a new layer to its knowledge graph:

“The Topic Layer is built by analyzing all the content that exists on the web for a given topic and develops hundreds and thousands of subtopics. For these subtopics, we can identify the most relevant articles and videos—the ones that have shown themselves to be evergreen and continually useful, as well as fresh content on the topic. We then look at patterns to understand how these subtopics relate to each other, so we can more intelligently surface the type of content you might want to explore next.”

But, even before Google came out with its Topic Layer, Cindy Krum, CEO & Founder of MobileMoxie, was all about what she called “entities” as mobile-first indexing was (finally) rolling out. See if you can spot the similarities:

“Entities can be described by keywords, but can also be described by pictures, sounds, smells, feelings and concepts; (Think about the sound of a train station – it brings up a somewhat universal concept for anyone who might hear it, without needing a keyword.) A unified index that is based on entity concepts, eliminates the need for Google to sort through the immense morass of changing languages and keywords in all the languages in the world; instead, they can align their index based on these unifying concepts (entities), and then stem out from there in different languages as necessary.”

Bringing it back to SEO-specifics, Cindy explains that both domains (traditionally associated with indexing) and the brands that operate them can be considered entities. “Indexing based on entities is what will allow Google to group all of a brand’s international websites as one entity, and switch in the appropriate one for the searcher, based on their individual country and language.”

So, what does any of this have to do with our SERP features of choice? Well, all of the suggested terms packed into them are the direct result of Google’s endless topic analysing and organizing. We might not be privy to every entity Google scrapes but we can certainly take cues from how they choose to express the final product on the SERP.

How we made the magic happen

In order to map the overlap in our particular query space, we took the highly scientific word-bag approach. Operating on a SERP-by-SERP level of analysis, we scooped each feature’s suggestions into its own bag, filtered out any stop words, and then compared one bag’s suggestions to another, looking for a match and tallying as we went.

So, for example, we’d examine all the PAA questions on one SERP against all the related searches on the same SERP. Each PAA suggestion got its own bag, as did each related search, and we removed the search term itself from all of the bags. If any remaining…

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