Query templates: Expanding the scope of topical authority

Topical authority isn’t built by covering a topic alone. It also depends on how well your content covers the different ways people search for that topic. Query templates provide a way to map those variations and build a stronger, more connected content network.

There are two main methodologies for building topical authority: covering every entity and its attributes within a topic or covering every variation of a query template. Examples of both methodologies are below.

• Entities of the same type share the same set of attributes. “Calorie” is an attribute of every entity in the “food” class, just as “symptom” is an attribute of every entity in the “disease” class. Processing an entire entity class through its shared attributes signals comprehensive coverage of the topic to the search engine.

• Query template variations, on the other hand, don’t require topical relevance to one another. WikiHow, for example, holds authority for the “how to” query template, which allows it to rank across many unrelated topics at the same time. In this case, the authority attaches to the query format rather than to a single topic.

The hybrid methodology is the strongest of these approaches. It covers all entities from the same class, with all of their attributes, across all query template variations, and it unites topical depth with query format breadth in a single content network.

The first case study, Visual semantics: The missing piece of topical authority , explains how to use web components and design elements to improve query responsiveness along with query relevance. 

The second case study, How semantics and topical authority improve local SEO , covers the “Query Deserves a Page” principle and its framework across 13 different local SEO projects. 

Reading both will make it easier to follow the concepts and results in this mini case study.

Why does Google use structural similarity between queries and documents?

Because it’s cheaper.

The cost of retrieval is always central to understanding Google’s ranking decisions because Google is primarily designed to save costs rather than to serve the best. If a website’s quality is 6/10 and its cost is 7/10, it’s not worth retrieving. The principle of cost of retrieval is explained in one sentence:

“The cost of ranking a site can’t exceed the cost of not ranking a site.”

Query templates help Google satisfy more users and drive more clicks while organizing more sources with lower computational needs. 

If a website satisfies a query and there is another similar query, Google triggers a test for ranking purposes. This created the concept of semantic content network , meaning that a group of web documents is semantically connected to cover all of the semantic query network to trigger a re-ranking.

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Query templates for a QR code generator

The first example project in this case study doesn’t appear in the previous two articles.

It’s a QR code generator that gained over 1 million extra clicks in three months, mainly through microsemantic changes, supported by technical SEO improvements and a CMS migration. 

To keep the focus on the query template aspect, I’ll keep the technical improvements and checks brief.

Three-month comparison for a QR code generator EMD project. The first example project demonstrates a hybrid approach to topical authority, targeting both attributes and template variations based on the QDP principle.

Technical improvements

Besides the query template- and query semantics-related reasons and the historical click data signals, the main technical improvements are listed below.

• The website was migrated from WordPress to Next.js with Sanity as the back-end CMS.

• During the migration, the image-to-image, HTML-to-HTML, CSS-to-CSS, and JavaScript-to-JavaScript migration principles were followed, meaning every asset type was mapped to its equivalent on the new stack.

• All non-indexed URLs were removed from the website to prune the source’s crawl profile.

• Response times were improved to increase crawl efficiency.

• No resources or URLs were left behind during the migration. Everything was moved to the new system.

• Structured data was updated.

• It was ensured that the “centerpiece annotation” of the website, the QR code generator itself, is served without requiring JavaScript rendering.

• The only change in the CMS migration was the back-end infrastructure. The content, layout, and URLs were all kept the same.

• The HTML structure was cleaned and the DOM size was reduced.

To show the importance of handling redirections at the back-end infrastructure level, I can use the image crawling and image ranking changes. I have two rules for every migration:

• Change only one thing at a time.

• Never leave any URLs or resources behind so the search engine can adapt to the new system faster.

If you look at the image performance data below, we’re losing rankings because we couldn’t redirect all of the images on the site. We were only able to redirect the most important ones. 

This partial redirection is a problem in itself because my default position is never to change image or video URLs at all. Indexing is far more costly and slower for these resource types, so any changes to them take much longer for a search engine to process and trust again.

Cost of retrieval is a concept that I use as one of the inspirations behind topical authority because it isn’t about delivering more quality. It’s mainly about being cheaper relative to your quality. The cost of ranking a site can’t exceed the cost of not ranking a site. 

If ranking you is costlier than not ranking you, deindexing begins. Since we couldn’t keep the image URLs the same during the migration, you can see how this is reflected in the crawl data below.

I always try to increase the number of crawl requests per URL because it consistently improves rankings, indexing speed, and crawl delay, and increases the number of query terms the site covers. 

In this case, however, the total crawl hits per day decreased after the migration, and that’s actually a positive signal. The decrease came from the non-necessary section, the “other file types” segment, while crawl requests for the HTML section increased.

Smartphone crawl requests increased as well. The crawl ratio of indexable HTML URLs that are self-canonicalized, included in the sitemap, and supported by internal links also increased, which is positive. 

But as you can see, image requests and image rankings moved in the wrong direction together due to a migration error.

Google creates landing page and image pairs to rank web documents. For that reason, image rankings affect a website’s overall rankings far beyond just image impressions or clicks.

According to the purpose, platform, and type of the QR code, the query semantics change, sometimes slightly and sometimes heavily, depending on the contextual domain. 

A contextual domain is the collection of all the context vectors that can be created from a term by adding one or two more words through vectorization.

Query component Position Variations Contextual noun Beginning of the query PDF, PNG, JPG, URL, Phone, Website, Menu, Hotel, Event, Facebook, Instagram, Dynamic, Static, Trackable Central entity Middle of the query QR Code Tool synonym End of the query Generator, Creator, Maker, Designer

For example, the predicates that we can use for “Facebook QR Code Generator” and “PDF QR Code Generator” are mostly shared, but they differ in ways that matter for relevance. 

The predicate “download” is semantically close and highly relevant to “PDF QR Code,” whereas it sits much further from “Facebook QR Code,” where predicates like “share” or “follow” dominate. 

Here’s a comparison of the index