Entity Analytics: How to Measure Your SEO Entity Performance

Entity Analytics: How to Measure Your SEO Entity Performance

Modern search engines and retrieval systems have shifted from keyword-based search to entity-based search. Therefore, as a result many information needs today involve searching for entities and understanding the relationships between them in order to obtain the right answers for searchers’ needs. In simple terms, this means that instead of relying only on term-based searching and term-oriented ranking, we and search engines will exploit the structure of the knowledge graph. That is how entity analytics is born.

In this article, we will focus on understanding how entity analytics is beneficial for developing modern SEO strategies and how it is different compared to previous keyword-based approaches that cannot be used anymore to establish a competitive SEO analysis and SEO entity performance in the modern world.

The casual process of performing keyword research and analysis is to gather keyword information from multiple sources like Google Search Console, Ahrefs, communication strategies or sales data and then obtain the keyword ranking information or keyword volume data points. Then, you would use this information to filter out preliminary queries that fit user needs, calculate their potential for topical authority and embed them into your final content plans.

To measure topical authority for a topic (eg “e-commerce”), we could measure how much (estimated) traffic a site gets from its underlying keywords. Example: if a site gets around 15% of available traffic for a topic and it is the highest share, then this site must be the most authoritative for that topic. Kevin Indig wrote an awesome article covering measuring topical authoritativeness based on defined keywords for a certain niche.

However, with entities in mind, the process is a bit different. We can take two individual approaches for SEO entity performance and entity analytics.

The first one is focused on working with entities in the following way:

To bring more clarity to this approach, we need to explain what graph embeddings, SBERT and wembedders mean. In simple terms, here is what they do:

The second approach that you can use to apply entity analytics to your SEO strategy is using the SEO Add-on for Google Sheets™ by WordLift that we are also using for our clients’ work and strategy planning. The plugin does the following:

This is completely different to keyword analysis, because a separate page for every entity is created accordingly. So imagine that you have an e-commerce web page or you are a publisher like The Next Web and you want to know which pages or news articles are the most popular but on an entity level. Creating those separate entities will allow you to inspect analytics for every separate entity. So instead of analyzing page performance rich of unstructured data like text, you will be able to do analysis on a micro level, inspecting every entity individually. 

Imagine what this could mean for you if you are an e-commerce platform and have multiple cars featured there. We are sure that you would like to know what your audience characteristics are for Audi or Tesla models for example. Our entity-based system establishes exactly that: micro-level analytics focused on entities through entity building. Every page reflects a separate entity, so every data point obtained from Adobe Analytics or Google Analytics will point you to the data points for a single entity instead of analyzing keywords for non-disambiguated data (text web page).

When dealing with multiple entity pages, you can perform entity clustering to obtain only the most interesting and dominant entities and filter out the rest. In fact, this is a recommended approach because over time, the entity corpus is going to grow more and more and some data cleaning and crawl budget optimization will be needed.

When dealing with multiple entity pages, you can perform entity clustering to obtain only the most interesting and dominant entities and filter out the rest. In fact, this is a recommended approach because over time, the entity corpus is going to grow more and more and some data cleaning and crawl budget optimization will be needed.

Entity analytics is a powerful technique when used in the right way and with the right tools. It is just a matter of time when it will get adopted by the wider masses but if you like to remain competitive in your niche, you will definitely need to try it out.

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