You are here

SEO, Contributed

Why Context Matters More Than Keywords

October 25, 2018

Google knows that context matters for query results. The search engine is now using updated algorithms and practices to determine the contextual meaning behind keyword-based searches.

In a recent blog post, Bill Slawski, director of SEO research for Go Fish Digital, says “context” is the SEO buzzword of 2018. I couldn’t agree more.

While most online searches are based on keywords, search engines are moving onto better practices—algorithms—to present their users with more relevant content.

Consequently, search queries increasingly rely on context, not just keywords, to produce results.

For example, the word “python” describes a venomous snake as well as a famous programming language. As a remedy, Google has implemented a series of patents and algorithms in the last 20 years to capture the intent behind users’ queries.

What Context Vectors Are and Why They Matter

Context vectors are vector representations used to retract similar words. Google recently patented "context vectors" to index a database of content via knowledge bodies such as Wikipedia.

Google will be able to embed a wide variety of written language into vectors by getting a patented AI under its RankBrain algorithm, which will help make user searches more contextually relevant.

Google will also factor users’ other inputs to identify intent—whether the user is searching for “Python” or “python.”

How Vectors Provide Facts and Context

Under this patent, a search result might show additional relevant content from comparable searches. To get a better understanding of this feature, input “tallest building in America” into the search engine.

Tallest Building in America Search

Google provides an answer but also shows how that structure compares to similar ones. This visual comparison makes the achievement relative to its competition and more accurately reflects the nature of the user's curiosity.

Predicting User Interests 

Recently, Google refreshed its “people also searched for” feature. Google built this function on a content vector to provide a better experience in the same mode as the comparative building images.

Take a search for Lord Buddha’s birthplace as an example. 

Lord Buddha's Birthplace Search
 
The answer appears in 
Google’s knowledge panel, a box that is located on the first search result page, powered by the Google knowledge graphs. But in addition to the answer, Google also displays what other people searched for in Nepal.

The results anticipate the user's desire to travel to Lord Buddha’s birthplace and displays useful links for planning such a trip.

A Timeline of Google’s Efforts to Fight Black Hat Practices

Black hat practices refer to aggressive SEO tactics that attempt to improve rankings by disregarding the audience and search engine guidelines. Google had been aware of these practices and webmasters’ tendencies to indulge in them. Like other search engines, Google has fought against these practices by updating its algorithm with new releases.

The Initial Clean-Up Using Panda: 2011

The Panda update was Google’s initial attempt to provide better search results by making quality content a necessity for high rankings.

Panda enabled websites that posted legitimate and helpful content to gain authority. The algorithm also punished sites that either copied other sites' content or published low-quality content stuffed with keywords

Getting Stricter With Penguin: 2012

Penguin was the next iteration after Panda.

In addition to combatting low-quality content, the algorithm focused on punishing sites involved in black hat SEO practices. Google monitored keyword stuffing, link spams, and doorways pages and decreased a company's rank if it followed fraudulent practices. 

Moving Beyond Keywords With Hummingbird: 2013

Hummingbird completely overhauled the previous set of algorithms. This release marked Google’s shift from keywords to user intent. As a result, Hummingbird ranked search results by relevance more than content.

But this change also affected how users found information online.

Optimizing User Research With Rankbrain: 2015

Google doubled-down on machine learning and natural language processing with its Rankbrain release. Rankbrain interpreted queries, no matter how obscure, and aimed to match them quickly to the best possible results.

The algorithm also monitored user behavior and downranked less-relevant pages. The tool used activity from similar searches to achieve this function.

As search evolves, Rankbrain has paved the way for Google to understand the context of a search query and show results accordingly.

The Rise of AI and Voice Searches

An ever-increasing number of people use voice searches. Google Assistant, the company’s voice-enabled AI tool, capitalizes on this popularity. Users say “OK Google” to initiate a voice-based search.

Google Assistant, available on mobile phones and smart home devices, is set to disrupt the search engine experience. However, these advances wouldn’t be possible without previous algorithm tweaks that located the implicit context in user queries.

The Future of SEO

In this decade, search results have moved away from keywords and now focus more on the context behind users’ inquiries. This transition has compelled Google to create algorithms that respond to user behavior and activity. 

Websites have a role in this shift as well. To capture current SEO practices, sites need to understand the context surrounding users’ intent, especially for targeted audiences. Optimization needs more than keywords to earn top results.

New analyses and strategies may be necessary to achieve even better SEO. 

 


About the Author

Headshot of Sudhir Singh

Sudhir is a marketing expert. He keeps up with industry trends and news, making it easy for him to report on relevant trends. When he is not spending time helping clients, you can find him hanging out with friends.