Google revealed its criteria to select the featured snippet text. Google explained how artificial intelligence triggers the answer box information. Utilizing the user’s geographic location, time, and freshness indicators it retrieves the best relevant information from the internet.

In his latest?blog?post, Google’s Danny Sullivan explains, “how the search giant works to pick the exclusive text for featured snippet”

Google’s Featured Snippets Time and Location Relevancy

The internet is overloaded with every kind of thin, generic, exclusive, and high-quality content. And to meet the user’s search intent, the search bots need to identify the best suitable result.

Based on the time zone a user may intend to get the latest events happening in his area. It is where the natural language processing works, the Bert algorithm comes into action. The algorithm returns a featured snippet based on the local or fresh information available on the net.

Danny elaborates this search process by an example of wildfire smoke across the West Coast on 10 September 2020. The natural event raised people’s curiosity to understand what is happening around them. As a result, Google witnessed a rising trend for the search query “why is the sky orange”

The orange sky phenomenal color, experienced by the people in North California triggered the trending query.

Google Trend Graph for why is the sky orange query

Google Search Trend Graph for why is the sky orange query

The search results generated must understand the critical context of the query. That is, identify the hidden and influencing factors behind the user’s query.

How Google Bert identify the snippet text for the answer box?

For the trending query, in a particular location, Google’s search system spots the fresh, latest, relevant, and unique content on the net.

In the case of the “why is the sky orange” query, Google utilized its freshness data indicators and the specific location.

The Bert algorithm recognized the latest content produced on the topic. The new content was relevant and covered the local information. This content was different, and detailing the natural phenomena across the Bay Area.??

The new information was unique and locally relevant as compared to the more specific and general information on the internet.

Bert ignores the generic terms (like sunset) association with the query while retaining the broader terms like “ocean” and “air”. The ruling out of generic topics helped the algorithm to identify and understand the new pattern. And Google provided the most relevant and fresh result in its featured snippet text.

Conclusions:

When I searched the same query today, Google showed

Freshness Indicators and Critical context working for featured snippet

The answer box information still compromises of the orange sky in California.

In his article, Danny Sullivan further explains the effective working of the Google search system with an example of a hazy sky query.

Google’s featured snippets search results based on the geographic location enhance the personalized user experience of its users. And Google can achieve these goals, as explained in the blog article by Danny Sullivan.

The importance of time and location for the algorithm to retrieve the best relevant information from billions of web pages is detailed in the article. The critical context associations of any query can be easier to identify with the time and location information.