Google Featured Snippets Increase Search Page Engagement Rates

Google is using a dynamic platform to evaluate Featured Snippets. It's not machine learning, but rather a way to loop through the results to find the best answers in real-time, suggests data released from a search consulting firm this week.

Stone Temple Consulting released a study this week identifying the rate at which Google replaces Featured Snippets, the information box that serves up alongside the search results to provide more information about the keywords being searched on. The study focuses on the 855,000 queries the consulting firm has been tracking since December 2014.

Google has nearly doubled the volume of rich answers from 22.6% of queries in December 2014 to 40.6% in January 2016, according to the data.

Now more than 55% of the queries that show Featured Snippets in Stone Temple Consulting's January 2016 data either didn’t show a Featured Snippet in July 2015, or show a different URL for the featured snippet than when it ran in July 2015.

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I think that's a big number," Stone Temple Consulting CEO Eric Enge said. "If it were a simple process the number would be stable, perhaps 10% or 20%. It says Google likely has a process that dynamically adjusts everything."

Enge believes Google compares the Featured Snippet for each search result and adjusts it on the fly.  

That's quite an accomplishment even for Google, Enge said. User engagement continues to rise as a result of the change, and while advertisers cannot buy their way into Feature Snippets, they can benefit from optimizing content on pages about their products and services on their Web site.

Enge believes that Google uses a machine-based process, not machine learning, to test the content from the Web page for Featured Snippets by cycling through and compares the results based on the overall impact on user engagement in the search results. Google's goal is not to find those that get the most clicks, but rather the ones that perform best for the search query.

Featured snippets are not personalized to the person searching, but rather the keywords used to search for the information. Google cycles through Web data until it finds the perfect formatted page with the exact information. For example, when someone asks how to reset an iPhone, Google wants to find the passage on a Web page that clearly describes the process.

Once Google finds the answer it tests the results. Based on the test, Google can measure the impact it has on the overall results. At some point they will continue to use the same information.

The increase in the number of answers to find the perfect information means that Google is becoming more aggressive with results, Enge said. Rich answers, which combines the Knowledge Graph and Featured Snippets, works very well for them, he said.

Google is also testing different display formats for the content such as a graph or a paragraph of text.

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