Google has been using one of its most important ranking signals for going on a year, and apparently it has so far helped improve search results on over half of queries.

Have you noticed a marked improvement in Google search results over the past year? Let us know in the comments.

Stone Temple Consulting, which has been publishing some of the most interesting research on Google search in recent memory, has some new findings out after a study on Google’s machine learning algorithm RankBrain. The data was gathered by comparing 500,000 search queries from both before and after RankBrain was implemented.

According to the firm, and as far as we know, this is the only study of its kind on RankBrain.

The study found that Google improved results on 54.6% of queries that it previously misunderstood. Examples of words and phrases RankBrain handles better, according to the firm, include: what is, who is, where is, without, not, and convert.

RankBrain was revealed in October pretty much out of nowhere. It didn’t come in an official announcement, but from an interview Bloomberg Business ran with Greg Corrado, a senior research scientist at Google. He said that Google had introduced the algorithm on a wide scale earlier in the year and that it quickly became the third most important signal out of hundreds in Google’s ranking algorithm. Before we look more closely at Stone Temple’s findings, here’s a quick recqp of what we learned about RankBrain from that initial interview.

1. RankBrain is the third most important ranking signal in Google Search.

2. RankBrain was deployed several months before October.

3. RankBrain uses artificial intelligence to put written language into mathematical entities (vectors) that computers can understand.

4. If RankBrain sees a word/phrase it doesn’t know, the machine guesses what words/phrases might have similar meanings.

5. RankBrain specifically helps with never-before-seen search queries.

6. RankBrain is better than humans (even Googlers) at guessing which results Google would rank number one for various queries.

7. RankBrain is the first Google search ranking signal that actually learns on its own.

8. Turning RankBrain off is as damaging to users as turning off half of Wikipedia pages.

9. RankBrain is so effective, Google engineers were surprised at how well it worked.

10. Machine learning is a major focus of Google right now, which probably means we’ll see RankBrain itself and other endeavors in this area improve greatly in the future.

Stone Temple’s Eric Enge suggests that Google may use RankBrain to impact selection of featured snippet results, trigger the delivery of a map where there wasn’t one shown before, and/or determine if the main impact of a given query would be an improved search results snippet.

“Predictably, one of the most common questions I get asked is how RankBrain will impact SEO,” says Enge. “Truth be told, at the moment, there is not much impact at all. RankBrain will simply do a better job of matching user queries with your web pages, so you’d arguably be less dependent on having all the words from the user query on your page.”

“In addition, you still need to do keyword research so that you can understand how to target a page to a major topic area (and what that major topic area is),” he adds. “Understanding the preferred language of most users will always make sense, whether or not search engines exist. If you haven’t already (hopefully you have!), you can increase your emphasis on using truly natural language on your web pages.”

According to Enge, the real impacts of RankBrain are an increase in overall search quality and in Google’s confidence that they can use machine-leaning within the core search algorithm.

Stone Temple put together this infographic highlighting its findings:

On a related note, word out of SMX is that apparently Google doesn’t completely understand RankBrain and what it’s doing. Hmmm. Let’s hope the company has a better handle on what its nightmare-inducing robots are doing:

Do you believe RankBrain is making Google a better search engine and helping users find what they’re looking for? Discuss.

Infographic via Stone Temple Consulting