Google’s Query Deserves Freshness

Google recently announced a search algorithm update that should promote fresher and more relevant search results. Although Google makes over 500 changes to its algorithm annually, the majority of updates do not affect a large percentage of search results. The new update, which seeks to build on the Caffeine web indexing system, will affect approximately 35% of all search queries.

According to Google’s engineer Amit Singhal, the following topics deserve fresh results:

• Recent events or hot topics. For recent events or hot topics that begin trending on the web, you want to find the latest information immediately. Now when you search for current events like [occupy oakland protest], or for the latest news about the [nba lockout], you’ll see more high-quality pages that might only be minutes old.

• Regularly recurring events. Some events take place on a regularly recurring basis, such as annual conferences like [ICALP] or an event like the [presidential election]. Without specifying with your keywords, it’s implied that you expect to see the most recent event, and not one from 50 years ago. There are also things that recur more frequently, so now when you’re searching for the latest [NFL scores], [dancing with the stars] results or [exxon earnings], you’ll see the latest information.

• Frequent updates. There are also searches for information that changes often, but isn’t really a hot topic or a recurring event. For example, if you’re researching the [best slr cameras], or you’re in the market for a new car and want [subaru impreza reviews], you probably want the most up to date information.

Our Take

While Google has indicated they understand that different search queries will require varying degrees of “freshness” based on a searcher’s intent, we are wondering how well Google will be able to match intent with result.

Google is anticipating 35 percent of searches are around this kind of up-to-the-minute data, which leaves a majority of searches still prioritizing on the “relevancy” of the data over its “recency.”