Analyzing user behaviour is a key ingredient to make a search solutions successful. By using Search Analytics, you gain knowledge of how your users use the search solution and what they expect to find. With this knowledge, simple adjustments such as Key Matches, Synonyms and Query Suggestion can enhance the findability of your search solution.

In addition to this, you can also tune the relevancy by knowing what your users are after. An exciting field in this area is to automate this task, i.e by analyzing what users click on in the search result, the relevancy of the documents it automatically adjusted. Findwise has been looking into this area lately, but there hasn’t been any out-of-the-box functionality for this from any vendor.

Until now.

Two weeks ago Google announced the second major upgrade this year for the Google Search Appliance. Labeled as version 6.2, it brings a lot of new features. The most interesting and innovative one is the Self-Learning Scorer. The self learning scorer analyzes user’s click and behaviour in the search result and use it as input to adjust the relevancy. This means that if a lot of people clicks on the third result, the GSA will boost this document to appear higher up in the result set. So, without you having to do anything, the relevance will increase over time making your Search Solution perform better the more it is used. It’s easy to imagine this will create an upward spiral.

The 6.2 release also delivers improvements regarding security, connectivity, indexing overview and more. To read more about the release, head over to the Google Enterprise Blog.