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E-Marketing Performance Blog

Site Search Analytics: Engines Don't Play Matchmaker, But You Should

We’re currently talking about how to use internal site search data to improve your website performance.  The first type of analysis we looked at was pattern analysis, which entails finding what popular queries have in common or what’s odd about them to gain insights into the content your visitors want and need.  Next, we’ll take a look at failure analysis to find where your site searches are going wrong so you can find what to fix first.

Failure Analysis

Zero Search Results – The first place to focus is on queries that are resulting in zero search results.  Within this group of queries, if you focus on those that are potentially relevant to your business, you will likely find areas where you’re not offering your visitors what they want.  Or, maybe your content is there but isn’t being found, and your site search engine requires some modification.  Or, maybe your content is there, but its language is different than that which searchers are using.  Search engines don’t play matchmaker.  That responsibility falls on you.


Useless Results – Your search engine may be delivering results that aren’t satisfying users for some reason.  You want to make sure your first page of results contains as many relevant results as possible.  How can you do this?  One idea is to grade the first page results for some of your top queries.  For example, you could give a great result a 2, an OK result a 1, and a bad result a 0 and then add up the scores of the top 5 results.  Those queries with low scores will give you an idea of the quality of search results for each query.  Then, you’ll know where to focus to improve the user experience.

Best Match – Is the best result for your queries showing at the top of the search results?  If not, is it at least in the top 5?  If not, you are failing your visitors.

Results Click % – What % of clicks does each result get for your important queries?  This KPI shows you what your users think is relevant to them.  If they are telling you that the best result is not at the top, this can help you make adjustments to move that result up on the page.

Search Exit % – What kinds of queries or groups of queries are searchers using that lead them to exit the site without clicking on any results?  This is a great place for insights into improvement.

Of course, you always want to be thinking about how to apply each of these types of analysis to your specific organization.  For example, a bookstore might use failure analysis techniques to figure out what book titles they may not be carrying that they should.  Or maybe they have the book, but users aren’t finding it for some reason.  Or maybe there are 10 editions of a book and the only way to know the best result is to analyze where users are clicking.  Each organization will be different, but the general principles are the same.


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