At Findwise we are currently looking deeply into search analytics for enterprise search, a way not only to assure quality and relevance for your results, but to actually know and understand the users better.
Web analytics has been around for quite some time, but there are several things that makes search special.
There are simple ways to look at ‘top queries’ (most frequently asked), ‘zero-results-hits’ (which of course can be a result of bad spelling, but many times by lack of information) and popular searches over time (for trends etc), ‘Top queries’ can be fixed by static tools, bad spelling by good spell-checking and lack of information by synonyms and adding the missing pieces. But I believe we are missing something important here:
When a user conducts a search, he is using it to either:
- find a specific piece of information or
- find more and/or related information about a topic
- but, by doing so, he might find information that brings new perspectives such as:
- information he didn’t know existed
The process of search should always be a dialogue between the user and the search application. Simple: The ‘what‘-questions always have to lead to the ‘why‘-questions.
The users doesn’t type a query for fun, they have an intention when doing so. Why do the user ask for a particular piece or area of information? Depending on the intention of the user (specific piece, related or general information), different tools can be used to enhance information retreival.
Done right, search analytics can be used for tuning your search engine (weighting of documents, improvements of spellchecking, synonyms etc) and clearly improve information retrieval, but just as important, work as a tool for information quality assurance and management.
Within the next couple of weeks this blog will cover further aspects and thoughts on this subject. If you haven’t read Maria’s ‘What differentiates a good search engine from a bad one?’ already, I recommend you to do so.