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I'm going to be carrying out research into how to rebuild a search engine from scratch for a large University data base. Existing search is slow and cumbersome.

I'll be researching user needs that will try and figure out:

What users are looking for; how they formulate queries; what they do with the results etc.

My question: has anyone got any researching guidelines for specifically search engine user needs?

EDIT There is no quantitative data capture set up. I wish there was.

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Getting to the specific data you're looking for is likely to require:

  1. Carrying out a large scale survey to determine user types asking questions that will help you identify things like frequency of use, motivation for use, and level of user ability.
  2. Interviewing a couple of archetypal users for each identified user type to find more detailed information about those user's usage patterns.
  3. Running some task-based user testing sessions on the existing product with more users based on the information from the interviews to differentiate between self-reported and actual usages.

From there you should be able to get a strong idea of who is searching for what and how - This is essentially the same for any research looking into product usage

  • And I'd love quantitative data for search terms so I can prioritise, but they have nothing to track this data. I don't want to run any tasks on the existing system as that's already been done by previous UX and we're totally rebuilding the engine. But usage patterns [and how users interact with other systems] is a good point. – colmcq May 2 at 9:52
  • Wouldn't you be able to get quantitative data for search terms from the logs? – Andrew Martin May 2 at 9:55
  • Edited question. – colmcq May 2 at 10:39

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