search log analysis
This article is part of a series about search log analysis which includes what people are searching for, bounce rates, spotting real opportunities and the geographical element.
I’ve been rooting around in the search logs for RNIB.org.uk. We use Google Analytics which isn’t accessible so most data has to be exported and shared in Excel.
So far I’ve got my hands on:
- the top 500 keyword referrers from external search engines (2008)
- top 500 keywords used on site search (last six months of 2008)
- top referring search engines
But that’s plenty to be getting on with.
I have to remind myself I’m only looking at the most popular terms and there’s a whole long tail I have no visibility of. There’s also some clearly dubious queries in the logs.
So far I’ve gone through the top 500 from external search engines and loosely categorised them. The categories aren’t particularly scientific;Â I’ve grouped all eye conditions into one category and grouped all queries about Helen Keller into another. Those don’t seem particularly equivalent categories but there are similar in size of queries. I’m following my instincts a bit at this stage.
For each category I’ve added up the total visits, and then worked up the average bounce, time on site and new visits per query type. I’ve also started adding information about whether the query is likely to be answered with a quick fact or should generate a longer journey.
Some of the questions I am trying to answer:
- Which queries should influence navigation design?
- Where should we be encouraging further/longer journeys?
- What content isn’t represented in the logs? We might need to work on optimising those.
- Which queries are a poor opportunity since the referral was accidental or mis-directed
As a side benefit I’ve already learnt what Bump-ons are.