How search can help you understand your audience - part 4

 by Martin Belam, 6 May 2003

Using search to understand the diversity of the audience

When I do presentations I often bring along printed materials. For everyone in the audience I print an A4 sheet of paper with between 15 and 20 search terms. Every search term on every sheet is unique. The impact depends on the size and specialism of the audience, but I am yet to do a presentation where it took more than 5 minutes for the BBC's audience to generate enough queries to provide every member of the audience with 15+ search terms. Statistically that says something about the size of the BBC's web audience and their interactivity.

More importantly it says something about the diversity of that audience. In any sample of search logs we look at, we see an incredible range of phraseology, interests and type of query. It teaches us what I think is the most important lesson to draw from the examination of search logs, and one which I believe applies to any website.

The majority of people working within the new media industry have a passionate and long understanding of the web. They may know the nuances of client-side development, server-side programming, visual design and copy writing. They may have a smattering of all of these. Most certainly they will be very technically literate and used to using computers, and have used the internet for some time. They may have an understanding of information architecture or search mechanisms.

The evidence of search logs reminds us that the majority of the web audience does not have this, and even if they do have a good knowledge of the web, they do not have an in-depth knowledge of every individual site. Naming conventions, departmental demarcation, strategic aims and site architecture may be obvious to someone running the site, but the audience is oblivious to them.

As I have observed in A Day In The Life of BBCi Search, the majority of users resorting to search will interrogate the site by simply sending one or two word queries to it. Analysing search logs allows us to predict what those queries will be, and work out how best to answer these queries to fulfill the users requirements without the need for them to understand the naming conventions, departmental demarcation or strategic aims. Instead we can use the interpretation of their actions to shape a better interaction with the site for future visitors, and we can use that interpretation to influence the content and navigation of a site to better suit all visitors, not just those who have resorted to search.

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