We’re continuing to discover uses for the clickstream data Trip has and the new use is the search safety net – which we’re currently testing.
The idea is that as you search Trip we note which articles you’ve clicked on and then, using clickstream data, predict other articles that might be related, or those you might have missed (hence the name). See the video embedded below.
There are two issues/problems/challenges:
- Lack of data. This only works on clickstream data, so it requires clicks! Very new articles or obscure articles will not have the data. As it happens, in the tests we’ve done, it’s been – broadly – really good. But when we roll it out, it’s something to consider.
- User experience. This is the biggest challenge is how will users interact with the ‘service’? In other words where do we put the results? Do we automatically show them somewhere on the results page? If so, will that annoy people who don’t want the service? Alternatively, we create some sort of ‘search safety net’ button which would require a user to click the button. This means many people will simply not see it and miss out.
Once we solve the user interaction side of things, we’ll roll it out. In the interim, if you want to give it a try (and be one of the first people to use it) then drop me a line (email@example.com).