KM: What inspired you to write this book?
LR: As an information architect, I sit squarely in the findability corner of user experience. Search is a huge component of findability, and when you think about it, search analytics is an obvious way to improve search performance. It’s essentially a way to close a feedback loop: users search, and we give them results, but we do very little to find out how well those results are actually serving users. By not analyzing query data, we miss out on all sorts of opportunities to improve search performance. An added bonus is that site search analytics can also help you improve your site’s navigation, metadata, and content. In fact, the book includes separate chapters on these topics.
Yet, for various reasons, little has been written about the topic. Neither the UX nor the Web Analytics communities have shown much interest in this sad orphan, which is too bad, considering how valuable it can be to both. I hope my book—the last chapter, specifically—helps change that.
KM: Lou, I find your writing style to be very approachable and hands-on. Your book does an excellent job of walking people through site search analytics, so once they’ve read the book, in addition to knowing about the topic, they can actually do site search analytics.
LR: Thanks! As Steve Krug would say, it isn’t rocket surgery. Anyone who can operate a spreadsheet and has an hour per month can get something of value from site search analytics.
KM: And that’s one thing you advocate doing in your book—along with many other useful tips we can follow. What’s another technique your book covers that you think every company should apply to its Web site?
LR: Pattern analysis. Everyone should play with query data to see what sorts of interesting patterns emerge. Get the most frequent 50 or 100 queries—the short head, as opposed to the long tail—into a spreadsheet and have as many people as possible look for patterns and other interesting things. You’ll be amazed at how quickly insights begin to emerge. It’s really a fantastic and fun way to dig deep into learning about user intent.
It’s also a good idea to regularly review the most frequent queries that retrieve zero results. You’ll immediately go into diagnosis mode. “Do we really not have that content? Should we? Is it there, but not titled properly? Is it mistagged? Jargony? Hey, this would be good ammunition for the next time our content authors balk at following our content guidelines….”
I’m convinced that doing little things like this on a regular basis would negate the need to redesign the structure of most sites—which would be a really good thing.
KM: When writing your book, who did you intend it for?
LR: Like all Rosenfeld Media books, the core audience is user experience practitioners—whether designers or researchers. But this particular title should also appeal to marketers and analytics people.
KM: You’ve touched on how site search analytics can help improve a site’s content, metadata, and messaging. So it seems site search analytics could really be part of a content strategist’s secret arsenal as well. Would you agree?
LR: I think so. You can learn a lot about how your deep content works—or ought to work—in terms of search and contextual navigation. I’d imagine such things are important to content strategists—though, admittedly, I’m not one.
KM: We often focus on what a Web site is doing right and sometimes tend to ignore the numbers that indicate what it’s doing wrong. But your book encourages us to look at these numbers through failure analysis. Does this approach negate the need for additional usability testing?
LR: Absolutely not. In fact, analytics are, in general, good at telling you only what is going on. They do little to explain why things are the way they are.
So, while site search analytics might help you to better understand users’ behaviors and arrive at some good hypotheses for why they behave the way they do, they are only hypotheses. You still need qualitative methods of user research like usability testing to get from hypotheses to conclusions.
KM: Site search analytics results dovetail nicely with persona creation, don’t they?
LR: Absolutely! By using your query data to describe a persona’s information needs, you can make your personas more evidence based—and, perhaps, make it more likely that people will take them seriously.
KM: These days, people are throwing the word silo around a lot, with respect to the various disciplines that make up Web development. In your book, you advocate finding complementary problem-solving practices from the UX and Web Analytics communities. Where is the common ground with site search analytics?
