Quantitative Information Architecture. Phew. It took me a few tries to avoid stumbling over that many syllables. The VanUE meetup last Tuesday was more foreboding in title than in reality. Don Turnbull gave an upbeat and (daresay) exciting presentation on the changing web analytics landscape. He gave great examples of how quantitative data (and the data scientists who are analyzing it) is transforming how we interact with the web. Google, Facebook, and Amazon (among many other online companies) are now able to make frighteningly accurate predictions about our online behaviour; everything from our searching habits and buying decisions to how we create our online personas and network with "friends".
Don explained that quantitative research methods are a valuable and sought-after disciple; they allow analysts to make comparisons over time as well as adapt their findings to other studies and user groups. Quantitative data allows us to understand what users actually do. It can tell us how long users stayed on a page, how they came to be on that page, where they went to afterwards, and where geographically they are located while they are doing their browsing. Analytic software is becoming increasingly prevalent and sophisticated. Don recommended Google Analytics as one of the best providers of this service.
Analytic software isn't just limited to the web though; you can install browser analytic programs to examine how your employees are using your intranet. Don gave a great example of a study he conducted that showed that most users within a company would first navigate to the external website to look up company information rather than try to locate it on the company intranet. This type of data could prove to be invaluable to information architects when designing site structure.
Don also demonstrated that using analytics can be a powerful tool when negotiating with decision-makers. By using figures, an IA can help add tangible evidence to their site architecture. By speaking in numbers, a UX team can help win over traditionally number-heavy executive members.
Quantitative research is on a tipping-point of sorts. With computational power and data storage so readily (and cheaply) available, companies are amassing astounding amounts of user information. Companies are hiring Data Scientists and Statisticians at an ever increasing rate. The marketplace is in need of analytical individuals to fill these roles and to help develop meaningful insights from their data warehouses.
For my first VanUE meetup, I was impressed with the number of engaged members that turned up on such a sunny afternoon and with the quality of the presentation. I've even been to the library to pick up a few of Don's recommended reads.
I always knew that data was cool!