Guerrilla Analytics

Guerrilla Analytics is pretty much what it sounds like – it’s about going out, without permission and without sanction, and conducting analytics on publicly available information, purely for the purpose of curiosity, case study, or for the common advancement of the discipline or technology.

In many ways, I admire the work that has been done by the dev community. JQUERY is an example of a developer led open-source technology, a common library that many front-end devs dip into. It’s just an awesome because it saves them so much time and effort. Many developers are truly technologists. And the really awesome ones go out and experiment. They actually really push the science, and frequently, when it comes to many of these projects, they do so with little expectation of pay or salvation. They do it because they love it. And it’s so thoroughly undermined other platforms (including Flash), that you’d have to call it Guerrilla.

Some of the best web analysts I know run their own sites and trick out their sites with analytics. By and large though, because of the nature of our work, we tend to work only on walled off, corporate data. We don’t always, necessarily, go around talking about our awesome insights. For most web analysts it’s a solitary analytical existence.

In another way, too, the Canadian Election Study offered a common basis of experience for most quantitative political scientists growing up. Everybody who spends extensive periods of time with the study know that dataset inside and out. It’s both a collective and solitary existence.

Web analytics, almost by definition, lacks that common dataset. It’s something I brought up on the WAA Research Committee yesterday, in the context of training. Granted, the WAA once invited all analysts to engage in a contest to see who could derive the best analysis out of their analytics tool, but admitely, access to the actual numbers was not universal, so it was impossible to really judge the validity of the work.

The production of easily assembled datasets is well upon us.

We’re seeing some Guerilla Analytics being done by Peterson, based around the publicly available information on Twitter. We’re seeing some of it happen in Social Media, though, I don’t know if I’d judge some of it to be ‘analytics’ quite yet. Though, a few people certainly are trying.

Going out, assembling data sets, and starting to solve problems for the sake of solving problems – is that technologist spirit. There’s a huge advantage in stepping outside the narrow possibilities of proprietary data and experimenting – then bringing back a lot of that knowledge, for the benefit of everybody. Is there any Guerrilla in you?