“…Given his blog title and constant heavy tool usage, I’d expect his approach to be hands-on, practical and down-in-the-weeds. But given his mentoring experience, perhaps he’ll be talking about training and helping new analysts as well.”
Until reading Gary’s words I had never considered blogging on the topic of training new analysts. But come to think of it, it's not a bad idea.
Semphonic is in the process of growing and with that comes new analysts. Right now we are in the process of hiring one or two new analysts who I will undoubtedly be (partially to mostly) responsible for building him/her/them from the ground up. Given the position I’m sitting it, this seems like the perfect time to start blogging in real time about the process, challenges, tips and ideas for training new web analysts.
Since this is the beginning it seems reasonable to start where an analyst’s career begins, with an interview. I’m lucky enough to get to grill all prospective employees once Gary and Joel have had their way with them. When I sit down with an interviewee here is what is running though my mind and the web analytics skills (I didn’t think people here would care to read about how interpersonal and presentation skills are important) I’m looking for.
• All prospective analysts come to Semphonic offices having prepared a basic analytics exercise. Most frequently this is a comparison between two months of data for a small to medium trafficked site using HBX, Omniture or a similar tool. Having someone run through their analysis in front of me is probably the single most telling ten or fifteen minutes of the interview.
• When someone is running through their presentation it is usually readily apparent if they understand, in general, what they should be looking for. I can teach tool usage in a few days, a variety of analyses in a few weeks, but teaching what to look for when there are thousands of numbers in front of you will take months, if ever. I don’t ask the inexperienced to go strait to the heart of a problem and create an elegant solution, just for their thinking to be “on track.” This could look like a lot of things, but usually manifests as someone spending time discussing several relevant KPIs (i.e. single page access rate, views/visit, visits/visitor, etc.) and connecting them to each other to create conclusions.
• A big part of web analytics is story telling. I want to hear an interviewee tell me an interesting, believable story of what users are doing on a site.
• I do not expect someone with no web analytics experience to fully grasp the concept of traffic segmentation, but I like to hear people hinting at bits and pieces of it. Also, just as problematic, if not more so, than someone not understanding segmentation, is a person thinking about it in terms of a previous job. Both a complete lack of understanding about segmentation and a strong non web analytics segmentation foundation are big red flags for me.
• General tech, Internet and computer application savviness counts. The more web sites someone sees and uses, the better I expect them to be at understanding what works and be able to generate fresh ideas. And, the more tricky computer apps someone has mastered the faster I expect them to pick up the ins and outs of an analytics tool.
• The ability for people to understand the difference between correlation and causation (in terms of real world application, not Webster’s Dictionary) is essential.
• Someone who is willing to look past his or her opinion of a site and directly at the numbers. A skilled, experienced analyst can and should inject plenty of informed opinions into their thinking, but just as Picasso perfected the human body before cubing it up, a new analyst must first go solely with the numbers. All too often I have heard interviewees lead into their presentation by explaining that a clients site is “very good” or “very bad” (usually the former, not the later—they are trying to make a good impression!). As soon as someone says this all I can see is a ticking time bomb of an analyst, who, when they have acquired the web analytics skills, will selectively seek out data to support an opinion rather than reference the data that truly tells the story.
• I want the interviewee to have loved doing the analytic exercise required of all applications. I’ll accept “liked a lot,” but anything less makes me worry. When I was doing the analysis leading up to my interview I remember seeing it as a break from my job hunt, a truly interesting and enjoyable real world puzzle. I want the person in front of me to have felt the same way. The more someone likes the work the faster they will progress. It’s not easy finding an employee who will go to sleep at night pondering techniques to try out the next day, but it’s also not a bad thing to strive for.