Do You have a '3 click tire kicker'?

I recently had a conversation about website optimization and conversion, where I was asked about past tactics I've used to convert users on a website. The person asking was concerned about the numerous user types and thus the need to create many landing pages. The person was initially against the my use of personas until I explained how they mattered.

In my example, I described a persona that I summarized as the young 'female who seeks trust', where the persona could be more deeply described as a teen female who used web-based profiles for personal expression and identity gratification, but who also didn't necessarily trust new new web services. We developed that persona from research, surveys, and observation. What was of interest to me was how the 'trust' issue would play out in terms of web activity. In the field, that persona came to be renamed the  '3 click tire kicker' since this user type was typically a female 14-24 who clicked on three different services info pages before downloading and installing our software.

What was most interesting was that log analysis showed that categorically, these users did not always click on the three same service pages. As long as they investigated three or more of the available services did they convert at a higher and more dependable rate. Post-conversion interviews and surveys revealed that users felt that there was alot offered by our technology and they could save time and effort by using our software.

I used this example to explain that a persona was the start of the site optimization process. We verified the persona and used it to identify a category of users - a segment that followed a certain conversion behavior - that we could then create pages that met their needs. By applying similar practices it would be possible to identify other segments that could require additional product requirements or implications. I may have been able to reverse out the same results without creating the persona, but it was a guiding heuristic in approaching the data that lead me to focus on a type of behavior. In any view of this example - a segmentation hypothesis (via a persona in this case) was an essential part of the insight generation process.

The caveat here is that the results and analysis were not necessarily that easy. I used both proprietary non-linear path analysis and manual log analysis of log snapshots of 10,000 rows to perform the analysis.  Type type of analysis is compute or manpower intensive. In a later post, I'll discuss other segmentation options.