Creating personas is easy, you simply collect the set of traits (characteristics) that describe a large segment of your users and assemble it into a persona. Identifying those large segments and extracting their traits is the real challenge.
If you think about your customers as a large collection of complex people, the task can be daunting. However, all you need to start is to find a few traits that effectively segment your customers into a few major groups. You can do this by looking at your customers one dimension at a time.
For example, let us consider the customer base of our online table company. Our customers are located around the country, representing many age groups and demographics. Let’s see how they are distributed across a few common dimensions:
In this case, the Amount of Purchases are fairly well distributed so there is no clear concentration of customers. Therefore, this is not a good trait for any of our personas.
Total Number of Purchases has an interesting bell curve shape, indicating a concentration of total purchases towards the center, but it fails to segment our customers into any logical groups. Instead, it looks like our customers behave like a single, large, segment over a spectrum of purchases.
Age gives us our first clear glimpse into effective trait, with two clear age groupings that separate from each other. This makes age an ideal trait for creating personas because there are two clear personas emerging here: young and old.
As you can see, it’s a simple matter of looking at customer distributions by various dimensions to identify clear separation which indicates a good candidate for building a persona. The dimensions you are looking for will create clear separation in your customers and allow you to effectively capture a large group with a single dimension.
Tomorrow we’ll talk about how to assemble these candidate traits into personas!
Quote of the Day: “Looking in the mirror, staring back at me isn’t so much a face as the expression of a predicament.” ― Colin Firth