While walking home the other day, I made an observation which I thought I’d share in a very Seth Godin way. Here goes:
I walk to and from work, usually waving hello and exchanging a few words with a neighbor who seems to incessantly prune her shrubbery. For a few days now, her son has been home from university, and each time I’ve seen him out in front of the house, he’s been working on his mountain bike(s).
After seeing him work on his mountain bikes a few days in a row, I thought to myself:
“man, he must really like mountain biking! every time I see him he’s working on his bikes!”
For a brief second I considered saying something like that to him, but then thought about how he might respond. Because we’d only encountered each other as I pass by my neighbor’s house as I walk to and from my work, he could have easily said,
“man, you must really like walking! every time I see you, you’re walking to work!”
On the surface, this might seem like a silly interaction, but what it uncovers is a deeper problem when attempting to do any product research or marketing. Based on my experience with my neighbor’s son, I would have attempted to market the “extreme sports” angle of my product, but that might be completely mis-directed.
Perhaps he was working bicycles so much because he was planning on riding a “Race for the Cure”, and his real interests are in volunteer work. Or maybe he was repairing bikes for a friend. Or any number of alternate possibilities.
However, if we only construct our customer personas from questionaires we send them in the mail, we are likely missing broad swaths of their personality, goals, and aspirations.
Aggregated action-based data (search data, credit card receipts) can help alleviate this single-sampling problem, but then you run the risk of missing the context, like an Amazon customer who only buys products because she can have them gift-shipped to her nephew.