Why do we often see just what we want to see?
Two recent posts on the Adobe Industry Insights blog got me thinking - they were on the biases we bring to the table. Both Congruence Bias and Expectation Bias deal with the tendency to highlight the things we believe, and avoid the things that we don't believe. We test things we believe are going to work, i.e. they are safe and often based on what others have done, and then we support the results based on what we believe should have happened. In both cases we have a natural tendency to want to 'prove ourselves right'.
This all plays out in defining and demonstrating the ROI of marketing campaigns.
In a recent direct-to-consumer campaign we cast the net wide in terms of targeting. It should come as no surprise that the results were poor - we included people that probably wouldn't respond. What we didn't know a priori was just who would be prompted to visit the store. The key question in our mind was: What characteristics of consumers correspond to response, not how do we maximize response? This led to some interesting conversations, both internally and with the client. My advice when it comes to testing:
"Be wrong, be very wrong."