Have you ever given, or listened to, a presentation based on reliable data – be it survey, clickstream or transactional data – only to have the informed recommendations promptly nixed by that “case study of one”?
I’ve experienced this more than a few times. In my earlier career conducting ad testing, it would happen in a variety of ways – from a critical stakeholder staying firm, “I think the message works, and I think it will resonate with my audience” to another saying, “Those numbers just don’t look right.” And with those words, the findings were swept away. I’m not alone. I’ve heard others facing the same plight. From marketing clickstream data to product usage numbers, there can be a body of data pointing to a particular course of action, only to be overruled by a vocal sales person who says with conviction “but my client uses that function all the time” or “my client told me they would never need that service.”
What’s going on? Why isn’t sound data winning the day? Put quite simply: emotions. We don’t have an emotional connection with numeric data. So, unless the numbers “feel right,” it’s easy to be swayed by the case study of one that does resonate. We can relate to these experiences viscerally whereas the numbers can leave a trail of doubt: what if we are missing that piece of the puzzle in them.
All is not lost. You can use the case study of one to your advantage by backing it up with the numbers and/or other data. A former colleague jubilantly came to me one day after a big presentation. The study had been a challenging one. Despite operational data to the contrary, there was little acceptance that customers were struggling to follow the set-up instructions and connect their modem to their network. The turning point came during the presentation when video footage from a usability test showed people trying to complete the task. Not only did it bring the data to life, but members of the product team quickly were able to identify the issue and immediately left to make changes.
The story is told best when we have all types and levels of information to bring it to life. Big data shows the behaviors, the actions taken, while numeric small data offers deeper insight into why they took that course of action. Last, but not least, qualitative (or thick) data provides the readily relatable clues that tie it all together, making the insight actionable. When we appeal to key stakeholders on both intellectual and intuitive levels, the data – all of it – is more likely to resonate and the appropriate business decisions are taken.