Proponents of exploratory data analysis assert that allowing the data to group naturally without any imposed framework is the most robust and unbiased approach for creating valid output. However, in a business setting there may be times when NLP yields results that are unactionable or confusing due to the difference between the traditional semantic meanings and the business use case. Amy and Mark examine the same data under two different frameworks and provide practical guidance on when to let the data do the talking, and when to let the business speak for itself.