In the era of "big data" this and "big data" that, we have a problem. Our minds are wired for language not data. Rarely do we have direct intuition about data, what it means, and what we ought to do with it. We need to invent the Rosetta Stone that bridges the hieroglyphics of machine learning with the ancient language of marketing.
Consider the following examples:
- What is the cost function of loyalty?
- What does unsupervised learning tell us about branding?
- Where does gradient descent take us in terms of understanding engagement?
- Loyalty has a cost (or a profit) that comes at a price. What is the allowable marketing cost of achieving it?
- Branding is often described as being in the mind of the beholder; thus we should not label things as A or B but rather be surprised by how consumers cluster things.
- Engagement is a cumulative set of interactions that may (or may not) move us toward conversion; we need to understand the marginal contribution of each step.