Thinking with Data

Chapter 6. Putting It All Together

We should look at some extended examples to see the method of full problem thinking in action. By looking at the scoping process, the structure of the arguments, and some of the exploratory steps (as well as the wobbles inevitably encountered), we can bring together the ideas we have discussed into a coherent whole.

The goal of this chapter is not to try to use everything in every case, but instead to use these techniques to help structure our thoughts and give us room to think through each part of a problem. These examples are composites, lightly based on real projects.

Deep Dive: Predictive Model for Conversion Probability

Consider a consumer product company that provides a service that is free for the first 30 days. Its business model is to provide such a useful service that after 30 days, as many users will sign up for the continued service as possible.

To bring potential customers in to try its product, the company runs targeted advertisements online. These ads are focused on groups defined by age, gender, interests, and other factors. It runs a variety of ads, with different ad copy and images, and is already optimizing ads based on who tends to click them, with more money going toward ads with a higher click rate. Unfortunately, it takes 30 days or so to see whether a new ad has borne fruit. In the meantime, the company is spending very large amounts of money on those ads, many of which may have been pointlessly displayed. The company is interested ...