Sometimes it is useful to work backwards in the “thinking like a data scientist” process. You can do this by first identifying the potential recommendations that the organization could deliver to its customers and frontline employees, and then working backwards to identify the supporting data and analytic requirements.
This chapter introduces a technique called the monetization exercise that seeks to understand how the organization's product or services are used by its customers, and then identify how the customer and product usage data can be used to create new monetization opportunities. The process works backwards to uncover the metrics, variables, data, and analytic techniques that you might need to support the new monetization opportunities.
The monetization exercise provides an opportunity to uncover new product and/or service opportunities through the identification and delivery of new customer and frontline employee recommendations. The monetization exercise works by first understanding the product usage patterns and customer usage behaviors associated with a particular product and service. The process then seeks to identify complementary or secondary recommendations that can be packaged and delivered along with that product or service (think the Data Monetization phase of the Big Data Business Model Maturity Index). Following is the monetization exercise process: