Schooling ‘Curmudgeon’ Denny Hatch on ‘New-School’ Marketing
In contrast, "new-school" marketing uses transaction data (who bought what, and when). Analysis is done at the individual customer level, recognizing that you can't predict what a particular customer will do unless you analyze at the customer level. The key metrics are predictive and forward-looking: "Risk Score," (measuring who will stay loyal and not defect); "Likely Buyer Score," (who is likely to purchase in the next 30 days); and purchase propensities that predict the probabilities of each customer buying each product or product category. Relevance comes from the offers made based on the purchase propensities.
Using transaction data is key. Companies already own this trove; they don't need to go outside to buy it. Further, by definition of a customer, they have it for each and every customer. Demographic and psychographic data is notoriously spotty and can be entirely missing for many customers. Most importantly, transaction data has been proven to be the most predictive. When it comes to purchasing, people vote with their wallets, not with their ZIP codes.
The Who, What, When Equation
The new, predictive metrics let you target the appropriate customers and offer them products matching their needs and wants. They also tackle what Hatch thinks is unknowable. He says, "What the CEOs, techies and bots do not reckon with is the 800-pound gorilla: WHEN." In fact, new-school marketers can identify when customers are likely to purchase with high accuracy.
Figure 1 (at right) shows the correlation between Likely Buyer Score and the percent of buyers in the following month. Customers were put in buckets according to their Likely Buyer scores, and then buying rates for each bucket were measured at the end of the next month. Clearly, there is a close correlation between the forecasted probability and actual customer behavior during the following month.