New Rules of Mathematical Marketing

Use science to market to your existing customers

June 2008 By Mark Klein

multipage

The marketing challenge all companies face can be divided into two parts: customer acquisition and marketing to existing customers. Today, search engine marketing is the dominant methodology for customer acquisition, and Google is the preferred vehicle. The equally important task of existing customer marketing has a growing consensus around a set of best practices called mathematical marketing (MM).

MM is the scientific process of marketing to existing customers based on a scientific understanding of how past customer behavior predicts future purchases. Key elements of the process include behavioral tracking, predictive analytics, behavioral targeting, testing, what-if analysis and results measurement. For comparison, the typical elements of SEM are keywords, ad impressions, clickthroughs, search engine optimization and Web analytics.

New developments that powerfully enable MM include software as a service delivery, visual math, faster algorithms and new test design methodology. Now that marketers have access to this toolset, the challenge is to apply the techniques and use the tools to create the most effective marketing campaigns.

Rule #1: Capture Transaction Data
Forget about MM unless you’ve got transaction data to understand what your customers do. There’s no behavioral tracking without it. Demographic, psychographic and firmographics data can all tell you something about your customers, but none of those are as useful as transaction data. Customers vote with their purses and wallets, not with their ZIP codes. Customer satisfaction data is highly questionable, too. There is a large body of evidence and academic research leading to the conclusion that people say one thing and do another. Typically, customer satisfaction data does not correlate with future buying behavior. Transaction data, on the other hand, leads to accurate predictions of purchasing.

Rule #2: Use Your Eyes
Analyzing transaction data to predict future customer behavior is not worth much unless you can interpret the results of your calculations. Unfortunately, few of us can translate tables of customer scores into actionable marketing campaigns. We are a visually oriented species and need a visual way to make sense of the mathematics.

Graphic representation of data is nothing new. But creating an accurate picture of 50,000 customers and predicting what they’re likely to do in the future is a more complex problem than simply creating a chart that tracks the price of IBM stock over the past decade.

Happily, this “complex problem” has been solved many times over. Whether you use behavior maps or some other technique, it is possible to make graphical representations of customer behavior that reveal clusters of similarly performing customers and suggest appropriate marketing campaigns. MM means not only doing a scientific analysis of customer transactions, but also presenting the analysis in visual terms so that innumerate marketers can understand what the analysis shows and apply the understanding to their campaigns.

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