Improve Marketing ROI Through Data Analysis

It’s no secret that if you use data correctly, you can add tremendous value to your company. The real key is the techniques to find and use this data to your advantage. That was the message offered during a session last week at the DMA’s List Day conference in New York.

A panel — consisting of Erik Findeisen, co-founder/CEO of FC Data, a direct marketing consultancy; Janette Barret, director of marketing services and analytics for International Masters Publishers; and Hao Chen, manager of decision science at Experian Marketing Solutions — discussed ways mailers can drive up their return on investment through the use of data and analytics. Here are three key tips they provided.

1. Acquire relevant data. Data needs to be mined according to your customer base. “Know who you’re speaking to,” Findeisen says. He suggests this can be done through several methods:

* demographic studies (age, gender, income, marital status, etc.);

* transactional analysis (such as RFM data), which he feels drives success in modeling elements;

* life cycle (new homeowners, marriages, births);

* psychographic data;

* attitudinal data (Why, he asked, would the customer be interested in your products or services over another?); and

* ethnic data. Most notably, mailers’ need to pay close attention to the rapidly growing Hispanic market.

2. Reactivate old customers by cross-selling a new product within the same affinity, Barret says. As an example, she cites a past campaign at International Masters Publishers that used matchbacks from older housefiles as targets for reactivation. These past customers had ordered a cycle of wildlife cards from 1999 to 2001. Mindful that the continuity publisher wanted to reach this customer base within this affinity, International Masters offered this group a wildlife DVD series.

The campaign proved very successful, netting a 40 percent response index and a 29 percent retention rate. In her testing, Barret sought to narrow the affinity down as much as possible, which she considered a major reason for the successful campaign.

3. Prioritize the level of data importance through testing. “Data is critical pieces of information,” Chen said. “Certain types are more relevant than others. It all depends on the application.”

He provided a series of models that Experian, the marketing solutions firm, has implemented in its testing, including three channel tests (direct mail, e-mail, mass media), three offer tests (regular price, free shipping, discount price), three creative tests and three contact frequency tests.

In evaluating the results, demographic, transactional and behavioral data proved to be most important in maximizing list performance.