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For more than two decades, multimedia publisher Rodale has been relying on modeling as a way to unite and maximize its very large customer database. Today, the company has more than 26 million active customers on file, and its modeling program is even more powerful than ever, enabling Rodale to send out hundreds of millions of promotions each year—including more than 140 million direct mail efforts—in support of its constantly evolving repertoire of magazines, books and DVDs.
Here, Todd Leiser, the Emmaus, Pa.-based organization’s vice president of database marketing, pauses to discuss what it takes to keep Rodale modeling strong.
TG: How has modeling enhanced Rodale’s direct marketing?
TL: Rodale first started regression modeling in the early ’80s, primarily to improve response rates of direct mail promotions to existing customers. Today, we continue to expand modeling applications into new media and the variables we predict. …
[Currently] 65 percent of all outbound direct mail is coming from our regression models. The predictable nature of the models enables us to roll out products with a higher degree of accuracy, allowing us to expand the reach of marketing programs (by modeling new internal and external universes). With the models in place, marketers also can spend more of their time on other aspects of the programs.
TG: What are some of the key variables you use?
TL: They are similar to any customer segmentation scheme—recency, profitability, long-term value … prior purchase activity. We expand the internal data with external overlay, focusing on behavioral/transactional traits, then general descriptors (age, gender, income). More important than ever is the channel of the last purchase. We [used to] run a more homogenous business, where direct mail dominated our activity and alternative media was only a small portion. [Our] source mix has changed over the years [and] that variable is becoming more of a driver. If someone is an online customer, [he or she] isn’t going to be as responsive to direct mail, and we have to incorporate that into our models.
Our business is primarily a free-trial, bill-me business, so prior payment activity, prior return activity [and] prior collection activity is always important in our models.
TG: How often do you update your models?
TL: We build new models for every new product. … We also build new models for different subsets of the customer base for those products. The model will be built when the product is new, and we’ll update it with a back test around the second rollout, six to nine months later. Typically, the life cycle of our products is two to three years, so that model won’t be updated unless that product looks like it’s going to have … continued life beyond that point or if there’s a significant creative or offer change.
Here, Todd Leiser, the Emmaus, Pa.-based organization’s vice president of database marketing, pauses to discuss what it takes to keep Rodale modeling strong.
TG: How has modeling enhanced Rodale’s direct marketing?
TL: Rodale first started regression modeling in the early ’80s, primarily to improve response rates of direct mail promotions to existing customers. Today, we continue to expand modeling applications into new media and the variables we predict. …
[Currently] 65 percent of all outbound direct mail is coming from our regression models. The predictable nature of the models enables us to roll out products with a higher degree of accuracy, allowing us to expand the reach of marketing programs (by modeling new internal and external universes). With the models in place, marketers also can spend more of their time on other aspects of the programs.
TG: What are some of the key variables you use?
TL: They are similar to any customer segmentation scheme—recency, profitability, long-term value … prior purchase activity. We expand the internal data with external overlay, focusing on behavioral/transactional traits, then general descriptors (age, gender, income). More important than ever is the channel of the last purchase. We [used to] run a more homogenous business, where direct mail dominated our activity and alternative media was only a small portion. [Our] source mix has changed over the years [and] that variable is becoming more of a driver. If someone is an online customer, [he or she] isn’t going to be as responsive to direct mail, and we have to incorporate that into our models.
Our business is primarily a free-trial, bill-me business, so prior payment activity, prior return activity [and] prior collection activity is always important in our models.
TG: How often do you update your models?
TL: We build new models for every new product. … We also build new models for different subsets of the customer base for those products. The model will be built when the product is new, and we’ll update it with a back test around the second rollout, six to nine months later. Typically, the life cycle of our products is two to three years, so that model won’t be updated unless that product looks like it’s going to have … continued life beyond that point or if there’s a significant creative or offer change.
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