Senior Advisors Wealth Management’s Joshua Mellberg on Predictive Modeling
February 2007 By Tracy A. Gill
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The best way for Joshua Mellberg, president and founder of Tucson, Ariz.-based financial planning firm Senior Advisors Wealth Management, to sell his company’s investment services is to meet with prospects face-to-face. And over the past few years, he has found direct mail is the key to getting his foot in that door.
“We do lead-generation seminars that allow prospects to see what we are about, what services we offer,” Mellberg explains. “For me to get in front of people, the most cost-effective way is mailers. … We’ve done telemarketing and it’s getting harder with the do-not-call lists, hiring the staff, constantly tweaking the [script]. We’ve also done newspaper ads. But I can spend $10,000 on a newspaper ad and fill one or two rooms, or I can spend that on a mailer and fill three or four rooms; it’s about seeing more people for less money.”
But even though his direct mail program had been performing well, Mellberg knew it could be doing even better. Averaging about 45,000 mailers per month, Mellberg had some ambitious objectives: increase the number of leads each direct mail campaign generated, improve the quality of those leads, and do it all for less money. Target Marketing recently caught up with him to discuss how a predictive modeling solution he implemented in summer 2006 helped him achieve those goals.
Target Marketing: What marketing challenges lead you to use predictive modeling? What were your goals?
Joshua Mellberg: We’re based in Tucson. … During the summer, we will get maybe a 0.8 percent return on our direct mail, but in the winter, there’s an influx of retirees coming to the area and we get [about] a 1.5 percent return. So I have to do a lot more mailers in the summer—my marketing costs double. … I thought there would be a better way to bring more people to come see me, or at least mail to people that are more likely to respond. … What I found was predictive modeling and a [database software and solutions] company called CopperKey.
I took all the people that came to my seminar over a couple month period, and I gave CopperKey that list. It found out what they had in common over about 30 different criteria and made a model from that. It then funneled the [prospects] through the model, rating them by how likely they are to respond.
“We do lead-generation seminars that allow prospects to see what we are about, what services we offer,” Mellberg explains. “For me to get in front of people, the most cost-effective way is mailers. … We’ve done telemarketing and it’s getting harder with the do-not-call lists, hiring the staff, constantly tweaking the [script]. We’ve also done newspaper ads. But I can spend $10,000 on a newspaper ad and fill one or two rooms, or I can spend that on a mailer and fill three or four rooms; it’s about seeing more people for less money.”
But even though his direct mail program had been performing well, Mellberg knew it could be doing even better. Averaging about 45,000 mailers per month, Mellberg had some ambitious objectives: increase the number of leads each direct mail campaign generated, improve the quality of those leads, and do it all for less money. Target Marketing recently caught up with him to discuss how a predictive modeling solution he implemented in summer 2006 helped him achieve those goals.
Target Marketing: What marketing challenges lead you to use predictive modeling? What were your goals?
Joshua Mellberg: We’re based in Tucson. … During the summer, we will get maybe a 0.8 percent return on our direct mail, but in the winter, there’s an influx of retirees coming to the area and we get [about] a 1.5 percent return. So I have to do a lot more mailers in the summer—my marketing costs double. … I thought there would be a better way to bring more people to come see me, or at least mail to people that are more likely to respond. … What I found was predictive modeling and a [database software and solutions] company called CopperKey.
I took all the people that came to my seminar over a couple month period, and I gave CopperKey that list. It found out what they had in common over about 30 different criteria and made a model from that. It then funneled the [prospects] through the model, rating them by how likely they are to respond.
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