How the ‘New’ Fingerhut Refurbished its Customer Database
When general merchandise cataloger Fingerhut was re-formed in December 2002 after being liquidated earlier that year by former owner Federated Department Stores (now Macy’s), the company’s foundation was its legacy file of customers who were active with the company prior to its closing. Over time, however, as the company grew to more than $300 million in sales as of the end of 2006, Fingerhut had to replenish those names with new ones.
Realizing its housefile would dry up fairly quickly, over the next few years Fingerhut actively prospected building predictive models off its legacy file. “Fingerhut had a wealth of information available on that file,” pointed out Jane Johnson, vice president with Fair Isaac, a firm Fingerhut worked with that specializes in data analytics and data management. Johnson, along with Fingerhut VP of Customer Marketing John Schlundt, spoke at a session during last week’s DMA07 Conference in Chicago.
As Johnson pointed out, the file from the former Fingerhut incarnation aged fairly quickly. In 2003, 95 percent of Fingerhut’s customers came from that legacy file. But this year just 2 percent remained. So Fingerhut implemented a non-legacy strategy.
The cataloger, which caters to a lower-income audience that prefers to buy items at full price in easy payment installment plans, expanded its acquisition efforts targeting prospects from similar catalogers, co-op databases, magazines and demographic sources. The company revived previously successful best practices, tested new concepts, and identified and attracted customers similar to those positively performing legacy populations, Johnson said.
The strategy encountered some roadblocks, such as limited data for modeling, limited flexibility in business decision making, long lead times translated to stale names in the mail, and little differentiation in offers due to limited targeting capabilities, Johnson said.
As a result, Fingerhut looked for a solution to improve its name yield. The cataloger “wanted to reduce execution time lines and cost per name acquired,” Johnson pointed out.
Last year, Fair Isaac built a prospect database for Fingerhut, which gave the cataloger “a wealth of information it didn’t have before,” Johnson said. As a result, Fingerhut will mail more than 65 million new customer acquisition catalogs this year. The company has doubled its circulation and acquisition rate without negatively impacting response.
Fingerhut increased its growth of names, acquiring 62 percent last year and 41 percent this year, Johnson revealed. New customer sales as a percentage of the cataloger’s total sales were 28 percent last year and 32 percent this year.
“The best part of a prospecting database,” Fingerhut’s Schlundt said, “is you don’t use just one piece of information, but two, three or four pieces and a model that’s been very successful. We have that added variable because we sell on credit. And for most of our customers, the credit offer is the enticing thing. We define people, then give them the offer associated with their credit risk. Then we capture the transaction amount based on their risk profile.”
Fingerhut’s next step is optimization. Fair Isaac is building out contact streams, building a decision model to optimize profitability, Johnson pointed out. “The big thing with optimization,” she noted, “is to understand action/reaction dynamics.”
