Lists and Prospecting: Re-evaluating Co-op Database Options

Until recently, if a consumer cataloger wanted to join a major cooperative database, it had two choices: the Abacus Alliance and Z-24, both founded in 1991. (A third option, SmartBase, was launched in 1995 by list firm Direct Media but was acquired and phased out by Abacus in the late 1990s.)

During the past few years, however, several more co-ops were introduced. I-Behavior and Prefer both launched in 1999, and NextAction debuted within the past year. These newer entrants to the market give catalogers more options — and more data to wade through.

Breaking the mold

With co-op databases, catalog members exchange their own buyer files for names from other catalogers in the co-op. The co-op providers take a member’s names, analyze data from them, then identify the best prospects available from other companies’ names in the co-op through their proprietary modeling methods. Mailers come away with a compilation of customers from other marketers whose buying behavior resembles that of their own buyers.

Although they’ve introduced new services over the years, Abacus and Z-24 for the most part have stuck to the basic model from which they were founded: offering models based on the recency/frequency/monetary behavior of buyers from participating catalogs.

The newer co-ops differentiate themselves largely by drilling deeper into the consumer data that their members share. Abacus and Z-24 provide information on the categories of catalogs from which consumers have purchased — a plus-size women’s apparel catalog, for instance, or an upscale home decor title. But the other co-ops offer SKU-level data. Although their methods vary, NextAction, Prefer Network, and I-Behavior categorize buyer names by the product category, not the catalog category, from which they shopped.

NextAction, for instance, classifies products in “multiple dimensions,” says Karen Crist, vice president of sales and marketing. If a customer has purchased a woman’s cashmere sweater in size large, NextAction’s software captures “large” and “cashmere,” and “that can mean a high-disposable-income family and apparel buyer,” Crist says. “We take that information and run models based on the large-size women’s apparel universe or by implying what it means about the buyer’s household-income level.”

Prefer, for its part, creates “three-dimensional profiles of customers’ shopping behavior outside of members’ companies” using SKU-level data, says president/CEO Doug Platt, “and we apply other direct marketing resources such as recency/frequency/monetary and demographics to our models.”

And through its Integrated Data Mapping System (IDMS), I-Behavior is able to automate the loading, consolidation, and summarizing of SKU-level purchase data, says president/CEO Lynn Wunderman. “Our system exists to classify people, not merchandise,” she says. “So we classify each order into a three-tiered category system, the one most indicative of the type of person behind each transaction. It also ensures consistency of classification, which is what drives predictive patterns.”

Digging deeper

The additional information that the newer co-op databases obtain enables catalogers to find worthy prospects that might otherwise be overlooked. For instance, a jewelry cataloger might pass on prospects who purchased from an apparel catalog. But SKU-level data could reveal which customers of the apparel title bought the jewelry items that make up a small portion of its merchandise offering.

“That’s lost in the modeling process with Abacus,” points out Steve Tamke, senior vice president of list brokerage at Hackensack, NJ-based list firm Mokrynski & Associates. “An Abacus model may not be able to identify [an appropriate prospect] from, say, a Bloomingdale’s, because the person wouldn’t be categorized as a jewelry buyer.”

Nonetheless, neither Abacus nor Z-24 plans to leverage SKU-level data. In fact, Paul Imbierowicz, Abacus’s vice president, product management, suggests that the value of such data is overrated.

“We worked with software companies to do algorithms and saw little to no incremental gains using product category levels,” Imbierowicz says. Most SKU-level category-level co-ops provide smaller numbers of names “that work pretty well,” he continues. But “we provide larger numbers of names that work as well on aggregate. And we found that SKU-level data didn’t help us provide larger numbers of names for our clients.”

What’s more, “true SKU-level data is prohibitively expensive to maintain,” says Peter O’Neil, senior vice president/general manager of the cooperative database business for Z-24 parent firm Experian. “And do you really need to know that someone bought a style and it was red, or that they bought size 10 rather than size 9? We don’t feel it’ll give that much of an additional lift to pay for the expense of gathering that level of data.”

Ups and downs

The Paragon Gifts, the Westerly, RI-based parent company of the Paragon gifts catalog and Practica home items title, has been a longtime user of the Abacus and Z-24 databases, says vice president of marketing Jim Harkins, “with an up-and-down history of usage and results.” But during the past year, Harkins has tested all three new co-ops. He is especially pleased with NextAction, which asks for the catalog copy in electronic form to assist with item categorization. This helps “capture some of the element of whimsy that drives The Paragon,” which is not a product category-driven book, Harkins says.

Medfield, MA-based medial support hosiery and footware cataloger Support Plus is also a fan of NextAction, says director of Internet and database marketing Jake Hill. The co-op has helped Support Plus with its add-a-name program, which seeks additional names within certain zip codes so that the cataloger can qualify for quantity postal discounts.

“We were able to get better-performing names added than when we used to use a flat pool of mostly nonresponsive names,” Hall says. “Next gave us a new add-a-name pool from its catalog database that had some segmentation done in it. This brought us both increased prospecting revenue and postage savings that we’d otherwise not have seen.” Support Plus is also testing Abacus’s add-a-name pool.

Indeed, most mailers that use co-op databases see no need to limit themselves to one. “We’re using all of [the newer co-ops] in conjunction with Abacus and Z-24, both of which we’ve used for years,” says Fred Neil, president of Seta Corp., a cataloger and marketing/fulfillment services provider. “There’s really a lot of parity among all of them now in response even though they all have different features to tout.”

There are probably quite a few similarities between all the co-op models, agrees Fran Wollman, vice president of the Pompano Beach, FL-based list brokerage division of Fasano & Associates. “Abacus has synergy, Prefer has catalog interaction. A lot of their models are comparable to each other.”

Partner Content

Hincapie Sportswear Finds Omnichannel Success in the Cloud - Netsuite
For more and more companies, a cloud-based unified data solution is the way to make this happen. Custom cycling apparel maker Hincapie Sportswear has leveraged this capability to gain greater visibility into revenue streams, turning opportunities into sales more quickly while gaining overall operating efficiency. Download this ecommerce special report from Multichannel Merchant to more.
The Gift of Wow: Preparing your store for the holiday season - Netsuite
Being prepared for the holiday rush used to mean stocking shelves and making sure your associates were ready for the long hours. But the digital revolution has changed everything, most importantly, customer expectations. Retailers with a physical store presence should be asking themselves—what am I doing to wow the customer?
3 Critical Components to Achieving the Perfect Order - NetSuite
Explore the 3 critical components to delivering the perfect order.
Streamlining Unified Commerce Complexity - NetSuite
Explore how consolidating multiple systems through a cloud-based commerce platform provides a seamless experience for both you, and your customer.