When Searching for Customers, Stronger Triggers May Work Best

May 07, 2007 9:39 PM  By

One of our clients, a large home decor marketer, enjoys a high average order value but has been challenged by an extremely low response rate, which has been declining significantly for several years. The low response rate reflects the fact that the merchandise the company sells is purchased infrequently—typically just once every five to ten years, with the average about every seven years.

Our client’s past marketing strategies epitomize classic direct marketing prospecting. For the most part, the merchant had simply rented lists of recent buyers of high-end home décor items which it believed to be synergistic with the merchandise it sells. These lists had been supplemented with a variety of transactional models provided by the cooperative databases. They used tried-and-true traditional techniques that work for most mailers, most of the time.

What’s the problem? Our client’s merchandise categories have become highly competitive during the past several years. Internet retailers who enjoy radically lower cost structures have invaded the category by offering similar merchandise without the associated high cost of a print catalog. Furthermore, the infrequent nature of the purchase makes prospecting highly inefficient, as demonstrated by the low response rates.

Our conclusion: While propensity to purchase through catalogs is a necessary condition for prospecting success, it is not a sufficient condition. We determined that our client also needs strong triggers—or early indicators—to better identify qualified prospects. These qualified prospects may need to be optimized for propensity to purchase through catalog, but absent the trigger, searching for a qualified prospect in a pool of names from a rented list or co-op database model is the proverbial search for a needle in a haystack.

Based on our research and analysis, we determined that these signals or early indicators may include a recent move, a cash-out refinancing, and the granting of a building permit for an existing residence. The theory: new movers often need to decorate, and individuals who are refinancing their home or have been granted a building permit are likely to be remodeling their home—and also need to decorate.

We identified large universes of qualified prospects that have recently moved, concluded cash-out re-financings, and/or received residential building permits. In some cases, these lists had the same geographical (zip) overlays as are applied to the client’s other outside lists and models. Generally, names were also optimized at a cooperative database.

On head-to-head tests, prospects developed from early indicator sources outperformed average prospects on a revenue per catalog basis by approximately 15%. After giving effect to two early indicator tests that were unsuccessful and will not be continued, the remaining pool of early indicator lists outperformed average prospects by nearly 35%.

Initial tests of 0-3 and 4-6 month movers are producing results favorable enough to justify relaxing the recency select and testing into 7-12 and 13-24 month segments. Even after stringent optimization, we have been able to mail 50%-65% of the 0-3 and 4-6 month segments. We believe it is possible that 60%-75% of the client’s prospecting could soon be derived from early indicator sources—up from less than 10% a short time ago.

A few caveats: Recency is obviously critical for new mover data. Often lists that appear fresh are stale by the time the mail piece arrives. For example, names on a “seven-day new deeds” list were estimated to be nearly two months old by the time the catalogs arrived in homes. As a result, we are considering alternative delivery mechanisms to substantially speed up delivery and improve recency. Also, optimization does increase the list cost but the increases in response rate more than justify the additional cost. Be aware that although first-level optimization sometimes provides a significant lift, in certain cases secondary optimization—using the client’s database as an optimization vehicle—is also required.

So, if finding new customers is no longer as easy as shooting fish in a barrel, consider putting aside your shotgun, picking up a rifle, and looking for “triggers” or early indicators in your prospecting efforts.

Mitch Siegler is a partner with San Rafael, CA-based catalog consultancy Lenser.