The Web, the Economy and List Sizes

With the decline in list sizes and the drop in co-op database performance and circulation, many catalogers wonder where the next phase of growth will come from.

Based on client survey data (see story, below), Mokrynski & Associates has identified three critical areas proven to increase customer acquisition and the value of outside lists in the strategy outlined in this article.

List selectivity. Recency, frequency and monetary as well as product selects are the foundation upon which mailers select. Acquisition depends on how much deeper a mailer can drill into valuable list segments.

Selectivity is the name of the game to meet the needs of mailers. The more selectivity offered, the more responsive the list will be to traditional and nontraditional mailers.

Increased selectivity will reduce the available universe to most mailers. But the benefit of reaching more targeted names will reflect positively in increased rollouts and the economic value of the list to both the mailer and list owner.

Options include enhanced selects such as demographics and lifestyle categories. Demographic selects include age, income, children’s age, home ownership and marital status. Lifestyle selects include reading, outdoor sports, pet ownership/interest and gardening.

Using these selects will reduce available universe 15 percent to 40 percent, depending on the select taken. However, opening niche universes will increase response, allowing more frequent and profitable use of the file.

List modeling. List modeling and optimization is emerging as an important new tool. This represents a major opportunity for many catalogers.

Technology gives brokers and managers the tools to improve performance on marginal lists and lets mailers drill deeper into continuation files, resulting in strong performance.

Good customer modeling lets mailers identify similarities with the list owner’s customers, including demographics, purchasing patterns, geographic locations and lifestyles.

These models, when applied, boost response 10 percent to 20 percent, opening new universes for mailers. The same modeling technique can be used when list performance varies season to season, thus generating more consistent and predictable use year-round.

Regression modeling applies similar principles from good customer modeling. However, models are built from the results of the mailer’s prior use of the list owner’s file. The performance levels increase with the response model, 15 percent to 35 percent. But the life cycle of the acquisition is greater as well as the overall model’s cost.

Internet vs. catalog names: The continuing increase in Web activity is changing the composition of many list rental files, and many mailers aren’t conducting full-scale match-backs. As Web orders rise, many mailers will be making list decisions based on incomplete data.

The percentage of Web sales continues to rise, mainly as a result of catalog circulation. However, because only about one-third of the mailers we surveyed match back Web sales to catalog, list results may be skewed.

The increased use of Web-based prospecting and promotional techniques raises issues of lifetime value and contact strategy. Many mailers are only beginning to test the best contact strategy for Web-generated buyers. Lifetime value may differ greatly for a Web-sourced versus a direct mail-sourced customer.

Ask the tough questions. Determine the percentage of Internet buyers on your prospect lists. A list with 50 percent Internet buyers versus a list with 20 percent should not receive the same sales allocation.

A list that seems to be a weak performer might be a winner when Internet sales are allocated more realistically, allowing acquisition strategies and the economics to change on a list-to-list basis.

If you are in doubt regarding the accuracy of this allocation method, another approach is to test catalog vs. Internet buyers on the list. Catalog responders will allow you to accurately track response and allow for better decision making.

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