Strategy: Find the Right Lists

Assuming you have the right merchandise, 70 percent or more of a successful mailing campaign is dependent on the lists you use. Proper list selection means the difference between profits or losses on the income statement. This includes the proper use of your housefile and the outside rented lists you use.

The specific lists you mail and the quantities of every list included in your plan are important considerations. I will talk about the different types of lists available and what you can do to improve your results.

All mailing lists can be classified into three different types:

1. Direct response lists. This type of list of proven mail order buyers includes people who have made an actual purchase by mail, phone or online. For example, your catalog housefile (buyers only; not the inquirers or non-buyers) is a perfect example of a direct response list. Cooperative databases such as Abacus, NextAction, Z-24, I-Behavior, Prefer Network and Wiland Direct all are direct response catalog buyer lists.

Catalogers prefer to use direct response lists, which are the most expensive type of lists and yield the highest response rate.

A word of caution: People who buy on the Web will likely make future purchases on the Web. This means, a cataloger that doesn’t have a strong Web site may want to avoid renting names of individuals who’ve purchased online.

Also, when renting lists, avoid customers who responded to search and affiliate programs rather than buying from a catalog mailing.

Start-up catalogers have difficulty obtaining direct response lists because they don’t have a housefile to exchange with other list owners. Business mailers also have difficulty renting and/or exchanging direct response lists with other business list owners. Most are reluctant to share their names with others.

2. Subscriber lists. Don’t overlook the fact that subscribers of consumer or B-to-B magazines can work for your offer and provide a source to help expand your prospecting universe. If you happen to advertise in a magazine, negotiate a deal with the magazine’s advertising department to get the names for free, or only pay for names selected for optimization. A lot of times the advertising department is willing to cut a better deal than the list manager at the magazine.

3. Compiled lists. These lists are compiled based on type of interest. Businesses, for example, are classified by standard industrial classification (SIC) codes. Dun & Bradstreet is a large compiler of businesses by SIC through its credit service. Compiled lists are used successfully by B-to-B mailers who want to target, for example, specific business sectors. There are many different types of consumer compiled lists, too.

4. Outside list optimization. If you’re a consumer mailer and are using subscriber and/or compiled lists, optimize the lists before you mail them. List optimization identifies mail order catalog buyers on the subscriber and/or compiled file and selects the best prospect names. This step will improve results while minimizing the risk of mailing to compiled names. If you optimize 100,000 names, for example, you should find at least 25,000 prospects worth mailing. Optimizing subscriber or compiled lists only can be cost-justified if you can arrange a “net” deal whereby you only pay for the names you mail.

5. Cost vs. response rates. List costs and response rates vary, of course. The chart below compares the approximate cost for the various types of lists and the average response rates you can expect.

Direct response lists, e.g., co-ops and outside catalog lists, yield the highest response rates. Subscription lists generally produce the next highest response, followed by compiled lists. Obviously, you’ll see that there is a direct relationship between the cost per thousand for the various types of lists and the response rates as shown in the chart.

Seasonality Factors

Typically, holiday is the best season for consumer catalogers as indicated by the 100 percent shown on the chart below. Your fall results will be 70 percent to 75 percent of your holiday results. Spring is 65 percent of holiday, and the slower summer months equal 60 percent of holiday.

So, maximize prospecting results during the holiday season. For example, assume a particular prospect list generates a response rate of 1.88 percent and $1.17 per catalog mailed (your revenue per catalog, or RPC) during the holiday season. Also, assume your incremental break-even point is $1 per book. The response rate for this same list mailed during the summer will be approximately 1.13 percent with an expected RPC of $.70 per book, which is way below your incremental break-even point. So you can prospect to this list above the incremental break-even point during the holiday season. But if you use this same list in summer, expect an incremental loss.

Should you test new lists or continue to use the proven winners? Always test new lists; continuously plant seeds to expand your prospecting universe. Out of 10 “new” test lists, two or three will be worthy of continuation. It’s really a matter of when to test, not necessarily what to test. I recommend testing new lists during your “best” season. If holiday, for example, represents 100 percent of the results you’ll achieve, test during holiday.

If you test new lists during the off season, chances are you’ll never roll out a single list because the results will not justify doing so. If response rates and the revenue per catalog mailed are maximized in October, test new lists in October. This becomes a true test and will yield the kind of results you can read and roll out with confidence.

Effective Rollout: An Example

Say you tested a list of 10,000 names for the first time and it generated $1.50 per catalog mailed, way above your $1 incremental break-even point. Assume the universe for this list is 100,000. On a remail, how many names should you take the next time? 50,000? 75,000? Or the full universe of 100,000? My rule of thumb is to double the quantity per reuse. For example, if 10,000 did well, retest 20,000 names, then go to 40,000 and so on. Mind you, the rollout will never perform at the same level as the initial test. There’s always some fallout as a result of statistical differences, e.g., sample sizes.

Start by using proven direct response lists. Keep in mind that product affinity is the most important factor to determine which lists to use. Be careful using subscriber and/or compiled lists (unless you’re selling B-to-B). For consumer catalogers, subscriber and compiled lists need to be optimized for product affinity prior to mailing. You’ll get your best results from proven mail order buyer lists whose product offering is compatible with yours.

Catalog Seasonality *

In General

Varies Somewhat By Market
Apparel – Often Stronger in Spring/Summer
Home – Stronger in Fall, but Holiday’s Still Best
*chart compliments of Mokrynski & Associates Inc.

Stephen R. Lett is president of Lett Direct Inc., a catalog consulting firm that specializes in circulation planning, forecasting and analysis. Contact: (302) 537-0375 or via e-mail at www.lettdirect.com.