Is a Prospect Database Right for You?
This can be extremely inefficient because list owners have to be paid multiple times and service bureaus have to run multiple merge/purges. Also, the data generated by each merge/purge is discarded rather than consolidated, analyzed and then leveraged to enhance future targeting initiatives.
Some mailers have found a better way by leasing outside lists for long-term usage. They have achieved this by building and maintaining what is known as a prospect database.
How can you determine if a prospect database is right for you? This article will describe five factors that you must evaluate. The more of these factors that describe your circumstances, the more likely it is that you should build a prospect database.
But first, a brief definition: A prospect database is a repository of non-customer names and addresses that have been overlaid with descriptive data. This descriptive data generally includes demographic elements such as age, income, length of residence, marital status and presence of children. Other elements can include mail-order responsiveness, shopping behavior and psychographics - such as "interest in photography." This data is combined with business rules, and often statistical techniques such as predictive models, to segment the prospect database.
5 Factors of Prospect Database Feasibility
Factor 1: List owners agree to either "flat-rate" or "net/net" usage arrangements. With flat-rate usage, the mailer pays an up-front fee for an unlimited number of contacts over a 12-month period. With a net/net arrangement, the direct marketer pays for the names each time they are mailed.
Both flat-rate and net/net usage is different from the "net" arrangements that are common in rental environments. With a net arrangement, payment is received for a certain percentage of the names that are rented, regardless of how many are actually mailed.
Flat-rate usage is easier to administer than "pay as you go" net/nets. This is because, with net/nets, overall payments have to be prorated among multiple contributors, each of which is likely to have different per-name fees.
For example: Assume that Marilyn appears on Lists A, B and C, and David on Lists A and C. Also assume that List A is leased for $0.09 per use, List B for $0.102, and List C for $0.12. Under this scenario, every time that Marilyn is mailed, the owners of Lists A, B and C must be compensated. Likewise, every time that David is mailed, the owners of Lists A and C must be compensated. Typically for Marilyn, the payments would be $0.03, $0.034 and $0.04, respectively. Likewise for David, they would be $0.045 and $0.06. Systems must be put in place to track usage at the name-level and distribute prorated payments on a regular basis.
With the net/net approach, one way to encourage list owners to contribute their names to the prospect database is to provide a minimum overall monetary guarantee throughout the lease period. Under this scenario, the goal might not even be to save money, but instead to maximize targeting with sophisticated data mining techniques coupled with robust overlay data and promotion history.
Factor 2: Direct mail prospecting is composed of a manageable number of outside rental lists. Some direct marketers input 100 or more rental lists into their merge/purges. For each list within a prospect database environment, usage arrangements must be first be negotiated, and - as described earlier - tracked on an ongoing basis. The greater the number of lists involved, the larger the logistical effort.
I have seen prospect databases work with hundreds of participating lists. However, success requires a significant investment of time and effort. In contrast, consider the kindergarten-to-grade-12 education market, which is a classic example of a circumscribed list rental universe:
This business-to-business - or, more accurately, business-to-institution - industry is composed of 88,000 public schools and 23,000 non-public schools. Three compiled list companies dominate the market, and their properties contain significant overlap. For any direct marketer who operates within this space, a significant number of prospects are being mailed time and time again and processed through the same hygiene and merge/purge steps over and over.
Factor 3: Compiled lists play a significant role in prospecting. Direct mail responsive names generally have a shorter shelf-life. This, by definition, is especially true for hotlines. When time-since-purchase is the overriding factor in success, sophisticated data mining techniques will assume less of a role in targeting. Hence, the universe of viable names within the prospect database will display significant churn. If compiled lists play a significant role, a prospect database is more likely to be helpful.
Factor 4: Targeting can be significantly enhanced with overlay data such as demographics. Direct mail responsive rental lists, by their very nature, contain implicit overlay data. It can safely be assumed, for example, that any given Neiman-Marcus customer is fashion-forward and affluent. In contrast, the interests and income level of the typical Hot Rod Magazine subscriber is very different.
Nevertheless, traditional rental lists contain - at best - very limited explicit demographic selects such as gender. This is in stark contrast with overlay data, for which hundreds of elements often are available. For some companies, overlay data combined with promotion history can drive powerful, statistics-based prospecting models.
Factor 5: Many promotions a year are targeted to the same prospects. Especially for compiled lists, the annual lease fee for flat-rate usage will be 2 1/2 or 3 times the rental rate. Therefore, lists mailed at least three times a year will be primary candidates for inclusion in a prospect database. At such frequencies, it is common for a prospect database to drive down overall acquisition costs.
The more times a year a list is mailed, the more inefficient and costly the process. Merge/purge costs, which typically average at least $10 per thousand records output, can accumulate rapidly over time. Instead, they can be replaced by more efficient prospect database update cycles. Likewise, money that was spent on traditional merge/purges can be used to fund the construction and maintenance of the prospect database.
An added bonus of a prospect database is that promotion history can be captured over time, and then employed to increase the effectiveness of direct mail targeting. Prospects who have not responded time and time again are less likely to ever respond.
Case study: As a general rule, prospect databases are most effective when they are part of a comprehensive marketing database. Combining prospects with customers and inquirers provides the 360-degree view required for sophisticated prospect and customer relationship management tactics and strategies.
One client contracted to build a comprehensive marketing database that combines customers, inquirers and prospects. The client, a business-to-institution marketer, was able to lower its outside list costs by 50 percent during the first full year of the marketing database. Then the client fine-tuned the prospect portion of the database for further savings by transferring back to rental status all lists that had not been mailed at least three times.