In the first installment of our four-part series, we discussed the evolution of prospecting solutions – from campaign-centric list processing events to customized, private prospect database solutions. In this second installment, we will cover some of the differences in handling data via a prospect database vs. today’s list-based environment, and the impact those changes have on the direct marketing industry standards for data rental agreements, list processing services, and business processes.
First, let’s revisit our definition of a customized prospect database. It is a company’s private, multisourced pool of consumer rental names that is hosted in an environment supporting end-user access to plan, execute, and measure data-driven marketing campaigns. With this definition in mind, consider that an inherent feature of a database – whether a house file or prospect solution – is data depth at the individual/HH (house hold) level and breadth across the universe of records. Since private prospect databases require this level of detail to be effective, they fundamentally change the way we think about, manage, and use rental data.
Let’s look at today’s practices related to rental data and the identify types of changes needed to support a private prospect database.
Data sources and content
This is the most complex aspect of change that we will discuss and it includes a number of considerations that we must address. Today, we…
- rent consumer prospect lists by making “selects,” e.g., 0-3 month buyers with $100 order size – but do not receive the detail data on our rental file.
- rent only what we plan to mail.
- create multibuyers segments to mail again and/or delete duplicate instances of individuals and/or HHs.
- have prospect circulation plans that include a variety of lists, each with its own unique data variables and values.
- mail the rental names and “discard” or return the prospect file.
To support a custom prospect database, we would need to consider the following requirements:
- The pool of names should be deeper and/or broader so we can select the right audience for the right promotions.
- The prospect database owner retains all records and their associated detail to create the prospect’s 360-degree view.
- To normalize data, marketers need to execute a data sourcing and management strategy that maximizes breadth and depth of coverage while still preserving list-specific attributes that can be sustained over time.
- To accumulate meaningful data and append promotion history information, we need to retain the prospect data files. Updates to these files will need to be incremental/delta files or full-file replacements, both of which require the list fulfillment provider to keep track of what records they have sent to what prospect database.
As marketers, we are aware of the importance of lists in our direct marketing efforts and we would never willingly limit our ability to test new data sources. As such, we must design our prospect databases to support one-time list use where the list is “loaded, used, and deleted,” with no residual presence on the database. Further, our list test success measures might go beyond traditional ones like response rate, average order size, sales/book, etc., to include more complex list interaction metrics and data conformity to prospect solution standards.
Do not solicits (DNS)
Direct marketing service providers typically execute the DMA Pander suppression process in a list processing or merge/purge environment. In the future, companies that host private prospect databases will need to suppress DMA DNS consumer records prior to an initial source file load to the database, and perhaps at the time each extracted mail file is output from the system to ensure compliance with best practices. Beyond the DMA Pander requirements, list owners who contribute their files to prospect databases will need to develop an efficient way to update all of their prospect database clients with their own ever-changing “do not share” consumer pool.
List owners have complete control over the inclusion of decoy records in their rental files today so they can insure and monitor legal and ethical use of their data. When multiple lists comprise a prospect database, the looming question is not how to deploy a decoy list, but when. For example, the database host company can develop business rules to deploy decoy lists for all list contributors whose data are used to support a campaign select, used as input variables to a prospect model, or some other criteria.
While we have touched on many issues that the industry will face as companies consider private prospect databases, these are just some of the challenges to overcome. But experience shows that when marketers (the prospect database owner), brokers, list owners, and service providers collaborate, we can successfully tackle the data considerations. As direct marketing industry professionals, we must think differently if we are to truly embrace private consumer prospect databases as a means to overcome new customer acquisition challenges.
In the next installment of this series, we’ll discuss how technology must change to support consumer prospect databases.
Caryn L. Gray is a senior marketing consultant for Experian’s Business Strategies Group.