For multichannel merchants and IT personnel alike, trying to obtain and integrate all the data needed for direct marketing campaigns is a serious, and often difficult, process.
Let’s say you wanted to send a direct mail campaign with a follow-up e-mail campaign to nonresponders. The basic criteria for a list selection might consist of a few suppressions, geographic area, transactional data/behavior, and number of marketing touches. On the surface, this sounds like a straightforward direct marketing campaign. But what about the data to support the campaign? Are the necessary data available and integrated? If not, what will it take to get them ready? Has the data integration become part of the marketing campaign, or are the data ready prior to the campaign, as should be the case? In this case, it is likely that the data needed to execute the campaign exist in two or three places within the organization–and possibly in as many as five or six places.
Proper integration of pertinent marketing data for effective and efficient direct marketing campaigns is essential, not only to the success of each campaign but also to the ongoing viability of your company’s entire marketing program. The following types of data are typical of those that need to be integrated for direct marketing:
- Customer and/or prospect data
- Multichannel contact data (postal address, e-mail address, phone number, etc.)
- Transactional data (for RFM)
- Multilevel managed data (individual, household, residence, unique business, unique e-mail address, etc.)
- Attributes of customers or prospects, such as interests, preferences, and affinities (can be self-reported or appended)
- Demographic/lifestyle data
- Segmentation data
- Predictive model data
- Campaign history
- Marketing touch tracking
- Suppression data (opt-outs)
- Derived data or categorizations of other data elements
This list does not address specific integration processes, such as data validation, data standardization, and application of business rules. It would take several articles to provide details on how to properly integrate data–in fact, books are written on the subject.
But here, at least, you’ve gotten to the first steps: recognizing the importance of data integration, determining the data that need to be integrated, and implementing the process of integrating the data, while accounting for the scope, complexity, and cost of the integration effort.
Jeff Barela is chief operating officer of Highlands Ranch, CO-based marketing database company Dovetail.