Top 10 Signs Your Data… Ain’t Integrated

Author: Jeff Barela-Dovetail

1. If you think your customers Millie Joan Smith, Daisy Jane Smith, and Billy Joe Jim Bob Smith are the same person…your data ain’t integrated.

2. If contacting individuals, households, residences or unique businesses is done via the “blanket approach”, you’re at the wrong picnic and… your data ain’t integrated.

3. If you’re more afraid of getting accused of SPAM than you are of eating it…your data ain’t integrated.

4. If email, snail mail, and voicemail aren’t included with female, male and opened email…your data ain’t integrated.

5. If you think firmographics is the latest new exercise trend…your data ain’t integrated.

6. If you think integrating your website data is something only Mr. Spock can do…your data ain’t integrated.

7. If you give 3 different people the same criteria for a record count, and you get 5 different answers…your data ain’t integrated.

8. If you think churn only applies to the dairy industry…your data ain’t integrated.

9. If you think modeling is used to find good looking customers…your data ain’t integrated.

10. When you take your car in for maintenance, and think, “wow, that reminds me, I need to do some database maintenance too”… your data ain’t integrated.

We hope you’re laughing. Or at least smiling. But in the real world, data integration is no laughing matter. For direct marketers and IT personnel alike, trying to obtain and integrate all of the data needed for direct marketing campaigns is serious, and often, difficult, business. And, For instance, let’s say you wanted to send a direct mail campaign, followed up by an email campaign, to non-responders. The basic criteria for list selection might consist of a few suppressions, geographic area, transactional data/behavior, and number of marketing touches (to manage fatigue), with the mailing to occur at a household level, and the emailing to occur at a unique email address level. On the surface, this sounds like a straightforward, normal, and intuitive direct marketing campaign. But what about the underlying data to support the campaign? Is the necessary data available and integrated? If not, what will it take to get the data ready? Is the data integration part of the marketing campaign, or is the data ready prior to the campaign, as should be the case? Data integration is indeed no laughing matter. For the selection criteria above, it is likely that the data needed to execute the campaign exists in two or three disparate places within the typical organization, and possibly in as many as five or six different places.

Proper integration of pertinent marketing data to effectively and efficiently conduct direct marketing campaigns is essential, and foundational, to the success of specific direct marketing campaigns and to the ongoing viability of an organization’s entire direct marketing program. The following types of data, while not all encompassing, are typical of the integrated data that an organization needs for direct marketing:

• Customer and/or prospect data

• Multi-channel contact data, i.e., postal address, email address, phone number, etc.

• Transactional data and dates (RFM)

• Multi-level managed data, i.e., individual, household, residence, unique business, unique email address, etc.

• Attributes of customers or prospects, such as interests, preferences, or affinities (can be self-reported or appended)

• Demographic/lifestyle data

• Segmentation data

• Predictive model data

• Campaign history

• Marketing touch tracking

• Suppression data (opt-out)

• Derived data such as region or categorizations of other data elements

The above list is a good starting point, but it does not address how the data is supposed to be combined when it is integrated. Routines and processes should be built to standardize, validate, and correct data, and items such as address standardization and merge/purge need to be performed on the data. For instance, what are the business rules for an active customer if they were active, went to inactive, and are now active again? Should this type of customer be considered the same as a customer who was always active? This is just one example of potentially dozens or even hundreds of business rules that need to be considered when integrating data.

It would take several articles to provide detail on how to integrate data—in fact, books are written on the subject, and no two organizations are exactly alike. But the first step is recognizing the need for data integration, and then having a discussion, or series of discussions, between marketing and IT to talk about the data that is needed, is available, and how to obtain and assemble it. In some organizations, depending on scope, this could be done on an ad-hoc project basis, but the data will typically become outdated quickly. It is ideal if Marketing and IT can work together to build an ongoing process and database to capture and integrate the data; in some cases, depending on an organization’s needs, outsourcing, or partially outsourcing, to a database marketing vendor may be the best option. The bottom line is that data integration is essential—scope, complexity, and cost are all important factors in determining what and how to integrate—each organization needs to determine what is best given all of these factors.

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