What's in Your Database?
Second Step: Data Pattern Analysis
To find bigger data anomalies that don't show up in what Miglautsch refers to as the "spell-check" phase of a data audit, you actually have to run some simple data mining programs.
Miglautsch asks marketers for some RFM reporting that helps him score the file and start looking for data patterns that don't make sense. For example, he remembers a marketer whose sales in the South were attributed to its main, southern retail location, rather than individual customers. Initial analysis suggested that sales in the South came from just one ZIP code. Further investigation turned up the data input problem.
What's interesting and critical about this type of analysis is that you determine not only the mistakes that need to be caught and corrected, Miglautsch states, but identify golden opportunities.
A catalog marketer whose primary customer base was in the Northeast, Miglautsch explains, found that response to its mailings dropped significantly in the South. Instead of scaling back efforts in the South, the marketer examined the reasons behind this sales challenge. The solution was in its creative, which featured snowy landscapes that didn't connect with southern customers, explains Miglautsch.
Product classification also should be carefully analyzed. Sometimes, marketers have so many SKUs that they're hard pressed to draw any definitive conclusions from their order history, says Peter Vlahakos, who heads up Donnelley Marketing's analytical team. Marketers can roll up their SKUs into product categories, he explains.
For non-address type information, such as product codes, order history and self-reported information, analysis can take several weeks to several months, says Kasmarski. The time frame depends on the availability and knowledge of the marketer's IT staff, number of fields, quality of the data, and the documentation on data sources.
Third Step: Assess Your Data Readiness
Depending on the activity you're trying to predict or the trends you want to identify, you can do modeling or segmentation with less than complete data in all fields, says Vlahakos.