Five data mapping strategies that optimize marketing

Customer segmentation projects command a significant commitment of time and resources to define and refine the ideal buying profile. To extract value from these profiles and optimize marketing performance, the segments must be effectively mapped to a CRM database and enhanced with demographic and behavioral data, like Experian’s ConsumerView℠ database, in order to create actionable intelligence. We asked Ian Rogenski, an Experian Principal Analytics Consultant with more than 16 years of analytics experience, to identify the top five mapping considerations when endeavoring segmentation work.

Here are Ian’s top five mapping considerations to help you optimize customer segmentation:

  1. Understand your ultimate marketing goal. Sometimes segmentation is about strategic understanding – knowing who your customers are and how they change over time. Marketers may also want the ability to track segments or communicate directly with customers in a relevant way. It is in these reporting and one-to-one marketing goals that mapping segments onto a database becomes critical.
  2. Define the key difference between segments. In order to effectively map segments, it is important to understand what makes the segments different from one another. Therefore, marketers need to define all the characteristics that comprise the segment profiles. Taking full stock of the data points that describe the segments is a critical step.
  3. Create a baseline. Build a baseline of data available from the CRM database to address gaps and identify points of linkage. Taking stock of data is critical for mapping the segments. This will support the ability to create linkage or a model to project the primary research out to the database.
  4. Plan to append the data. Append data to both the research data and the CRM database with a reliable and comprehensive third-party data source (such as ConsumerView) to provide insight into your segments. When building a mapping model, having consistent data across the data sources is a critical feature.
  5. Validate segments against business requirements. The business requirements need to be honed in on when projecting the segments. For example, requirements could include the segment, the sales associated with each segment or the demographic profile of the segments. With these requirements in hand, the modeler can apply the science to build a baseline model and then apply the art of statistics on the back end. Optimizing the final segment assignment, by targeting the business requirements, can make or break the value of the solution.

For more insights into how to build effective mapping strategies email


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