Building a program to increase customer loyalty, and customer engagement
The client developed a long list of nearly 80 potential features and benefits for possible inclusion within the loyalty program, from various shipping benefits, to point redemption systems, to membership tiers. To make this manageable from a data collection perspective, our Marketing and Data Science team leveraged a two-phased approach – MaxDiff and a discrete choice exercise. A MaxDiff exercise was used to assess interest in 24 binary program features, which were then fed into the discrete choice exercise. The discrete choice exercise was then used to derive interest in various program components (e.g., point system vs. cash back, welcome gift, etc).
- Provided specific recommendations of features and benefits to include in the loyalty program that would maximize loyalty and engagement.
- Eliminated costly benefits that were under consideration but would not boost interest in the program
- Delivered a business decision tool (BDT) so the client could test take rates with various feature configurations as the program evolves over time
- Identified optimal messages for the loyalty program
- Created rich profiles of target consumers for the loyalty program based on key behaviors, psychographics and demographics