How to Use Analytics for Your Medicare AEP Direct Mail Campaign

How do marketers determine the proper number of touches during the Medicare AEP campaign to drive lead volume through direct mail? The best way is to leverage audience analytics to determine the investment.

Direct mail continues to be a workhorse during AEP, the most recent Medicare Shopping and Switching Study by Deft Research showed that 27 percent of Medicare Advantage members read the direct mail they received.[1] Direct mail, and its low-tech and tangible approach, cuts through the digital clutter, builds brand awareness, and leads to attributable action.[2] Furthermore, 83 percent of Americans born between 1925 and 1945 are most likely to trust direct mail information when they make purchasing decisions.[3]

The best practice is to use predictive models for Medicare audiences because there’s a mechanism that ranks the probability that a prospect will interact with your brand as a result of marketing activities. These models can be built to predict response or conversion behaviors, allowing marketers to optimize investment by choosing the appropriate mail depth to meet their goals. However, the compressed marketing window of AEP demands that health insurers approach targeting in a compliant way that ensures all eligible people receive information equally, so health insurance providers can meet this requirement with the use of model-based performance.

There is a relationship between the model depth (probability to respond) and number of touches a prospect receives during AEP. Here are a few examples:

Baseline

This is a business-as-usual scenario, in which a four-touch tactic is deployed across the target prospect universe during AEP. This is an even investment that yields uneven return (ROI), due to uneven performance across the targeting model spectrum.

Scenario 1

Here, matching up number of contacts to the model depth would yield a 38 percent reduction in spend, and 11 percent reduction in lead volume with a 30 percent increase in CPL efficiency.

Scenario 2

In this example, you can use the budget savings for the more productive model cells. During AEP you would want to maximize the lead funnel to drive sales. Namely, you could increase touches in the middle deciles that provide positive lift and better overall performance.

Scenario 3

This scenario reduces overall budget by 23 percent, with a reduction in lead volume of just under three percent. The CPL efficiency increases by 20 percent above baseline. This allows the savings to be redeployed to a variety of programs such as digital addressable media to support direct mail and lead-nurturing efforts.

Conclusion

Medicare marketers who have audience targeting models in place and have an undifferentiated contact cadence, should begin to test the relationship between those models and touches. This will help you understand each interaction and will also inform future AEP campaigns.

Interested in how to launch a successful Medicare AEP campaign? Join the webinar