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How To: Use Loyalty Data to Power Customer Retention and Reactivation

Retailer? Here’s a best practice-based methodology for marketing testing and optimization (with three more to download)

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Customer-centric retail brands looking to provide personalized customer experiences across all marketing channels know that it is crucial to test and optimize consistently. The problem is, most customer data platforms (CDPs) only provide basic testing and optimization tools that do not scale or ensure personalized and consistent omnichannel customer experience (CX).

With brands looking to maintain a differentiated and consistent brand experience to consumers, both in-store and direct-to-consumer (DTC), addressing the above problem is of key strategic importance.

Today, we will present you with a women’s activewear retail brand who has overcome this challenge by taking advantage of the Optimove platform to optimize their marketing operations. This brand reduced CAC by 75% and customer churn by 32%, all while increasing average customer LTV by 12%.

How’d they do it, you ask?

Using loyalty data to power customer retention and reactivation.

This is just one methodology (with three more to download) that demonstrates how marketers can easily use Optimove to discover customer insights, test their hypotheses, and optimize their CRM campaigns.

Using Customer Loyalty Data to Power Retention and Reactivation

Loyalty programs provide marketers with many opportunities to build long-lasting relationships. They allow you to differentiate communications with each customer based on membership patterns. Your loyalty program also offers a unique opportunity to segment, analyze, and interact with customers based on both their membership status and historical brand interaction.

The activewear retailer, mentioned above, leveraged customer loyalty program data to analyze the reactivation rate of both one-time purchasers and churned repeat customers. Since Optimove provides bespoke customer lifecycle stages based on each brand’s own data, the retailer’s marketers were able to identify new segments and opportunities easily. And then activate them via time-based campaigns with tailor-made offers for each segment.

As seen in the following two charts, customers who had been loyalty program members reactivated 7X more often than customers who were not in the loyalty program at the time they churned (reactivation rate of 7% vs. 1%):

Using these customer loyalty insights, these marketers decided to provide the “No Loyalty Level” group with incentives similar to those given to their Promotion and Gold groups, to incentivize reactivation and retention. The marketers also set up monthly recurring campaigns with varying levels of incentives, based on how long each customer was inactive.

To reduce implementation efforts, treatments were repurposed across segments, when possible, resulting in the following marketing plan:

In Sum

Based on years of experience optimizing customer marketing in the retail industry, Optimove has productized solutions that enable marketers to devise and execute personalized multichannel strategies, based on each individual customer’s unique behaviors and characteristics. 

To learn more, download the full use case here.

Read part 2 here, a best practice-based methodology for marketing testing and optimization.

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Rony Vexelman

Rony Vexelman is Optimove’s VP of Marketing. Rony leads Optimove’s marketing strategy across regions and industries. Previously, Rony was Optimove's Director of Product Marketing leading product releases, customer marketing efforts and analyst relations. Rony holds a BA in Business Administration and Sociology from Tel Aviv University and an MBA from UCLA Anderson School of Management.