Case Study
A leading health and wellness brand wanted a more sophisticated way to re-engage existing customers through Amazon DSP. While the brand already targeted previous purchasers, it recognized that not all past customers have the same likelihood of purchasing again.The goal was to identify and prioritize the customers most likely to return to the purchase cycle.
CHALLENGE:
Traditional retargeting often treats all previous purchasers as equally valuable, resulting in inefficient media spend and missed opportunities to focus on the customers most likely to buy again. The brand needed a more precise approach that could improve repeat purchase performance while maximizing the value of existing customer audiences.
WBX leveraged its Repeat Purchaser Audience Studio Model to score previous customers based on their likelihood to make another purchase. The model identified high-propensity repeat purchasers and benchmarked them against a traditional past-purchase retargeting audience to measure performance.
WBX Audience Studio leveraged a closed-loop AI system and self-improving models focused on repeat purchase probability, scoring previous customers based on their likelihood to purchase again. The custom audience was activated via Amazon DSP campaigns and benchmarked against a traditional past-purchaser retargeting audience. Conversion rates were measured across both audiences.
RESULTS:
The model converted at 24.14% — 3.6x higher than the traditional pretargeting audience