Case Study

Leading Electrolyte Supplement Brand – New-to-Brand AI Audiences

An electrolyte supplement brand sought a more effective way to identify and reach NTB customers through Amazon DSP. While Amazon’s standard in-market audiences provided access to active researchers, the brand wanted a precise audience strategy focused on identifying consumers most likely to become first-time buyers.

CHALLENGE:

Find Higher-Propensity New Customers

In-market audiences are often based on broad category interest and shopping behavior, but do not always identify the consumers most likely to become new customers. The brand needed a more predictive approach that could improve prospecting efficiency and drive stronger acquisition performance.

SOLUTION:

NTB Audience Studio Model

WBX leveraged its NTB Audience Studio Model to score shoppers based on their likelihood of becoming new-to-brand purchasers. The model was activated through Amazon DSP and benchmarked against Amazon’s leading supplement-related in-market audiences.

METHODOLOGY:

WBX Audience Studio leveraged a closed-loop AI system and self-improving models focused on new-to-brand conversion probability, scoring shoppers based on their likelihood to become new-to-brand customers. The custom audience was activated via Amazon DSP campaigns and benchmarked against Amazon’s available in-market audiences. Conversion rates were measured across all audience segments to evaluate the effectiveness of predictive customer scoring in driving new-to-brand acquisitions.

RESULTS:

The model converted at 0.53% — 1.64x higher than the best Amazon in-market audience.