Case Study
An electrolyte supplement brand wanted a more precise way to identify likely new-to-brand customers instead of relying on broad in-market audiences available to every advertiser. The brand wanted a stronger way to reach shoppers most likely to become new customers rather than relying on generic audience segments.
CHALLENGE:
WBX used the NTB Audience Studio Model to score shoppers based on their likelihood to become new-to-brand purchasers, then benchmarked the model against Amazon’s available in-market audiences.
WBX Audience Studio leveraged a closed-loop AI system and self-improving model focused on 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% — 2.0x higher than the best Amazon in-market audience.