AdZeta provides an AI‑driven platform that predicts customer lifetime value (pLTV) and uses those forecasts to power value‑based bidding on major ad networks such as Google, Meta, TikTok, and programmatic DSPs. Growth teams can target high‑LTV segments, reduce wasteful spend, and improve ROAS, CAC and overall profit margins. The service is monetized through a usage‑based subscription model tied to the volume of ad spend managed through the platform.
Funding
Funding not disclosed
Founders
Product
Problem
E‑commerce advertisers typically bid on short‑term metrics such as CPA, which treats every click equally and leads to substantial budget waste on low‑value acquisitions. Without a reliable estimate of a user’s future lifetime value, brands cannot prioritize high‑profit customers during acquisition.
Solution
AdZeta delivers an AI‑powered predictive LTV (pLTV) platform that ingests a brand’s first‑party data—transaction history, site/app behavior, CRM attributes—and generates user‑level LTV forecasts before the first purchase. These forecasts are exposed as platform‑native value signals through the ValueBid™ framework, enabling Google, Meta, TikTok and programmatic DSPs to execute value‑based bidding automatically. The system continuously retrains its deep‑learning models to reflect seasonal shifts and emerging purchase patterns, ensuring prediction accuracy over time. By directing spend toward high‑LTV segments, advertisers reduce wasted spend by up to 40 %, lower CAC, and achieve 20‑50 % higher ROAS while maintaining sustainable profit margins. All signal delivery is performed via secure server‑side APIs with full auditability and SOC 2 compliance.
Target Audience
The primary users are growth and performance marketing teams at direct‑to‑consumer e‑commerce brands and agencies that manage multi‑channel paid media campaigns and need data‑driven profit optimization.
Features
- Predictive AI engine that processes hundreds of real‑time first‑party signals to output user‑level LTV probabilities and confidence intervals.
- Custom‑trained deep‑neural models tailored to each vertical, delivering 85 %+ LTV prediction accuracy.
- ValueBid™ framework that translates LTV scores into bid adjustments on Google OCI, Meta CAPI, TikTok API, and major programmatic DSPs.
- Automated bid optimization: high‑LTV users receive increased bids, low‑value users are deprioritized, all in real time.
- Secure server‑side activation with identity resolution, deduplication, and exportable logs for full audit trails.
- Continuous model retraining and seasonal adaptation to keep forecasts aligned with evolving consumer behavior.
- Privacy‑first architecture compliant with SOC 2 and GDPR, using aggregated data patterns rather than personal identifiers.
- Integration layer that plugs into existing martech stacks via RESTful APIs and tag‑manager connectors (sGTM, CAPI).