AI Signals is Treasure AI's enterprise-scale machine learning platform. It turns unified customer data into ML-driven predictions and segments at enterprise scale, with no infrastructure to build and no data leaving the platform.
Out of the box, AI Signals provides training and inference infrastructure that auto-scales with data requirement, an expanding library of model types, and the convenience of unified customer profiles living in the same environment as training and prediction. The platform is computationally scalable and API accessible, so a data team within a marketing organization can start a project quickly and deliver results fast.
- Recency, Frequency, and Monetary (RFM) Analysis
- Customer Lifetime Value (CLTV) Forecasting
- Next Best Product (NBP) Recommendation
- Next Best Action (NBA) Recommendation
- Runs inside the secure Treasure AI environment, with direct access to the clean, unified, and enriched customer data already in your CDP.
- Integrates with your existing Treasure AI components, so all data processing stays in one environment.
- Works out of the box, with no technical setup or infrastructure maintenance required from data teams.
- The Treasure AI engineering team continuously improves and expands the ML toolsets through regular updates.
| Question you're asking | Use |
|---|---|
| Who matters, based on past purchasing? | RFM AI Signals: descriptive segments, no modeling required |
| How much will this customer be worth? | CLTV AI Signals: a value forecast and percentile rank |
| Which product should I recommend next? | NBP AI Signals: a ranked list of products, services, or content |
| Which action should I take for this customer? | NBA AI Signals: a learned per-user policy across candidate actions |