Predictive Targeting with ML

Predictive targeting uses machine learning to identify users most likely to convert, buy high-value products, or become long-term customers - often before they show explicit purchase intent.

Predictive Signals

ML models analyze hundreds of behavioral signals to predict future actions:

• Browsing Behavior: Pages viewed, time on site, scroll depth, and navigation patterns
• Search Intent: Query patterns, comparison shopping signals, and research behavior
• Engagement History: Email opens, ad clicks, social interactions, and content consumption
• Purchase Patterns: Recency, frequency, monetary value (RFM), and product category affinity
• Contextual Signals: Device type, time of day, location, and seasonal patterns

Prediction Models

Implementation Approaches