What is predictive segmentation based on likelihood to purchase?

Predictive segmentation uses machine learning models to score subscribers based on their likelihood to purchase. The model analyzes patterns like email engagement, website behavior, purchase history, and timing to assign a probability score.

Subscribers with high scores receive targeted offers, personalized product recommendations, or limited time incentives. Those with low scores might enter nurture sequences or educational content flows instead. This approach focuses resources on the highest intent audience.

Platforms like Klaviyo, Blueshift, and Salesforce Marketing Cloud offer built in predictive models. Custom models can be built using Python, R, or third party tools and integrated via API.

The model's accuracy depends on data quality and volume. It needs enough historical transactions and behavioral signals to identify meaningful patterns. Test predictions against actual outcomes and refine over time.

Predictive segmentation reads the currents before the ship sets sail. It positions your message where the wind is already blowing in your favor.