How behavioral AI decisioning works

When a visitor arrives on a website with behavioral AI, the AI agent observes their event stream pattern. In five clicks, the AI uses its model built from billions of past sessions to predict the likelihood the visitor will complete a purchase.

This prediction model uses only on-site behavioral data, never any personal data.

With the purchase prediction for the visitor, the AI agent assigns the visitor session into one of three segments: likely-to-buy, on-the-fence, or unlikely-to-buy.

Using this segment, the AI will deliver an action from the real-time engine to the visitor.

Based on their segment, each visitor may receive an action to motivate conversion, cart size, or another valuable result. Retailers work with Session AI to design, test, and monitor actions.

The entire process takes less than 100 milliseconds.

For the visitors who came to buy, retailers want to increase cart value. The right in-session actions can include upsells and loyalty offers. Most importantly, these retailers avoid presenting discounts and promos that are not necessary to convert these visitors.

On-the-fence visitors can be persuaded to buy with the right incentives. Common actions include time-bound discounts, free shipping, and social proof. In-session marketers monitor which incentives work best for their sites, and quickly see much higher conversion and margin.

Unlikely-to-buy visitors aren’t ready to buy anything. Using behavioral AI increases the chance these visitors will become future customers. The best actions include email capture, links to content, and find-your-store messages.