Predict
When a visitor arrives on a website with in-session marketing, the AI 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.
Segment
With the purchase prediction for the visitor, the model 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.
Act
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.
Delivering actions based on purchase intent
In-session marketing segments site visitors into three groups based on their purchase intent. Visitors in each group may receive an on-site action designed for their segment.
Likely-to-buy visitors: upsell and cross-sell
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: real-time incentives
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: engagement
Unlikely-to-buy visitors aren’t ready to buy anything. In-session marketing increases the chance these visitors will become future customers. The best actions include email capture, links to content, and find-your-store messages.