AI decides what, when and where to offer the customer.

Next-Best-Action is based on four predictors that AI determines for each customer individually: what they should see now (a product recommendation or offer), when is the best time to contact (best time to contact), which channel to reach them through (best contact channel) and what is the likelihood to buy.

Together they create a complete instruction for every interaction - without guessing, without averaging.

Business value: more accurate marketing decisions for every customer, a higher campaign response rate, consistency between prediction and execution across all channels

The same model that drives email communication personalizes content on the website in real time.

A banner on the homepage, the order of products in a listing, a recommendation frame on a product card and a pop-up when a customer hesitates before buying - every element is selected based on the current session and the customer's history. The customer does not see a page „for everyone” - they see a page that responds to their current purchase intent.

Business value: higher conversion on key catalog pages, an increase in AOV thanks to accurate recommendations, a better shopping experience without IT work on every change

NBA works not only in outbound campaigns - it also supports contact initiated by the customer.

When a customer opens a web chat, the service agent immediately sees an NBA recommendation: what to offer, which offer to show, what to focus the conversation on. In a brick-and-mortar store, the cashier sees the NBA for a specific person on screen - a complementary product to the one just bought, a special offer matched to purchase history. Every touchpoint becomes an opportunity for the right action.

Business value: higher AOV in the customer service channel, consistency of recommendations between digital and physical channels, an increase in cross-sell effectiveness without additional team training

NBA is not a one-time configuration - the model learns from every interaction and continuously improves the accuracy of predictions.

A higher open rate for an email sent on Tuesday morning? The model remembers. Better conversion from an SMS than from a push for a given segment? The model adjusts the channel recommendation. We monitor prediction effectiveness and deliver reports showing how NBA affects revenue, CLV and engagement - without having to build an in-house data science team.

Business value: growing accuracy of recommendations over time, transparent ROI from the NBA model, optimization without manual analytical work