How Multi Maker Works
Multi Maker reads the bet a customer is about to place and suggests relevant, well-priced multis in the moment, when the customer is most likely to add to their bet slip.
Contextual Bet Analysis
Every suggestion is built from the customer's current selection, not a generic list of popular multis.
Real-Time Suggestion Delivery
Suggestions appear as the bet slip is built, not after the bet is placed, when it's too late to act on them.
Uptake Optimisation
The model learns which suggestions convert and continuously improves what it recommends and to whom.
Reward Suite Linkage
Multi suggestions can be paired with Reward Suite incentives, giving customers an extra reason to add to their slip.
Why Multi Maker
Higher Multi Placement
Relevant, well-timed suggestions increase the rate at which customers place multis.
Built for the Moment
Suggestions are delivered while the customer is actively building their bet, not after the fact.
Learns Continuously
Uptake data feeds back into the model, sharpening future suggestions over time.
Pairs With Reward Suite
Combine multi suggestions with automated rewards for stronger retention results.
Increasing Multi Placement
Generic “popular multis” lists rarely match what a specific customer actually cares about. Multi Maker builds every suggestion from the bet the customer is placing right now, so the recommendation is relevant to their actual interests rather than a one-size-fits-all list.
Relevance is what drives uptake, a suggestion built from a customer’s own selections converts at a meaningfully higher rate than a generic prompt ever could.
Delivered at the Right Moment
A multi suggestion delivered after a bet is placed is a missed opportunity. Multi Maker surfaces suggestions while the bet slip is still being built, exactly when the customer is in a position to act on them.
That timing difference is the entire value proposition: the same suggestion, delivered a moment too late, converts far less often.
A Model That Keeps Improving
Multi Maker doesn’t run on a static set of rules. Every suggestion that is accepted or ignored feeds back into the model, refining what it recommends and to which customers, over time.
This means suggestion quality improves the longer the system runs, without any manual retuning required from your team.
Better Together With Reward Suite
Multi Maker and Reward Suite are designed to work from the same customer data, so a multi suggestion can be paired with a relevant reward automatically, no manual coordination required between the two products.
Together, they give customers both a reason to bet bigger and a reason to keep coming back.