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How can bonuses become more efficient? Three recommendations for operators

iGaming operators working under higher taxes and bonus restrictions can improve their efficiency by managing promotions from a central structure and personalizing them based on player data. Ionut Negrescu of Software Mind explains that three areas need focus in this process.

How can bonuses become more efficient? Three recommendations for operators
Photo: NEXT.io

In the United Kingdom, the Remote Gaming Duty rate rose from 21 percent to 40 percent on 1 April 2026. According to HM Revenue & Customs data, this change came a few months after the UK Gambling Commission limited bonus wagering requirements to 10 times. The Commission also banned promotions that mix different products, such as offering free spins with a sports bet. Operators in other markets are facing similar tax and incentive rules and competitive pressure.

Promotions remain one of the strongest ways to retain players, but on many platforms they are also among the least efficient tools. Operators' promotion stacks are often not deliberately designed and build up over time. A casino aggregator's free spin tool, a sports betting supplier's separate bonus module, the CRM's own campaigns and a layer added by a jackpot provider can all run at the same time. After mergers and acquisitions, a group may run several of these stacks side by side.

According to Negrescu, the solution is a central promotion orchestration layer that manages eligibility, compliance rules, segmentation and reporting. Reward distribution, however, stays in existing supplier systems where provider-specific capabilities are needed. Not all tools need to be replaced at once. Because integration maturity varies from supplier to supplier, operators first standardize business rules and reporting, route new campaigns through the central rules layer, and migrate older promotions brand by brand.

Many operators divide their players into groups such as new depositors, VIPs and players who have not returned for a long time. However, each group is often given a fixed offer. Under high taxes and limited wagering requirements, an offer the player does not value achieves nothing. A personalized system, by contrast, adjusts the offer based on what the platform knows about each player. Negrescu describes a project with Romania-based gaming hall operator The Jack in which a leaderboard tournament doubled loyalty participation. Although the project was carried out in a physical venue, the approach also applies to online platforms.

The same data can reveal not only high-value players but also early signs of harm. Deposit limits, self-exclusion status and sudden changes in behavior should be built into the bonus logic so they are checked before an offer is sent. In addition, rankings based on a single figure, such as gross gaming revenue, can be misleading. A high-spending player who claims bonuses right away may be less valuable than a steady player who does not need a bonus. A model that combines multiple data points makes segmentation dynamic, and the promotion engine changes offers accordingly.

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