AI might send a special promotion around those events. Or, if a player prefers to bet on a specific sport, programmatic display models can ensure the most relevant matches are at the top of the page where the bettor can easily access them.
AI-driven personalisation extends the bettor’s discovery process by allowing bookmakers to engage customers with the right message at the right time. For example, serving bonuses at a time when the AI has learned that a customer usually decreases their betting, rather than at pay day when they always bet.
Te more interesting and relevant content you see, the more likely it is that a punter will come back. And that’s how AI increases retention and brand loyalty— by showing you content that you want to see before you even know it existed.
What room does AI-driven fraud detection services leave for human operations? Are they still necessary?
Te threat of match-fixing is ever present and evolving all the time. We are seeing a record year-on-year increase in the number of suspicious matches we detect, and with more and more matches to monitor, we are continuously investing in technology to improve our quality and our efficiency – it’s absolutely essential.
The threat of match-fixing is ever present and evolving all the time. We are seeing a
bookmakers don’t have access to this depth of data, as most profiling systems are manual, so realistically they can only touch 10 per cent of their customer database.
Operators can use the insights to determine the type of bets they offer to customers. For example, some customers will be offered restricted bets, while trusted or VIP players will be offered larger bets. Tose customers identified as low risk receive significantly reduced live time bet delays, enhancing the user experience with a super-fast betting experience.
Ultimately, the use of AI risk management leads to possibly the most granular use of risk management tools to achieve the desired ‘risk / return’ profile, which limits lower quality business and enhances high quality with as few constraints as possible
How advanced are AI-driven personalisation models relative to 'traditional' marketing or CRM? What scope is there for these models to grow?
If you consider that traditional CRM platforms are rule based and require human input in order to ‘tell them what to do’, CRM tools configured by artificial intelligence are smarter, faster and always learning as the AI continually updates its parameters.
record year-on-year increase in the number of suspicious matches we detect, and with more and more matches to monitor, we are continuously investing in technology to improve our quality and our efficiency – it’s absolutely essential. While the AI has enabled us to monitor more matches annually, one thing mustn’t be forgotten – it’s the people in our Integrity unit that drive the product and service forward every year.
Tese models work by detecting patterns in player behaviour and using that information to distribute messages, bonuses and bets to customers more effectively and efficiently, with a much better return on the marketing spend. Bet recommendation models, for instance, enable a more personalised betting experience and spreading turnover across a higher number of events, with a better use of content.
If a player tends to bet on underdog teams, the
While the AI has enabled us to monitor more matches annually, one thing mustn’t be forgotten – it’s the people in our Integrity unit that drive the product and service forward every year. A diverse workforce like ours unlocks innovation in every area, and while AI will continue to take more and more responsibility, it must be remembered that it’s our team of highly skilled Integrity betting and investigations experts that are using the technology to deliver impactful outcomes for our partners.
Whilst the advantages of AI are clear, operators can't afford to stand still whilst they change business models wholesale. What is the best approach to AI adoption?
Most operators lack the right combination of size, talent, and access to data. Because these factors are such a rare commodity, proprietary development isn’t often realistic.
Rather than investing in proprietary algorithms, third-party technologies offer a more accessible approach to artificial intelligence. Engaging a third-party specialist is ultimately a smarter, more sustainable long-term solution.
External solutions can be customised to meet the specific needs of any size operator and operators can choose which services they require. Whether they want to retain full control over the technology or lean on the dedicated infrastructure of third-party experts, the operator is always behind the scenes calling the plays.
Bookmakers shouldn’t be afraid of losing autonomy by engaging a third-party specialist like Sportradar. Rather, they should focus on how to utilise these capabilities for their benefit of their business and how to turn them into a competitive advantage.
NEWSWIRE / INTERACTIVE / MARKET DATA P59
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