AI has had a profound impact on personalised offerings across various industries, transforming the way businesses understand and cater to individual customer preferences.
The gambling sector is no different, and whether it is through recommender systems, content personalisation or personalised marketing, it is clear that AI-driven systems are already with us.
“The popularity of sports betting worldwide has given operators access to an increasingly large pool of customer data,” says Andreas Hartmann, director of personalisation at VAIX, which is owned by Sportradar.
Previously, such data loads were way too big to be analysed by the traditional data processing methods at the disposal of even the biggest bookmakers. But the emergence of AI tools and their capability when it comes to data has changed the nature of the game.
Operators are now turning to Artificial Intelligence – AI, for short, in case you have been living under a rock – to process their data and extract meaningful insights that offer a better understanding of their customers.
“Training on the events customers have bet on previously, the AI knows the type of content those customers are interested in,” says Hartmann. “That combination of deep, customer insight and advanced AI enables operators to deliver personalised betting experiences tailored to the interests and preferences of individual customers, at scale.”
In this brave new world, in gambling as in many other aspects of a consumer’s interactions with commercial organisations, the personalisation that is now possible drills down to each individual user.
“One of the key things to remember is that each customer is different,” Hartmann points out. “They place different types of bets, they’re interested in a different range of sports, and are online at different times of day.”
The AI tools now being deployed “recognise this and engineer a bespoke sports betting experience based on individual interests and preferences,” Hartmann adds. “It’s completely unique and tailored to the individual user.”
Recognising the opportunity
The potential inherent in AI deployment at scale across the sector is already being recognised by the biggest operators in the space. To take one example, during DraftKings recent second quarter earnings call with analysts, CEO Jason Robins noted that AI is offering the opportunity to “do more with less”.
“I think that’s really the thematic,” he said. “We’ve been working on machine learning for a long time and base-level AI. I think some of the advances in what third-party tools are out there and available are really hitting inflection point in the last months.”
He noted that DraftKings was now using AI as a tool to help consumers in the creation of multiples, “really honing and optimising the marketing engine”.
As Hartmann says, AI-driven personalisation is used for front-end personalisation “whereby a customer sees content and betting markets of interest to them”.
As far as the operator is concerned, meanwhile, their CRM AI-driven personalisation and customer segmentation can “complement each other and have a positive impact on an operator’s customer engagement and retention rates”.
“For example, if we segment those players at risk of churn, operators can use our CRM solution to serve them a personalised bonus message to re-engage them. They’re more likely to engage with something that they’re interested in.”
When it comes to predictive personalisation, then, AI can anticipate customer needs and preferences before the customer even realises them. For example, it can automatically reorder consumable products or suggest timely services based on historical data.
“Now that the AI models exist, we can personalise every aspect of the customer journey”, Hartmann says.
“The use of AI personalisation technology is becoming more prevalent, and without it, operators won’t be able to differentiate their offering and risk getting left behind by the competition.”
In the future, AI personalisation will change the user interface with customers logging into a betting platform and, rather than seeing rafts of sports events, the AI will predict the type of bets that a customer wants to see. That is, the contents will be hyper-personalised, based on a customer’s previous betting activity.
Naturally, such processes will bring up issues around data privacy and algorithmic bias.
AI offers sports-betting operators a lot of new tools, but with these tools comes responsibility. To mitigate the dangers, it’s crucial to adopt ethical AI principles, invest in research and development, establish clear guidelines and regulations, promote transparency, and continuously monitor and evaluate AI systems for potential issues.
“Operators can incorporate AI-driven personalisation into their responsible gaming strategies,” says Hartmann.
He points out that the technology can detect whether a customer’s betting behaviour suddenly changes. For example, if a customer’s deposits increase, their bet frequency increases, or the amount wagered changes. The AI alerts the operator to this change in behaviour, and the operator can then take an appropriate course of action.
“What’s more, because the technology is scalable, it provides operators with a means of safeguarding all of their customers, which is a real strength,” he adds.