How data science can fuel safer gambling strategy

Gambling companies are now being encouraged to take care of their players, promote safe gambling and curb addictive behaviours. The ultimate target is to foster healthy gambling habits to create a sustainable business and improve player retention.

Promoting safe gambling sounds simple, but how do gambling companies actually accomplish this? Let’s start with the tools operators have for accomplishing this task, primarily customer data. In compliance with KYC and AML regulations, gambling companies store identity and financial information of gamers. Add data collected for customer engagement and retention, and the customer’s image becomes complete.

Data science techniques can turn the data collected by gambling operators into powerful tools by creating a better understanding of what drives problem gambling and how to get players back down to safer levels.

Here is what you can derive from your data using data science analytic methods.

Determine indicators of problem gaming

A good place to start would be to find patterns in the behaviour of customers who tend to get into trouble, especially considering the impact of the Covid-19 pandemic on everyday life and on not only physical health but mental health.

One specific circumstance is the substantial change in the gambling market itself, as basically all sports betting events disappeared for a significant period of time earlier in the year. For example, in the UK, search trends suggest that when the lockdown started, people began to play online slots more often.

Having vast data sets means online gambling operators are fully equipped to find explicit and hidden dependencies that lead to risky behaviour in play.

Impose safeguards for at-risk players

Of course, there are various tools available that allow players to set limits on the amount they spend and their duration of play. Players can also have themselves excluded from a game and corresponding advertising and lock their accounts for a certain period of time.

But we should not forget the human factor. Due to continuing lockdowns and the second wave of Covid-19, people may even feel more depressed, isolated or experience more financial distress. Bearing this in mind and with the indicators of other problems at hand, we can build extensive safeguard systems utilising data science-based predictive modelling.

In brief, the online gambling safeguard systems can detect signs of risky behaviour at early stages and impose time or financial limitations to keep gambling as a harmless leisure activity.

Create game design to prevent harm

We have established research and development (R&D) centres to produce truly innovative software. What we’ve learned is that data science R&D results in extremely efficient solutions in many domains. We are sure that with proper R&D applied to online gambling, warnings and controls infused into game design will allow players to effectively manage their gambling online and enable operators to support a lifelong customer.

Get all-round reporting

Just as important as introducing interventions is to know what is going on with your customer. All the data at an operator’s disposal can be turned into hundreds of valuable reports on everything you ever wanted to know about your players.

An all-round reporting tool generates the reports you need for marketing, planning, regulatory compliance and more.

The output of data science applied in online gambling

Data science provides paths for smarter customer care through efficient measures against problem gambling, better understanding of risky behaviour in online gaming, intelligent game design created to protect customers and all-round reporting to fuel all gambling operator activities.

Operators primed to protect their business understand that healthy and sustainable online gambling behaviour means supporting and gaining lifelong customers, with data science the magic pill.

Ukraine-based Natalya Zheltukhina has worked in IT for more than 15 years with extensive experience in various industries. She is head of e-learning growth at Sigma Software Group, having worked for the provider since 2016.