Often, when we’re caught in the middle of a compelling gaming experience, we might find that our judgment is impaired. We might make decisions that, if we were to pause and reflect, we would probably reconsider.
There’s nothing inherently wrong with this. When users visit a casino, they’re looking to immerse themselves in possibilities. Having a good time is the primary objective; making money is a distant second.
But sometimes, it’s a good idea for a casino operator to politely tap their clients on the shoulder, and to ask whether a given course of action is really sensible. In some cases, it might be appropriate to seek help. Through behavioural data, the right machine learning algorithm, and real-time alerts, operators have a means of intervening.
What are real-time alerts?
A real-time alert is a notification that appears on the screen of a given player, interrupting the action in the middle of a game. It might be triggered by a specific problem behaviour, such as a spike in deposits, or an unusually long session.
This helps to generate some distance between the game and the player, and for the latter to reconsider their choices. For a good example of how this works in practice, we might look at the casino online at MrQ, which uses prompts and reminders to empower users to stay in control of their experience.
How alerts support safer play
You might suppose that alerting the player in the middle of the action would feel intrusive. And this is sometimes the case. But that’s part of the point. What’s more, the moment of intervention might not always occur when the gameplay is actually unfolding, but during other parts of the experience, like the point at which funds are being deposited.
Through the right alerts, we might prompt the user not only to reconsider their actions, but to get into the habit of reflecting on their relationship with gambling more broadly. They might end up setting their own alerts, with the help of time trackers and ‘reality check’ functions.
The technology behind real alerts
It’s easy to set up an alert whenever an arbitrary threshold is crossed. This might, for example, be a specific quantity of money deposited, or a specific amount of time played.
But increasingly, we can be more subtle and exacting about when we intervene. By looking for patterns in deposits and gameplay, and using machine learning to analyse the data of specific players, and countless others who share the same attributes and preferences, we can often intervene much earlier, and more effectively.
Impact on players
When players benefit from alerts, they’re more likely to set limits for themselves, and to avoid harmful practices and behaviours. As the technology evolves, we’re likely to see it become even more specific and targeted – and we might see regulators demand it be used more often.
