While Artificial Intelligence (AI) and Machine Learning (ML) are often used interchangeably, they are two distinct terms. It is true that AI and ML are closely related, but the distinction is important.

Artificial Intelligence (AI)

Artificial Intelligence is when machines make decisions by mimicking the cognitive functions of human intelligence. The aim is for a machine to perform complex tasks like a human would. Logic and decision trees allow the machine to learn, reason, and correct itself autonomously.

Examples include a machine being able to understand and interact with language, both spoken and written. Being able to analyze data and make recommendations is another key aspect of Artificial Intelligence.

Machine Learning (ML)

Machine Learning is a part of Artificial Intelligence. It relates to the ability of a machine to learn from experience and improve as a result. Contrary to explicit programming, machine learning utilizes algorithms to study large volumes of data. This is then used to make informed decisions based on statistical models.

The more data the algorithm has, the more it improves. This means machine learning tends to get better over time. However, the quality of the data is important as it must be structured in some way rather than being random.

Artificial Intelligence vs Machine Learning

In essence, Artificial Intelligence is the overriding concept of a machine being able to sense, act, reason and change like a human would.

Machine Learning is a subset of Artificial Intelligence. It is the autonomous learning by a machine based on the data it has extracted. Note that Machine Learning does not mimic human intelligence, its sole aim is to provide increasingly accurate output when performing a specific task based on the data it has analyzed.

Note that other things such as natural language processing and deep learning fall under the umbrella of Artificial Intelligence but these are not considered Machine Learning.

How Do Operators Use AI and ML?

One of the key uses for Machine Learning is in marketing as there is plenty of data to be analyzed. Let’s go through this from the perspective of a casino.

When a player signs up for a casino, there is already a certain amount of contextual data available to the operator. This includes browser, device and geolocation information. This data can be used to promote games that have been historically popular with players in that location and using that specific device and browser.

Of course, this is all quite vague.

However, as a customer starts to play, more data becomes available. This includes things like average balance, average deposit amounts, regularity of deposits, average bet amounts, the type of games played, and when those games are played. All of this helps build up a player profile and allows for more tailored recommendations.

These recommendations can come in the lobby, on the site, or in the marketing funnel. As the player journey continues, the lobby can be adapted based on their preferences. Furthermore, how and when a casino markets to a player can also be amended based on what they like and when they like to play.

This data can get very granular. For example, you can send a push notification at a particular time of day on a particular day of the week for a specific casino game that you think would be most attractive to that individual customer. Statistically, as you are offering a tailored recommendation at the right time, you are more likely to engage with that player.

This means you can use AI as a key plank of your retention strategy. You can encourage regular players to keep playing or to intice lapsed players back to your casino.

Conclusion

It is clear that machine learning can be a game changer when it comes to marketing as it provides a tailored experience for each player. As the process is automated, there is no manual cost to doing this. Furthermore, these experiences can be altered to favor a casino’s KPIs, bottom line, and costs as well as other parameters.

In a crowded marketplace where things have never been so competitive, it is clear that AI and specifically machine learning can be used to provide more engaging and personalized experiences. This can be crucial for making your marketing spend go further. It can also help boost your profits and help your casino to stand out from the crowd.