Rise of the machines

Driven by data, dominance in the egaming sector is a case of who can crunch information in real-time and provide the best possible experience for their customers.

Industry leaders are becoming increasingly familiar with the importance of harnessing machine learning and predictive data analytics to stay ahead of the competition. In the future, it’s safe to say machine learning will be widely integrated into these systems, with a growing focus on deep learning or artificial intelligence, and how it can impact a business’ bottom line.

Playing catch up

The massive volumes of structured (transactional), semi-structured (clickstream) and unstructured (social media) data available to egaming companies gives organisations a great opportunity to deliver qualitative value and gain a competitive advantage. However, machine learning and predictive data analytics are still not being utilised to their full potential.

‘Risk areas’ are one common example. The standard response from the industry is to close or restrict the accounts of punters who they perceive to be a risk, or in other words, those who win big money in the early stages of their customer cycle. This is mainly because they don’t know what the long-term outcome of that player will be.

The industry is over-zealous and protective when it comes to risk largely because it’s hard to predict, with any great certainty, what the long-term risk of a new customer is. Targeting players with relevant offers is another area where predictive analytics is not being utilised as it should be.

Scientific learnings

Sportsbook companies must create a bespoke, tailored approach to ensure the best customer experience and to stay competitive. They can best achieve this through integrating predictive data analytics and machine learning into the sportsbook technology framework.

What will really separate the wheat from the chaff is those forward-thinking firms who find a way of integrating real-time information into their data environment quickly. Consider employing data scientists who truly understand the data and can work to use the technology that will facilitate data movement in real-time. This dedicated team of data engineers fundamentally need to understand the commercial benefits of the data that can be harvested.

Only when more data scientists are employed within the industry will there be potential to integrate neural machine learning into gaming. The training sets that can be used when it comes to data are getting bigger and bigger, providing more data than ever before, and the machine learning algorithms are ultimately there to fulfil a company’s requirements. The more data you have, the more statistical accuracy and relevance can be generated, in turn providing more commercial value.

Put your money on AI

Currently, we are using machine learning to optimise the interactions between our customers and our product. Through feeding every action and reaction into a series of models we can fine-tune our offerings to be both appealing and effective, while creating an initial picture of individual preferences.

We can gauge an ever-increasing understanding of each customer and their needs across all channels through ongoing analysis of customers’ profiles. Having an all-inclusive view of not just another player but a real person enables us to manage communication on a personal level; tailoring markets and content with offers, designed to meet the customer’s individual needs.

Technology-wise, we have deliberately created an agnostic system, which allows us to adapt and use our data environment sensibly. From storage to the ability to have huge data sets which don’t negatively impact performance, we have data at the heart of the business.

Looking to the future, harnessing the latest technological innovations such as neural machine learning will be essential to making sure the customer always has the best possible experience and can focus on the most important thing above all else – the bet.