Since being founded by Gary Ellis and Gary Larkin in 2021, Koin has built a reputation for innovation in entertainment and lifestyle payments, with a focus on meeting the demands of highly-regulated retail and online gaming markets.
In keeping with Koin’s strategy of continually pursuing data-driven growth ambitions, this summer the company named Hemash Bhatti to the newly-formed position Head of Data Strategy & AI.
Hemash brings over 15 years of experience building data and analytics programs for Fortune 500 companies, work that required scaling solutions in highly regulated and complex environments.
He emphasizes that meaningful, structured data is the foundation to successful AI, and how AI can transform raw data into real-time engagement, helping operators personalize experiences and offers, while growing loyalty beyond the casino floor.
“AI risks being a ‘buzzword’ these days because of how it is being applied in diverse ways,” he suggests. “There are misconceptions about what it is and exactly how it applies. AI is only as strong as the data foundation beneath it. We operate in an industry that is rich in data but poor at applying it.”
Hemash observed that while operators and other industries are investing heavily into applications in many different touchpoints, reports such as those from Gartner indicate up to 80 percent of AI initiatives are failing primarily because of poor data.
“We have access on the operator side to a wealth of data that ends up being siloed and disconnected,” he explained. “Important data on customers and players that is not brought together in a meaningful way. Building a strong data foundation is essential for AI applications to succeed. It is important to develop a comprehensive and consistent unified view of our customers and players.
“From a business perspective, there are significant cost implications to bad data. If we must go back and fix the data, which is common, it can cost five to ten times more than if it was done right in the first place.”
Hemash emphasizes that applying data effectively requires both strategic perspective and technical execution, saying “it may require taking a higher view of our customers and players to identify the signals they are showcasing to us”.
“The result will reveal opportunities that will allow for us to create experiences that feel personal and relevant,” he continued. “AI is a tool that can be used, but it is not always the right tool. There are small iterative changes that we can start with in terms of our people, platforms, and processes. No approach will achieve success or scalability unless it is built upon a strategic understanding of our customers. The data must be ‘un-siloed’ in a meaningful way.”
Hemash recognizes that operators develop strict, rule-based loyalty programs. They know when individual customers are on property, but the ability to hold them and sustain their loyalty fades once they leave the gaming floor. The challenge is how can AI be leveraged to create more meaningful engagement.
“We know that we want to be more aspirational in developing rich and engaging experiences for customers and players,” he said. “This is accomplished through leveraging loyalty apps, website experiences, or any outreach media. We also know that most organizations are striving toward omni-channel experiences or even channel-less experiences.
“When we bring together explicit data, like loyalty sign-ups or stated preferences, with implicit signals, such as booking a room or attending a concert, we can create enriched profiles of each guest. That allows us to deliver engagement that feels relevant both on-site and off-property.”
Building on that, Hemash points out that the real challenge for operators is acting on those signals. “Once we know a guest has booked a room or is attending a concert, the next step is intelligently grouping them into meaningful segments and matching them with the right offers,” he explained.
He believes that the next question should be: “How can we provide them with a richer experience while they are here, and, looking at their previous engagements, to anticipate how to make their experiences more relevant and rewarding from the moment they begin?”
“Having a solid view of our customers and a strong data foundation in which we are able to identify them across their journey is part of the challenge,” Hemash continued. “This enables the reduction of data debt that occurs and enables us to reuse this data across multiple AI applications, driving a higher ROI.”
Hemash acknowledged that retention is a top priority for every operator and pointed to the long-tail of AI use cases as an area of major opportunity.
“When these applications are built on clean data, even a one or two percent improvement in areas like promotion response or churn reduction, can translate into millions of dollars in added revenue or efficiency,” he said. “And when you stack dozens of those small improvements together, the cumulative impact is transformational.”
Hemash emphasized, “It is important for any organization to take a moment to step back and intentionally look at everyday business activities, but more importantly to act on how to move beyond that. How we can ensure that our approach is data-driven and that we are leveraging the right tools, like AI, when they are suitable for our use cases.
“AI will be transformative for gaming, but the transformation should feel seamless in how it is implemented and unmistakable in the outcomes it delivers.”
