As casinos expand their vision by building special palaces—from state-of-the-art entertainment venues to upscale restaurants and convention areas—they relish the assessment prowess of Big Data.
This tool serves as advanced information, with two characteristics. It is available to those willing to pay for it, and most useful to those who can discern it. Big Data targets optimal hotel-room price-points, the appropriate range for comps or a snapshot of a gambler’s loyalty tier. It removes or reduces guesswork in a time-crunched industry. Millions of dollars can ride on making the right deal to the right audience mere seconds ahead of a rival.
The companies who serve operators know the role of actionable intelligence. Agilysys, Duetto, Rainmaker and VizExplorer are among gaming’s data stalwarts. While their products vary, collectively they enable casinos to make snap, accurate decisions.
The outfits enjoyed a strong 2016, watching the data world blossom. As the market expands, they have something valuable for operators.
“Big Data will be used to create a ‘smart casino,’” says Dr. Ralph Thomas, chief data scientist and general manager, gaming division, for VizExplorer. “Operators will be able to differentiate the entertainment experience they offer guests through the optimization of their slot floors to the players that matter, and will be able to drive meaningful interactions with players by enabling their hosts with sales intelligence, customize the offers, and respond to events on the slot floor in real time with the use of data to drive player engagement and loyalty.”
Once the data materializes, operators fashion a creative interpretation plan, according to Marco Benvenuti, co-founder and chief analytics and product officer at Duetto.
“What makes all this data actionable for casinos are deep integrations across the properties’ entire tech stack,” he says. “The better that a casino’s property management system talks to its CRM and revenue management system, the better that casino is able to take its valuations of guests—gaming and non-gaming customers alike—and develop a profitable strategy for reinvestment and direct marketing.
“Integrated systems optimize casino profitability by identifying high-value guests and getting them to the property at the ideal reinvestment rate, according to demand for any booking date.”
Robert Shecterle, director of marketing for Agilysys, acknowledges data’s emerging force.
“Casinos already rely on Big Data to help drive revenue today, and this trend is growing at light speed,” he asserts. “Data is leveraged to build a competitive advantage at some of the largest operations across the globe. Operators will have to embrace Big Data to remain competitive in their markets.
“The information will provide answers to questions like ‘What’s the value of a particular guest or guest segment?,’ ‘Which guests are most and least likely to respond to an offer?,’ and ‘What is the ratio of gaming to non-gaming spend by guest segment?’ These are all very important questions that can be easily answered with data analytics.
“Big Data provides, in detail view, the alternative places where guests are spending their dollars, enabling operators to better accommodate shifts in revenue opportunities and guest expectations.”
This information has enormous value if multiplied. Rainmaker has made groups a focal point of product strategy, according to Angie Dobney, its vice president of pricing and revenue management services.
“Groups are one of the most significant sources of non-gaming customers, and this is an area where Big Data is starting to make a big difference,” Dobney indicates. “There are multiple providers of data that tell group hotels about the relative quality and behavior of groups. We partnered with clients at an event this this year to bring their lead-scoring data into our group revenue management process.
“In addition to the information about group business, the behavior of groups is an area where Big Data is changing the game. Imagine if you had historical information about a particular group. If you knew, for example, how many rooms washed from the group block between the booking date and the arrival date, that could enable the hotel to refine its forecasts.”