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Andrew Cardno

Founder and Chief Technology Officer, VizExplorer

Andrew Cardno

It’s not a stretch to call Andrew Cardno a “visionary” for the gaming industry. Cardno was one of the first to realize the possibility for data that casinos have collected for a couple of decades now. He says the depth of this information makes the gaming industry a leader in the data analytics field. As chief technology officer and founder of VizExplorer, Cardno has created many different programs and platforms the casinos can use to improve their fiscal performance on the gaming floor. He spoke to GGB Publisher Roger Gros from his offices in San Diego in March.

GGB: For many years, casinos were very in touch with their players. They knew who their players were, they had VIP and casino hosts, and direct mail that was very successful. But a lot has changed over the past decade. How do analytics help in knowing the player?

Andrew Cardno: The way the industry has adapted to analytics is something that we all should be proud of. We’re a leading industry in analytics. It always brings me back to one of my good friends, a GM at a casino in Tunica, who told me that we’re like this collection of small businesses. We’ve got food and beverage, we’ve got hotel, of course we’ve got gaming, and we’ve got different kinds of gaming. And that drives a need to be able to be fully informed about our customers.

The industry has a greater need to bring data together in real time than any other industry I know of. If you don’t have a complete picture of your player, you’re not giving that customer the right kind of service.

Tell us about how VizExplorer came to be. What was the inspiration?

When I founded the company, I set out with a goal of never having to build another data warehouse again, and it’s a bit of a joke, because it’s what I was doing for many years.

But to leverage the technology platforms that are out there, to bring together all the data in real time, we developed our integration hub that allows that data to come together and to be used to its greatest gaming optimization. So, we used the data infrastructure we put in place, for this one application. We proved the value of having that real-time data, of having all the data about gaming machines, so I could understand what games people like. Or, how are my preferences for games changing?

We just solved one of the hardest questions that I’ve worked on in gaming, which is: If I bring a new game onto the floor, taking out participation and all the other costs associated with it, what is the incremental revenue from that game—how much of it is truly incremental to the casino? We’ve solved the math behind that, and we’re really proud of it.

Do you provide any information to help casinos make those decisions about what slots to add or remove and where to place the machines on the floor?

Absolutely. At one point, I won a Smithsonian Laureate for Heroism in Information Technology for slot floor optimization. And that was even before I understood how important the customer was. We kind of have this joke at VizExplorer, in the data science team, that we keep learning new math models, and then inventing even better ones through replacement, but at the core of understanding how to do that is the customer. So, we used to analyze gaming machines based on theoretical win per day, or actual win per day, or handle pulls, or some other metric that was a measure of the performance of the game. And it worked really well. But we were mostly under-supplied and there was plenty of opportunity for growth in the industry. It wasn’t that difficult.

So, what changed?

Well, in today’s world, we’re mostly over-supplied. So, no longer can you optimize your games in that way; it just doesn’t work. Just think about the simple example of the high-limit room; it just doesn’t work to add more games in the high-limit room.

So, you need to look at the floor through a different lens. And the lens that we bring forth is the lens of the customer. We do a market-basket analysis. We have an issued patent on preference filters, for analyzing the market basket in the casino. It’s one of the hardest math problems we’ve solved. So now, irrespective of the performance of the game, I’m looking at what I need to do to make my customers get the experience they need to get. So, I’m optimizing the customer experience. Very different math models. We’ve been really successful with that.

It’s completely flipping analytics on its head. This is something slightly provocative, but I don’t really care about the slot win-per-day metrics. We need to focus on optimizing the customer experience, that every customer gets the games they need, so it can fill out all those market baskets and optimize all those market baskets on the floor. And just to defend that a little bit, because I know some people might be a little bit agitated by me saying that, just think about video poker. It’s not the greatest-performing game on the floor, but it would be unthinkable to remove it, especially in Las Vegas. You just couldn’t remove it, because you would lose those customers.

So, you have to work really hard on optimizing your video poker games, and then you go to your video reel, and your video slot, and your different types of games. It completely changes the way you look at a gaming floor, and we’ve got a deep track record of doing that.

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