There's a number of psychological phenomena that come into play with a gambler. One, called the Gambler's Fallacy is the false belief that if there's a streak of some sort, say in roulette the ball lands on red five times in a row, then next time has a better chance of landing on black. It doesn’t. The same fallacy holds for slot players who migrate to a machine that hasn’t hit in a while hoping that payout is imminent. It’s not. Many gamblers also subscribed to various, and sometimes crazy, superstitions. Often when a player gets a decent slot pull they’ll try and repeat what they did right before the bet. If they coughed and took a sip of their drink, they’ll turn that into a ritual and repeat the pattern before each pull. Crazy but common. I can go on with some of the wildly interesting and weird things I’ve seen, but the point is that those who gamble (a little or a lot) tend to manufacture hopeful outcomes and scenarios so as to justify continued betting. Of course, a marketer for a casino tries to accomplish getting players in the door and increasing coin-in from every player. However, the very nature of a gambler puts the bigger onus on the former, getting them in the door, as the psychology helps with the latter. The fact being that once a gambler is in the door the odds are they’ll gamble. Over 60% of the US population gambles. So, the bigger challenge is getting them in the door. That brings us to our story of getting new players to visit the two casinos where I managed the marketing and promotions. Casinos have amazing data from a few sources. One is the player’s clubs that almost every casino offers and the second is from ATM machines. Basically, Players Club data lets us know all contact and geographical information, all coin-in data, dates, and more. ATM data shares who withdrew or took credit advances and how much (they don’t need to be Players Club members) along with some geographical data. There’s much that can extrapolate from this data. So how did we get record numbers of new visitors and increased revenue? A bit over-simplified, but we first created a grading system to identify different levels of play that incorporated data such as zip code, age, coin-in, frequency, and other points. Since this was Players Club data we weren’t targeting them as new - because they’re already players. But, we used it to build personas highlighting who we should target. (Some sharp-eyed casino enthusiasts might be thinking “wait, doesn’t the different levels of Players Club status already do this?” Yes, but it’s flawed by being incomplete and yet treated as accurate.) We took these highly defined targets, cross-checked them with cash withdrawal data, and created direct mail lists segmented with targeted offers matching different personas - resulting in many different versions of content being sent out, but that resonated and was fitting with each recipient’s potential spend. Normally, and without too much data analysis, I could determine that a specific zip code, on average, offers $300 casino win while another zip code may average $35 casino win based just on players club data. This cursory data is all well and good but it’s lacking sophistication and missing huge factors such as on player data, highlighting the differences within zip codes such as age, sex, and micro-targeting via nine-digit zip code data (Zip+4 averages just a handful of homes and allows for micro-geo-targeting.) The result was direct mail with granular targeting that matched a fitting incentive to a highly segmented audience and brought in thousands of additional non-players club members each month. Additionally, on average, this converted over 500 new members per month. Lessons learned:
At the time digital printing was available and would have allowed us to do even more granular targeting with even greater targeted messaging, but for the sake of cost and initial setup time, I didn’t segment as deep as I could and should have. Once we tasted the success we lost our drive to change or test the formula for greater returns.
What can you do today:
Send out a survey and learn about your customers.
Then dive into data analysis with the goal of creating defined personas of your customers. Now you can laser focus your next campaigns and messaging to be dead on to your audience(s).