Learning from the Airlines
Most of us realize that complex algorithms are constantly changing the price of airline tickets and the availability of seats. We’ve accepted the reality and adopted some basic heuristics to adapt, like booking early or choosing the least desirable flights at ungodly times.
Or we pit machine against machine and use websites like Google Flights, Priceline, Kayak… The list is endless and we don’t need to know exactly how these sites work, just that it helps us find the best value given factors important to you at the time, such as flight date, time of day, and route. You may not realize that these options are given to you to let you make that value decision in real time, adjusting to what you are seeing. You don’t even realize that you yourself are the other half of the algorithm.
This capability enables the industry to serve all segments of the market across a spectrum of price elasticity: spontaneous travel -> planned vacation -> business travel. Data on Saturday We accept and interact with massive volumes of data and complex machine learning in our daily lives. But many don’t realize that when Saturday comes and it’s time to set aside the smartphone and grab your golf clubs and a bloody mary, data is right there with you – setting your greens fees, influencing your tee time and even your pairings.
Hakkōda recently sat down with PGA club pro Scott Heger in Charleston, SC for bloodys and a chat about how subtly the industry has adopted the use of data.
Scott is the Head Golf Professional at Ironwood Golf Club in Fishers, Indiana.
Hakkōda: Scott, it’s great to see you again! We love to combine golf and data.
Scott: It’s good to sit down with you guys. I’m glad you find this interesting. Golf is a sport but it’s also a business and an experience. Our players build long term relationships with their courses and teaching pros so it’s natural that we adopt data techniques to deliver the best experience possible.
Hakkōda: We find this interesting because these rounds are mostly an escape from the hustle of the week. It’s a time to catch up, some friendly competition and be away from our laptops.
But before we get to greens fees and tee times, I guess we have to recognize that the use of data is really all over the course these days.
Scott: It really is. It started with rangefinders and GPS on the course and in teaching we use pretty sophisticated cameras and telemetry to measure arm speed, club head speed, ball spin, approach angle and a number of other factors. It’s important not to get overwhelmed with data. Instrumentation of the sport has been a game changer but you still have to translate that to ‘feel’. We use the data to train muscle memory and program what ‘feel’ is most effective on the course.
Hakkōda: Let’s dig into why we sat down today. You and your club are using some pretty sophisticated programs to set greens fees. What can you tell us about that?
Scott: Like most things, greens fees started off simple. One price. Then it evolved to prices determined by day of week and time of year. That worked fine for years. But many other factors influence demand and as more and more of these other data points moved digital, we started to incorporate them into setting pricing.
Hakkōda: What other data elements factor into greens fees?
Scott: Pricing calculations combine 15 different variables each time we update the rates which happens every 15 minutes. That’s 96 updates per day and 672 per week. Examples include: Weather by hour, Conversion Rate, Utilization Rate, RevPatt (Revenue Per Available Tee Time)
APR (Average Rate Per Round), Competitor Rates, Trade Liquidation, Website Analytics.
RevTech Plus is the software we use and essentially it’s a revenue management software that uses real time data that predicts consumer behavior at the micro-market level. The primary goal is to maximize revenue growth by selling the right product to the right customer at the right time for the right price. Hakkōda: And how does all that data get used to set the price for any given customer.
Scott: I didn’t write the software, I’m the Head Pro not Head Programmer but as you can imagine it’s adjusting the price based on historical patterns and live demand analysis.
Hakkōda: So it’s optimizing price with demand.
Scott: That sounds right, but think of it this way, it’s matching the price to the value. Demand is setting the value. So rather than one price that at times is overvalued and othes undervalue, it’s matching that and letting the players participate in that – just like airline tickets.
Hakkōda: How much can prices vary?
Scott: Probably not as much as airline tickets. Price differences can be from a few dollars to 20-30% plus or minus typically.
Hakkōda: So a twosome paired with me and my partner can be paying a different price? Maybe $10 less?
Scott: Very likely. And the tee times in front of you and in back of you are likely different as well. We aren’t talking about massive differences.
Hakkoda: So for example, a micro, Indy area event might change prices as a whole, but on any given weekend it could vary more by tee time?
Scott: Exactly. Let’s say it’s the week of the Indy 500 and there is lots of demand in the area due to spring fever, race week, etc. That might push up prices 20-30% for everyone that week. But on a Sunday morning two players who get paired up in a foursome might pay less if they booked a few hours later than their playing partners.
Hakkōda: Scott, thank you for sitting down with us.
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