By Harvey Silverman, Silverback Golf Marketing
How is it that 25 and more years ago, golf courses filled their paper tee sheets daily, and the only “data” they had was what the cash register spit out at the end of the day for reconciliation? True, there were more golfers and fewer places to play. But still, simple local awareness produced lots of toes on the tees.
I’ve watched my last webinar and education session and read my last white paper about Big Data and Business Intelligence for golf courses. Instead, I went to a data profiling company I’ve used for years. “Big data” is their business, and I wanted to learn how it might apply to golf courses. (A mutual non-disclosure agreement prevents me from revealing the company’s name, but I can direct you to them if I’ve piqued your interest after reading this article.)
The first thing said to me was, “Keep It Simple,” keeping out what typically the last “S” stands for. But let’s change that to “Keep It Satisfyingly Simple,” meaning let’s determine the most manageable data to assemble that provides the best bang for the buck.
One recent white paper defined business intelligence as “a set of dozens, if not hundreds of reports that take your data and aggregate it into meaningful insights.” Can you tell me what you’d do with a report that details “occupancy by spending habit over time”? How long in your busy day would you have to study such a report and understand the many nuances, strategize a plan, and act upon it, along with the dozens or hundreds of others?
That isn’t KISS; that’s “make my eyes cross and never see my family again because I have all these reports to digest and act upon” that might make my business more successful. Or, MMECANSMFABIHATRTDAAU.
Golf point-of-sale systems have become more responsive to the data needs of golf course operators. It’s easier than ever to identify customers who haven’t returned in 30/60/90 days or this decade or century. Or find those new to the franchise. Or easily display the top 100 spenders. Or who bought Titleist balls.
Along with “big data” like this might come smart automated messaging based on customer type and behavior. These and others are the rudimentary elements that make a business more intelligent and better. But do they meet the high bar of “big data?”
To be more fine-tuned and maybe launch an effective customer acquisition campaign, you could use “big data” help. It will cost you a few bucks. Like most other things, the ROI will depend solely on your ability to craft the programs and messaging that fits the type of customer you hope to attract. I’m talking just regular daily fee golf here, not weddings, banquets, and outings – although data is available to help with those too. The question to ask yourself is, “How much are you willing to spend to accomplish your goals while keeping it simple?”
I sent a client’s customer database (with permission) to the data profiling company. Let’s call it a “Database Physical” as we dive deep to examine the database’s health and see what else we can learn and what’s not helpful. My client does a good job of harvesting the basics: first name, last name, email address, phone number, and zip code. (Note – if your PoS system inserts first and last names in a single cell, tell them to stop it or find one that doesn’t.) Expecting the golf shop staff to ask for more is intrusive to the customer, time-consuming, and violates our KISS principle.
Like most physicals, we start with the heartbeat – how healthy is the customer email database? The data-profiling company will test the database and eliminate non-responsive email addresses – the ones you send to that bounce over and over. A clean database will improve your inbox deliverability.
Next, we’ll attempt to fill in the blanks in the email field by matching name, phone, and/or postal address compared to an existing and active email in the data profiler’s data warehouse. It’s called “email append.” For far less than a dollar each, you’ll have supplemented your current database and be able to communicate with customers who have already visited, transacted, and know who you are.
The data-profiling company matches customer data within their vast data warehouse of consumer data. Everyone in that warehouse is “third-party opt-ins.” That is, people who have knowingly or sometimes unwittingly agreed to have their data shared with “trusted partners” when they register on a website, or make online purchases, or respond to an email or social media offer.
So now we’ve cleaned your database and appended it to bolster your customer communication capabilities. Your database is healthier but might need a transfusion like a customer acquisition campaign. The data profiler can “clone” your database and find others who look like your current customers across critical metrics like age, gender, occupation, and income – all things you don’t have now. And they have an interest in golf.
Here are a few things we learned in the Database Physical performed on my client’s database:
- Two-thirds of the customers reside in the course’s home state. We thought it was all local. Should the course look at targeted ads in the most popular other states?
- The gender mix is 80% male, 20% female. That’s relatively consistent with the national golf mix. But just 53% are married. Is there an opportunity to create a program for married couples and also singles?
- 85% of those married have children present in the household. It seems like a fertile group to promote junior and family golf.
- 23% are age 55-64. It is a critical data point as the course discusses raising its senior age to 65 and eliminating senior weekend rates. 23% is a sizeable group that might require some tender loving care when learning their senior status is diminished.
- 34% have household incomes of $150K and up. Are these the best candidates for memberships? And we can further prequalify potential membership candidates by knowing their credit score.
- If finding ways to fill late afternoon tee times is a priority, maybe we want to know the 13% of customers who are “trades” people. You know, plumbers, carpenters, electricians, etc. They typically work early in the morning and are off by 3:00 or 4:00, so prime candidates for those late day times or leagues.
- Reinforcing the rule of never promoting a political issue in your customer communications is that the “political affinity” breakdown is nearly evenly split 1/3-1/3-1/3 Democrat, Republican, and Independent, respectively (the course is in a blue state). Meaning, you’re likely to piss off up to 2/3 of your customers with any misplaced or mistimed political innuendos. You should know this already, and the proof is in the big data.
The findings listed above are elementary “big data” points to sophisticated marketers. I’ve left out things like “Anglers Lifestyle Segments” (it’s not about fishing), intent behaviors, modeling of cluster audiences, and other elements that stray from our Keep It Satisfyingly Simple standard.
If you think a “Database Physical” is a good idea for your business, let me know, and I’ll point you in the right direction. You can craft your own program, and the data profiler will rent you contact lists based upon segment selections such as those listed above. It’s probably as “big” as you need to be.
Harvey Silverman is the proprietor of his marketing consultancy, Silverback Golf Marketing, and the co-founder of Quick.golf, golf’s only pay-by-hole app. Harvey authored NGCOA’s “Beware of Barter” guide and has spoken at their Golf Business Conferences and Golf Business TechCon.