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Entering a new era is all well and good - The Economist famously described data as “the new oil” - but the simple act of gathering data isn’t enough. It’s an excellent starting point, but it’s unlikely to be useful without a degree of lateral thinking and careful planning. What business decisions in your leisure centres might be made differently by properly activating data?
Do you weaponise your data properly?
Well, activity history can be analysed using machine learning algorithms to predict viability of new classes and increase profitability. Basic visitor data can be used to help determine staffing levels required to maximise efficiency without impacting customer experience. Usage data from gym equipment can guide future upgrade decisions. However, this is all fairly low-level, basic stuff. What happens when you ask your data more interesting questions? What happens when you layer and stack data to show different things? What metrics would you need to combine, or start to measure, in order to assign a quantified member cancellation prediction score to every customer in your database?
Think of the interactions that take place in a typical leisure centre during one visit, and the possible data points you could choose to collect. Collecting the data needn’t be onerous, either.
Consider this scenario:
A customer drives up to your gym, and an ANPR reader reads their numberplate and automatically opens the barrier for them, flagging their arrival at reception so the welcome team can greet them by name as they walk in. All they need to do is swipe their mobile phone with an RFID sticker through the barrier, and then slip on a wristband to gain access to the changing rooms, use the lockers, sign in to different machines to track workouts, and then buy themselves a drink afterwards.
All of a sudden, through data, you’re able to ask really interesting questions. How many staff members greet that customer? How long does that customer spend in the changing rooms - are they overcrowded? Does that customer have a tightly defined workout routine, or do they wander around and use lots of different equipment? Do they buy an energy drink from the vending machine? Do they log onto your WiFi and get some work done afterwards in the cafe? All of this and more can be tracked, logged, queried and analysed.
Data is a modern marketer’s dream. You’re able to predict take-up of new product offerings, and slice and segment your customers in really intelligent ways to identify upsell opportunities. What about offering the mother-of-two who works out at 6:30am every day places for the tennis academy over the school holiday, and pre-register her children because they used to have swimming lessons with you? You can have RFID wristbands ready for the kids at reception when she’s next in. Or texting the Friday night 5-a-side league with a free beer in the bar at one of your World Cup screenings next month?
This open access to data is already opening up new opportunities and partnerships - even within the leisure industry. Think of Virgin Active and Vitality health insurance. Their tie-up means that Vitality get visibility over customers’ activity history at Virgin gyms, and they use that to provide customers with a sophisticated bonus scheme for maintaining a healthy lifestyle.
On a slightly more altruistic note, imagine a similar scheme that allowed an NHS doctor to monitor patients’ activity levels - leisure centres could be ranked locally in terms of effectiveness against health outcomes and given greater subsidy or win more members as a result, with concrete, reliable data to back that up. Watch case study from EveryoneActive using Gladstone Health.
What’s holding you back from using your data?
There are often a couple of issues that hold leisure operators back from making full, or best, use of their data. Firstly, in a typical modern leisure centre, there are endless different sources of data - as we’ve discussed above. This is great news from a data-gathering perspective, but the problem encountered is in trying to bring it all together. Integrated business insight dashboards pulling in live data from equipment out on the floor, booking stats from leisure management systems and customer satisfaction scores can seem a far-flung utopian dream. It’s too much to expect leisure centre managers to perform complex data science analytics as well as their day jobs.
The second problem is data integrity, and whilst this doesn’t necessarily apply as universally as the first, it is in many ways more serious. If you’ve got to a stage in the business where you’re already making data-driven decisions, it’s really important that the data used to make those decisions is trustworthy and infallible. This means that your data-gathering, analysis and reporting should be done automatically, avoiding human error from manual report compilation, and ensures that even across multiple sites, everyone is using the same formulae to calculate key metrics. Beyond the increased trust, automated reporting saves significant staff costs. Consider auditing your processes and investigate how reliable your data is.
It’s worth having a think
It’s important to remember that gathering data from your Leisure Management Software for its own sake isn’t going to get you anywhere. Like anything in business, you need a well-thought out strategy. When you’re considering what to measure, it might be helpful to start backwards: what are the biggest questions you’re trying to answer, or what challenges is your leisure operation facing? Try and work out what data would help you answer those questions and confront those problems, and lastly - figure out how to measure that.
The leisure industry hasn’t been at the cutting edge of innovation where data science is concerned. Consider the retail sector: it’s dominated by a handful of big brands who can afford to invest the resources into proper data-gathering, analysts and data scientists, as well as a long-held recognition across the sector that unlocking data can yield incredibly valuable insights. Think of the Nectar card scheme, the My Waitrose card or the Tesco ClubCard. These schemes aren’t about corporate brands wanting to give back to their customers: they’re a powerful vehicle to unlock customer preference data.
Don’t lose hope just yet
However, all need not be lost: Gladstone’s eyeQ query builder & business intelligence tools help do just that. For Gladstone customers, it integrates straight into the platforms you’re already using, and we’re looking at partner integrations and the ability to feed in data from third-party sources to provide a holistic view of your operations.
Guy Bickerton, head of Data Services at Gladstone, says:
“If it’s stored in your system, we will be able
to extract it, and in the format you require.”
It gives customers the ability to build custom queries without any SQL programming knowledge, and save and export reports for detailed analysis by stakeholders in easy-to-use Excel formats. eyeQ works hand-in-glove with our Business Process Manager to enable easy, meaningful interactions with your data, like mail-outs or flagging accounts for follow-up later. There are some really exciting developments on the way, including GUI improvements and natural language processing, which helps reduce complexity even further and gets everyone on your team involved with data.
To give you some concrete examples of how to use data to solve real-world problems, Guy and his team recently helped a client out who were having issues with a small minority of members abusing their online booking system. The customer had a serious issue where members would make bookings across multiple sites, often on the same day, with the intention of only attending one class. We helped the operator identify no-shows or members making late cancellations in order to apply fines to their accounts, as well as using intelligent logic across their databases that automatically cancels any simultaneous bookings made.
The data services team can also assist operators who have recently upgraded to Gladstone's latest GDPR releases. If your consent mechanisms already complied with GDPR best practice, we can help you migrate your existing preferences which are saved in your database, although hidden from view (post GDPR upgrade) to the new member consent tables in the latest versions. Download this document to learn more.
If you’re interested in finding out more about data analysis and reporting in the Gladstone database - speak to one of our consultants in the Data Services team, click here to register your details and a Data Consultant will be in touch.