Why Machine Learning will underpin responsibility and customer loyalty in the gambling sector
The gaming sector is one bound by the tightest of tightropes. As an operator, you exist – just like any other – to drive commercial returns. However, you are also duty-bound to act responsibly and have your customer’s best interests at the very heart of your operations.
Each is mutually dependent; as a business, there is zero benefit in having your customers burn-out or self-exclude. Keeping punters safe and gambling fun are sacrosanct to success.
To this extent, the data you hold on your customers will not only inform their experience on the platform but also dictate your ability to monitor for problematic behaviour which might need intervention. And if this data is incomplete or siloed, you simply can’t have a single point of truth of the customer, allowing you to keep them both loyal and safe.
But it’s what you do with this unified data, which will drive the biggest returns. This is why we have conducted independent research into the drivers behind loyalty, and the role of responsibility in gambling, looking at the complicated relationship between the two.
While it might be little surprise that having the best odds is a primary loyalty driver for customers, the responses to personalisation issues demonstrate that a race to the bottom isn’t the only route to retention.
When quizzed as to what would make then loyal to an operator, regular gamblers (once a month or more) stated:
- Functionality: 94%
- Range of sporting bets available: 89%
- Having the best special offers: 88%
These results sum up a great user experience and the demand-driven by variety – showcases the opportunities ML brings, themselves being entirely reliant on the right CDP to bring data together in the first place and ensuring its cleanliness.
Poor data only reveals poor insight, while incomplete data skews results and delivers a misleading customer view.
Consider someone looking for a new house and stating the specifics only; three bedrooms, off-street parking, decent garden, two bathrooms, good-sized kitchen. And a lounge, of course, maybe a snug?
But who is the person behind the data? Each specification only gives a small clue as to what they value in their living space. Is the snug a playroom for an excitable toddler? Is the garden space for children to expound energy? How many of them drive, so how big does the off-street parking need to be?
Without knowing the person you can’t sell the product.
The competitive nature of the gambling industry means lazy mistakes can’t be allowed to happen.
It’s important to note that understanding the customer has never been more important than in 2020, where a huge percentage of the population has been affected by the impact of the Covid-19 pandemic. Furlough, redundancies, pay cuts – all have either eaten into disposable income or cut it off entirely.
It’s with this in mind that understanding your customer now is most important. If your customer has switched from betting £20 a week on football, but the cadence has slowed to once a month, then pushing weekly special offers is inappropriate at best, irresponsible at worst.
Given the tectonic shifts in income, a customer being reminded of what they could spend before (but now can’t), isn’t going to exactly cheer them up. More importantly, it won’t make them feel understood. A combination of real-time data and ML will give an iterative understanding of the customer and allow for personalisation to be constantly refined – driving loyalty as a result.
Our research also found that loyalty is heavily associated with responsibility, with 83% of respondents stating the latter was very important to the former. This demonstrates clearly that neither commerciality and responsibility have to be compromised for the business to thrive.
The sheer scale of customer data available has expanded beyond human beings’ ability to monitor and manage effectively. ML fuels enhanced data analysis and interpretation, which is allowing businesses to not only stay afloat but to thrive in this data-rich ecosystem.
All this insight is at your fingertips.
ML will yield an unprecedented view of where opportunities lie, but only if the system has clean data to work within the first place – a process reliant on a high-quality Customer Data Platform.
This year has shown that understanding individuals is more critical than ever, and the gambling sector is no different. It’s intrinsic standing as a pastime means it remains an important and fun escape for the majority – and ML can inform the degree to which the experience is an enjoyable one. Crucially, for those who might have a potentially problematic relationship with gambling, the ML opportunity can keep them safer than ever before.
The adoption of ML into any gambling business is genuinely an open goal.