A clever blend of data is key to building loyalty

Whenever I go to York railway station and decide I want a coffee, I make the subconscious choice to go to Starbucks rather than any of the other outlets. Is this because I feel loyalty to Starbucks? No – it’s because I can get my espresso in a china cup rather than a paper one. At what point does a customer become loyal to a particular brand, anyway? Do they ever actually think: ‘I’m loyal to Brand X’? I’m not sure we have these conscious Road to Damascus moments.

However, buying coffee is often dictated by availability – and being desperate enough to choose the lesser of many evils. More considered choices, such as supermarket, insurance provider or next car purchase, are much more likely to bring loyalty into the equation.

We talk about ‘choice architectures’ during the decision-making process, in which defaults, frames and price anchors have a bearing on consumer choices. Ideally, brands want our decisions to be based on experiences we have had with that brand, product or service. The abundance of data now available to brands gives them the opportunity to influence, and hopefully enhance, the experience that customers have. As a result, they can have a positive influence when that customer comes to re-evaluate their needs.

Take car insurance. Aviva offers Drive, an app that monitors driving skills. Once the driver has completed 200 miles, they get an individual score out of 10 based on things such as cornering, braking and acceleration. Drivers who score 7.1 or more save an average of £170 on Aviva’s comprehensive car insurance. So this piece of IoT thinking (a mobile phone in my car) not only potentially makes me a safer driver but could also save me money. Forget the tricks of behavioural economics theory on the insurance quote page – I’m in.

What would prevent me from cancelling my gym membership? Personalised prompts from my gym to keep coming back if I start missing sessions are useful. So the fact that gyms like Pure Gym provide usage statistics means that they can use the data to understand my behaviour and react when that behaviour changes.

And if one of the reasons I don’t come in is because I hate when it’s too busy to use my favourite machines, why not let me know when it’s busy so I can plan my sessions accordingly?

One of the biggest issues Telco companies have when considering churn is the impact of ‘bill shock’, when a customer is distraught at the size of their mobile phone or data usage bill. And yet, data can tell them in advance when a customer is likely to go over their minute or data limit. My bank warns me when I’m in danger of going overdrawn, therefore my Telco provider can easily do the same thing.
In a similar vein, my credit card provider reminds me when I haven’t looked at my online statement for a while. Yes, it shows a sense of corporate responsibility to make sure I keep an eye on my finances but it also makes sense from a business perspective. If I run into trouble financially, having a credit supplier that has an eye out for me means their card won’t go near the shredder.
This stuff isn’t rocket science, so why aren’t more brands doing it? For some older organisations, pulling together all of their various data can be a painful process, while some companies feel they need to have the perfect data set before getting the ball rolling (they don’t – just take some data offline and play with it). There is a (slightly controversial) theory that some marketers think they know best and are afraid that the data will tell them otherwise or even take their jobs away.
But really, it’s just about data making brands even better – by looking at some of the real influences on customer loyalty and tapping into the data available to shift the loyalty dial in their favour.