Shoppers don’t mind sharing their data. They mind what you do with it

Key takeaways:

When a WIRED journalist asked McDonald’s for a copy of everything its loyalty programme held on him, he got back a 515-page file. It predicted how often he’d visit, what he’d spend and what he’d order. It even concluded he was very unlikely to ever stop being a customer. Unsurprisingly, the reaction online was outrage at how much one brand knew, and a fresh debate about loyalty data sharing.

Shoppers themselves, however, tell a different story. In our latest report, The Retail Loyalty Index Pulse 2026, we asked 2,000 UK shoppers what puts them off loyalty schemes. Sharing personal information was the least common complaint, named by just 3.4% of consumers. By far the biggest frustration was receiving offers that have nothing to do with what they actually buy. So, for retailers, the real question isn’t how much customer data you hold. It’s whether you’re using it well.

Loyalty data sharing: what retailers get in return.

Customers join a loyalty programme for all sorts of reasons, from points and member prices to personalised offers, exclusive experiences and simply feeling recognised. What retailers get in return is something much more valuable: identity. Every scan turns an anonymous transaction into a known customer with a history. Over time, that history builds into a detailed picture of habits, shopping missions and preferences.

Grocery has run this playbook for decades. Now, brands well beyond grocery are catching up, and the logic is simple. The more often customers identify themselves, the richer the loyalty programme data becomes, and the better a retailer can understand what each customer comes in for.

What good loyalty programme data looks like.

Which brings us back to that 515-page file. It caused a stir, but the data in it covers the fundamentals of loyalty modelling that any good programme should have.

A forecast of future visits, for example, tells a retailer when an offer is most likely to land well. Expected spend sets a baseline for each customer. Favourite products power “buy again” rewards, while a likelihood-to-lapse score shows who needs attention and who doesn’t.

Seen that way, predicting that a regular customer will stay loyal is exactly what a loyalty model is designed to do. It means the brand knows who its most valuable customers are. Take Tesco Clubcard. It holds a far fuller picture of its members’ weekly shop, and it was named the UK’s favourite loyalty programme in The Retail Loyalty Index 2026, which ranked 51 of the country’s biggest schemes. That’s no coincidence. Shoppers can see clearly what they get back for sharing their data.

Turning customer data into relevance and recognition.

Of course, collecting customer data is the easy part. The real value comes from using it to make each customer feel understood. Picture a parent who does a big family shop at the weekend and grabs a meal deal alone midweek. That’s two very different missions from one customer. Send them offers built around neither, and the programme quickly starts to feel like noise.

That’s why we see three pillars behind every strong loyalty programme, with customer data powering all of them. The first is rewarding the behaviour you want more of, which gives customers a clear reason to choose you over a competitor. The second is personalisation: matching offers to what each customer actually buys, as well as the products they’re likely to enjoy next. And the third is surprise and delight, the well-timed treat that shows a retailer has noticed. In every case, the more you know about the customer in front of you, the better each pillar works.

Using headroom to apply customer data responsibly.

Knowing what a customer spends today is only half the picture. The more useful question is how much headroom they have, meaning what they realistically could spend, and would happily spend, if the right offer came along.

One customer, for instance, might add a premium product to their regular basket if it’s suggested at the right moment. Another is already at their limit and shouldn’t be pushed any further. Modelling headroom lets retailers tell the two apart. As a result, they stop asking customers for more than they can give, and they keep the focus on winning a bigger share of the shopping customers already do.

Responsibility matters too. If a brand ever misused customer data, say by engineering compulsive behaviour the way some social platforms have, it should be called out. So far, though, we’ve yet to see anything like that in retail loyalty. Most customers are happy with the trade, especially when it means a reward on the product they buy most.

Closing the gaps in your data.

Even the richest data still has blind spots. Purchases made through third-party marketplaces and delivery apps often never reach the loyalty programme, which means a growing slice of customers becomes invisible.

Experience plays a part as well. Quality, value and ease will always count for more than any points balance, and one slow or frustrating visit can undo months of good work. The answer, then, is to make identifying yourself the easiest option, through faster checkout, ordering ahead or member-only prices. When the experience is better for known customers, the data grows on its own.

How customer data is becoming a revenue stream.

Beyond loyalty itself, this data is now opening up entirely new revenue. Retail media has turned it into one of the most valuable assets a retailer owns. Footfall, screens, apps and dwell time all add up to engaged audiences, and customer insight makes targeting much sharper than broadcast media can offer.

What’s more, it’s no longer just a supermarket game. McDonald’s has recently launched its own media network, with ambitions to make it a billion-dollar business over time. Yet plenty of retailers are sitting on similar customer data and digital assets without using them at all.

The customer data is there. Execution is the gap.

Ultimately, shoppers aren’t asking retailers to collect less data. They’re asking for loyalty that feels built for them. And yet our analysis of leading UK retailers found they’re collectively missing out on £806.9 million in gross margin a year through programmes that don’t turn engagement into commercial return.

The good news is that most retailers already hold the loyalty programme data to change that. The next step is to turn it into decisions; whether that’s spotting who’s about to lapse, knowing which offer will land with which customer, or understanding how much headroom each shopper really has.

At HyperFinity, we help retailers make those decisions with confidence, using the data they already have to build offers customers value and results the business can measure. If you’d like to find out what your loyalty programme data could be telling you, get in touch with our team. And for a closer look at what UK shoppers really want from loyalty, download The Retail Loyalty Index Pulse 2026.