Part of the Bright Sparks series, written by Christa Norton, Marketing Director
There is a peculiar moment in modern customer experience when helpful becomes unsettling. Even intrusive.
You browse for a pair of trainers. Or even less. You pause while scrolling on TikTok on a pair of trainers. For the next fortnight, those trainers follow you around the internet. You buy them. You don’t buy them. They continue following you as does every other pair of trainers on the market.
In the marketing world, we call this personalisation: the more we know about customers, the more targeted our offering to them becomes, and the better the experience we provide, the more likely they are to buy again and again.
And sometimes that is demonstrably true.
For example, Spotify uses listening behaviour to introduce us to music we might like. Tesco’s proudly and openly use our loyalty data to offer discounts on products we actually buy. Netflix remembers what we watch so we don’t have to begin every Friday evening overwhelmed by 7,000 equally plausible choices.
This is data earning its keep.
YouGov research in 2025 found that 57% of British consumers say personalised advertising “creeps them out”. Gartner found something even more interesting: whilst customers experiencing personalisation were 1.8 times more likely to pay a premium, it also produced a negative experience for 53% of customers in its study. Those customers were considerably more likely to regret their purchase. Or switch brands next time.
Apparently, we can be persuaded to spend more while enjoying the experience less. We spend more that time, maybe even next time, but our brand loyalty is damaged and our propensity to simple “unsubscribe” multiplies.
Perhaps the problem isn’t personalisation. It’s just the assumption that more of it must inevitably be better. Having been a bridesmaid multiple times in the 90s, it is something I lovingly refer to as ‘The taffeta conundrum’.
But knowing something about a customer isn’t the same as understanding them or their behaviour.
Once again Spotify provides a wonderfully ordinary example. It allows users to exclude particular listening from their Taste Profile. So when you play a Disney soundtrack 47 times to soothe a poorly child, it doesn’t then feed into your algorithm. In effect, it’s allowing users to give the algorithm guard rails, and by doing this, Spotify gives users some agency in how their data is used beyond binary tick boxes.
Context matters elsewhere too – especially when the volume of information held or gathered, vastly outweighs the benefit to the customer. A supermarket remembering the coffee I buy every week might save me money. An airline remembering my seating preference might save me time. But do I need my broadband provider to understand my lifestyle, aspirations and preferences?
Probably not. I need the broadband to work.
Before adding something, ask what problem it solves. Does it make the boat go faster?
The same discipline should apply to personalisation.
How does knowing this particular thing about the customer allow us to engage better? Does it remove effort? Make something quicker? Prevent a problem? Introduce something genuinely useful?
Or are we personalising simply because the data and technology make it possible and we are more concerned about making money now than providing a long term positive experience?
That’s an important distinction. Personalisation requires information to be collected, connected, contextualised, interpreted and retained. Kept safe. Used well. Customers are more and more aware that, in sharing their data, they are making a value exchange, and that has to work for them too – not just the seller.
There will be plenty of occasions when that exchange is worthwhile but when they aren’t you risk damaging the fragile trust that exists between modern consumers and the companies they engage with. In 2020 IPOS MORI found that 73% of us trusted certain brands over politicians, religious leaders and the media.
That trust is the Holy Grail for any organisation but perhaps the ambition perhaps shouldn’t be to create the most personalised experience possible. It should be to understand when personalisation actually improves the experience in the first place.