We’ve come a long way from a time when loyalty schemes meant collecting stamps. We’ve moved on from the classic points-based loyalty card, too. At a time where consumers have the freedom to be promiscuous and fickle with their purchases, encouraging customers to keep coming back to your business is more important than ever. Yet many of the old tricks no longer work like they once did.
Last year it was announced that while 92% of the UK’s adult population is signed up to at least one loyalty scheme (the average shopper is signed up to three), 20% haven’t redeemed any of their points.
As the likes of Tesco Clubcard (which played a key role in the supermarket’s growth in the 1990s) and Sainsbury’s’ Nectar Card scheme have found, the way consumers respond to loyalty points has changed. With rival supermarkets like Aldi and Lidl offering groceries at cheaper prices, much of the benefit has been lost.
More than this, younger consumers also appear to be rejecting older, more convoluted schemes, with one report finding that a third (36%) of under 25s found loyalty schemes to be too complicated.
While money offers are still a key motivator for signing up to a loyalty scheme, there is a clear desire to move away from this ‘one size fits all’ approach. The same report found that 74% of respondents would join a scheme with personalised rewards, while 89% say ease of use would influence their shopping habits.
In order for loyalty schemes to be more relevant, delivering the personalised experience that shoppers demand, they require data. More importantly, accurate data. As we know, quality data enables better customer service, and better customer service encourages loyalty.
Why is data quality important to customer loyalty?
To make first contact: Getting customers to sign up is a big part of the challenge. Surveys have shown that many shoppers – particularly younger ones – find it off-putting. In fact, 31% of under 25s felt the signing up process was too long and complex.
This puts brands in a losing situation. Customers either do not bother filling out the forms, or errors creep into the data. Which is more of a problem than you might think – one report found that 25% of brands experienced problems due to poor contact data quality. Trip at this first hurdle and your communications will never reach the right target or the right channel.
For personalisation: If the future of loyalty schemes is to deliver unique customer experiences, then customer data needs to be accurate. For offers to be relevant to them based on their location, interests or behaviour, if any element of this is wrong then it would undermine the usefulness of a loyalty scheme. Get it right and not only will you see a greater uptake on your offers, but customers will feel rewarded by being treated like an individual.
For timeliness: For loyalty offers, timing is as important as content. Having up-to-date data can be used for many loyalty-based strategies. At one end of the scale, this could simply be a reward activated on their birthday. It could also mean sending reactivation strategies to customers who have yet to use your scheme, or understanding why certain people redeemed an offer and others didn’t, and being able to send a follow-up message based on their actions. Without clean data, identifying patterns within customer behaviour would be misleading and more likely futile.
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