“We don’t want to waste the money on customers who would have bought anyway.” This is a concern we hear often in our work with global retailers. It has become almost a mantra in personalized marketing. It makes sense, of course. If a customer is already planning to come to the store and buy an item for full price, who in their right mind would want to give her a discount?
Yet we regularly counsel retailers that, in addition to cross-sell and stretch offers, their personalized offer mix should include some offers on a customer’s favorite items.
Why do we recommend this counter-intuitive approach? It is not just because we are such nice guys (though we like to think we are). It is also because offering customers a discount on things they already buy is very good for the bottom line.
How is it possible to generate a return by paying a customer to do something she was going to do anyway? The answer lies in our assumptions about what the customer was going to do anyway. A lot of the time, these assumptions can be spectacularly wrong.
Let’s start with an idea that many of us carry around in our heads. Most of us assume that our loyal customers have a core set of items they buy on a weekly basis. Obviously, we know not everything they buy is bought weekly. Laundry detergent does not run out every week. Ice cream is a seasonal treat. But even if not everything is in the core set, the fact remains that we believe there is a core set. It is different for different customers, of course. But typical items might include bread, milk, eggs, or bananas.
But now we must turn to the data. We took a sample of Platinum customers from a leading supermarket chain – these are the core, committed customers who are largely loyal to a single banner – and looked at the number of items they were purchasing regularly.
These top customers were buying an average of 658 unique items over the course of a year. The number of items they were buying on a weekly basis? Only 4 items.
If we cast a wider net to include items purchased monthly, we get an additional 24 items. Together, these 28 items purchased at least monthly made up 26% of customers’ annual sales. That leaves nearly three quarters of their sales that came from items purchased less than monthly.
These numbers are surprising to most people – even industry veterans. I have had the opportunity in past roles to look at the data from my own purchase history, and it followed the exact same pattern. I was shocked. It turns out we don’t just have some wrong ideas in our heads about what our customers do. Sometimes we do not even have a clear picture of what we do ourselves.
So what does all this tell us? It is true that you don’t want to waste money trying to get someone to buy something they were going to buy anyway. But the chance of this happening turns out to be much lower than we think.
Even if you aim to give customers a set of offers with their most frequently purchased items, you will almost always be giving them an incentive to do something they were not going to do without that incentive. They might have bought the item from a competitor. They might have delayed their purchase (and ended up consuming less). Or they may have selected an alternative product. One thing is clear: the data tells us that the likelihood they were going to do it anyway is actually quite small.
As you develop your strategy for retail personalization, don’t be afraid to include offers on your customers’ favorite items. And when someone on the team expresses concern that you are wasting money on people who would have bought anyway, you can tell them not to worry. After all, now you’ve got the numbers to prove it.