I recently joined Melissa Moore on the Retail Tea Break podcast to discuss something that’s been bothering me for years: how most retailers use promotions.
The conversation covered much ground – from the 150-year history of promotional codes to why your loyalty program is probably too complicated. But it all comes down to one central problem. Most retailers are fishing with dynamite when they should be using the right bait.
The blanket discount problem
Here’s what typically happens: A retailer approaches the end of a sales period, realises they’re not hitting targets, and panics. The answer? Stick 20% off everything.
Do they sell more? Absolutely. Discounts work. But they’ve just damaged two things simultaneously.
First, there’s the immediate margin hit. People who would have paid full price are now paying less. That’s money left on the table.
Second (and often more concerning) is the long-term brand damage. When you immediately drop from £49.99 to £39.99, customers start wondering if that product was ever worth £49.99 in the first place. You’ve just trained them to wait for discounts.
I saw a perfect example recently. A brand launched a gorgeous new autumn/winter range with a big campaign. Less than a week later, everything was 20% off. What signal does that send?
What makes offers “intelligent”
The technology behind promotions has evolved dramatically. We’ve gone from metal tokens you’d exchange for free Coca-Cola at the local chemist (yes, really) to paper coupons your mum would cut out (younger readers: ask your parents) to digital codes that can be applied automatically.
However, while the delivery mechanism changed, the fundamental approach stayed the same for over a century: blanket offers to everyone, hoping to shift stock or hit sales targets.
What’s different now is our ability to collect and analyse behavioural data. We can understand who’s on your site, what they’re looking at, where they’ve come from, and—crucially—whether they need an incentive to buy.
Intelligence comes into play in two key places:
Targeting: Who sees an offer, in what context, and at what stage of their journey. Someone browsing casually needs a different treatment than someone with items in their basket or someone actively at checkout.
Optimisation: What’s the right offer? Is it 10% off? Free shipping? A gift? And are we constantly learning and improving?
The Ferrari problem
I use this example in conference talks: Lots of people want a Ferrari. The desire is there—that’s intent. But if the price is wrong, desire doesn’t matter.
The interesting bit? Would people still want it if you dropped the price so that everyone could afford one? Probably not. Part of a Ferrari’s appeal is that not everyone has one.
Those are the two big levers in retail: intent and price. When you understand what a customer wants and what the right price point is to convert them (not just what works for everyone) you create a genuinely personalised experience.
Customers get what they want at a price that feels like a good deal. You protect margins on customers who would have bought anyway. Everyone wins.
Keep loyalty simple
The discussion turned to loyalty programs, and here’s where I got a bit direct with Melissa.
I’d been to a conference where lots of small and medium retailers envied M&S’s Sparks card program. They wanted something similar—elaborate point systems, multiple tiers, and complex reward mechanisms.
My challenge: Let’s start with what you’re trying to achieve.
In retail, you’ve really only got three objectives:
- Get more people to buy
- Get them to spend more
- Get them to do it more often
With loyalty, you’re explicitly focused on repeat purchases. The big drop-off is between the first and second purchase. If you can bridge that gap, you’re winning.
When you strip away the complexity, most elaborate loyalty programs ultimately deliver one thing: a discount or reward. So why not just make that simple?
The reasons someone bought from you the first time are essentially the same reasons they’ll buy a second time. Don’t overcomplicate it. Focus on: What will get them from purchase one to purchase two?
You don’t need a whole team managing a points program, and you don’t need customers downloading apps that won’t open at checkout. You need clarity and value.
Peak season: your testing laboratory
We’re heading into Golden Quarter (or whatever peak period is relevant for your sector), and here’s what most retailers miss: This is your best learning opportunity.
During peak periods, you get more traffic and conversions, which means more data and faster learning. This is when you should aggressively test to understand what works with your customers.
Then you roll those insights out for the rest of the year.
Many retailers hit January and watch traffic fall off a cliff. They wonder what happened. What happened is they didn’t use peak season to learn.
If you’re new to testing, start simple. Most retailers have a welcome discount (usually 10% or 15%) that’s been untouched for years. Test it. Try 5%, 10%, 15%, or 20%. Try free shipping instead. Try a gift.
And here’s the critical bit: Look beyond basic metrics.
Yes, 15% off will probably drive the most conversions. No prizes for guessing that. But dig deeper:
- How many people actually use that discount?
- What’s the impact on margins?
- What’s the lifetime value of customers acquired at different discount levels?
- Do certain offers attract better long-term customers?
Maybe you get slightly fewer sign-ups at a lower discount rate, but the customers you acquire are more valuable over time. That’s worth knowing.
The common mistakes
The number one issue I see is retailers getting stuck in a death spiral of promotions. They’re not getting the performance they want, so they discount more. This trains customers to expect discounts, which means they need to discount more to get results.
We sometimes describe ourselves as the methadone program for brands addicted to promotions. You can’t just stop cold turkey – your performance will disappear. But you can introduce intelligence gradually.
Start with the funnel position. Offer different things to people browsing, people with items in their baskets, and people at checkout. They have different intent levels. Treat them differently.
Over time, add more layers, segments, and sophisticated targeting. But begin with something you can actually implement and learn from.
The merchandising connection
An interesting tangent we explored: using promotions to solve merchandising challenges.
When you launch new products, you often guess the right price point. I brought up the Oasis reunion tour pricing debacle as a perfect example of getting this wrong.
They launched tickets expecting to charge around £130. Demand was higher than expected, so dynamic pricing kicked in and tickets went to £300-400. People were furious.
The mistake? They should have started higher and used promotions to drop prices if demand was soft. That would have been less controversial, but they still achieved their revenue goals.
For retailers, this means launching at a price point you think is right. Then, use targeted promotions to test demand and optimise sell-through rates. Are products not moving fast enough? Test what a price reduction does. Are hot products flying off the shelves? You’ve priced it right.
My long-term vision (admittedly a bit of a fantasy) is that retailers shouldn’t need seasonal sales. If we truly understood the demand for every product in inventory, we could use dynamic pricing through promotions to ensure everything sells at the correct rate. No overstocks. No desperate clearances. No landfill.
Will this happen? Probably not completely. Retailers love big seasonal sales for the attention they bring. However, the capability is there for brands that want to be more precise.
What’s next
For RevLifter, we’re continuing to develop our technology around behavioural analysis. The goal is to build a platform that essentially runs itself: it analyses what’s happening on your site, identifies gaps and opportunities, and recommends specific offers for specific products at specific times.
The retailer just says yes or no. The system handles the rest and continuously optimises.
We’re not there yet, but every campaign we run with retail partners teaches us more about customer behaviour and how to predict what will work.
For retailers heading into peak season: This is your moment to learn. Test aggressively. Look beyond surface metrics. Use the traffic surge to understand what really works with your customers.
Then carry those lessons into the quieter months when every conversion matters even more.
I featured on this Retail Tea Break episode to talk about RevLifter’s approach to offers and promotions. This article was written with the assistance of AI.
