Retailers arent discounting to be generous. They discount to drive conversion. But when you throw codes at everyone, all the time, it stops working. And, theyre not always needed.
Our 窪蹋勛圖厙 Gap report found 83% of online shoppers say theyve used a discount code when they would have paid full price.
Thats not incremental revenue youre gaining. Thats margin erosion.
Worse still, this catch-all approach conditions customers to expect a discount. Once theyve had that 10% off, theyll wait for it next time.
Shoppers arent fooled. They know the discount game. And theyre playing it better than most retailers. Ive definitely logged in to my account, added some items to my basket and waited for that abandon basket email to come through. More than once.
But weve already covered the problem with the status quo of discounting, both from the ecommerce leaders perspective and why we think intent changes things. This piece is about how to solve it.
To be clear. Were not saying discounting needs to stop. But it does need to change.
Rethink: Why Youre Discounting
Conversion rate matters. But it doesnt tell the full story.
Of course if you give somebody a better deal theyre more likely to convert. So when it comes to the pros of discounting, we feel its smarter to be looking at metrics like:
- Incremental revenue: Are you gaining additional purchases, or giving away a % to those youd have had anyway?
- Margin protection: Are discounts going to those who actually need them? Who wouldnt purchase without?
- 窪蹋勛圖厙 to purchase: Are you helping someone over the line, or just handing out money to all?
Most retailers discount too early, too often, and to too many people. The fix isnt more codes. Its smarter targeting.
So where do you start?
Rethink: Who Youre Discounting
At Made With 窪蹋勛圖厙, we use a framework that maps where a visitor is in their buying stage (Engage, Build, Maintain, Convert), and what behavioural signals theyre showing (Focused, Struggling, Abandoning).
That gives us 12 core intent-based segments. And not all of them need a discount.
Start with visitors in the Maintain or Convert stages who are showing signs of struggle or abandonment. These people have intent. Youre just helping them follow through on it when they signal theyre hesitating, or going to leave.
On the other side, visitors in earlier stages or those showing focus dont need an incentive nudge (at least not yet!). Give them one, and youre spending margin unnecessarily.
Once you know who to target, the next step is how and when to show the offer.
Optimise: Two Plays to Start Discounting With 窪蹋勛圖厙
You dont need to build something new. Just optimise what youre already doing. Once youve tightened your audience, its time to rethink your triggers and delivery.
Play 1: Trigger discounts for high-intent abandoning visitors
Most retailers show discounts on landing. Pop-ups fire after 30 seconds, three pages, or immediately. But these rules have nothing to do with actual buying behaviour, theyre just proxies.
Instead, you should look for visitors with purchase intent. Then wait for signs of abandonment. Only then do you trigger the offer. And deliver it to visitors directly on site - not through an email sign-up campaign.
Appliances Direct adopted this play and focused their incentives on the Convert Abandon segment, also known as visitors showing high intent but clear exit signals. By targeting only this segment, they saved 42% in margin while maintaining conversion rates. See how Appliances Direct did it.
Better Bathrooms also used this exact approach to great effect. By targeting Maintain 窪蹋勛圖厙 Abandon visitors showing hesitation on PDPs, they triggered context-aware discounts only when abandonment looked likely. The result? A 25.6% increase in conversion rate without widening the net. Read more about Better Bathrooms' approach.
Why does this work?
- These visitors are already ready to buy, but somethings causing them not to
- You reduce giving away unnecessary discounts to casual browsers
- You create a smoother journey (no email sign-up delay, no inbox hunting for a code)
Besides, our 窪蹋勛圖厙 Gap report found 85% of online shoppers leave the site just to go find a discount code anyway. So either dont make blanket offers, or dont make them. Serve it when it matters instead.
Play 2: Offer timely incentives for struggling visitors
Not every visitor needs a discount. But some need a little help before they slip away.
While we recommend most retailers start by targeting Abandon signals, theres a critical opportunity earlier in the journey. Struggling visitors. Our Maintain and Convert Struggle segments are shoppers who have shown clear intent, but are starting to lose confidence or momentum.
By detecting this behaviour in real-time, you can intervene. Either with the same promotional offer or a lighter-touch incentive, such as free delivery or even a lower-value discount.
These nudges help prevent drop-off before it turns into abandonment, while letting you reserve larger offers for those who really need them.
You can also factor in a visitors intent to return to site in the future. If someone is abandoning with high purchase intent but is unlikely to come back, you might want to push a stronger offer.
This is where the nuance of real-time intent shines. Youre not treating everyone the same. Youre responding with the right kind of support at the right time.
The core segments in our framework make these two plays possible with minimal effort. But the power of real-time intent data can take discount strategies even further.
Grow: What Comes Next
By this point, youve cut waste and improved impact. But what if you could push performance even further without giving away more?
Once youve refined your targeting and timing, the next stage is relevance and context. This is where Optimise starts becoming Grow.
Made With 窪蹋勛圖厙 lets you track affinities to products, categories, price points or brands based on rising purchase intent. You can use this to personalise the discount depending on visitor interests or your margin.
Seasalt Cornwall used this data to deliver category-based discounts only to visitors in the Maintain Abandon segment - those with clear product interest showing signs of hesitation. The result? An 89% uplift in conversion rate by focusing offers where they mattered most. Read the full Seasalt case study.
But this is just one way of interpreting it. Other examples include:
- Varying the discount amount based on product margin (e.g. 20% off dresses, 5% off jewellery)
- Offering an alternative incentive, such as free delivery on larger high-ticket goods, to further protect margin
- Using copy that makes the discount feel personal (Still thinking about that top? Heres 10% off)
Now youre not just nudging in the right time and place, but with the right offer for them. Tailoring both incentive type and depth to how your visitors are behaving, and where they are in their journey.
This is where smarter discounting becomes smarter merchandising.
What Happens When You Get This Right?
When intent-based discount works, you dont see conversion drop. You see:
- Stable conversion overall (because the people who dont need a discount dont miss it)
- Higher conversion for those who do receive the discount
- More incremental revenue and margin saved
You also build a better customer base. One thats not hooked on the discount drug.
Discounting doesnt have to feel like a trick. It can feel like understanding your visitor, and using the levers you have available to you.
Your First Three Steps
If you're looking to make an impact fast, heres where to begin:
- Replace early blanket discount pop-ups with intent-based triggers
- Offer high-intent abandoning visitors a discount while theyre in-session
- Intervene with high-intent struggling visitors, offering the same or a lighter incentive
From there, you should explore your segments further. Looking at affinity and intent to return data to identify the next priority.
This isnt about giving more or even less discounts. Its about giving smarter discounts, only when they make a difference.
Want to see how Made With 窪蹋勛圖厙 makes this possible? Get a demo of our real-time intent agent.
