Do AR try-ons cause more returns? What an International Journal of Research in Marketing study found
A virtual try-on makes a product feel more certain before you buy. Four experiments show what happens when the real thing arrives with a flaw. Reviews and realistic rendering took most of the sting out.
In four experiments, AR try-on previews raised return intentions after a flawed product arrived. Positive reviews and realistic rendering reduced the effect.
Marketing in 3 · Issue 38 · Week of 28 September 2026
The moment of truth is when the box opens. Photo: Philippe Murray-Pietsch on Unsplash.
The short answer
They can, when the product turns out worse than the preview suggested. In four experiments where every shopper received a flawed product, people who had tried it on in AR were more likely to return it than people who had seen photos. Their expectations had been higher, so the letdown stung more. The effect shrank when positive reviews appeared in the preview and disappeared when the rendering was highly realistic.
Key takeaways
In a lab test with a flawed pair of shoes, 65% of people who had tried them on in AR returned them, against 37% of people who had seen photos.
AR raised expectations first, and those higher expectations produced more regret and then more return intent. Preview format had no direct effect once these two were counted.
Positive reviews shown in the preview removed the extra return intent and reversed it. AR shoppers then wanted to return less than photo shoppers.
A highly realistic preview removed the gap, because it set expectations closer to what the product really looks and feels like.
What the researchers did
Retailers add AR try-ons because they help shoppers picture a product on their own feet, face or living room. The usual
hope is that fewer surprises mean fewer returns. Minghao Li and colleagues at the University of Nottingham Ningbo China
asked a less comfortable question. If a preview makes a product feel more certain, what happens when the real product
lets the shopper down?
Their idea is what they call the virtual idealization paradox. An AR preview makes a product look personal and
informative, so shoppers fill in what it cannot show, such as fabric texture, fit and small flaws, in a flattering way. That sets
a higher bar. If the delivered item falls short, the gap between hope and reality is bigger, regret is stronger and a
return becomes more likely.
They tested this in four experiments. In each, one group previewed a product with an AR try-on and another saw ordinary
photos. Then everyone was told, or shown, that the product they received was flawed. The flaw was held constant, so any difference in
returns came from the preview.
Study 1
104 students in a lab, a real pair of slightly defective shoes, and a real return code in the box
Study 2
815 online shoppers in China, shoes previewed by AR video or photos
Study 3
1,539 shoppers, adding positive reviews to the preview or leaving them out
Study 4
1,675 shoppers, an interactive shop with a knit scarf shown at low or high realism
Measures
Return intention on a 7-point scale, expectations, and regret
A better view, then a harder fall
In the lab, participants tried on shoes through a shopping app, or looked through six photos. They then opened a box
holding shoes with small colour differences and workmanship flaws. To return them, they had to scan a code in the box and
enter their ID.
Of the people who had used the AR try-on, 65% started a return. Of those who had seen photos, 37% did.
The online study checked why. People who had seen the AR preview expected more from the product and reported more regret
once told it was unsatisfactory, and both fed into higher return intention. Once expectations and regret were taken into account,
the preview format had no direct effect left. In other words, the whole effect ran through the raised bar.
Share of shoppers who returned flawed shoes, by preview type
Share of shoppers who returned flawed shoes, by preview type
Group
Value (%)
Photos only
37
AR try-on
65
Study 1, laboratory experiment, 52 participants per group. 19 of 52 returned after photos, 34 of 52 after the AR try-on.
Reviews as a cushion
The third study asked whether something in the preview could soften the fall. Half the participants saw a stream of positive customer
comments about the product and the try-on, and half did not.
Without reviews, AR shoppers wanted to return the flawed shoes more than photo shoppers did. With reviews, the pattern reversed and
AR shoppers wanted to return them less.
The authors' explanation is that regret depends on whether the choice still feels justifiable. When other people have praised
the product, keeping it is easier to defend, and that matters most for AR shoppers, who had the bigger disappointment to
explain away. They did not measure that justification directly, so it is a reading of the pattern and not a proven step.
Return intention after a flawed product, by preview and reviews (1 to 7 scale)
Return intention after a flawed product, by preview and reviews (1 to 7 scale)
Group
Value ()
Photos, no reviews
4.6
AR, no reviews
5.0
Photos, with reviews
4.3
AR, with reviews
3.9
Study 3, group means, 1,539 participants.
Realism closes the gap
The fourth study changed the preview's quality. Shoppers browsed a scarf in a simulated shop. In the low-realism version, the
scarf looked smooth with little visible texture. In the high-realism version it showed finer detail and more natural
variation in the material.
With low realism, the AR group again showed more return intent for the flawed scarf. With high realism, the difference
vanished. A richer picture seems to have pulled expectations down to something closer to the physical product.
The same pattern showed in the mediation analysis. Under low realism, AR raised expectations, which raised regret and return
intent. Under high realism, that chain was no longer reliable.
Return intention after a flawed product, by preview and realism (1 to 7 scale)
Return intention after a flawed product, by preview and realism (1 to 7 scale)
Group
Value ()
Photos, low realism
4.6
AR, low realism
4.8
Photos, high realism
4.4
AR, high realism
4.4
Study 4, group means, 1,675 participants.
What it means for a retailer
This is not a case against AR. The study only looks at what happens after a product disappoints, which is when a preview
matters least. If the product is as good as shown, a higher bar is no problem.
What it does show is that a preview is a promise. Anything it leaves out, such as texture, fit variance or material
quality, is filled in by the shopper, usually favourably. The practical answer is to make the preview carry more of the
truth, and to give shoppers a reason to stay comfortable with a decision that was reasonable when they made it.
Marketing in 3 steps
Ready. Set. Market.
1
ReadyDecide and prepare
Find where reality drifts. List the three things customers say were different from what they expected, using your return reasons and reviews. Colour, texture and fit are the usual suspects.
Check your preview against the real item. Place the real product next to your preview on one screen. Note every detail the preview makes look better than the item, and fix the three biggest ones first.
2
SetBuild it
Add one honest line to the preview. Put a short note beside the try-on, such as "Colour and texture may vary slightly from the screen." Keep it to one sentence, in plain words, where the shopper can see it.
Put real reviews inside the try-on. Show your average rating and two recent reviews on the same screen as the preview. Pick reviews that mention fit or feel, and not only praise.
3
MarketLaunch and measure
Test with and without the changes. Split visitors evenly, so half see the new preview and half see the old one. Run it for at least four weeks, or until each group has 500 orders.
Compare return rates, not just sales. Count orders returned within 30 days for each group, as a share of orders. Keep the changes if returns fall and sales do not drop by more than you can afford.
What to expect
Higher conversion, mixed returns. A try-on can lift sales and still raise returns on items that vary, so track both.
Bigger effects where the product varies. Fabric, colour and fit differences leave the most room for a flattering guess.
Cheap fixes first. Reviews and a short expectation note cost far less than rebuilding a 3D model.
Realism takes work. A more detailed render needs better product data, so start with your highest-return products.
Where it does not work
Scenarios, not sales. Apart from the lab study, people imagined receiving a flawed product and reported what they would do. Real returns involve costs and habits the studies do not capture.
One country. All the participants were in China, where return norms and trust in reviews may differ from yours.
Shoes and a scarf. Furniture, electronics or luxury items may behave differently.
A flaw was always present. The studies show what AR does when a product disappoints, not how often that happens in practice.
Questions marketers ask
Does AR increase product returns?
Once a product disappointed, yes. AR users showed the higher return intent in all four experiments (Li, Huang, Yuan & Chen, 2026, International Journal of Research in Marketing). The studies did not test products that met expectations.
Why would a better preview lead to more returns?
It sets higher expectations. The bigger the gap between what shoppers expected and what arrived, the more they regret the purchase, and regret leads to returns.
How can retailers reduce the effect?
Two things worked in the experiments. Showing positive reviews within the preview softened it, and making the rendering highly realistic removed it.
Does this mean retailers should drop AR try-ons?
No. The paper does not say AR hurts sales or returns in general. It shows a risk that appears when the product falls short, and it points to ways of reducing that risk.
Are the results based on real purchases?
Only partly. The lab study used real shoes and a real return code, but the three online studies used imagined scenarios and stated intentions.
Also new this week
International Journal of Research in Marketing · 2026
A meta-analysis of 298 effect sizes from 111 experiments finds that 360-degree views, AR and VR moderately improve consumer responses compared with images and videos. The effect is stronger when text overlays the virtual content and for experiential shoppers, and weaker for VR on a PC and for familiar brands. Add overlay text to your try-on.
A meta-analysis of 126 samples and 36,386 consumers links four AR and VR qualities to different stages of the customer journey. Immersion matters most before purchase, vividness at the point of purchase, and presence and interactivity afterwards. Match the feature you invest in to the stage you want to improve.
Source
Li, M., Huang, B., Yuan, R., & Chen, R. (2026). The virtual idealization paradox: How augmented reality previews increase product returns through elevated expectations. International Journal of Research in Marketing. https://doi.org/10.1016/j.ijresmar.2026.07.001
This brief is written for practitioners from the published article. Open access (CC BY 4.0): free to read at the publisher. Numbers are as reported by the authors; read the article for full methods.
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Bruno Schivinski is Associate Professor of Marketing at Gdańsk University of Technology. He studies how consumers engage with brands in digital and social media.
