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Every resale item is one-of-a-kind. You can't photograph thousands of unique items on models—it's economically impossible. Virtual try-on transforms any flat lay into professional try-on imagery instantly. This isn't an incremental improvement. It's an upgrade that was previously impossible.
The resale market is exploding: $367 billion globally by 2029, growing at 10% annually. A record 58% of US consumers shopped secondhand in 2024. Online resale grew 23%—its fastest rate since 2021.
But resale platforms face a unique photography challenge: every item is one-of-a-kind. You can't do model shoots at scale when you have thousands of unique pieces. Virtual try-on solves this—transforming any flat lay into on-body visualization instantly.
$367B
Global resale market by 2029
90%
Say photo quality drives purchase
23%
Online resale growth in 2024
Enter your current metrics to see how virtual try-on transforms your resale platform's conversion and engagement.
Monthly Revenue Lift
$75K
+75% growth
Returns Avoided
$3K/mo
88 fewer returns
Annual Net Impact
$848K
Total benefit per year
*Projections based on industry research. Actual results may vary based on implementation and product category.
Traditional fashion e-commerce relies on professional model photography. According to industry analysis, 95.6% of high-end fashion e-commerce uses model photography—because it works. Photos showing how garments look on a body drive purchases.
Traditional model photography requires: Hire model → Schedule shoot → Style garment → Photograph → Edit.
For one item. At resale scale—thousands of unique items—this is economically impossible. The RealReal processes millions of items. Poshmark has $1.7 billion in GMV. You cannot photograph each one on a model.
Research consistently shows that 90% of shoppers cite photo quality as the top driver of purchase decisions. Professional on-model shots increase conversion rates by up to 33% compared to lower-quality visuals.
90%
Say photo quality is top purchase driver
+33%
Conversion lift from on-model photos
-22%
Returns when product matches photo
Flat lay images "lack a sense of scale" and fail to showcase items in real-world contexts. Unlike on-model shots that offer "practical understanding of size, fit, and functionality," flat lays cannot reduce returns or increase customer satisfaction as effectively.
Resale is stuck with flat lays because the alternative—model photography at scale—is impossible. Until now.
Unlike traditional retail, most vintage and resale platforms operate with "all sales final" policies. This makes purchase confidence absolutely critical.
When buyers can't return for fit issues, they need extreme confidence before purchasing. Without that confidence, they don't buy. Virtual try-on provides the visualization that creates purchase confidence—without the safety net of returns.
Nearly 90% of consumers worry about authenticity in resale marketplaces. Combined with fit uncertainty, this creates a significant conversion barrier. VTO addresses the fit uncertainty, letting authentication systems handle the trust component.
Resale shopping is fundamentally different from traditional e-commerce. 80% of thrift shoppers say they enjoy the "treasure hunt" of searching for items. The brain releases dopamine—the pleasure neurotransmitter—during the search.
80%
Thrift shoppers browse extensively, seeking hidden gems. This creates massive engagement but selective purchasing—shoppers look at many items but buy few.
54%
According to OfferUp's Recommerce Report, more than half of secondhand shoppers specifically seek unique pieces they can't find elsewhere.
Virtual try-on creates consideration data that reveals what shoppers actually want. When someone virtually tries on an item, they're expressing genuine interest—even if they don't purchase.
This data can help resale platforms surface hidden gems, recommend similar items, and inform pricing and inventory decisions. The treasure hunt becomes data-driven.
Vintage sizing presents a unique challenge that makes fit visualization essential. There is no easy conversion between vintage and modern sizes due to decades of progressive vanity sizing.
In the 1937 Sears catalogue, a woman with a 32" bust wore a size 14. By 1967, she wore a size 8. Today, she wears a size 0.
Marilyn Monroe wore a size 12 or 14 in the 1950s—which would be a size 6 or 8 in today's sizing.
| Era | Sizing Adjustment |
|---|---|
| 1950s/1960s | Add 6 sizes to modern size |
| 1970s | About 4 sizes larger than modern |
| 1980s/1990s | 1-2 sizes larger than modern |
Even within eras, sizing standards didn't exist—brands made up their own scales. Shrinkage is real: cotton items washed many times have changed from original fit. The size label tells you almost nothing about how a vintage item will actually fit.
Gen Z is driving resale growth—and they expect digital innovation. According to a 2024 Harris Poll, 63% of Gen Zers have purchased clothing secondhand, significantly outpacing the general population (47%).
48%
Look secondhand FIRST before buying new
46%
Of apparel budget planned for secondhand
79%
Agree that wearing vintage is trendy
Gen Z is already comfortable with AR filters on social media. Virtual try-on is a natural extension of their shopping behavior. They expect digital innovation—platforms that don't offer it risk seeming outdated.
39% of younger shoppers have made secondhand purchases on social commerce platforms in the last year. VTO creates shareable content that drives organic discovery.
Virtual try-on transforms resale photography from an impossible challenge into a competitive advantage. Any flat lay, hanger shot, or seller photo becomes on-body visualization—instantly.
Upload a flat lay. Get on-body visualization. No model, no photoshoot, no waiting. Each unique item gets professional-quality try-on imagery without the traditional production requirements.
What was impossible at scale becomes instantaneous.
Traditional photography multiplies cost with each item. VTO has the same cost whether you have 100 items or 100,000. Scales with your inventory without scaling your production costs.
Unit economics that finally work for resale.
Vintage sizing is chaos, but VTO with body measurement shows how this specific item will fit this specific body. The label becomes irrelevant—the visualization tells the truth.
Solves the vintage sizing problem entirely.
Every virtual try-on is a signal of interest. Aggregate this across your inventory to surface trending items, inform pricing, and understand what your shoppers actually want.
Turn browsing behavior into actionable insights.
The resale market is experiencing unprecedented growth, and visualization technology is proven to drive results:
The RealReal
$600MAnnual revenue, 14% YoY growth, record Q4 2024
Poshmark
$1.7BGMV, luxury items achieve 92% sell-through rate
Depop
$457MUS revenue, 90% of users under 26, 31.6% growth
Online Resale Growth
+23%2024 growth rate—fastest since 2021
3D Visualization Conversion
+94%Conversion rate increase with 3D product visualization
Virtual Try-On Confidence
+65%More likely to purchase with VTO
Return Reduction
-22%When product visualization matches reality
Given resale's unique dynamics—one-of-a-kind inventory, no-return policies, vintage sizing chaos, and photo-driven purchases—we project the following impact ranges:
| Scenario | Conversion Lift | Engagement Increase | Data Value |
|---|---|---|---|
| Conservative | +20% | +30% | Significant |
| Moderate (Expected) | +40% | +60% | Substantial |
| Aggressive | +65% | +100% | Transformational |
For a resale platform with 500,000 monthly visitors, 1.5% conversion, and $75 AOV—a 40% conversion lift means $2.25M additional annual revenue. Plus the try-on data that reveals what your treasure hunters actually want.
Resale platforms have always faced an impossible choice: professional model photography that doesn't scale, or flat lays that don't convert. Virtual try-on eliminates that choice entirely.
Every unique item in your inventory can now be visualized on-body. Every vintage piece with confusing sizing can show exactly how it fits. Every treasure hunter browsing your platform generates data about what they actually want.