How to Calculate the ROI of a Virtual Try-On App

Most virtual try-on pitches lead with a big percentage: fewer returns, higher conversion, more revenue per visitor. Those numbers came from somebody else's store, with a different catalog, a different audience, and a different baseline. Before signing up for anything, it is worth working out what the tool would actually need to do for your own numbers to make sense, then checking that against what you observe once it's live.

What is the ROI formula for a virtual try-on app?

Strip away the marketing and the formula is simple. Additional revenue equals incremental orders multiplied by your average order value. Incremental orders equals the extra conversions you get from shoppers who use try-on, above what they would have converted at anyway. ROI is that additional revenue divided by the tool's monthly cost.

• Additional orders = (visitors who use try-on) times (their conversion rate with try-on minus your baseline conversion rate).
• Additional revenue = additional orders times your average order value.
• ROI multiple = additional revenue divided by what the tool costs you that month.

Nothing in that formula depends on a vendor's marketing claim. It depends entirely on your own visitor volume, your own baseline conversion rate, and two estimates you control directly: how many shoppers will actually try the feature, and how much it changes their odds of buying.

What numbers do you need before you start?

1. Monthly product page visitors: pull this from your existing analytics, not a guess.
2. Baseline conversion rate: your store's current rate, without try-on, on the pages where you'd add the feature.
3. Try-on adoption estimate: what share of visitors will actually tap the button. Early data across the category tends to sit in the low single digits to around 10 to 15 percent of visitors on pages where it's placed prominently, but this varies enough by audience and placement that your own estimate matters more than a category average.
4. Conversion lift estimate: how much more likely a try-on shopper is to complete a purchase versus a shopper who doesn't use it. Set this conservatively if you have no data of your own yet: a 10 to 20 percent lift is a reasonable starting assumption to test against, not a promise.
5. Average order value: your existing AOV for the product category you're evaluating.

Should reduced returns be part of the calculation?

Conceptually, yes. A lower return rate keeps more of the revenue you already booked, since a returned order costs you the product's shipping both ways plus the processing time, on top of losing the sale. Online apparel return rates commonly fall somewhere between 25 and 40 percent depending on the category, so the dollar amount at stake per order is real.

In practice, leave returns out of your first-pass ROI model unless you already have your own before-and-after return data for a specific product or category. A general industry range tells you the problem is large; it does not tell you how much of your specific return rate is driven by fit, which is the part virtual try-on can actually influence, versus shipping damage, changed minds, or other causes it can't touch. Once you have a few months of real return data with try-on live, add it in as a second, more precise pass rather than guessing upfront.

A worked example, step by step

Say a store gets 50,000 monthly visitors to product pages, converting at 2 percent today, an average order value of 60 US dollars, and expects 5 percent of visitors to use try-on with a 20 percent conversion lift for those who do.

• Try-on users: 50,000 times 5 percent, which is 2,500 visitors a month.
• Their lifted conversion rate: 2 percent times 1.20, which is 2.4 percent.
• Orders from try-on users: 2,500 times 2.4 percent, roughly 60 orders, versus 50 orders if they'd converted at the plain 2 percent baseline.
• Additional orders: about 10 a month.
• Additional revenue: 10 times 60 US dollars, or roughly 600 US dollars a month.
• Monthly try-ons to price out: 2,500. Corlen's Starter plan (49.99 USD for 250 try-ons, 0.20 USD per try-on after that) would run about 500 US dollars at this volume, but the cheaper match is the Growth tier: 149 USD for 1,000 included try-ons plus 0.16 USD per try-on beyond that, roughly 389 US dollars total for 2,500 try-ons.

In this example, the additional revenue and the cost land close to each other, which is the point of running your own numbers rather than trusting a headline ROI figure: the outcome depends entirely on your adoption rate and conversion lift, both of which you should treat as hypotheses to test, not facts to assume.

Calculate your own number with Corlen's free ROI calculator

Corlen's ROI calculator runs exactly this formula against your own inputs, live, with sliders for visitors, baseline conversion, adoption, and lift, plus a field for average order value. It automatically prices your estimated monthly try-on volume against Corlen's current API plans, picking whichever tier costs less at that volume, and shows the full calculation underneath so nothing is a black box. It's a planning estimate built from your own numbers, not a guarantee, exactly as its own disclaimer says.

For the pricing side of this on its own, see how much does a virtual try-on app cost. To see what a shopper actually experiences before you model adoption assumptions around it, try Corlen on your own photo, or read the developer docs if you're evaluating the API for a custom integration.