Google's Virtual Try-On Arrives in Search Results April 30 — As AI Startups Race to Solve Retail's $849 Billion Returns Crisis

US retail returns hit $849.9 billion in 2025 — 15.8 percent of all retail sales, according to the National Retail Federation. For online purchases, the return rate climbed to 19.3 percent. Gen Z shoppers, aged 18 to 30, averaged nearly eight online returns per person last year. Most of those returned items never made it back to store shelves. Starting April 30, Google is deploying virtual try-on technology directly inside product search results — part of a growing wave of AI solutions targeting what has become the retail industry's most expensive unsolved problem.

What Google is launching on April 30

Google's virtual try-on feature, which has been in testing through Google Labs, will become accessible directly within product search results across Google platforms starting April 30. The technology allows shoppers to see how clothing looks on different body types before making a purchase decision — without leaving the search page.

The placement matters as much as the technology itself. Google is embedding try-on at the exact moment a consumer discovers a product, not buried inside a brand's app or website. For retailers, this means AI-assisted fit decisions happen at the highest-intent touchpoint in the shopping funnel: the product search result. The consumer who searches for a specific jacket and can immediately see how it fits on a body similar to theirs is a fundamentally different buyer than one scrolling through flat-lay product photos.

The $849 billion problem AI is trying to fix

The scale of the returns problem is difficult to overstate. The NRF's $849.9 billion figure represents more than the GDP of most countries. Online returns at 19.3 percent mean roughly one in five online purchases comes back. And the economics of processing those returns are brutal: most returned items cost the retailer more to receive, inspect, and restock than the refund itself. Many never return to inventory at all.

Gen Z has accelerated the problem through "bracketing" — ordering multiple sizes of the same item with the explicit intention of returning most of them. Eight returns per person per year is not carelessness. It is a rational response to the fact that online sizing is unreliable and 82 percent of consumers consider free returns essential when choosing where to shop. Retailers are caught between consumer expectations and unsustainable logistics costs.

The industry response is a mix of technology and policy. Virtual try-on and AI-powered sizing tools represent the technology side. Charging for return shipping and incentivizing exchanges over refunds represent the policy side. Neither alone solves the problem.

Does virtual try-on actually reduce returns?

Catches, an AI try-on app focused on luxury brands, projects a 10 percent increase in conversions and 20-to-30 times ROI for its brand partners. Those are projections, not audited results — but they reflect the industry's bet that better pre-purchase visualization leads to fewer post-purchase regrets.

Simeon Siegel, Senior Managing Director at Guggenheim, offers the most measured assessment of AI fit technology: it "will never be as good as trying something on in person" but represents "a great way to bridge the gap." Siegel frames the returns problem as a strategic opportunity, noting that "figuring out how to proactively use returns and then how to minimize them can be a meaningful driver of business and profitability."

The honest limitation is that virtual try-on addresses only one category of returns — wrong size or fit. It does nothing about changed minds, impulse purchase regret, or finding a better deal after buying. And the physical shopping preference remains strong: IBM and NRF data from January shows 72 percent of consumers still shop in stores specifically to see and touch products before committing. AI fit tech is competing with a deeply held consumer preference for physical experience.

Siegel adds a caution that applies to every retailer chasing AI solutions: "All of those are really interesting use cases, as long as companies don't abandon who they are." And: "What you sell is always going to be more important than how you sell."

Mubboo's Take

Google putting virtual try-on inside search results is the clearest signal yet that AI is moving from discovery assistance to purchase confidence. The $849 billion returns problem will not shrink with better product photography or marketing copy — it requires technology that helps consumers make better decisions before they buy. For Mubboo's Shopping channel, this reinforces our core editorial approach: we do not just surface products, we provide the judgment that helps consumers decide whether a product fits their specific situation, budget, and lifestyle. Virtual try-on solves fit. Editorial comparison solves "is this the right product for me?" Both reduce returns. Both serve the consumer who wants to buy right the first time.