Can Technology Solve Fashion’s Persistent Sizing Crisis?
By Shiona McCallum
Senior Technology Reporter, BBC News
Published 15 November 2025
For many shoppers, the frustration of inconsistent clothing sizes remains a daily struggle. A pair of jeans labelled size 10 in one shop may be a size 14 in another, leaving customers confused and disheartened. This problem of erratic sizing is not only inconvenient but also costly: fashion retailers are estimated to lose around £190 billion annually due to returns triggered by sizing issues. As shoppers grapple with which size to buy from which brand, a wave of returns causes supply chain inefficiencies, increased waste, and dissatisfied customers.
The Roots of the Sizing Problem
Walking through London’s popular shopping districts, it is common to hear shoppers express distrust in high-street sizing. Many admit to buying clothes based on appearance rather than size labels, often ordering multiple versions of the same item and sending those that don’t fit back. This practice contributes to a growing culture of mass returns.
The fashion industry’s approach to sizing has long been inconsistent. Variations in body shapes globally, personal fit preferences, and what experts describe as “vanity sizing”—brands deliberately adjusting sizes to appear more generous and appeal emotionally to consumers—have all compounded the issue. As Paul Alger, Director of International Business at the UK Fashion and Textile Association, explains, "People aren’t mannequins, they’re unique, and so are their fit preferences. It’s very difficult; it’s very subjective."
Tech Steps In: New Solutions to an Old Problem
Recognizing the scale of the crisis, a new generation of technology companies is working to address sizing challenges using innovative tools. These include 3D body scanning solutions like 3DLook, True Fit, and EasySize, which use smartphone photos to create highly accurate body measurements and recommend the best-fitting sizes at checkout.
Virtual fitting-room platforms are also gaining popularity. Google’s virtual try-on and companies such as Doji, Alta, Novus, DRESSX Agent, and WEARFITS let shoppers build digital avatars to preview how items might look and fit, enhancing customer confidence for online purchases.
Artificial intelligence is further advancing the field, with AI-powered shopping agents entering the market. Startups like Daydream enable users to describe what they want, then recommend suitable items. OneOff collates celebrity-inspired looks for shoppers seeking similar styles, while Phia scans thousands of websites to compare prices and analyze size insights to help customers make informed choices.
Fixing the Problem Before It Starts: The Fit Collective Approach
While most current sizing technologies focus on helping customers pick the right size during or after shopping, UK startup Fit Collective is pioneering a different strategy—addressing the problem earlier in the production process.
Founded by Phoebe Gormley, a tailor rather than a data scientist, Fit Collective uses artificial intelligence and machine learning to analyze comprehensive data sets—including returns, sales figures, and customer feedback—to understand exactly why clothes do not fit as expected. The platform then provides clear, actionable guidance to design and production teams, allowing them to adjust patterns, sizing, and materials before manufacturing begins.
Gormley illustrates how even small changes, such as reducing garment length by a few centimeters, can meaningfully cut return rates. This approach not only saves manufacturers money but also spares consumers the hassle of ill-fitting clothing and the inconvenience of returns.
Since its launch last year, Fit Collective has raised £3 million in pre-seed funding—the largest such round for a solo female founder in the UK—highlighting strong investor confidence in tech-driven solutions to this age-old dilemma.
Challenges Remain
Despite the promise of technology, experts caution that sizing will likely remain a nuanced issue. Alger notes that “body measurements rarely align precisely with a number on a label,” and consumer preferences vary widely. Moreover, the entrenched practice of brands establishing their own sizing norms each season means that standardization is far from simple.
A Sustainable Opportunity
The high volume of returns driven by sizing problems also has sustainability implications, increasing waste and environmental impact. Sophie De Salis, sustainability policy adviser at the British Retail Consortium (BRC), sees smarter sizing and AI tools as vital components in the industry’s move toward sustainability. “BRC members are working with innovative tech providers to help their customers buy the most suitable size and reduce returns,” she says.
As sustainability pressures rise and return costs become a boardroom concern, it is likely more fashion brands will embrace data-driven design and sizing strategies. Though no single tool will entirely solve sizing inconsistencies, the emergence of startups like Fit Collective alongside an ecosystem of virtual try-ons and size-prediction platforms signals momentum toward lasting change.
Looking Forward
For shoppers weary of puzzling over conflicting size labels, these technological advancements offer hope of a future where buying clothes online or in stores means greater confidence, fewer returns, and a better fit. With AI and data analytics reshaping how clothing is designed and sold, fashion’s sizing crisis may finally be heading toward resolution.
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Watch the related BBC segment ‘Tech Now: Fixing fashion’s sizing problem’ available on iPlayer.
