Sizing intelligence is strategic priority as brands prepare for AI-driven commerce
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A new report from Coresight Research, ‘Shifting the Size and Fit Paradigm: A three- pillar framework to reduce returns and future-proof for agentic commerce’ (May 2026) identifies the consumer, technological and market forces reshaping the fashion landscape and advises on how brands and retailers can prepare and succeed in the face of these seismic shifts. In this article the sizing technology company Alvanon, a partner on the report, summarises some key findings and actionable recommendations.
Sizing and fit is not just a technical product development issue but is a strategic business intelligence issue, according to new research from Coresight Research in partnership with apparel sizing technology company, Alvanon. The report demonstrates that brands must establish stronger “sizing intelligence" frameworks to reduce returns, improve inventory planning and prepare for the rise of AI-powered shopping.
With online apparel returns continuing to cost the sector, Coresight estimates that the average US online apparel return rate reached 23.4 percent in 2025. Based on an online apparel and footwear market worth $201.1 billion, this equates to approximately $47.1 dollars of returned merchandise. Nearly 70 percent of shoppers who returned clothing purchased online cited size and fit as the reason, highlighting what the report describes as a significant opportunity for retailers to reduce returns and build consumer confidence.
AI shopping agents raise the stakes
The research identifies agentic commerce, predictive sizing technologies and changing consumer body profiles driven by GLP-1 weight loss medications as three forces reshaping expectations around sizing and fit.
As AI agents increasingly assist consumers with product recommendations and purchasing decisions, brands with inconsistent or incomplete sizing data risk becoming less visible. AI systems depend on structured, machine-readable product information to compare and recommend products accurately. Inaccurate or inadequate sizing data will result in lower recommendation confidence, errors being replicated at scale and brands being deprioritised over time if high return rates generate negative performance signals.
The transition is already under way. A December 2025 Coresight survey found that 58 percent of US consumers familiar with AI had used or intended to use AI tools for shopping, while 29 percent said they were more likely to shop on websites offering AI agents to improve customer service.
Predictive sizing tools depend on reliable data
Retailers are increasingly adopting predictive sizing technologies to help online customers select the right size. However, the report stresses that these tools are only as effective as the data underpinning them.
“The quality of recommendations is therefore a direct reflection of the sizing intelligence from which they draw.”
Structured information such as garment measurements, grading rules and fabric characteristics must be anchored in consistent sizing standards to enable accurate recommendations, including for new products that have no historical sales data.
GLP-1 users drive demand for clearer fit information
The growing use of GLP-1 weight loss medications is also impacting apparel demand. According to a November 2025 and March 2026 Coresight survey, 70 percent of US GLP-1 users reported dropping at least one clothing size.
As consumers experience more frequent body changes and wardrobe refreshes, brands face increasing pressure to provide clearer fit guidance and more dependable and stable size recommendations.
Three-pillar framework
Coresight proposes a core three-pillar framework to future-proof sizing and fit strategies.
“A disciplined approach to size and fit standards forms the foundation of any efforts to improve customer confidence and reduce returns.”
The first pillar focuses on establishing consistent size and fit standards across categories, including clear body measurements, size definitions and grading rules.
The second pillar centres on product information management (PIM), which converts fit strategies into structured data attributes such as per-size measurements and fabric stretch characteristics. Effective PIM systems also provide insights that can continuously refine sizing recommendations.
The third pillar is the product detail page (PDP), which the report describes as the final checkpoint before purchase. Around 40 percent of US shoppers said they had abandoned an online apparel purchase because of confusing or missing product information.
To improve conversion and reduce returns, sizing information on PDPs should be specific, clear and actionable.
Sizing as business intelligence
The report concludes that sizing should be viewed as a business intelligence strategy that is shared across the value chain.
Accurate body and fit data can inform design, merchandising and assortment planning decisions, helping retailers optimise inventory, reduce waste and forecast demand more effectively.
As consumer body profiles become increasingly diverse and dynamic, brands that base sizing strategies on real customer data will be better positioned to strengthen loyalty and gain a competitive advantage.
“Traditional one-size-fits-all assumptions are no longer effective“ the report concludes, arguing that sizing intelligence is now essential as the industry enters the era of AI-enabled commerce.
To access the full report click here.
This report is made available to non-subscribers of Coresight Research through its sponsorship by apparel sizing technology company, Alvanon.