Weight Loss and Search for Smaller Clothes

The effects of the increasing use of GLP-1 diabetes drugs including Ozempic and Wegovy for weight loss have triggered an expensive problem for retailers: incorrect size curves.

Impact on Retail Size Curves

Impact Analytics, an AI-based retail planning and forecasting company, announced that size small has become the most popular size for women on Manhattan’s Upper East Side, the epicenter of non-diabetic use of GLP-1 drugs. Compared to 2022, sales of women’s button-down shirts in small sizes (XXS, XS, and S) have increased in 2024 by 12%, while sales of large sizes (XXL, XL, and L) have decreased by nearly 11%. This data has significant implications for high-end clothing retailers that primarily serve women over the age of 30 in urban areas.

Financial Ramifications

“The slimming down of America will have an enormous impact on retailers and could cost them approximately $20 million each year due to incorrect size curves. These losses will only accelerate as more people take GLP-1 drugs for weight loss,” said Prashant Agrawal, Founder and CEO of Impact Analytics. “Retailers generally make buying decisions for upcoming seasons at least six months in advance, and if this impact to the curve isn’t addressed, it will have ramifications on retail sales that will extend well into the holiday season and beyond.”

GLP-1 Drug Usage in NYC

New York City leads the world not only in fashion but also in GLP-1 drug usage. Nearly 44% of the city’s GLP-1 prescriptions go to New Yorkers who do not have a Type 2 diabetes diagnosis. This demographic skews younger and nearly 75% are female. Impact Analytics observed that GLP-1 drug prescriptions in New York City are concentrated in the affluent neighborhood of Manhattan’s Upper East Side. This usage concentration provided a unique opportunity to examine its retail impact.

Data Analysis and Findings

Impact Analytics data scientists examined multi-year sales from 2022 to 2024 at flagship stores of fashion apparel retailers on NYC’s Upper East Side. In 2022, sales of women’s button-down shirts in size small (S) were 25% of sales and have increased to 31% in 2024. A similar shift in the size curve was observed across women’s and men’s apparel. This data spurred Impact Analytics to focus their analysis on shifts in clothing size curves, reflecting changes in customers’ body sizes.

Retailer Responses and Future Outlook

“Most retailers have clung to the same size curves for years despite evidence suggesting their inaccuracy,” said Agrawal. “The impact of that will continue to erode retailer margin integrity unless immediate action is taken to update them.”

Size curves are specific to each product type and influence which sizes are included in the assortment and the quantity of each size ordered. Poor size curves directly impact the buying and allocation processes, resulting in lost sales due to stockouts and excess inventories that are subsequently marked down. For a billion-dollar business, even a 2% transition to lower sizes over the next five to ten years can significantly impact profitability, potentially turning margins negative and resulting in a reduction of tens of millions of dollars.


Impact Analytics implemented a comprehensive methodology for calculating size curves to ensure robust and consistent insights at both the product and category levels. Focus stores in specific geographies, such as NYC’s Upper East Side, were considered. The calculation of size curves started with sales data (units), supplemented with lost sales data. Lost sales were meticulously calculated at the most granular level—product x size x store x day—to ensure accuracy. Adjustments for stock-outs were made to prevent misinterpretation of size curves due to inventory shortages. This methodology included a multi-year analysis, covering 2022, 2023, and up to April 2024, allowing for the identification of insights over time.

About Impact Analytics

Impact Analytics offers a holistic suite of solutions to help retailers and brands future-proof their businesses using predictive analytics. With tools for planning, forecasting, merchandising, and pricing, Impact Analytics enables retailers to make smart data-based decisions rather than relying on last year’s figures. The company also offers tools to automate functions traditionally managed manually and to unify reporting, providing a single source of truth for data-based decisions. Founded by Prashant Agrawal, a former senior consultant at McKinsey and Boston Consulting Group, and an Adjunct Professor at Columbia University, Impact Analytics has been pioneering AI in retail forecasting, planning, and operations for nearly a decade.