When we talk about size inclusivity, it’s not just about offering larger sizes – it’s about ensuring those sizes actually fit. 67% of women wear a size 14 or larger (via Michaela Leitz-Aslaksen). Yet, shopping for plus-size clothing remains an ongoing challenge, often leaving customers frustrated. Many women I know struggle to find brands that carry larger sizes, and even when they do, the fit is often off.
So, why does this continue to happen?
Why the Fit is Often Wrong
- Brands Don’t Have Accurate Customer Data
Without real, updated size charts based on customer measurements, brands can only guess what their size ranges should be. For example, a brand might assume that a size Large fits a certain set of measurements, but the reality often tells a different story.
When brands don’t have data-driven insights, they rely on assumptions, leading to a disconnect between the clothes they produce and the actual bodies wearing them. This is a major barrier to achieving true size inclusivity.
- Brands Lack Tools to Predict Which Sizes to Carry
Without accurate data, brands miss critical insights such as which styles customers in particular sizes and body shapes are actually looking for. As a result, they overlook a major market opportunity and ultimately miss out on reaching a significant portion of their audience – something that directly impacts size inclusivity.
The consequences of this gap are far-reaching:
– Most size charts are designed for an hourglass body shape, making it difficult for customers with different body types to find a proper fit. This oversight undermines size inclusivity for a large segment of shoppers.
– Linear grading (increasing each size by the same amount) fails in plus sizes because body proportions shift as sizes increase. For instance, most plus-size women aren’t hourglass-shaped, yet brands continue using this flawed grading system, which hampers size inclusivity.
How Data Transforms Sizing and Creates Better Fits
In my experience running a fashion brand that offered sizes XS to 4XL, we saw that plus-size returns were initially high. However, once we started gathering customer data, the results were clear: our linear grading system didn’t align with real customer measurements.
By adjusting our grading system based on this data, we were able to align the size chart with actual customer needs. This small change led to a significant decrease in return rates – and more satisfied customers, advancing our goal of size inclusivity.
At SizeSense.ai, we are planning to develop an analytics dashboard that reveals exactly what measurements your customers have and how to build size charts that reflect them. This will help brands make more accurate sizing decisions and take real steps toward size inclusivity.
✅ Better data = better fit = happier customers.
Size Recommendation Tools: A Game-Changer for Inclusive Sizing
Size recommendation tools should do more than just suggest a size based on arbitrary measurements. They should help brands create clothes that actually fit their customers – no matter their size or shape. This is how we can truly make size inclusivity a reality in the fashion industry.
This is the core mission of SizeSense.ai. We aim to take the guesswork out of sizing and deliver highly accurate size recommendations that are tailored to each individual’s body. By providing personalized recommendations, we help brands produce clothes that actually fit, feel great, and empower customers to feel confident in their skin.
By integrating data-driven sizing tools like SizeSense.ai, brands can enhance their size inclusivity and improve customer satisfaction. It’s about time we stop assuming and start using real data to make size inclusivity a priority.
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