Reducing Returns and Unsold Inventory: What Consumer Data Tells Us About Fit & Quality
Discover how fashion brands can slash return rates and unsold stock by decoding what consumer data reveals about fit, sizing, and product quality, turning feedback into powerful retail strategy.
Returns are rising. Stockrooms are overflowing. And fashion retailers are losing billions. Behind the scenes, poor fit and quality misalignment are often to blame. In fact, According to a McKinsey report, 63% of apparel retailers plan to adopt AI-powered inventory tools by 2025, not just to optimize logistics, but to understand why customers send products back. The answer? It's in the reviews, ratings, and return reasons.
Today’s most forward-thinking brands are diving deep into consumer feedback to decode what shoppers really want transforming data into smarter assortments and fewer wasted SKUs. Here's how they're doing it.
The True Cost of Fit & Quality Issues
According to industry reports, the majority of fashion returns boil down to two main reasons:
- Poor fit or sizing
- Low perceived quality or durability
These issues don’t just result in returns, they also lead to negative reviews, hesitant repeat purchases, and growing piles of unsold inventory that can’t be moved without heavy discounts.
And yet, brands often treat this as a product or logistics issue, when the solution lies in listening to their consumers more closely.
The Power of Consumer Data: What Shoppers Reveal About Fit & Quality
Customer feedback is more than just a star rating, it’s a goldmine of specific, actionable insight. When analyzed at scale, it reveals recurring issues, hidden patterns, and opportunities to improve.
Key Insights from Fit & Quality Feedback
- Fit Frustrations Lead to High Return Rates
Terms like “too tight,” “runs large,” or “odd fit” appear frequently in negative reviews, especially for online-first retailers. Identifying these patterns helps brands recalibrate sizing or better guide customer choices. - Material Expectations vs. Reality
Comments such as “cheap fabric” or “not as soft as pictured” often reflect unmet quality expectations, which correlate with poor product ratings and return spikes. - Style-Specific Feedback Loops
Certain silhouettes or materials generate higher satisfaction in specific markets. For example, structured blazers may receive positive reviews in colder regions but underperform in warmer climates due to discomfort.
Turning Consumer Voice Into Competitive Advantage
By acting on customer data, retailers can significantly reduce inefficiencies while boosting satisfaction.
Strategic Benefits:
- Reduced Return Rates: Brands using sentiment analysis have seen up to 18% fewer returns on optimized products.
- Faster Design Iteration: Fit-related feedback helps designers make targeted improvements, cutting development time by weeks.
- Smarter Assortment Planning: Understanding regional preferences enables localized product mixes and reducing unsold inventory.
- Increased Loyalty & LTV: Products that meet expectations result in repeat purchases and stronger brand affinity.
Conclusion
Returns and unsold inventory aren’t inevitable. They're signals, clues waiting to be decoded. Brands that pay attention to what their consumers are saying about fit and quality don’t just improve products; they future-proof their business.
About Woven Insights
Woven Insights is a comprehensive market analytics solution that provides fashion brands with real-time access to retail market and consumer insights, sourced from over 70 million real shoppers and 20 million analyzed fashion products. Our platform helps brands track market trends, assess competitor performance, and refine product strategies with precision.
Woven Insights provides you with all the actionable data you need to create fashion products that are truly market-ready and consumer-aligned.
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