From the manufacturer to the consumer and back again. Returnalyze empowers you with full visibility in one dashboard and a set of tools to see and respond to your consumers’ behaviors:
From the manufacturer to the consumer and back again. Returnalyze empowers you with full visibility in one dashboard and a set of tools to see and respond to your consumers’ behaviors:
Adrianna Papell® is a global leader in occasion wear, specializing in luxurious, intricately designed dresses for bridal and social events. Since 1980, the brand's mission has been to help women feel beautiful and confident, from weddings to special celebrations.
Operating in social occasion wear - a category with inherently high returns - Adrianna Papell faced return rates exceeding 60% as customers often purchased multiple dresses for events and returned all but one. The brand recognized that even modest improvements in return rates could significantly impact profitability and operational efficiency.
Before Returnalyze, Adrianna Papell lacked:
Visibility beyond raw return data into specific reasons driving returns
Ability to distinguish between unprofitable high-return styles and profitable ones
Insights to optimize product descriptions, size guidance, and category focus
Data-driven intelligence to inform inventory decisions and assortment strategy
Adrianna Papell needed deeper insights to transformreturn data into actionable business intelligence. They partnered with Returnalyze to understand not just what was being returned, but why, and which actions would have the greatest impact on profitability.
Returnalyze's proprietary algorithms analyze millions of return events, moving beyond simple return codes to surface actionable insights that improve conversion and prevent returns. The platform enabledthe merchandising team at Adrianna Papell to:
Identify sizing and fit issues by product category, price point, and manufacturer
Distinguish between high-return styles that wereunprofitable versus still profitable
Analyze return patterns across dress categoriesversus lower-return categories like sportswear
Make informed decisions on product descriptions, color assortments, and inventory strategy
Returnalyze transformed Adrianna Papell's approach to returns from reactive returns cost management to proactive profit optimization. Adrianna Papell
Data-driven intelligence that separates profitable high-return styles from problematic ones
Strategic insights informing inventory, assortment, and category growth decisions
Improved customer experience through better fit guidance and product information.
Within one year of implementation, Returnalyze delivered measurable improvements:
Root-cause returns intelligence enabled immediateaction across high-impact areas. By adjusting size guidance on product pages, refining descriptions for fit-sensitive styles, and focusing on lower-return colorways, Adrianna Papell achieved a 10% reduction in returns.
Returnalyze revealed that a high-volume, high-return dress Adrianna Papell had discontinued was still profitable despite its return rate. This insight enabled them to reintroduce the style, focusing on colors with lower return rates for more profitable management.
Return data bSTRATEGIC CATEGORY GROWTHy category showed sportswear had significantly lower return rates than dress categories. These insights helped Adrianna Papell make strategic decisions about which categories to grow and where to focus resources.
By identifying specific sizing and fit issues driving returns, Adrianna Papell adjusted product descriptions and size guidance, helping customers make better purchase decisions and reducing fitrelated returns.
Analysis across manufacturers and price points revealed patterns that informed sourcing decisions and quality control, enabling more targeted improvements where they mattered most.