What's Happening?
Retailers are increasingly implementing AI styling solutions to address the limitations of manual styling in e-commerce. A Forrester TEI study, commissioned by Stylitics, revealed that retailers typically style only 5-10% of their product catalogs by hand.
This leaves a significant portion of products unstyled, impacting average order value and increasing return rates. AI styling for fashion e-commerce aims to automate the creation of complete outfits and bundles from a retailer's catalog, adhering to stylists' predefined rules. This technology reads product attributes, inventory, and imagery, then uses artificial intelligence to assemble looks for product pages, email campaigns, and advertisements. The goal is to scale merchandising efforts without a proportional increase in staff, allowing stylists to focus on defining brand aesthetics and campaign pieces while AI handles the broader catalog.
Why It's Important?
The adoption of AI styling is crucial for U.S. e-commerce businesses facing challenges in catalog coverage and customer engagement. Unstyled products often lead to smaller basket sizes, as shoppers are presented with only one item rather than a complete look, contributing to decision fatigue. Furthermore, a lack of styled imagery can increase return rates, as customers may struggle to visualize how a product fits into an outfit, leading to incorrect purchases. By automating styling, retailers can achieve 100% catalog coverage, potentially increasing average order value and reducing returns. This shift allows human stylists to focus on high-value creative tasks, while AI handles the repetitive, large-scale application of styling rules, ultimately enhancing the online shopping experience and driving revenue growth for fashion retailers.
What's Next?
Retailers are expected to continue evaluating and integrating AI styling solutions, focusing on systems that allow stylists to maintain control over styling rules and outputs. The hybrid model, where human stylists define the brand's aesthetic and AI applies these rules at scale, is gaining traction. Companies will likely prioritize solutions that demonstrate clear ROI, such as increased average order value and conversion rates, as seen with Rhone's 39% increase in AOV and 10x ROI within 100 days of launching an AI styling feature. The expansion of AI-generated on-model imagery, even for products initially shot as flat lays, will further enhance the visual appeal and completeness of online catalogs. The industry will also see continued development in how personalized outfit recommendations are delivered across various customer touchpoints, including product pages, email, and social media, leveraging consumer data for tailored suggestions.
Beyond the Headlines
The widespread integration of AI styling in e-commerce raises deeper implications regarding the future of human creativity and labor in the fashion industry. While AI is presented as a tool to augment human stylists, the long-term impact on employment roles and skill sets within fashion merchandising warrants consideration. There's also an ethical dimension concerning the transparency and explainability of AI algorithms in styling decisions; retailers must ensure that the AI's 'taste' aligns with their brand identity and can be audited or adjusted by human experts. Furthermore, the reliance on AI for personalized recommendations could lead to filter bubbles, potentially limiting consumer exposure to diverse styles and trends. The balance between algorithmic efficiency and human-driven innovation will be a critical aspect of this technological evolution in retail.
