The E-Commerce Basics Brands Need to Get Right

The survey from BoF Insights' "Inside Fashion & Sports E-Commerce," in collaboration with Amazon Fashion & Sports, reveals that one in five European consumers abandon online fashion or sports purchases due to lack of adequate product information. However, only 19% of brand and retailer leaders consider fixing foundational data as their top priority, while 54% focus on user experience (UX) and brand expression. AI investment follows. Critical confidence barriers for online shoppers remain around fit, materials, and quality.

Retail expert Stacey Widlitz warns that brands should not rush into adopting AI without first cleaning and organizing their data. Swiss outdoor brand Mammut is holding off on advanced technologies like AI-driven recommendations and virtual try-on until its data foundations are solid. The brand replaced technical specifications with a simple fit scale after customer research found shoppers were confused by such details.

Mammut also matches content to the product, providing full photography and video for technical jackets and simpler pages for basic T-shirts.

AI can generate visual assets at scale, such as videos, 3D models, and multi-angle variations from a single product image, reducing production costs. It can also standardize product imagery across categories and enrich product descriptions by extracting attributes from basic inputs and customer reviews. AI audits catalogues for gaps in product information, preventing early sales momentum loss.

To apply these insights, fashion and sports leaders should first assess their current data quality and ensure it is clean and organized before investing in AI. By building solid product data foundations, brands can create a better e-commerce experience that delights customers and drives higher conversion and lower return rates.