Fashion Nova Boosts Mobile Conversions by 14% with Marqo’s AI-native Search
Company Overview
A "leading multi-billion dollar online fashion retailer" is one of the fastest-growing online fashion retailers globally, known for its trend-driven apparel, accessories, and footwear targeting Gen Z and Millennial shoppers. With millions of monthly active users, a fast-moving catalog of 50,000+ SKUs, and a highly social media-driven marketing model, their digital storefront is its primary revenue channel.
With over 80% of traffic coming from mobile devices, creating a fast, intuitive, and visually driven search and discovery experience is crucial for customer acquisition, retention, and basket growth.
Challenge
As its product catalog scaled and trends shifted faster than ever, this retalier’s keyword-based search struggled with several persistent issues:
Difficulty understanding style-centric and aesthetic-driven queries
Y2K denim jacketmesh corset topLimited ability to handle vague, incomplete, or typo-prone searches (especially on mobile)
No semantic understanding of new product trends and viral styles frequently requested by customers
Missed opportunities to upsell or surface complementary items during high-intent search sessions
The retailer needed a modern, AI-powered search solution to boost mobile conversions, increase average order value, and reduce search abandonment.
Solution
In mid-2024, this retailer partnered with Marqo, an AI-native vector search engine built for eCommerce discovery. Within a few short weeks:
Marqo replaced the existing keyword search on both desktop and mobile experiences
AI-powered semantic search enabled results based on style, cut, material, color, and occasion — not just exact keyword matches
Trend and aesthetic-driven queries like “festival outfit” or “Y2K bodysuit” instantly returned relevant, shoppable results
Visual similarity and complementary product suggestions were introduced on search and product detail pages
Personalization was layered in, factoring in customer behavior, purchase history, and browsing preferences
Results
After a 6-week A/B test on 15% of site traffic, the retailer saw immediate and material improvements:
20%↑
20% increase in search revenue
14%+
14% increase in mobile conversion rates driven by faster, more accurate, and intuitive search
25%↑
25% improvement in add-to-cart rate for style-driven and descriptive searches
3.5%↑
3.5% lift in average order value powered by complementary product recommendations and upsell modules
Reduction in search abandonment rates
Particularly on mobile where vague, fast-typed queries were previously underserved
What This Means
For a fashion-forward, fast-moving brand like this retailer — where trends, aesthetics, and social-driven discovery fuel purchasing decisions — keyword search was no longer sufficient.
By integrating Marqo’s AI-native vector search, the company:
Delivered a seamless, mobile-optimized discovery experience tailored to trend-conscious shoppers
Increased core conversion and order value metrics with minimal engineering effort
Enabled dynamic merchandising and trend adaptation without constant manual intervention
Future-proofed its product discovery and upsell strategy for a hyper-competitive, mobile-first eCommerce market.
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