Poshmark Elevates Product Discovery and Boosts Revenue with Marqo’s AI-Powered Search
Company Overview
Poshmark is a leading social commerce platform where millions of users buy and sell secondhand fashion, accessories, and home goods. With an extensive catalog of listings updated daily by a global seller community, Poshmark connects buyers and sellers through a dynamic, mobile-first marketplace blending social engagement with shopping.
As search and discovery are central to the Poshmark experience, optimizing these interactions is critical for driving sales, improving user retention, and supporting the platform’s fast-growing seller network.
Challenge
With millions of unique listings across diverse categories, Poshmark’s traditional keyword-based search system struggled to keep up:
Difficulty interpreting style-driven or exploratory queries
boho summer dressvintage streetwear lookLimited understanding of visual style, color, and trends
High bounce rates from search results that didn’t match shopper intent
Missed cross-selling opportunities across related products and bundles
To keep pace with user expectations and stay ahead in a competitive resale market, Poshmark needed a smarter, AI-driven search solution.
Solution
In partnership with Marqo, Poshmark integrated an AI-native vector search engine designed for richer, more intuitive product discovery.
Key upgrades included:
Replacing keyword-only search with semantic, intent-based search across mobile and desktop
Training Marqo’s models on Poshmark’s rich image, category, and seller metadata to improve result accuracy and personalization
Enabling visual similarity search, so users could explore products based on style and look, not just text
Providing scalable, API-driven search enhancements with minimal engineering overhead
Results
Within just a few weeks of rollout, Poshmark saw significant improvements:
$8M↑
In incremental revenue from improved product discovery and cross-selling
22%+
Lift in add-to-cart rates for visual and trend-based searches (e.g., “retro sneakers,” “minimalist gold jewelry”)
22%↑
Lift in add-to-cart rates for visual and trend-based searches (e.g., “retro sneakers,” “minimalist gold jewelry”)
4.5%↑
Increase in average order value as users engaged with bundles and curated recommendations
Reduced search latency on mobile
Resulting in stronger engagement and lower bounce rates
What This Means
For Poshmark, modernizing search wasn’t just a backend upgrade — it directly unlocked business value. With Marqo, the platform transformed search into a smarter, more intuitive engine that helps shoppers discover the products they love faster, while driving meaningful revenue gains for both sellers and the marketplace.
Reduced shopper drop-off by minimizing zero-result searches and irrelevant product matches
Increased retention by keeping buyers engaged within the discovery journey, improving conversion and average order size
Delivered context-aware, style-focused search experiences across a diverse, community-driven marketplace
Future-proofed Poshmark’s discovery platform to support new categories, seasonal trends, and evolving customer behaviors — all through a fast, scalable integration
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