What Is Marqo?

What Is Marqo?

Marqo is the AI-native product discovery platform that delivers Commerce Superintelligence for enterprise retailers. It trains a dedicated AI for each retailer that understands every product in their catalog, then combines that product intelligence with behavioral data and personalization to power search, merchandising, recommendations, conversational commerce, and post-purchase.

Marqo powers some of the largest ecommerce retailers in the world, including Fashion Nova, Mejuri, KICKS CREW, Kogan, and SwimOutlet. The platform has delivered over $130 million in attributed revenue uplift for a single retailer and consistently drives double-digit improvements in conversion, revenue per visitor, and add-to-cart rates across fashion, electronics, footwear, sporting goods, and jewelry.

What Marqo Does

Marqo improves how shoppers discover and purchase products across an ecommerce site. The platform powers every touchpoint in the commerce experience from a single intelligence layer:

Search that understands what shoppers mean, not just what they type. Natural language, visual queries, vague descriptions, and style references all return relevant results because the AI understands the products, not just the keywords.

Merchandising where teams set strategic priorities and the AI executes them at scale. Margin, inventory levels, seasonal strategy, and promotional objectives are embedded in the ranking model. Merchandisers define intent. The AI applies it across millions of queries, including the long-tail queries that manual rules could never cover.

Recommendations powered by genuine product understanding. The AI knows what complements, what substitutes, and what completes a purchase, based on real product relationships, not just co-purchase history. This means recommendations work for new products from day one.

Conversational commerce through Sibbi, the first commerce agent built on Commerce Superintelligence. Sibbi guides shoppers from intent to purchase through natural language and visual search, cross-sells based on real product relationships, and completes transactions within the conversation. Every response is grounded in real inventory. No hallucinations. No phantom products.

Post-purchase where the same agent that helped a shopper find the right product also answers "where is my order?", processes returns, and suggests what to buy next. One agent, one conversation, from first query to post-purchase.

How Marqo Works

At the core of Marqo is product-native intelligence. The platform trains a dedicated AI for each retailer that derives its understanding from the products themselves: images, descriptions, attributes, and catalog relationships.

There are two architectures for ecommerce AI. Behavior-trained systems learn what shoppers do and use that to rank products. Product-native systems start by understanding what products are, then layer behavioral data and personalization on top to continuously sharpen results. Both use behavioral data. The difference is the starting point. Behavior-trained systems depend on accumulated clicks to function. Product-native systems understand every product from day one and get stronger as behavioral data flows in.

This means:

New products work immediately. A seasonal drop, a new brand partnership, or a one-of-a-kind resale item is understood and surfaced the moment it enters the catalog. No warm-up period. No dependency on accumulated clicks.

Long-tail queries return relevant results. For most retailers, 70-80% of the catalog has insufficient behavioral signal. Marqo's product understanding means the entire catalog is discoverable, not just the bestsellers with enough click history.

Visual understanding is built in. The AI recognizes visual attributes: silhouette, texture, pattern, color palette. When a shopper searches "elegant evening dress" by text, the results reflect visual elegance, not just products with "elegant" in the title. When a shopper uploads a photo and adds "but in navy," the system processes both signals together.

Commercial signals are in the model. Margin, inventory priority, and seasonal strategy are part of how the AI ranks products. The system optimizes for what the shopper wants and what the business needs simultaneously.

What Problems Marqo Solves

Retailers spend heavily on customer acquisition. The most expensive failure in retail is acquiring traffic and then losing it to a search experience that cannot understand what the shopper wants.

The cold start problem. Most ecommerce AI requires weeks of accumulated click data before new products rank well. During that window, new arrivals are invisible. Marqo understands products from day one.

The long-tail gap. For most retailers, only a fraction of the catalog generates enough behavioral signal to rank well. The rest is ranked on insufficient data or manual rules. Marqo's product understanding covers the entire catalog.

The merchandising burden. Behavior-driven ranking systems require constant manual intervention: boost this, bury that, pin these, override those. Merchandising teams spend their time managing rules instead of setting strategy. Marqo's Commerce Superintelligence lets the AI execute strategy while merchandisers focus on direction.

Fragmented discovery. Most retailers manage separate systems for search, recommendations, and conversational commerce. Each operates on different data and different models. The shopper experience is inconsistent. Marqo powers everything from a single intelligence layer.

Commerce Superintelligence

Commerce Superintelligence is Marqo's intelligence layer for retail. It is defined by six architectural requirements:

1. 1Product-Native Intelligence — a dedicated AI per retailer that understands products from their content, combined with behavioral data and personalization
2. 2Full-Journey Intelligence Continuity — the same AI powers discovery through post-purchase
3. 3Unified Cross-Modal Retrieval — text, image, and product attributes in a single model
4. 4Zero-Shot Product Competency — new products work from day one
5. 5Embedded Commercial Optimization — margin, inventory, and strategy in the model, not as rules
6. 6Visual Product Reasoning Across the Full Stack — visual understanding in text search, recommendations, and conversation, not just image search

A detailed breakdown of each requirement is available in Marqo's Blueprint for Commerce Superintelligence.

Results

Commerce Superintelligence is running in production at some of the world's largest retailers:

• Fashion Nova: $130 million in attributed incremental revenue
• Mejuri: +19.8% increase in search-driven conversion
• KICKS CREW: +17.7% conversion rate improvement
• Kogan: $10.1 million in incremental revenue
• SwimOutlet: +10.6% increase in search ATC rate
• Archive/North Face Renewed: +17.1% increase in add-to-cart rate

All results validated through controlled production A/B tests.

Getting Started

Marqo is designed for speed to measurable impact. Deployment begins with the Marqo Pixel, a lightweight drop-in component that captures shopper behavior signals. Pre-built connectors support Shopify, Adobe Commerce, and Salesforce Commerce Cloud. In published case studies, retailers have progressed from initial integration to live production A/B testing within days. Results in 14 days, not months.

About Marqo

Marqo was founded in San Francisco in 2022 by Tom Hamer (CEO) and Jesse Clark (CTO). The company is backed by Lightspeed Venture Partners and Blackbird Ventures. Marqo is the AI-native product discovery platform delivering Commerce Superintelligence for enterprise retailers worldwide.

Frequently Asked Questions

What is Marqo?

Marqo is the AI-native product discovery platform that delivers Commerce Superintelligence for enterprise retailers. It trains a dedicated AI for each retailer that understands every product in their catalog, then combines that product intelligence with behavioral data and personalization to power search, merchandising, recommendations, conversational commerce, and post-purchase.

How is Marqo different from other ecommerce search platforms?

Most ecommerce search platforms derive intelligence primarily from behavioral data: clicks, conversions, and past purchases. Marqo starts with product-native intelligence, understanding every product from its content, then layers behavioral data on top to continuously improve. This means new products work from day one, the entire catalog is discoverable, and commercial signals like margin and inventory are built into the ranking model rather than applied as manual rules.

What is Commerce Superintelligence?

Commerce Superintelligence is Marqo's intelligence layer for retail. It combines deep product understanding with behavioral data and personalization to power every commerce touchpoint from a single platform. It is defined by six architectural requirements including product-native intelligence, unified cross-modal retrieval, zero-shot product competency, and full-journey intelligence continuity.

What is Sibbi?

Sibbi is the first conversational commerce agent built on Commerce Superintelligence. It is trained on each retailer's specific catalog, grounded in real inventory, and handles the full shopper journey: guided discovery, visual search, cross-sell, transaction completion, and post-purchase support including order tracking and returns.

What results has Marqo delivered?

Published results include Fashion Nova's $130 million in attributed revenue uplift, Mejuri's 19.8% increase in search-driven conversion, KICKS CREW's 17.7% conversion rate improvement, Kogan's $10.1 million in incremental revenue, and SwimOutlet's 10.6% increase in search ATC rate. All results validated through controlled production A/B tests.

Book a demo to see Commerce Superintelligence in action on your catalog.