Marqo vs Nosto: E-Commerce Search Platform Comparison [2026]

Marqo vs Nosto: AI-Native Search vs Bundled Personalization

Marqo and Nosto both serve ecommerce retailers, but they approach the problem from opposite directions. Nosto bundles search alongside personalization, pop-ups, and email into a broad platform. Marqo builds AI-native product discovery from the ground up. This guide breaks down what each platform does, where they diverge, and how to decide which is the right fit.

Overview

Nosto (branded as experience.AI) is a Commerce Experience Platform that bundles personalized search, category merchandising, product recommendations, dynamic bundles, A/B testing, behavioral pop-ups, and personalized email into one platform. Search was added to the platform through the acquisition of Searchnode, a keyword-based search provider. Nosto's pitch is consolidation: replace multiple point solutions with one vendor.

Marqo is an AI-native product discovery platform built from the ground up for ecommerce. Every component, from the models to the indexing to the ranking logic, was designed around the specific challenge of helping shoppers find products they will buy. Marqo delivers Commerce Superintelligence: a single intelligence layer that combines deep product understanding with behavioral data and personalization to power search, merchandising, recommendations, and conversational commerce.

The core difference: Nosto acquired search and bolted it onto a personalization platform. Marqo built search as the foundation and made every other capability an extension of product understanding.

Search Quality

Nosto's search is powered by Searchnode, which was acquired and integrated into the platform. The underlying architecture is keyword-based search enhanced with NLP and behavioral signals. Nosto markets four AI types: Predictive (behavioral ML), Semantic (query understanding), Visual (image categorization), and Generative (ChatGPT integration). In practice, these are conventional recommendation and NLP techniques repackaged under AI branding.

Nosto's search requires behavioral data to improve relevance. New products, new categories, and low-traffic queries receive less intelligent treatment until sufficient interaction data accumulates.

Marqo trains a dedicated AI for each retailer on their specific catalog. The model learns the specific vocabulary, product relationships, and purchase patterns unique to that retailer. It understands every product from the moment it enters the catalog, before any shopper has interacted with it. New products rank on merit from day one.

In published benchmarks across a dataset of over 4 million ecommerce products, Marqo's ecommerce models outperformed Amazon Titan by 38.9% on MRR (Mean Reciprocal Rank), a standard information retrieval metric.

Marqo's AI research lab has produced some of the most widely adopted models in ecommerce, including the world's most popular ecommerce embedding model and the most popular fashion embedding model on Hugging Face, with over 4.8 million monthly downloads.

Multimodal and Visual Search

Nosto offers Visual AI, but it focuses on automatic image categorization and visual similarity for personalization rather than true multimodal product search. The system categorizes product images by attributes (color, pattern, style) and uses those categories for recommendations. It does not support shopper-uploaded image queries combined with text refinement in a single search.

Marqo supports native multimodal search. Text and images are processed within the same model. A shopper can upload a photo of a jacket and add "but in a darker color" in a single query, and the system processes both signals together. Image-to-product matching, visual similarity, and cross-modal refinement all operate natively without requiring separate systems or manual tagging.

Ecommerce Focus

Nosto covers a wide surface area: search, recommendations, pop-ups, A/B testing, personalized email, and dynamic bundles. This breadth means search competes for product investment with pop-up builders and email personalization. The platform is designed for mid-market DTC brands, primarily on Shopify and Shopify Plus.

Marqo is an AI-native product discovery platform built exclusively for ecommerce. This focus shows up in every layer of the product. The models are trained on product data. The ranking logic natively incorporates commerce signals like margin, inventory levels, seasonality, and conversion rate. Marqo serves retailers across fashion, marketplaces, electronics, home goods, and specialty retail at enterprise scale.

Marqo's dedicated AI powers intelligent cross-sell and upsell recommendations that go beyond basic "customers also bought" logic. The model understands product relationships at a semantic level: it can suggest a complete outfit from a single dress query, recommend complementary furniture pieces that match a sofa's style and material, or surface accessories that pair with an electronics purchase. These recommendations are grounded in actual product understanding, not just behavioral correlation, which means they work from day one for new products and new categories without historical purchase data.

Merchandising and Ranking Controls

Nosto provides rule-based merchandising with behavioral automation. Merchandisers can boost, bury, and pin products, and the system learns from behavioral signals over time. These tools work for high-traffic queries but do not scale to the long tail.

Marqo's Commerce Superintelligence integrates merchandising signals directly into the ranking model. Retailers configure business objectives, such as margin improvement, sell-through rate, or new product exposure, and the model applies those objectives across the entire query distribution. Commercial signals are embedded in the model's training objective, not applied as rules after ranking. Merchandisers retain full manual control for high-priority queries while the AI handles the long tail automatically.

Conversational Commerce

Nosto recently announced Huginn, an agentic personalization system. Huginn is positioned as autonomous personalization agents that optimize experiences without manual intervention. It is not a shopper-facing conversational commerce agent and does not handle product discovery conversations, transactions, or post-purchase support.

Sibbi is Marqo's conversational commerce agent, built on Commerce Superintelligence. Sibbi is trained on each retailer's specific catalog and grounded in real inventory. It handles guided discovery, visual search, cross-sell, transaction completion, and post-purchase support including order tracking and returns. One agent, one conversation, from first query to post-purchase.

Customer Results

Nosto publishes case studies with modest results. Their highlighted case study, Credo Beauty, reports an 8.65% search conversion rate and 1.2M in app revenue. For comparison, Marqo customers report results at a different scale entirely: a leading fast fashion retailer reported 130M in revenue increase, Kogan reported 10.1M in incremental revenue, and Redbubble reported 11M in incremental revenue.

Marqo has delivered the largest published revenue uplifts in the product discovery category. A leading fast fashion retailer reported a 130M revenue increase following implementation. Additional results include Kogan's reported 10.1M in incremental revenue, Redbubble's reported 11M in incremental revenue, Mejuri's reported 19.84% increase in search revenue per user, and KICKS CREW's reported 17.7% uplift in conversion rate. SwimOutlet saw a 10.6% increase in search add-to-cart rate and went from sign-up to production A/B testing in less than two weeks. See the full results on our Customer Stories page.

Comparison Table

Who Each Platform Is For

Nosto works for: - Mid-market DTC brands on Shopify that want one vendor for search, recommendations, pop-ups and email - Teams that prioritize platform consolidation over best-in-class search - Retailers whose primary discovery challenge is personalization rather than search relevance

Marqo is the right choice for: - Ecommerce retailers who need discovery that drives revenue, not just returns results - Teams that want Commerce Superintelligence: product understanding combined with behavioral data powering every touchpoint - Retailers competing on discovery, personalization, and conversion where long-tail search performance matters - Organizations that want conversational commerce as a native capability, not backend automation - Mid-market and enterprise retailers who need search that scales across large, complex catalogs

Frequently Asked Questions

Is Nosto's search the same quality as a dedicated search platform?

Nosto's search was acquired through the Searchnode acquisition and integrated into the broader platform. It is a capable keyword search with NLP enhancements, but it was not built as an AI-native search engine. For retailers where search is the primary revenue driver, a purpose-built platform will typically deliver better relevance, especially on long-tail queries and new products.

How long does it take to see results with Marqo?

Marqo's product-native intelligence delivers improvements from the moment the catalog is ingested. The dedicated AI understands products before any shopper interacts with them. Behavioral data then refines results over time. SwimOutlet went from integration to live A/B testing in less than two weeks.

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

See what your catalog looks like through Commerce Superintelligence. Book a demo and we will run Marqo on your products live.