Magic Quadrant for Search and Product Discovery

Market Overview

Market Evolution

• GenAI UI: Many vendors have experimented with new GenAI-based conversational UIs for discovery. Widely established and accepted patterns remain elusive. The whole industry is approaching an inflection point in the evolution of new discovery UIs (see GenAI Product Discovery Requires a New Digital Commerce UX). New UIs are hard to establish, and certain large vendors are likely to lead the way to general acceptance of hybrid visual and conversational discovery UIs.
• Guided selling assistants: Gartner has consolidated a fragmented set of use cases into guided selling assistants, a customer-facing offering that enables self-service product discovery and recommendations (see Hype Cycle for Digital Commerce, 2026). These may be separate customer journeys from a core search experience (typically at the category or even product level), but we increasingly expect them to be integrated into the core discovery experience.
• GenAI and agentic commerce: The emergence of conversational answer engines such as ChatGPT, Google Gemini, and Perplexity.ai, and the use of these platforms to discover products, is increasingly replacing traditional web search engines and even digital commerce catalogs. This shift from answer engine to agent may present an existential threat to the existing S&PD market and the traditional worldwide web of “pages.” However, at present, the majority of traffic to commerce sites and subsequent transactions are handled by human interaction, not AI agents. Organizations that need to provide and retain control over optimal first-party customer experiences and data will require discrete, brand-level S&PD experiences to reflect the new answer engine capabilities, at least in the medium term.
• SEO evolution into GEO and AEO: With product category and detail pages (PDPs) becoming landing pages, recommendations and other discovery elements must be optimized within those page types. These also need to become better at providing the content underpinning GenAI: SEO becomes GEO, AEO, and agent-oriented content (AOC), as content descriptions become more natural language and descriptive for easier LLM consumption. As GenAI platforms themselves crawl and interact with websites, having better product data will also remain critical.
• Catalog enrichment: Poor catalog data remains a problem for S&PD clients, particularly in B2B environments. While Gartner’s best practice places the management and enrichment of product data firmly in the product information management function, we recognize this is not always possible and does not always lead to improved search retrieval outcomes. Several S&PD vendors now include product catalog enrichment capabilities as part of their offerings.
• Algorithmic merchandising AI: This is increasingly automating merchandising, especially by using customer behavior and product conversion data. However, many organizations still seek to retain curated/visual merchandising as an important tool, as AI has yet to access business strategy, tactics, or the contents of warehouses.
• Retail media networks: The growth of retail media networks is impacting S&PD by requiring the facilitation of sponsored product placements. While curated merchandising can cover some of these requirements manually, organizations are increasingly seeking automation for sponsored product placements, integration with third-party network APIs, and the ability to auction placements.
• Live proof of concept (POC): Most organizations now demand to run some form of S&PD product A/B test as a POC, using tags to capture customer search data against an incumbent solution or against direct competitors. We now evaluate vendors’ ability to support this capability.
• Free API calls: More recently, many vendors have abandoned charging for subsequent autocomplete and search-as-you-type API calls, as this pricing model proved unpopular. Now, only the first query letter or letters (depending on the algorithm) are used to determine pricing.