Bloomreach published a detailed guide to AI shopping assistants for ecommerce, framing the technology as no longer optional for retailers (Bloomreach Blog). The guide distinguishes AI shopping assistants from traditional rule-based chatbots: modern assistants understand shopper intent, access live product catalog data, and maintain conversation context, enabling product discovery, guided recommendations, cart assistance, and order support (Bloomreach Blog).
The guide identifies six evaluation criteria for merchants: deep catalog and merchandising integration, use of personalization signals, proactive versus reactive engagement, platform and integration fit, measurement and attribution, and omnichannel capabilities (Bloomreach Blog). For commerce practitioners, this framework addresses a critical gap—how to move beyond demo-stage capabilities to production-ready implementations that tie assistant interactions to measurable business outcomes. Bloomreach highlights its own Loomi conversational agent for enterprise retailers, citing a case study where The Foschini Group achieved a 35.2% higher conversion rate, 39.8% higher revenue per visit, and 28.1% reduction in exit rate among shoppers who interacted with the agent during Black Friday, and where a large US office supplies retailer drove $10M in incremental annual revenue (Bloomreach Blog).
The guide segments solutions by merchant type and tech stack—from Shopify-native tools like Rep AI and Manifest AI for small to mid-market brands, to platform-agnostic enterprise options, reflecting the maturation of the AI shopping assistant category in 2026 (Bloomreach Blog).