# Home Depot Rolls AI Shelf Helpers Into 2,000 Stores After 10% Mobile Conversion Lift *The retailer's in-store assistant builds on a mobile tool that drove measurable sales uplift through product guidance.* By **Jenny Huang Goodman MPA MSc MHSA, Principal** — The Stash Edge, Hako Shikin LLC. Published 2026-09-02. Canonical: https://www.pops4.com/stash/articles/home-depot-hersheys-anthropologie-2026-09-02t03-6 Subject: Home Depot, Hershey's, Anthropologie Tags: conversational commerce, omnichannel, ai tooling, retail assist, product guidance, point of sale --- Home Depot is deploying AI product assistance across **2,000** physical stores after its mobile chatbot delivered a **10%** lift in conversion rate, according to Retail Dive. The mobile tool answered customer questions about project needs and product specs, and the retailer now extends that same conversational layer to in-store kiosks and associate tablets. The mechanics are simple: a shopper asks about grout for a wet basement or wire gauge for outdoor lighting, and the AI surfaces the right SKU with installation context. Home Depot built the assistant on its own product data and supplier manuals, training the model on the questions service desk staff field every day. The tool sits inside the existing mobile app and now also on fixed terminals near high-consideration aisles like plumbing and electrical. The **10%** conversion gain came from shortening the path between question and cart. Shoppers who engaged the mobile assistant were more likely to add a product within the session than those who searched manually or asked a floor associate. Home Depot reported the figure in its earnings commentary and attributed part of the lift to the AI's ability to cross-reference compatible products, like recommending a specific primer when a customer selected exterior paint. The in-store rollout extends the same conversational interface to moments when a phone screen is inconvenient—hands full of lumber, gloves on, or standing in front of a wall of fasteners. Associates use tablets loaded with the assistant to answer questions on the spot, and kiosks in aisles let customers type or speak their project needs. The system pulls from the same product graph, so the answers stay consistent whether the shopper is at home planning or in the store buying. For a small physical-product brand, the steal is not the AI layer itself but the structure: a single conversational guide that spans pre-purchase research and point-of-sale decision. Start with a simple chatbot on your site—Tidio, Chatbase, or a custom GPT wrapper—that answers the three questions your support inbox sees most. Train it on your product specs, compatibility notes, and use-case pairings. If you sell camping gear, teach it to recommend a sleeping bag based on temperature rating and pair it with the right pad. If you sell skincare, map ingredient concerns to product lines. Next, bring that same guide into physical retail or events. Print QR codes that open the chat interface and place them on shelf talkers, booth signage, or product hangtags. A customer scans, asks a question, and gets the same answer your online visitor would receive. You can run this for under **$100** a month with a hosted chatbot plan and a QR generator. Track which questions drive conversions by tagging chat sessions that lead to purchases, then refine the prompts and product pairings. The broader pattern is conversational commerce moving from digital-only to omnichannel. Home Depot's **10%** lift came from making expertise available at the moment of intent, whether that moment happens on a couch or in aisle seven. A small brand with clear product knowledge and a simple tech stack can run the same play, turning scattered FAQs into a single assistant that works everywhere a customer decides to buy. ## The takeaway Home Depot's AI assistant lifted mobile conversion 10% by answering product questions at intent; small brands can deploy a trained chatbot across site and retail QR codes for under $100/month. --- ## Publisher **Hako Shikin LLC** — Virginia Beach, Virginia. Founded 1997. ASI 217876 · DUNS 18-204-6339. Principal and author: **Jenny Huang Goodman MPA MSc MHSA**. - Author: https://www.huanggoodman.com/about - LLM context: https://www.pops4.com/stash/llms.txt - MCP endpoint, for AI agents: https://mcp.pops4.com/mcp - Client dashboard: https://dashboard.pops4.com/ - Catalogue: 70,000+ products, 200+ brands