Answer pre-purchase questions to convert hesitant shoppers with AI

Shoppers with a question about sizing, compatibility, ingredients or delivery dates often leave instead of asking. Basic chatbots answer from a static FAQ, live agents aren't online at 11pm, and email replies arrive after the shopper has bought elsewhere. Every unanswered question is a lost sale, and the questions themselves rarely make it back to the team that writes the product pages.

1. Install Yuma Sales AI on your Shopify storefront (a two-click install). It runs as its own widget on product pages and reads your live catalog, inventory, product specs, reviews, policies and past support history, so there's no FAQ to build. Anything that needs a human escalates to your helpdesk with the full conversation.
2. Add sales guidance to your Yuma Handbook: brand voice for pre-purchase conversations, when to recommend add-ons, and discount rules (who can get a code, how much, and how often).
3. Connect Claude to Yuma through the Yuma MCP and run the pre-purchase prompts (https://docs.google.com/document/d/1cCbBuXSzwhzGCdZFdMO5xfUkfPqKhASaRtEV-iBRTn0/edit?usp=sharing) on the last 30 days of chat conversations. Find the top questions by product and the ones that most often end without a purchase.
4. Fix your product pages. Add the answers to the most common questions (size guides, compatibility, ingredients, delivery dates) so fewer shoppers need to ask at all.
5. Write tests for the tricky cases before you go live: an out-of-stock variant, a compatibility question your catalog can't answer (the agent must not guess), a shopper fishing for a discount, and someone stuck between two sizes.
6. Let the built-in split test run. Every Sales AI deployment is tested against a control group without Sales AI by default, so after two to four weeks you can compare conversion rate, revenue per visitor and average order value against shoppers who never saw it.
7. Review every week: conversations that ended without a purchase, answers the agent was unsure about, and how discount codes were used.
8. Expand once results hold: turn on cart recovery nudges and product recommendations. If your store has no support chat yet, add Yuma Chat AI so the same assistant handles order questions and spots upsell moments mid-conversation, all from one Handbook.

Shoppers get an accurate answer in seconds at the moment of doubt, instead of leaving the site to search or waiting on an email reply. In Yuma's A/B tests, merchants have seen up to an 18% lift in revenue per visitor and up to a 6% lift in conversion rate. The questions shoppers ask also become a prioritized list of product page fixes for the merchandising team.

Never let the agent guess on compatibility, allergens, ingredients or sizing beyond what your catalog says; route those to a human with the full conversation. Cap discount codes and make them single-use so the widget doesn't train shoppers to ask for money off. Read results from the control group comparison rather than before and after, so seasonality doesn't distort them, and split results by desktop and mobile. Try it on your own store with a 30-day free Yuma trial (https://yuma.ai/support-ai).

Answers are only as good as your catalog data; missing specs lead to escalations instead of answers. Lift varies with traffic, category, price point and how complete your product pages are, and the figures above are strong results rather than guarantees. Discounts can pull forward sales that would have happened at full price. Brands with regulated claims, such as supplements or skincare, need strict Handbook rules on what the agent may say.