Turn structured catalog details into clear recommendations, comparisons, and buying answers that stay connected to what your store actually sells.
Product finder
Catalog answer · demo store
Best matchNorthstar Goods
Sora Mini Bag
Compact · adjustable strap · coral
The Sora Mini Bag is the closest match: compact profile, adjustable crossbody strap, and enough room for daily essentials.
Answer from structured product data
Translate needs into product matches
Capture the next commercial step
Route uncertain details to a person
Where catalog search breaks
The product-aware conversation has to bridge natural language and structured data without inventing the missing specification.
A shopper asks for “something light for everyday use” while the catalog stores category, material, size, and variant fields.
Translate the intent into filters without forcing the shopper to learn the catalog.
Dimensions, features, variants, and policies are often split across product pages and support content.
Bring the relevant facts into one concise decision.
Availability, fit, delivery, and bundle questions can signal that a customer is ready to buy or needs one final confirmation.
Make the next action obvious while the decision is active.
From need to match
The agent interprets the shopper’s constraints, searches catalog data, explains the match, and captures the next buying step.
Understand
Identify the use case, size, style, feature, budget signal, or other detail that actually changes the recommendation.
Make the catalog answerable
The strongest answer combines clear product fields with the delivery, return, and buying information around the item.
Catalog source stack
Sources the team can maintain
Products
Names, descriptions, and categories
Variants
Color, size, and option details
Buying FAQs
Delivery, returns, and care
Human fallback
Live or uncertain product details
Conversational merchandising
The product conversation can narrow, compare, explain, and continue—while the catalog stays the source of truth.
Match natural customer language to the structured details that make one product more relevant than another.
Explain meaningful differences using known product and variant information instead of generic sales language.
Move from the recommendation to the product, a lead, an order request, or a human confirmation.
Launch one product-finding job
Choose a category with repeated fit or comparison questions and make that path strong before expanding across the entire catalog.
Start with a category where size, use case, feature, material, or variant consistently slows the purchase.
Make sure the product and variant details behind that decision are complete, consistent, and understandable.
Connect the policies and FAQs customers need alongside the product facts.
Decide when the agent should ask a clarifying question or route stock, pricing, and special cases to a person.
Include the fields customers use to decide: clear names and descriptions, relevant specifications, categories, variants, and any maintained availability or buying details your workflow can safely expose.
It can explain differences present in the connected product data. Keep the comparison focused on known fields and avoid claiming a winner when the shopper has not shared the deciding constraint.
Yes. Combine catalog data with website pages, FAQs, or files containing those policies so product and support context can appear in the same conversation.
Only present availability as current when the connected source supports that claim. Otherwise ask for confirmation details or route the request to a teammate rather than guessing.
Continue exploring
Use Google Sheets as a lightweight source for chatbot knowledge, product data, and repeatable support answers.
Feed structured CSV data into a chatbot workflow for product questions, repetitive support answers, and quick imports.
Handle pre-sales questions, product discovery, and lead capture with a grounded chatbot that can still escalate to a human.
Make the catalog conversational
Connect the structured details, add the buying context, and give shoppers a clear route from need to next step.
