Large catalogs create hesitation when buyers cannot compare options quickly.
Octobot turns this recurring friction into a guided support conversation with clear limits and follow-up.
Product recommendations
AI Product Recommendation Chatbot
A useful recommendation starts with the customer's need, not a generic product push.
RecommendationsCatalogBuyer intent
Who it is for
Built for stores and b2b catalogs where customers need help selecting between products, plans, or variants..
The team wants faster answers without losing quality control.
Octobot turns this recurring friction into a guided support conversation with clear limits and follow-up.
Human agents need better context when the conversation cannot be automated.
Octobot turns this recurring friction into a guided support conversation with clear limits and follow-up.
Use cases
What the page should help a US prospect understand.
Search intent: Commercial. The content focuses on the buying question behind this keyword, not a translated French page.
Ask qualifying questions and suggest relevant options from documented product information.
This is positioned as a real workflow, with measurable value and a human fallback when needed.
Ask for missing context before handoff.
This is positioned as a real workflow, with measurable value and a human fallback when needed.
Use conversation data to improve support content and workflows.
This is positioned as a real workflow, with measurable value and a human fallback when needed.
Implementation
How this workflow becomes useful instead of generic AI copy.
1
Define the first safe scope
Use product attributes, comparison pages, compatibility notes, and buying guides.
2
Set a handoff rule
Do not recommend items outside documented constraints or availability.
3
Review the outcome weekly
Track unanswered questions, handoff reasons, topic volume, and customer feedback.
Measurement
What a buyer should expect to improve.
Product questions become guided buying conversations.
This outcome can be reviewed through conversations, handoff reasons, topic trends, and customer feedback.
Cleaner handoffs to the team.
This outcome can be reviewed through conversations, handoff reasons, topic trends, and customer feedback.
Better visibility into recurring customer friction.
This outcome can be reviewed through conversations, handoff reasons, topic trends, and customer feedback.
Test Octobot with your real customer questions.
Start with your current support content, review the first answers, and keep human handoff for important conversations.