Primary users
- Online shoppers
- Sales teams
- Merchandisers
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CommerceSolution blueprint
Product Recommendation Assistant
Guides shoppers to relevant products using needs, constraints, and catalog data.
Intended outcome
A more guided buying journey based on available product facts.
Success measures are selected during discovery and validated against available baseline data. This blueprint does not promise a universal performance result.
Operating workflow
How the solution works
Ask goal and preference questions
Filter against structured catalog attributes
Explain recommendations and trade-offs
Hand off to cart or sales support
Integration scope
Systems this may connect to
Commerce platformProduct information systemInventoryCRM
Specific vendors, APIs, permissions, data contracts, and rate limits are confirmed before implementation.
Delivery
What an implementation includes
Discovery and workflow map
Users, current process, data sources, decision boundaries, exceptions, and measurable success criteria.
Solution design
Architecture, model and retrieval choices, interfaces, integrations, permissions, and human review points.
Configured implementation
The agreed application experience, automation logic, prompts, data flows, and operational controls.
Validation and handover
Representative testing, deployment documentation, administrator guidance, and prioritized improvement backlog.
Scope this solution
Adapt Product Recommendation Assistant to your process and systems.
Share the current workflow, users, data sources, decision boundaries, and systems that must connect. Surutech will propose a practical implementation scope without inventing capabilities or performance claims.