ThinkWithPrompt by SynotticThinkWithPrompt

Recommend the right product to a customer from my spec sheet

Answers customer questions by matching their needs to your catalog's specs, compatibility, and limits, without guessing.

Customer SupportRTFStandardFill-in Template

The prompt

Help me answer a customer's product question using only my product data. Customer's question: [PASTE - e.g. "Which walker supports 350 lbs and folds for a car trunk?"] What I know about the customer: [needs, measurements, current product they own, constraints] Product data: [PASTE spec sheet or catalog rows - model, weight capacity, dimensions, compatible parts/batteries/accessories, warranty, price] Our policies: [returns, warranty, when to escalate] Steps: 1. Restate the customer's must-haves and nice-to-haves. 2. Filter the catalog against the must-haves (capacity, size, compatibility). Show which products pass and why the others fail. 3. If they asked about replacement parts or batteries, match by the exact specs in my data (model numbers, voltage, connector, capacity) and list every product each part is compatible with. 4. Note any trade-offs between the options that pass. Return: - A short, friendly reply I can send the customer. - An internal table: Product | Meets must-haves? | Key specs | Notes. - Anything missing from my data that I need to check before answering, marked [CONFIRM]. Rules: never assume a spec or compatibility that isn't in the data, and never round a capacity limit in the customer's favor. For medical, mobility, or safety products, include a line suggesting they confirm fit and suitability with their clinician or the manufacturer.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • needs, measurements, current product they own, constraints
  • returns, warranty, when to escalate
  • CONFIRM

How this prompt is built

This prompt follows the RTF structure (Role, Task, Format). RTF tells the model who to be, what to do and what shape the answer should take. It is the quickest structure that still gives noticeably better results than a bare request.

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