Win/Loss Review — Fintech
Extract transferable lessons from a closed deal. Purpose-built for fintech contexts.
A structured sales team prompt for follow-up & pipeline: extract transferable lessons from a closed deal, tailored to a fintech product where trust, security, and compliance dominate the conversation. It walks the model through a proven process with an explicit quality bar, and delivers a win-loss writeup.
The prompt
Variables to fill in: {{deal_or_pipeline}}{{context}}
You are a revenue operations mentor obsessed with pipeline truth and disciplined follow-through. I need your help in the context of a fintech product where trust, security, and compliance dominate the conversation.
TASK: Extract transferable lessons from a closed deal.
DELIVERABLE: Produce a win-loss writeup: timeline, turning points, why we won/lost in the buyer's words, and two process changes to make.
PROCESS:
1. Review the inputs below. If anything critical is missing or ambiguous, ask me up to three clarifying questions before producing the deliverable.
2. Work from the actual pipeline facts in the inputs; call out wishful thinking wherever you see it.
3. Every touch and every review must produce a next action with an owner and a date.
4. Prefer honest, specific communication over activity theater.
5. Produce the deliverable in a clean, skimmable format I can use directly.
QUALITY BAR:
- Follow-ups add value each time — a reason to reply, not a 'just checking in'.
- Forecast language distinguishes evidence from hope.
- Templates stay short enough that a rep will actually use them.
INPUTS:
- The deal(s) in question: stage, value, last interaction, next step if any: {{deal_or_pipeline}}
- Anything relevant: buyer behavior, internal pressure, quarter timing: {{context}}Try it out
Open in Playground →Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.
Fill in the variables
How to use
- 1Fill in the {{deal_or_pipeline}}, {{context}} variables with your real details — specifics in, specifics out.
- 2Paste the prompt into ChatGPT, Claude, Gemini, or any capable model.
- 3Answer the clarifying questions it asks; that step is what makes the output fit your situation.
- 4Iterate on the deliverable: ask for alternatives, tighter versions, or a different angle on any section.
Pro tips
- If the output feels generic, add more concrete detail to the inputs — names, numbers, and constraints sharpen everything.
- Works well in a thread: keep the conversation going to refine a win-loss writeup.