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AI agent for technical sales representatives

Technical Win-Loss Review Agent

Learn from every closed deal which technical points decide the outcome

AnalysisDecisionsIT and developmentSales
See how it worksGet access
Technical Win-Loss Review Agent: what goes in, what the agent does and what you get

What it does

After a deal closes, the notes say 'went with a competitor' and nothing about the technical reasons. After each closed deal, this agent reads the notes, demo recordings, security questionnaires and competitor mentions, and extracts the technical reasons: missing integration, a demo failure, a performance question, a compliance gap. It compares them with earlier deals to see whether a pattern is real. It checks its conclusion against at least three similar deals before suggesting a change to the pitch, demo or product feedback. It drafts the proposal with the evidence. The sales lead approves the changes. Edge case: one loss cites price in the notes but the call recording shows an integration gap, so the agent weighs the recording.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Deal closed won or lost 2 USES A TOOL Read notes, transcripts, questionnaires andcompetitor mentions 3 DOES Extract technical reasons that supported or hurt thedeal 4 USES A TOOL Compare with earlier deals of similar size andsegment 5 CHECKS THE RESULT Does the reason appear in at least three similardeals? If not: record it as a single case and keep watching.Back to step 3. 6 DOES Draft changes to the pitch, demo or product feedback 7 USES A TOOL Check the draft against the three examples for fit 8 YOU APPROVE Sales lead approves the changes 9 USES A TOOL Update the demo script or send product feedback 10 RESULT Win-loss review with evidence
Read the steps as a list
  1. Deal closed won or lost
  2. Read notes, transcripts, questionnaires and competitor mentions
  3. Extract technical reasons that supported or hurt the deal
  4. Compare with earlier deals of similar size and segment
  5. Does the reason appear in at least three similar deals?If not: record it as a single case and keep watching. Back to step 3.
  6. Draft changes to the pitch, demo or product feedback
  7. Check the draft against the three examples for fit
  8. Sales lead approves the changesThe agent waits here for your OK.
  9. Update the demo script or send product feedback
  10. Win-loss review with evidence

How it decides

It treats a reason as a pattern only when it appears in at least three similar deals, and weighs evidence from recordings above notes.

  • Require three similar deals before calling a pattern
  • Weigh call recordings above notes when they disagree
  • Separate technical reasons from price and timing reasons
  • Record each reason with the deal and date

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Deal segments to compare
  • Pattern threshold (default 3 deals)
  • Transcript sources
  • Reason categories
  • Who receives product feedback

What keeps you in control

It always asks you first

  • Sales lead approves pitch and demo changes
  • Product manager receives approved feedback

Hard limits

  • Never share customer names outside the company
  • Never change the product roadmap, only send feedback

It stops when

  • Done: the review is saved and approved changes are made
  • Stop: not enough similar deals to draw a conclusion

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensAfter losing a 120-seat deal, the agent found the technical reasons were no single sign-on with the customer's identity provider and a slow report demo. Notes said price. The recording showed the buyer asking about SSO twice. Checking earlier deals, the SSO gap appeared in 4 of 7 similar losses. The agent drafted a pitch change and product feedback. The second check on fit with all 3 earlier examples passed, and the lead approved.

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