LeadHaste
IntermediateNo variables to fill — paste & go

Run a 'why we lose' analysis on your lost deals

Reclassifies your CRM's fictional loss reasons into a real cause taxonomy, finds the dominant patterns and the cheapest one to fix, arms you with buyer interview questions that get past politeness, and installs a twice-monthly loss review — turning 'we lose on price' folklore into a fixable diagnosis.

The prompt
You are a win-loss analyst who has studied thousands of lost B2B deals and knows the foundational problem: the loss reasons in your CRM are fiction. 'Price' means the value case never landed. 'Went dark' means the deal was never real or the champion got overruled. Reps record the buyer's polite excuse, not the cause — and companies then 'fix' the excuse.

Run a why-we-lose analysis:
1. Reclassification: take my lost-deal data and re-sort it into a cause taxonomy — no decision (status quo won), lost to competitor (and on what dimension), disqualified late (was never a fit), process loss (we fumbled: slow follow-up, wrong stakeholders, weak business case), and priced out (real budget mismatch, not value doubt). For each deal, state your confidence and what evidence would raise it.
2. Pattern read: the 2-3 dominant loss patterns, with any concentration by segment, deal size, competitor, rep, or stage — and the one pattern that would be cheapest to fix.
3. The interview kit: 8 questions for lost-deal interviews with buyers, designed to get past politeness ('walk me through the week you decided'), plus the ask-for-the-interview email that gets a yes from someone who just rejected you.
4. Counter-plays: for each dominant pattern, the specific change — in qualification, discovery, proof, or process — that addresses the cause, with the metric that shows it working.
5. The ongoing system: a lightweight loss-review ritual (15 minutes, twice a month) so this analysis stays alive instead of being a one-time archaeology project.

Avoid: taking CRM loss reasons at face value, blaming price by default, patterns claimed from three deals, and fixes that amount to 'reps should try harder'.

Before you write anything, interview me. Ask me these questions ONE AT A TIME, waiting for my answer each time:
1. Share your lost-deal data from the last 1-2 quarters — recorded reason, deal size, segment, stage reached, and competitor if known.
2. What do reps say in deal debriefs about why deals die — the hallway version, not the CRM version?
3. Which losses hurt most — which deals did you genuinely expect to win?
4. Who are you losing to most, including 'no decision'?
5. Have you ever interviewed a lost buyer? What happened?

Once you have my answers, run the analysis. Where my data is too thin to support a pattern, say so and tell me exactly what to start capturing.

How to use it

  1. 1

    Copy the prompt into Claude, ChatGPT, or any LLM.

  2. 2

    Export 20+ lost deals with whatever fields you have — more deals beat richer fields for pattern-finding.

  3. 3

    Answer question 2 honestly; the hallway explanations usually contain more truth than the CRM picklist.

  4. 4

    Send the interview ask to your five most painful recent losses within the week — recency drives response rates.

  5. 5

    Implement one counter-play at a time and give it a full sales cycle before judging.

Best practices

  • Interview won deals occasionally too — knowing why you win sharpens the loss taxonomy.

  • Have someone other than the deal's rep run lost-buyer interviews; buyers soften the truth for the person they rejected.

  • Treat 'no decision' as its own competitor with its own counter-play — it usually beats every named rival combined.

  • Recut the analysis quarterly; loss patterns shift when you fix one, and last quarter's diagnosis expires.

Example: what this looks like in practice

A sales leader at a 55-person procurement software company pastes 34 lost deals from the last two quarters, 60% tagged 'price'. The model reclassifies: only 4 look genuinely priced out; 13 are no-decision losses concentrated in deals that never got a second stakeholder involved, and 9 are process losses where proposals followed discovery by 12+ days. The cheapest fix: a proposal-within-5-days rule plus a multi-threading gate before any proposal. The interview kit goes to eight lost buyers; three accept, and one reveals the CFO killed the deal over an integration fear no rep had surfaced. Two counter-plays and one quarter later, no-decision losses drop by a third — and 'price' quietly disappears from the loss-reason vocabulary.

Best fit

Roles
Sales LeaderRevOpsFounder / CEO
Company size
SMB (11–50)Mid-market (51–500)Enterprise (500+)
Audience
B2B
Industries
Any industry
Works with
Any LLM
Difficulty
Intermediate

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Prompt FAQ

Frequently asked questions

Because they record the buyer's polite exit line, not the cause. 'Price' is the easiest thing for a buyer to say and the hardest to argue with — but win-loss research consistently finds that most 'price' losses trace to an unquantified business case, a missing champion, or status quo inertia. Fixing the recorded excuse (discounting) instead of the cause makes results worse, not better.