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Prompt Details

Model
Chat - (gpt-5.4)
Token size
408
Example input
[YOUR BUSINESS PROBLEM]: Monthly recurring revenue declined 23% over two quarters despite customer count staying flat.
Example output
PROBLEM STATEMENT: Monthly recurring revenue declined 23% over two quarters despite customer count staying flat. LEVEL 1 BRANCHES: A. Revenue per existing customer is declining B. New customer revenue is below target C. Revenue recognition timing has changed D. Pricing model is misaligned with value delivered LEVEL 2 BRANCHES: Under A: - Upsell conversion rate dropped from 34% to 17% - Enterprise renewal rate declined from 91% to 76% - Average contract value shrank from $840 to $650 Under B: - New customer ACV 31% below sales team forecast - Sales cycle lengthened from 42 to 67 days - Win rate against top competitor fell from 58% to 41% Under C: - Multi-year contracts now recognized differently - Professional services revenue shifted to Q3 - Refund rate increased from 2.1% to 4.8% Under D: - Freemium tier cannibalizing paid conversions - Annual plan discount too aggressive at 40% - No price increase in 3 years despite cost growth LEVEL 3 BRANCHES (Under A — highest priority): - Sales-to-CS handoff broken: no context transfer - CSM caseload too high at 87 accounts per person - Upsell trigger not defined: no playbook exists OVERLAP CHECK: Branch A and B overlap slightly on win rate. Fix: A covers existing customers only. B covers net new only. Separate the cohorts. GAP CHECK: Tree misses external factors (market contraction, competitor pricing changes). Add Branch E: External market conditions. PRIORITY: Branch A most likely holds the root cause. Customer count is stable but revenue is falling — this is a monetization failure, not an acquisition failure. Fix the upsell engine first. HYPOTHESES: A: Broken CS handoff is causing upsell failure, not product dissatisfaction. B: Sales is discounting to close rather than selling value. C: Revenue recognition change is masking real growth in underlying bookings. D: Freemium cannibalization accounts for 30%+ of conversion shortfall.
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Mece Issue Tree Builders Mckinsey Methods

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GPT-5.4
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Structure any business problem in minutes. McKinsey consultants use MECE (Mutually Exclusive, Collectively Exhaustive) on Day 1 of every strategy engagement. Now fully prompted for AI. ✓ 3-level issue tree automatically built ✓ Overlap detection included ✓ Gap analysis included ✓ Priority recommendation ✓ One hypothesis per branch For founders, operators, and strategists who need to think clearly under pressure. Copy. Paste. Replace [YOUR PROBLEM]. Done. Works with Claude, ChatGPT, and Gem
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