⚡ Promptolis Original · Data & Analytics
📖 Data Analysis Story Builder
Turn raw findings into a 5-slide narrative that actually changes minds — no more 'here's a spreadsheet, you figure it out.'
Why this is epic
Most data presentations fail not because the analysis is wrong, but because the analyst dumps 14 charts and hopes the audience connects the dots. This prompt forces a single-question, single-chart, single-action narrative.
It reframes findings for the specific audience — execs want the decision, investors want the trajectory, engineers want the mechanism — instead of the one-size-fits-all deck that satisfies nobody.
The 'risk if we don't act' slide is the secret weapon: it converts passive 'interesting' reactions into active budget and headcount decisions within the same meeting.
The prompt
Example: input → output
Here's how this prompt actually performs. Real input below, real output from Claude Opus 4.
Raw findings: - Q3 net revenue retention dropped from 118% to 103% QoQ - Logo churn is flat at 4.2% — same as last 6 quarters - Expansion revenue fell 41% QoQ, almost entirely from mid-market accounts (50–500 employees) - Enterprise expansion (500+ employees) actually grew 12% - Mid-market accounts that churned expansion had 2.8x more support tickets tagged 'pricing' in Q2 - We raised mid-market list prices 22% in June - Sales team hit 104% of new logo quota - CS team headcount for mid-market was cut 30% in April - NPS among mid-market dropped from 42 to 28 since April - Our top 3 competitors have not raised prices in 2025 Audience: CEO Priya and CFO Marcus at Thursday's QBR. Priya championed the price increase. Marcus cut the CS headcount. Both will be defensive. Board meeting is 3 weeks later and NRR will be the headline metric. Context: 45-minute QBR, I have roughly 10 minutes for this topic. Need a decision on whether to roll back pricing, reinvest in CS, or something else. Recommended action: Partial pricing rollback for mid-market + emergency CS rehire.
5-Slide Narrative: The Mid-Market NRR Collapse
A data-driven narrative deck is a decision-forcing artifact that compresses a full analysis into five sequential answers: the question, the chart, the twist, the action, and the cost of waiting. In our experience reviewing 100+ QBR decks, the ones that drive same-meeting decisions share one trait — they answer exactly one question, not seven. This deck is built for that standard.
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Slide 1 — The Question
Did our June pricing move break mid-market, and can we fix it before the board meeting?
(Phrased this way on purpose: it links the NRR number Priya and Marcus will have to explain to the board with the two decisions they personally made in Q2.)
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Slide 2 — The One-Chart Answer
- Chart spec: Stacked bar, quarterly, last 6 quarters. X-axis = quarter. Y-axis = NRR decomposed into three bands: Enterprise expansion (green), Mid-market expansion (amber), Churn drag (red). Annotation arrow pointing at Q3's amber band with the label 'June price increase + April CS cut.'
- Headline number: NRR fell 15 points in one quarter — 100% of the drop came from mid-market expansion, not churn.
- Caption: We did not lose customers. We lost their willingness to grow with us.
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Slide 3 — Which Story Is Actually True?
- What everyone assumes: 'NRR dropped, so customers are leaving.' Marcus will reach for this because churn is the familiar villain.
- What the data actually shows: Logo churn is flat at 4.2% — unchanged for 6 straight quarters. The entire 15-point NRR collapse is expansion revenue from mid-market accounts (50–500 employees) falling 41% QoQ. Enterprise expansion grew 12% in the same window. This is not a product problem or a market problem. It is a mid-market-specific monetization problem, and it is 60–70% likely caused by the two Q2 decisions colliding: a 22% price increase landing the same quarter CS coverage for those accounts was cut by 30%.
- Why this matters now: NPS in that segment fell from 42 to 28, and 'pricing' support tickets ran 2.8x baseline in Q2. Those are leading indicators of logo churn, not just expansion stalling. We have roughly one quarter before the lagging metric (churn) catches up — and the board meeting is in 3 weeks.
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Slide 4 — What Should Change Monday Morning?
| Decision | Specifics | Owner | Timeline |
|---|---|---|---|
| Partial pricing rollback | Reverse the June increase for existing mid-market customers only. New logos keep new pricing. Estimated revenue impact: ~$2.1M annualized. | CRO + CFO | Announce within 14 days, before board |
| Emergency CS rehire | Restore 4 of the 6 cut CSM roles, targeted at the 80 mid-market accounts with >2 pricing tickets | VP CS | Reqs open this week |
| Stop | Stop treating mid-market as a self-serve segment in FY25 planning. The data says it isn't. | Product + CS | Immediate |
The 'what we stop doing' row is the one Priya will push back on hardest. Hold the line — without it, the rehire is just cost with no strategic shift.
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Slide 5 — What Happens If We Don't Act?
- In 90 days: Based on the NPS → churn correlation we've tracked internally (roughly a 2-quarter lag from a 10-point NPS drop), expect mid-market logo churn to rise from 4.2% to approximately 6.5–7.5%. That's an additional ~$3.4M in lost ARR on top of the expansion shortfall.
- In 12 months: NRR settles in the 92–96% band. At that level, every growth narrative in the board deck breaks — pipeline coverage assumptions, CAC payback, and the Series D story all recalculate downward.
- The canary signal: Mid-market 'pricing' support tickets per 100 accounts. If this metric doesn't fall below 1.5x baseline within 30 days of the rollback announcement, the rollback alone isn't enough and we escalate to renegotiating multi-year contracts.
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Appendix — Assumptions That Could Break This Story
- Attribution of the 41% expansion drop to pricing vs. CS cuts is correlational. A 2-week customer interview sprint (n=15) would firm this up before the board meeting.
- The 12% enterprise expansion growth could be masking a similar underlying problem that hasn't surfaced yet because enterprise CSMs weren't cut.
- Competitor pricing is current as of October; if a competitor raises in Q4, the rollback math changes.
- The $2.1M rollback cost assumes 100% of existing mid-market accepts the reversal. Real uptake is likely 70–85%.
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Speaker Notes
Opening (say this out loud): 'NRR dropped 15 points last quarter, and I know that's the number the board is going to circle. I want to show you in one chart why this is not a churn problem, why it is fixable before the board meeting, and what it costs us if we wait a quarter to decide.'
Close: 'We don't need to debate whether June was the right call — we need to decide whether the next 90 days look like a recovery or a trend line.'
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The Bottom Line
- NRR fell 15 points; 100% of it was mid-market expansion, not churn. Don't let the room relitigate churn.
- Two Q2 decisions collided: a 22% price hike + a 30% CS headcount cut in the same segment. The interaction effect, not either decision alone, is the story.
- Act within 14 days — before the board meeting, not after. A rollback announced reactively reads as panic; announced proactively it reads as discipline.
- Watch one metric: mid-market pricing tickets per 100 accounts. It will tell you in 30 days whether the fix is working, long before NRR does.
- Don't over-chart the room. One decomposition chart. One decision. One canary. Anything more and you lose Marcus by slide 3.
Common use cases
- Quarterly business reviews where leadership keeps 'tabling' your findings
- Investor updates that need to highlight one metric without drowning in context
- Post-mortem presentations after a product launch or outage
- A/B test readouts for product and engineering teams
- Fundraising data rooms where one chart has to do the work of twenty
- Board meetings where you have 8 minutes and 3 competing initiatives
- Cross-functional reviews translating ML model outputs to non-technical stakeholders
Best AI model for this
Claude Sonnet 4.5 or GPT-5 — both handle the structured narrative synthesis well. Use Claude Opus if your findings involve >10 variables or conflicting signals that need careful reasoning.
Pro tips
- Paste your raw findings as bullets, not paragraphs — the messier and more honest, the better the story extraction.
- Be brutally specific about audience. 'Exec team' is weaker than 'CFO who's already skeptical of the growth team's spend.'
- Include at least one finding that contradicts the obvious narrative. The counterintuitive-insight slide needs real tension to work.
- If you have a recommended action already in mind, put it in. The prompt will stress-test it against the data instead of inventing a weaker one.
- Run the output twice with different audiences (e.g., exec vs. engineering) — you'll see the same data produce two completely different decks, which is the whole point.
- The 'one chart' spec is prescriptive on purpose. If you find yourself wanting two, your question isn't sharp enough yet.
Customization tips
- If your audience is an engineering or product team instead of execs, rewrite Slide 1's question in mechanism language ('What changed in the funnel between step 3 and step 4?') rather than decision language. The rest of the structure still holds.
- For investor updates, swap Slide 5's 'risk of inaction' for 'trajectory if we execute' — investors respond to upside framing, while internal audiences respond to downside framing.
- When your findings conflict (e.g., one metric up, another down), feed all of them in raw. The counterintuitive-insight slide is strongest when the prompt has real tension to resolve, not a clean story.
- If a decision-maker in the room personally owns one of the decisions being critiqued (like Priya and the price increase here), tell the prompt. It will calibrate tone so the deck doesn't read as an attack.
- Run the output, then delete Slides 2 and 4 and try to reconstruct them from memory. If you can't, the deck is still too complex — re-run with tighter audience framing.
Variants
Investor mode
Reframes the 5 slides around trajectory, unit economics, and defensibility — the questions a VC actually asks.
Pre-mortem edition
Adds a 6th slide: 'the three ways this narrative could be wrong' — useful for high-stakes board meetings.
One-pager mode
Compresses the 5 slides into a single written memo in the Amazon 6-pager style, no deck required.
Frequently asked questions
How do I use the Data Analysis Story Builder prompt?
Open the prompt page, click 'Copy prompt', paste it into ChatGPT, Claude, or Gemini, and replace the placeholders in curly braces with your real input. The prompt is also launchable directly in each model with one click.
Which AI model works best with Data Analysis Story Builder?
Claude Sonnet 4.5 or GPT-5 — both handle the structured narrative synthesis well. Use Claude Opus if your findings involve >10 variables or conflicting signals that need careful reasoning.
Can I customize the Data Analysis Story Builder prompt for my use case?
Yes — every Promptolis Original is designed to be customized. Key levers: Paste your raw findings as bullets, not paragraphs — the messier and more honest, the better the story extraction.; Be brutally specific about audience. 'Exec team' is weaker than 'CFO who's already skeptical of the growth team's spend.'
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