Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
npx mdskills install sickn33/data-storytelling@sickn33? Sign in with GitHub to claim this listing.Comprehensive frameworks and templates for transforming data into executive narratives
1---2name: data-storytelling3description: Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.4---56# Data Storytelling78Transform raw data into compelling narratives that drive decisions and inspire action.910## Do not use this skill when1112- The task is unrelated to data storytelling13- You need a different domain or tool outside this scope1415## Instructions1617- Clarify goals, constraints, and required inputs.18- Apply relevant best practices and validate outcomes.19- Provide actionable steps and verification.20- If detailed examples are required, open `resources/implementation-playbook.md`.2122## Use this skill when2324- Presenting analytics to executives25- Creating quarterly business reviews26- Building investor presentations27- Writing data-driven reports28- Communicating insights to non-technical audiences29- Making recommendations based on data3031## Core Concepts3233### 1. Story Structure3435```36Setup → Conflict → Resolution3738Setup: Context and baseline39Conflict: The problem or opportunity40Resolution: Insights and recommendations41```4243### 2. Narrative Arc4445```461. Hook: Grab attention with surprising insight472. Context: Establish the baseline483. Rising Action: Build through data points494. Climax: The key insight505. Resolution: Recommendations516. Call to Action: Next steps52```5354### 3. Three Pillars5556| Pillar | Purpose | Components |57| ------------- | -------- | -------------------------------- |58| **Data** | Evidence | Numbers, trends, comparisons |59| **Narrative** | Meaning | Context, causation, implications |60| **Visuals** | Clarity | Charts, diagrams, highlights |6162## Story Frameworks6364### Framework 1: The Problem-Solution Story6566```markdown67# Customer Churn Analysis6869## The Hook7071"We're losing $2.4M annually to preventable churn."7273## The Context7475- Current churn rate: 8.5% (industry average: 5%)76- Average customer lifetime value: $4,80077- 500 customers churned last quarter7879## The Problem8081Analysis of churned customers reveals a pattern:8283- 73% churned within first 90 days84- Common factor: < 3 support interactions85- Low feature adoption in first month8687## The Insight8889[Show engagement curve visualization]90Customers who don't engage in the first 14 days91are 4x more likely to churn.9293## The Solution94951. Implement 14-day onboarding sequence962. Proactive outreach at day 7973. Feature adoption tracking9899## Expected Impact100101- Reduce early churn by 40%102- Save $960K annually103- Payback period: 3 months104105## Call to Action106107Approve $50K budget for onboarding automation.108```109110### Framework 2: The Trend Story111112```markdown113# Q4 Performance Analysis114115## Where We Started116117Q3 ended with $1.2M MRR, 15% below target.118Team morale was low after missed goals.119120## What Changed121122[Timeline visualization]123124- Oct: Launched self-serve pricing125- Nov: Reduced friction in signup126- Dec: Added customer success calls127128## The Transformation129130[Before/after comparison chart]131| Metric | Q3 | Q4 | Change |132|----------------|--------|--------|--------|133| Trial → Paid | 8% | 15% | +87% |134| Time to Value | 14 days| 5 days | -64% |135| Expansion Rate | 2% | 8% | +300% |136137## Key Insight138139Self-serve + high-touch creates compound growth.140Customers who self-serve AND get a success call141have 3x higher expansion rate.142143## Going Forward144145Double down on hybrid model.146Target: $1.8M MRR by Q2.147```148149### Framework 3: The Comparison Story150151```markdown152# Market Opportunity Analysis153154## The Question155156Should we expand into EMEA or APAC first?157158## The Comparison159160[Side-by-side market analysis]161162### EMEA163164- Market size: $4.2B165- Growth rate: 8%166- Competition: High167- Regulatory: Complex (GDPR)168- Language: Multiple169170### APAC171172- Market size: $3.8B173- Growth rate: 15%174- Competition: Moderate175- Regulatory: Varied176- Language: Multiple177178## The Analysis179180[Weighted scoring matrix visualization]181182| Factor | Weight | EMEA Score | APAC Score |183| ----------- | ------ | ---------- | ---------- |184| Market Size | 25% | 5 | 4 |185| Growth | 30% | 3 | 5 |186| Competition | 20% | 2 | 4 |187| Ease | 25% | 2 | 3 |188| **Total** | | **2.9** | **4.1** |189190## The Recommendation191192APAC first. Higher growth, less competition.193Start with Singapore hub (English, business-friendly).194Enter EMEA in Year 2 with localization ready.195196## Risk Mitigation197198- Timezone coverage: Hire 24/7 support199- Cultural fit: Local partnerships200- Payment: Multi-currency from day 1201```202203## Visualization Techniques204205### Technique 1: Progressive Reveal206207```markdown208Start simple, add layers:209210Slide 1: "Revenue is growing" [single line chart]211Slide 2: "But growth is slowing" [add growth rate overlay]212Slide 3: "Driven by one segment" [add segment breakdown]213Slide 4: "Which is saturating" [add market share]214Slide 5: "We need new segments" [add opportunity zones]215```216217### Technique 2: Contrast and Compare218219```markdown220Before/After:221┌─────────────────┬─────────────────┐222│ BEFORE │ AFTER │223│ │ │224│ Process: 5 days│ Process: 1 day │225│ Errors: 15% │ Errors: 2% │226│ Cost: $50/unit │ Cost: $20/unit │227└─────────────────┴─────────────────┘228229This/That (emphasize difference):230┌─────────────────────────────────────┐231│ CUSTOMER A vs B │232│ ┌──────────┐ ┌──────────┐ │233│ │ ████████ │ │ ██ │ │234│ │ $45,000 │ │ $8,000 │ │235│ │ LTV │ │ LTV │ │236│ └──────────┘ └──────────┘ │237│ Onboarded No onboarding │238└─────────────────────────────────────┘239```240241### Technique 3: Annotation and Highlight242243```python244import matplotlib.pyplot as plt245import pandas as pd246247fig, ax = plt.subplots(figsize=(12, 6))248249# Plot the main data250ax.plot(dates, revenue, linewidth=2, color='#2E86AB')251252# Add annotation for key events253ax.annotate(254 'Product Launch\n+32% spike',255 xy=(launch_date, launch_revenue),256 xytext=(launch_date, launch_revenue * 1.2),257 fontsize=10,258 arrowprops=dict(arrowstyle='->', color='#E63946'),259 color='#E63946'260)261262# Highlight a region263ax.axvspan(growth_start, growth_end, alpha=0.2, color='green',264 label='Growth Period')265266# Add threshold line267ax.axhline(y=target, color='gray', linestyle='--',268 label=f'Target: ${target:,.0f}')269270ax.set_title('Revenue Growth Story', fontsize=14, fontweight='bold')271ax.legend()272```273274## Presentation Templates275276### Template 1: Executive Summary Slide277278```279┌─────────────────────────────────────────────────────────────┐280│ KEY INSIGHT │281│ ══════════════════════════════════════════════════════════│282│ │283│ "Customers who complete onboarding in week 1 │284│ have 3x higher lifetime value" │285│ │286├──────────────────────┬──────────────────────────────────────┤287│ │ │288│ THE DATA │ THE IMPLICATION │289│ │ │290│ Week 1 completers: │ ✓ Prioritize onboarding UX │291│ • LTV: $4,500 │ ✓ Add day-1 success milestones │292│ • Retention: 85% │ ✓ Proactive week-1 outreach │293│ • NPS: 72 │ │294│ │ Investment: $75K │295│ Others: │ Expected ROI: 8x │296│ • LTV: $1,500 │ │297│ • Retention: 45% │ │298│ • NPS: 34 │ │299│ │ │300└──────────────────────┴──────────────────────────────────────┘301```302303### Template 2: Data Story Flow304305```306Slide 1: THE HEADLINE307"We can grow 40% faster by fixing onboarding"308309Slide 2: THE CONTEXT310Current state metrics311Industry benchmarks312Gap analysis313314Slide 3: THE DISCOVERY315What the data revealed316Surprising finding317Pattern identification318319Slide 4: THE DEEP DIVE320Root cause analysis321Segment breakdowns322Statistical significance323324Slide 5: THE RECOMMENDATION325Proposed actions326Resource requirements327Timeline328329Slide 6: THE IMPACT330Expected outcomes331ROI calculation332Risk assessment333334Slide 7: THE ASK335Specific request336Decision needed337Next steps338```339340### Template 3: One-Page Dashboard Story341342```markdown343# Monthly Business Review: January 2024344345## THE HEADLINE346347Revenue up 15% but CAC increasing faster than LTV348349## KEY METRICS AT A GLANCE350351┌────────┬────────┬────────┬────────┐352│ MRR │ NRR │ CAC │ LTV │353│ $125K │ 108% │ $450 │ $2,200 │354│ ▲15% │ ▲3% │ ▲22% │ ▲8% │355└────────┴────────┴────────┴────────┘356357## WHAT'S WORKING358359✓ Enterprise segment growing 25% MoM360✓ Referral program driving 30% of new logos361✓ Support satisfaction at all-time high (94%)362363## WHAT NEEDS ATTENTION364365✗ SMB acquisition cost up 40%366✗ Trial conversion down 5 points367✗ Time-to-value increased by 3 days368369## ROOT CAUSE370371[Mini chart showing SMB vs Enterprise CAC trend]372SMB paid ads becoming less efficient.373CPC up 35% while conversion flat.374375## RECOMMENDATION3763771. Shift $20K/mo from paid to content3782. Launch SMB self-serve trial3793. A/B test shorter onboarding380381## NEXT MONTH'S FOCUS382383- Launch content marketing pilot384- Complete self-serve MVP385- Reduce time-to-value to < 7 days386```387388## Writing Techniques389390### Headlines That Work391392```markdown393BAD: "Q4 Sales Analysis"394GOOD: "Q4 Sales Beat Target by 23% - Here's Why"395396BAD: "Customer Churn Report"397GOOD: "We're Losing $2.4M to Preventable Churn"398399BAD: "Marketing Performance"400GOOD: "Content Marketing Delivers 4x ROI vs. Paid"401402Formula:403[Specific Number] + [Business Impact] + [Actionable Context]404```405406### Transition Phrases407408```markdown409Building the narrative:410• "This leads us to ask..."411• "When we dig deeper..."412• "The pattern becomes clear when..."413• "Contrast this with..."414415Introducing insights:416• "The data reveals..."417• "What surprised us was..."418• "The inflection point came when..."419• "The key finding is..."420421Moving to action:422• "This insight suggests..."423• "Based on this analysis..."424• "The implication is clear..."425• "Our recommendation is..."426```427428### Handling Uncertainty429430```markdown431Acknowledge limitations:432• "With 95% confidence, we can say..."433• "The sample size of 500 shows..."434• "While correlation is strong, causation requires..."435• "This trend holds for [segment], though [caveat]..."436437Present ranges:438• "Impact estimate: $400K-$600K"439• "Confidence interval: 15-20% improvement"440• "Best case: X, Conservative: Y"441```442443## Best Practices444445### Do's446447- **Start with the "so what"** - Lead with insight448- **Use the rule of three** - Three points, three comparisons449- **Show, don't tell** - Let data speak450- **Make it personal** - Connect to audience goals451- **End with action** - Clear next steps452453### Don'ts454455- **Don't data dump** - Curate ruthlessly456- **Don't bury the insight** - Front-load key findings457- **Don't use jargon** - Match audience vocabulary458- **Don't show methodology first** - Context, then method459- **Don't forget the narrative** - Numbers need meaning460461## Resources462463- [Storytelling with Data (Cole Nussbaumer)](https://www.storytellingwithdata.com/)464- [The Pyramid Principle (Barbara Minto)](https://www.amazon.com/Pyramid-Principle-Logic-Writing-Thinking/dp/0273710516)465- [Resonate (Nancy Duarte)](https://www.duarte.com/resonate/)466
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