Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentati
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Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
name: data-storytelling
description: Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
Data Storytelling
Transform raw data into compelling narratives that drive decisions and inspire action.
When to Use This Skill
Presenting analytics to executives
Creating quarterly business reviews
Building investor presentations
Writing data-driven reports
Communicating insights to non-technical audiences
Making recommendations based on data
Core Concepts
1. Story Structure
Setup → Conflict → Resolution
Setup: Context and baseline
Conflict: The problem or opportunity
Resolution: Insights and recommendations
2. Narrative Arc
1. Hook: Grab attention with surprising insight
2. Context: Establish the baseline
3. Rising Action: Build through data points
4. Climax: The key insight
5. Resolution: Recommendations
6. Call to Action: Next steps
3. Three Pillars
Pillar
Purpose
Components
Data
Evidence
Numbers, trends, comparisons
Narrative
Meaning
Context, causation, implications
Visuals
Clarity
Charts, diagrams, highlights
Story Frameworks
Framework 1: The Problem-Solution Story
# Customer Churn Analysis
## The Hook
"We're losing $2.4M annually to preventable churn."
## The Context
- Current churn rate: 8.5% (industry average: 5%)
- Average customer lifetime value: $4,800
- 500 customers churned last quarter
## The Problem
Analysis of churned customers reveals a pattern:
- 73% churned within first 90 days
- Common factor: < 3 support interactions
- Low feature adoption in first month
## The Insight
[Show engagement curve visualization]
Customers who don't engage in the first 14 days
are 4x more likely to churn.
## The Solution
1. Implement 14-day onboarding sequence
2. Proactive outreach at day 7
3. Feature adoption tracking
## Expected Impact
- Reduce early churn by 40%
- Save $960K annually
- Payback period: 3 months
## Call to Action
Approve $50K budget for onboarding automation.
Framework 2: The Trend Story
# Q4 Performance Analysis
## Where We Started
Q3 ended with $1.2M MRR, 15% below target.
Team morale was low after missed goals.
## What Changed
[Timeline visualization]
- Oct: Launched self-serve pricing
- Nov: Reduced friction in signup
- Dec: Added customer success calls
## The Transformation
[Before/after comparison chart]
| Metric | Q3 | Q4 | Change |
|----------------|--------|--------|--------|
| Trial → Paid | 8% | 15% | +87% |
| Time to Value | 14 days| 5 days | -64% |
| Expansion Rate | 2% | 8% | +300% |
## Key Insight
Self-serve + high-touch creates compound growth.
Customers who self-serve AND get a success call
have 3x higher expansion rate.
## Going Forward
Double down on hybrid model.
Target: $1.8M MRR by Q2.
Framework 3: The Comparison Story
# Market Opportunity Analysis
## The Question
Should we expand into EMEA or APAC first?
## The Comparison
[Side-by-side market analysis]
### EMEA
- Market size: $4.2B
- Growth rate: 8%
- Competition: High
- Regulatory: Complex (GDPR)
- Language: Multiple
### APAC
- Market size: $3.8B
- Growth rate: 15%
- Competition: Moderate
- Regulatory: Varied
- Language: Multiple
## The Analysis
[Weighted scoring matrix visualization]
| Factor | Weight | EMEA Score | APAC Score |
| ----------- | ------ | ---------- | ---------- |
| Market Size | 25% | 5 | 4 |
| Growth | 30% | 3 | 5 |
| Competition | 20% | 2 | 4 |
| Ease | 25% | 2 | 3 |
| **Total** | | **2.9** | **4.1** |
## The Recommendation
APAC first. Higher growth, less competition.
Start with Singapore hub (English, business-friendly).
Enter EMEA in Year 2 with localization ready.
## Risk Mitigation
- Timezone coverage: Hire 24/7 support
- Cultural fit: Local partnerships
- Payment: Multi-currency from day 1
Visualization Techniques
Technique 1: Progressive Reveal
Start simple, add layers:
Slide 1: "Revenue is growing" [single line chart]
Slide 2: "But growth is slowing" [add growth rate overlay]
Slide 3: "Driven by one segment" [add segment breakdown]
Slide 4: "Which is saturating" [add market share]
Slide 5: "We need new segments" [add opportunity zones]
Slide 1: THE HEADLINE
"We can grow 40% faster by fixing onboarding"
Slide 2: THE CONTEXT
Current state metrics
Industry benchmarks
Gap analysis
Slide 3: THE DISCOVERY
What the data revealed
Surprising finding
Pattern identification
Slide 4: THE DEEP DIVE
Root cause analysis
Segment breakdowns
Statistical significance
Slide 5: THE RECOMMENDATION
Proposed actions
Resource requirements
Timeline
Slide 6: THE IMPACT
Expected outcomes
ROI calculation
Risk assessment
Slide 7: THE ASK
Specific request
Decision needed
Next steps
Template 3: One-Page Dashboard Story
# Monthly Business Review: January 2024
## THE HEADLINE
Revenue up 15% but CAC increasing faster than LTV
## KEY METRICS AT A GLANCE
┌────────┬────────┬────────┬────────┐
│ MRR │ NRR │ CAC │ LTV │
│ $125K │ 108% │ $450 │ $2,200 │
│ ▲15% │ ▲3% │ ▲22% │ ▲8% │
└────────┴────────┴────────┴────────┘
## WHAT'S WORKING
✓ Enterprise segment growing 25% MoM
✓ Referral program driving 30% of new logos
✓ Support satisfaction at all-time high (94%)
## WHAT NEEDS ATTENTION
✗ SMB acquisition cost up 40%
✗ Trial conversion down 5 points
✗ Time-to-value increased by 3 days
## ROOT CAUSE
[Mini chart showing SMB vs Enterprise CAC trend]
SMB paid ads becoming less efficient.
CPC up 35% while conversion flat.
## RECOMMENDATION
1. Shift $20K/mo from paid to content
2. Launch SMB self-serve trial
3. A/B test shorter onboarding
## NEXT MONTH'S FOCUS
- Launch content marketing pilot
- Complete self-serve MVP
- Reduce time-to-value to < 7 days
Building the narrative:
• "This leads us to ask..."
• "When we dig deeper..."
• "The pattern becomes clear when..."
• "Contrast this with..."
Introducing insights:
• "The data reveals..."
• "What surprised us was..."
• "The inflection point came when..."
• "The key finding is..."
Moving to action:
• "This insight suggests..."
• "Based on this analysis..."
• "The implication is clear..."
• "Our recommendation is..."
Handling Uncertainty
Acknowledge limitations:
• "With 95% confidence, we can say..."
• "The sample size of 500 shows..."
• "While correlation is strong, causation requires..."
• "This trend holds for [segment], though [caveat]..."
Present ranges:
• "Impact estimate: $400K-$600K"
• "Confidence interval: 15-20% improvement"
• "Best case: X, Conservative: Y"
Best Practices
Do's
Start with the "so what" - Lead with insight
Use the rule of three - Three points, three comparisons
Show, don't tell - Let data speak
Make it personal - Connect to audience goals
End with action - Clear next steps
Don'ts
Don't data dump - Curate ruthlessly
Don't bury the insight - Front-load key findings
Don't use jargon - Match audience vocabulary
Don't show methodology first - Context, then method
Download bundled/skills/data-storytelling/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does data-storytelling live?
The publisher keeps it at https://github.com/foryourhealth111-pixel/Vibe-Skills.
Which agents can use data-storytelling?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.