Data Storytelling

by wshobson46891e7e60daNo licenseListed Oct 8, 2026Updated Oct 8, 2026

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

Instructions onlyData & AnalyticsCommunication
AI-generated overview

Turns analytics into persuasive narratives for stakeholders, reports and executive presentations.

What it does
Provides guidance on structuring data into a narrative using setup, conflict and resolution, a six-step narrative arc, and three pillars of data, narrative and visuals. It offers do's and don'ts for presenting insights, such as leading with the so-what and ending with action. Detailed patterns and worked examples are kept in a separate reference file.
When to use it
Use it when presenting analytics to executives, building quarterly business reviews or investor presentations, writing data-driven reports, or communicating insights to non-technical audiences. It suits situations where recommendations must be drawn from data.
Requirements
No scripts or tools are required; it is instructions only. Reading the bundled reference file is optional.

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 baselineConflict: The problem or opportunityResolution: Insights and recommendations

2. Narrative Arc

1. Hook: Grab attention with surprising insight2. Context: Establish the baseline3. Rising Action: Build through data points4. Climax: The key insight5. Resolution: Recommendations6. Call to Action: Next steps

3. Three Pillars

PillarPurposeComponents
DataEvidenceNumbers, trends, comparisons
NarrativeMeaningContext, causation, implications
VisualsClarityCharts, diagrams, highlights

Detailed patterns and worked examples

Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.

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
  • Don't forget the narrative - Numbers need meaning

Source and attribution

Source:wshobson/agentsinplugins/business-analytics/skills/data-storytellingat commit46891e7

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

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