Why this book exists
A framing chapter on why data storytelling needs structure, balance, and narrative intent.
The full journey, chapter by chapter.
The book is organized as a progression from storytelling principles to character building, audience understanding, delivery, and retelling.
Why You Need to Become a Data Storyteller
- The need for data storytelling
- What data storytelling is
- Making and delivering a data-driven story
The Role of the Storyteller
- Three types of data storytellers
- Core storyteller skills
- Possible storytelling scenarios
Making a Successful Data-Driven Story
- Preproduction, production, postproduction
- Theme and subject
- Working in a team
First Act: Defining the Hero
- Who the hero is
- How to extract the hero from the data
- Humanity and concreteness matrices
First Act: Defining the Sidekick
- Who the sidekick is
- Adding the sidekick to your story
- Hook, context, and first plot point
Second Act: Defining the Problem
- Introducing and describing the problem
- Problem types
- Simplification and the five senses
Second Act: Defining the Antagonist
- Types of antagonists
- How to extract the antagonist from the data
- Reaction, action, and pinch points
Third Act: Setting the Climax and Next Steps
- The dark night
- The climax
- Structuring the ending and next steps
From Making to Delivering a Data-Driven Story
- Completing the making phase
- Starting the delivery phase
- Adapting presentation without losing the core
What the Audience Wants and Knows
- Defining the audience
- Understanding expectations and knowledge
- Adapting key moments of the story
What the Audience Thinks
- Audience perceptions
- The stomach-heart-brain theory
- Adapting the story response by response
Retelling the Story
- Why stories must be retold
- Choosing channel, time, and context
- How audiences become new narrators
The AI Revolution in Data Storytelling
An unpublished extra chapter, available free to download as a companion resource for readers.