Narrative structure
A narrative structure can transform complex analytics data into a clear, compelling story that guides stakeholders through your insights and recommendations.[1] Use this approach whenever you need to explain data findings, justify decisions, propose changes, or drive action based on analytics insights — from daily team updates to board presentations, incident reports to success stories, and any situation where you need others to understand and act on your data.
Here's how to apply it:
- Begin with a clear problem statement or business question. For example, "We noticed a 25% decrease in daily active users over the past month."
- Present relevant background data and context. "Historical data shows stable growth until December, when we launched the new UI."
- Build tension by revealing key metrics and trends. "Session duration dropped 40%, and user feedback mentions confusion with navigation."
- Highlight the main insight or discovery. "The new menu structure is creating friction for core user workflows."
- Connect findings to business impact. "This engagement drop could lead to $100K monthly revenue loss."
- Close with specific, data-backed recommendations. "Propose reverting to the previous menu layout while testing alternative designs with focus groups."
This structured approach transforms raw analytics into an actionable story that resonates with both product and business stakeholders.
