How to tell stories with your data - Thierry Ngutegure

Join us for an insightful session with Thierry Ngutegure, Head of Data Insight at SALT agency, as he dives into the art of storytelling with data. Learn practical tips on effectively gathering, analysing, and presenting data to your team and senior management. Thierry shares his expert advice on making data meaningful and engaging, ensuring your insights drive impactful business decisions.
Key Takeaways with Resources:
Understanding Data Collection:
Focus on Relevance: Only collect data that will answer specific questions relevant to the business.
Avoid Hoarding: Don’t collect data just for the sake of it. Understand why you are collecting each data point.
Initial Data Analysis:
Thought Process: Analyze data with a clear objective in mind. Look for patterns, insights, and anomalies.
Collaboration: Share data across teams to avoid silos and get a comprehensive view of the audience.
Crafting the Narrative:
Setting the Stage: Provide context by explaining why the data matters.
Present the Conflict: Highlight the problem or opportunity the data addresses.
Key Findings: Focus on the most important insights.
Conclusion with Action Points: Clearly outline the next steps based on the data.
Visual Demonstration:
Effective Tools: Use tools like Google Data Studio or Tableau for visualizations.
Psychological Cues: Use colours, shapes, and sizes that intuitively convey meaning (e.g., red for bad, green for good).
Resource: Extreme Presentations (extremepresenta...) for structuring data visualizations.
Presentation and Verbal Conveyance:
Engage Stakeholders: Tailor your presentation to your audience, whether they are team members or senior management.
Interactive Elements: Include clickable links or interactive elements to make the data more engaging and accessible.
Tailoring the Story for Different Audiences:
Understand the Audience: Different stakeholders have different priorities. Tailor the data story to meet their needs.
Common Language: Develop a common understanding of metrics across different departments.
Using AI in Data Management:
Leveling the Playing Field: AI can democratize data analysis, making it accessible to non-experts.
Caution with AI: Use AI for initial data processing, but always validate its outputs.
Resource: There’s An AI For That (theresanaifort...) - A directory of AI tools.
Practical Tips:
Empathy and Collaboration: Foster a culture of empathy and collaboration between analysts and other departments.
Prove Yourself Wrong: Approach data with the mindset of disproving your hypothesis to ensure objectivity.
Third-Party Research: Leverage third-party research to supplement your data and provide broader context.
Resources: WARC (www.warc.com) for marketing research, Statista (www.statista.com) for statistical data, Mintel (www.mintel.com) for market research.
Final Thoughts:
Continuous Learning: Engage with communities, seek mentorship, and continuously learn about new tools and techniques.
Human Element: Focus on understanding human behavior and psychology to make data more relatable and impactful.
Additional Resource Mentioned:
Dr. Grace Kite and Magic Numbers: For insights on long-term marketing effectiveness. Magic Numbers (magicnumbers.c...)