According to a McKinsey estimate, "...69 percent of data processing and 64 percent of data-collection activities could feasibly be automated." This suggests that the ability to collect, organize, and analyze data will soon become table stakes for marketers rather than a distinguishing skill.

However, to truly leverage the power of data and AI, marketers must become adept at data storytelling. Simply presenting numbers and statistics is not enough; we must be able to explain the significance of the data and provide actionable recommendations based on the insights.

In my experience of reviewing marketing reports across various organizations, I often find that people can successfully identify and present relevant data but struggle to explain its meaning, importance, and implications.

To effectively communicate data-driven insights, you could consider using this three-part framework:

1. Data Summary: Start by summarizing the key findings from the data analysis. Identify the most important patterns, trends, or insights, and distill the information down to its core, focusing on the points that matter most to your stakeholders and their goals.

2. What It Means: This is arguably the most important aspect of data storytelling. Explain the significance of the insights and what they mean for your (internal and external) audience. Connect the findings to business objectives, customer needs, or market trends. Clearly articulate the implications of the data and why your audience should pay attention to what you’re presenting.

3. What to Do with It: Finally, provide clear, actionable recommendations based on the insights. Outline the steps that should be taken to seize opportunities or tackle challenges revealed by the data. Explain how the insights can inform marketing strategies, campaigns, or tactical decisions. Give your stakeholders clear guidelines on your recommendations and their implications in terms of trade-offs like time/cost vs. ROI.