How to make your data insight land with your audience

Data insights are the essential unit of value in analytics. They are the moment when we’ve squeezed the juice from data, extracting something useful.

“An INSIGHT goes way beyond just founding something "interesting" in the data. An insight is an unexpected shift in the way we understand things that inspires us to act.” — João António Sousa, Director of Growth at Kausa.ai

Brent Dykes + Joao

  1. SHIFT in UNDERSTANDING

  2. UNEXPECTED REASON

  3. ALIGNS with what the target audience CARES ABOUT

  4. EFFECTIVE COMMUNICATED



Why Data Insights?

We use data as a medium for communication. It isn’t that different from visual communication mediums (images, video), text-based communication (books, articles, poems), aural (music), action (games), and taste (cooking). There is a pervasive trend in many forms of communication toward smaller units of exchange, more easily shared and remixed. Tweets, TikTok, memes, Slack for business communication, song-based music releases.

Which leads us to the centrality of the Data Insight. This is the future elemental communication mechanism that will be how we communicate and share in the analytics world. They will displace the dashboard, report, and even my beloved data story.

What makes a compelling data insights?

First, save the good ones and throw out the bad ones. A good data insight does two things:

  1. It speaks to the need of its target audience

  2. It is actionable.

Second, right-size it. A good data insight is only so big that your audience can quickly grasp it. It carries a single punchline.

Third, wrap your data insights in context to explain why it matters.

Fourth, understand and position the insight relative to existing understanding and assumptions. The data insight’s risk/reward tradeoff relates to how far it asks the audience to change their current thinking.

Fifth, package the insight for sharing. Use this knowledge of context, pre-existing assumptions, and precision of message. Deliver it in a form that is easily transportable.

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A 12-Point Checklist for Public and Open Data Sites (with Examples)