There are 3 ways that you can add context to the analysis.Ī. Data Storytelling Tip #3 – Add Context to AnalysisĪdding context to the analysis makes room for the key messages. Strike off what’s not relevant to the data storyģ. Use the following checklist to ensure reasonable edits. But, an independent editor will only pick the ones that align with the moral. Data scientists and analysts can be biased towards including every insight in the story. Pro Tip: Take help from an editor who is independent of the analysis team. This can be termed as a classic editing process of getting rid of irrelevant content. You need to pick only the ones that support the intent of your story. But, you can’t include everything in your story. In your data analysis, you might come up with multiple analyses and insights. Data Storytelling Tip #2 – Build Analysis to Support the Moral The rest of the elements in the story such as the quarterly comparison of NPS are building blocks that are important to the story. Here, the story has one key moral – Acme’s NPS improved by 6% due to product quality and research. This increase in NPS was mainly due to better product quality & research. Despite lower satisfaction with support, Acme’s NPS grew. After doing an analysis of their customer data we created a data story on their Net Promoter Score (NPS).Īcme Corp’s NPS improved by 6%. Let’s take the example of Acme Corp, a fictional organization. All of them concentrate on one single actionable takeaway. Data Storytelling Tip #1 – Start with the MoralĪll powerful stories are woven around a moral. Include these 5 elements in your data story to make it stand out. Basically, storylines are plot outlines, based on which a data scientist or analyst explains a story in a structured format. You can say that a storyline is the face of your data story. 5 Data Storytelling Tips to Structure Data StoriesĪ storyline binds the data, insights, and narrative into one thread. However, one thing remains common – an enthralling storyline. You can create a data story in any format – text narrative, video, audio, GIF, and many more. A data narrative with proper message draws the audience’s attention to the patterns and sparks the emotions that lead to making decisions. They might find it difficult to consume the insights, let alone the visuals.Įvery narrative or story must convey a message. But, showing visual dashboards to business executives without a narrative can be a bit overwhelming. These insights can be identified as patterns when we analyze and visualize the data. Why Data Storytelling?ĭata is a collection of numbers, which hides meaningful and actionable insights. In one of our data storytelling articles, we talked about how to create insightful data stories. However, there are two important steps that you need to complete before forming a data story – define an audience and find insights to support the story. The task of a data storyteller is to convey actionable insights, evoke emotions, and help stakeholders make decisions. The same goes for a data story too. In this article, we’ll share 5 data storytelling tips that will help you organize your data stories. Every successful story (novels, movies, songs) is full of details, strong characters, and emotional backgrounds.
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