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How do you improve your data visualizations with feedback?

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Data visualizations are powerful tools to tell stories with data, but they are not always easy to create or understand. How do you know if your charts, graphs, maps, or dashboards are effective, engaging, and clear? One of the best ways to improve your data visualizations is to get feedback from your audience, peers, or experts. In this article, you will learn how to ask for, receive, and apply feedback to enhance your data storytelling skills.

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1 Why feedback matters

Feedback is essential for any creative process, including data visualization. It can help to identify and fix errors, inconsistencies, or gaps in your data or design, simplify and clarify your message, enhance and refine your visual style and aesthetics, and align your visualization with your purpose and audience's needs and expectations. Additionally, feedback can uncover new insights, perspectives, or opportunities for improvement.

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Ruchi Sharma

Sharing The Joy of Knowledge || Top Storytelling Voice || Content Strategist || Storyteller || SEO Driven Content Creator || Educator
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Combining data visualisation with storytelling requires a fine balance and understanding how well the audience resonate with it is important. The feedback not only helps you in improving your future data stories but they also gives you insights about choosing the formats, which data visualisations to select and more.

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2 How to ask for feedback

Gathering feedback can be a daunting task, especially if you lack confidence in your work. Nonetheless, there are some practices that can make it easier and more effective. It’s important to ask for feedback early and often, not just at the end of a project. Additionally, you should be clear and specific about what kind of feedback you want and why. When selecting who to ask for feedback, consider people such as your target audience, subject matter experts, or data visualization professionals. Utilize the right tools and methods to solicit feedback, such as surveys, interviews, tests, or online platforms. Lastly, remain open-minded and respectful of different opinions and perspectives.

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Ginger Zumaeta

I advise companies on creating messaging to spread ideas, drive decisions and close deals. → ?? Keynote Speaker | ?? Author | ?? Messaging Strategist.
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One of the things I advise folks to do is to DRAW (you read that right - draw, with ink and paper) their data visualization to stress-test if they are truly communicating the point of the visual. If you can portray your the #story you're trying to tell in a simple drawing, you're on to something. Do this first. Then, when folks respond, go build it. Too many data visualizations fail to tell the story they were intended to tell because they say too much.

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3 How to receive feedback

Receiving feedback can be stressful, especially if it is negative or critical. To make the most of it, you should listen carefully and attentively without interrupting or defending yourself. Ask questions and thank the feedback giver for their time and effort. It's also helpful to take notes and summarize the main points and action items. Lastly, evaluate the feedback objectively to decide what to accept, reject, or modify.

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4 How to apply feedback

Applying feedback can be a challenge, especially when you have conflicting or contradictory suggestions. To improve your data visualization, prioritize the feedback based on its relevance, importance, and feasibility. Create a plan and timeline to implement the changes, then test and compare the before and after versions of your visualization. Don't forget to communicate and share the results of your feedback process with your stakeholders, and reflect and learn from your feedback experience to identify areas for further improvement.

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5 How to give feedback

Giving feedback can be rewarding, especially if it helps someone else improve their data visualization. However, it's important to be careful and constructive with your comments. You should be specific and concrete rather than vague or general when giving feedback, and provide evidence and examples to support your statements. Focus on the strengths and weaknesses of the visualization itself, not the person who created it, and make sure to balance the positive and negative feedback. Additionally, you should suggest solutions and alternatives rather than just problems or criticisms.

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6 Feedback tools and resources

If you want to learn more about how to improve your data visualizations with feedback, you can explore Datawrapper Academy, a free online course that teaches you how to create and critique data visualizations. Additionally, Chartable offers data visualization best practices, examples, and reviews. You can also join Data Viz Feedback, a community that provides peer feedback and advice on data visualizations. Furthermore, Data Stories is a podcast that explores the art and science of data visualization. Finally, The Data Visualization Checklist is a practical guide that helps you evaluate and improve your data visualizations.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Becky Nahm

Award-winning former journalist helping organizations tell their stories, become thought leaders and reach relevant audiences.
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Data visualization is powerful but isn't easy. It can feel similar to writing a recipe or how-to guide. In each case, the creator has all the information and may omit key components or steps. Feedback is crucial to spot holes. It might be worth considering whether to separate feedback on information and format from creative design elements. When planning data visualization projects, I try to build in time to step away and revisit the work with fresh eyes.

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How do you improve your data visualizations with feedback?

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1 Why feedback matters

2 How to ask for feedback

3 How to receive feedback

4 How to apply feedback

5 How to give feedback

6 Feedback tools and resources

7 Here’s what else to consider

Storytelling

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