What are some effective techniques for visualizing and communicating research findings and recommendations?

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Data analytics is a powerful tool for generating insights and solving problems. But how do you communicate your research findings and recommendations effectively to your audience? In this article, you will learn some techniques for visualizing and communicating your data research results in a clear, concise, and compelling way.

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Lucas Elliott

Digital Analytics???? || Marketing ???? || Research ????????

1 Know your audience

Before you start creating your visuals and reports, it’s important to understand who your audience is and what they need. Audiences may vary in terms of their familiarity with your data, expectations, and goals. For example, a technical audience may require more details and explanations, while a business audience may be more interested in summaries and implications. To tailor your communication to your audience, ask yourself the following questions: who are they and what is their background? What is their main purpose and interest in your research? How much time and attention do they have? What are the key messages and actions you want them to take away?

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Lucas Elliott

Digital Analytics???? || Marketing ???? || Research ????????
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One way to create materials that are inclusive of different audience types is to provide visualizations and findings that are high level, while also including opportunities to dive deeper where needed. As an example, you can embed high level charts and snapshots directly into decks - but then provide links to interactive dashboards (if available) for those who wish to dive deeper into the details.

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2 Choose the right visuals

Visuals are essential for making your data research findings and recommendations more engaging, understandable, and memorable. However, it's important to choose the right visuals that match your data type, analysis purpose, and audience preference. Charts and graphs are great for showing trends, patterns, comparisons, and distributions; tables are great for precise values, categories, and rankings; maps are great for geographic data and spatial relationships; diagrams are great for processes, flows, and structures; and icons, images, and colors can add context, meaning, and appeal.

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Matthew Gratt

Growth Marketing & Lead Generation Consultant for Insurance, Real Estate & Financial Services Firms
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Never ever use a pie chart. Tables are great. Bar charts are great. Most people will want the raw data anyways, so make that available. Time series data should be shown in context with data from previous periods - the simple time series charts are great for that.

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3 Follow design principles

When choosing visuals, you should adhere to certain design principles to make them more effective and attractive. Simplicity is key; avoid clutter, noise, and unnecessary elements, and focus on the most relevant information. Alignment is also important; align your elements for a sense of order and harmony. Contrast is another principle to consider; use different sizes, shapes, colors, fonts, and positions to create emphasis and hierarchy. Repetition is essential too; repeat elements to create a sense of unity and coherence. Lastly, balance your elements to achieve stability and symmetry.

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Lucas Elliott

Digital Analytics???? || Marketing ???? || Research ????????
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When developing visualizations, consider inclusive and accessible visualizations wherever possible. As a very basic example, instead of using red and green color scales for positive/negative data, you can use orange and blue - which is more accessible to folks with different types of colorblindness.

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4 Write clear and concise text

Creating visuals alone is not enough to effectively communicate data research findings and recommendations. It is important to also write clear and concise text that complements and enhances the visuals. The text should include a title, which is a short phrase that summarizes the main point of the visual or report, and a subtitle, which provides more context and details. Labels, annotations, and captions are also needed to identify and explain elements, highlight features or insights, and describe and interpret the visual. These components can help provide valuable information about the data source, methodology, findings, and implications.

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5 Tell a story

The final technique for visualizing and communicating your data research findings and recommendations is to tell a story. A story can be an effective way to grab your audience's attention, establish your credibility and authority, provide context for your research, explain your analysis process, highlight key findings and insights, recommend actions and solutions, and persuade your audience to act or change. To tell a story, you should follow a simple structure with an introduction that sets the scene and introduces the problem or question, a body that presents data, visuals, and text in a logical sequence that supports your argument or answer, and a conclusion that summarizes the main points and provides recommendations with a call to action.

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6 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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Nilesh Angane

Senior Technology Manager | Data Storytelling | Data Analytics | Data Viz | Cloud | Gen AI | Machine Learning | Power BI | Qlik | Tableau
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I believe we can create visually appealing infographics to convey key data and insights in a concise and engaging manner. Craft a narrative around your findings, using a logical flow to guide your audience through the research process and conclusions. Represent processes or decision trees using flowcharts to simplify complex concepts and make them more accessible. Generate word clouds to emphasize frequently occurring terms, helping to identify common themes or keywords. Use heatmaps to highlight patterns, trends, or areas of significance within your data, providing a quick overview. Finally, illustrate connections between different elements of your research, aiding in the visualization of relationships and dependencies.

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What are some effective techniques for visualizing and communicating research findings and recommendations?

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1 Know your audience

2 Choose the right visuals

3 Follow design principles

4 Write clear and concise text

5 Tell a story

6 Here’s what else to consider

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