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3 Key Phases Of Any Good Data Visualization Project

Forbes Agency Council

Johnnie is the CTO of Wonderful, a design and development agency building products from mobile apps to ecomm websites.

Business-to-business content is ripe with the potential to connect to readers’ values and drive impactful change within industries and communities. And there’s arguably no single more important aspect of that content than data.

While data is a powerful catalyst for change, preparing and presenting it can be a complex process. Here are three key phases of successful data visualization projects.

1. Data Capture And Interpretation

Let’s start at square one, assuming the data isn’t ready or is incomplete. Start by addressing the following questions:

• What is the information we need?

• What questions do we need to ask to get that information?

• Who or what will we be observing or surveying?

• What period of time do we need to complete the observation or survey?

Once you’ve collected your data, you’ll need to analyze it to establish trends or patterns, draw logical conclusions, and frame the key points of your overarching story. A strong message should be spelled out here.

While well-crafted data visualizations can be an enormous benefit to the organizations that build them, poorly crafted ones can create serious problems.

How do you protect your project from crumbling under the weight of “bad” data?

Avoid drawing conclusions based on ‘junk’ data.

Junk data can be anomalies or outliers in the data set that don’t represent a trend or sustained pattern over time. For example, the year 2020 was an anomaly, and “trends” observed during it may not be counted as trends at all. However, unsustained trends shouldn’t necessarily be thrown out. Outliers and anomalies exist, so acknowledge them with an inclusive statement, or provide access to the full data set via a downloadable CSV file. This will add credibility and provide backing to the project.

Avoid drawing conclusions based on ‘sparse’ data.

Sparse data refers to a thin data set that doesn’t include enough information to draw accurate conclusions. This generally indicates that you haven’t collected enough data to achieve your objective.

If sparse data becomes a hindrance, ask yourself:

• Was the sample size too small?

• Was the time frame too tight?

• Was the technology used to collect the data functioning properly?

Be honest about your findings.

When the data you’ve collected directly contradicts the theory you set out to prove or the story you hoped to uncover, own it. This will let your audience know that the project was not created to push an agenda, establishing your organization as an honest and credible source of information. Transparency supports a positive brand reputation and a thought leadership edge.

2. Journey Visualization

Here you’ll lay out the complete story and its graphical representations. Start by deciding where your audience will need to begin their journey in order to end at your final destination. This requires you to create a cohesive narrative that bolsters key messages and presents a clear call to action.

Consider the audience.

To find where your data story begins, you must take into account the various levels of experience and expertise in the audience in comparison to the intricacy of the subject matter. It’s important to make sure that your project includes a proper introduction and that the path to your story’s conclusion is well lit for each audience segment.

Maintain brand consistency.

As visuals come to life, you should strive to keep graphic elements consistent with current branding to create a familiar, linear experience. Keep the overall mood and tone in mind as you lay out the framework of your visuals. This can be executed through textures, line work, colors and imagery.

Always think a few steps ahead.

Now you can get to the fun stuff—producing the visuals! Creativity is endless, but capabilities and resources can create roadblocks to your dream results. Create a brief plan for navigating that by outlining:

• What do we have at our disposal?

• What can we easily obtain?

• What do we need to figure out?

Pro Tip: Create two concepts with two different looks for consideration. This shows multiple perspectives and provides alternate routes if needed.

3. Technical Development

At this point, the designers are handing off creative and developers take center stage. As you build out your visualizations, incorporating audio, motion, maps, emotion and all the elements that make this project unique, remember it’s important to hold true to the plan and allow the story to unfold in the way that best suits the content and intended audiences. Continually revisit the plan and objectives.

Pro Tip: From your developers to the marketing team, have a clear understanding of technical skills and comfort levels. This can help avoid unnecessary friction or compromising the vision.

Numbers are not stories.

Buy-in and enthusiasm are great, but get everyone to check emotions at the door. Excitement can be blinding and cause team members to underestimate the enormity of the task. Ego can also be crippling since the story that stakeholders want to tell may differ from what is true and builds a connection to the audience. Stay focused on the end goal and assure that the intended story is respected.

Accessibility is paramount.

Improve the mobile navigation experience by properly sizing buttons, graphs, maps and infographics to adjust to various screen resolutions. The last thing you want is to have beautiful, engaging data sets and stories that deliver on desktop but become disjointed to visitors on mobile.

There are many resources for ensuring your data visualization meets accessibility criteria. Visual design elements like forms, typography, color palette and mobility play a critical role in keeping your visualization accessible to as many users as possible.

Finally, quality assurance and testing are extremely important. Collect feedback by releasing beta or sandbox versions to small sample groups who represent your audiences. QA testing can yield valuable UX data used to refine the experience before it is presented to the end user.

Data plays a key role in completing an intended journey for your audience and illustrating what people can do when empowered with the information. It can impact businesses, families and communities.


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