More data is being collected than ever before, meaning there’s more noise to sift through for insights. Luckily, advanced data transformation tools and technologies built into data visualization platforms are lowering the barrier to entry and making the ability to wrangle data more accessible.
Studies suggest that most people are visual learners. (They retain information better when they see it in images, charts or diagrams). So, data visualization plays a major role in information processing, data-driven decision-making and increasing data literacy.
You’ve invested in building your team. You’ve invested in building out your data model. And you’ve adopted your analytics platform of choice. Now, you need to invest in the right reporting practices for your organization, ensuring they’ll meet your current needs and scale. Today, we'll dive into 3 key steps for making impactful data visualization and tips for avoiding common mistakes.
Choosing the right data visualization is crucial for effectively communicating insights and driving action. It starts with knowing your audience—understanding their needs, preferences and levels of expertise. This ensures that the chosen visualization resonates and engages them.
Next, having a clear goal for your data visualization is essential; whether you aim to inform, persuade or facilitate decision-making, your objective will shape how you present the data.
And lastly, selecting the visualization that best represents your story is key. Different types of visualizations — charts, graphs, or infographics — serve distinct purposes and can evoke varying interpretations of your data. By aligning audiences, goals and data viz formats, you can create compelling visual narratives that not only convey information but also inspire action.
A big piece of data visualization is knowing who the target audience is. Are they data scientists, business analysts, C-Suite members or just general audience members?
Different types of audience members will read and understand data differently. Consider your audience's technical expertise and learning style when choosing visualization techniques.
Tailor your approach to ensure effective communication. A bar chart might be enough for a general audience, while a more advanced heatmap or scatter plot might be necessary for data scientists.
Below are a few nice-to-haves regardless of audience:
What questions should it answer? What's the story you want to tell? Is it to inform your audience about the findings? To persuade your audience to follow a certain direction? Or, is it more about exploring and diving deeper into the data?
A clear goal will guide your visualization choices. For example, if you want to persuade stakeholders to invest in a new project, a compelling line chart showing projected growth can be effective. If you want to inform, maybe you go with a simple line chart with an explanation of the trend you’re seeing.
Start with a clear objective and identify the key questions you want your visualization to answer. Focus on the most important insights and avoid overwhelming your audience with too much information.
Different types of visualizations — charts, graphs, or infographics — serve distinct purposes and can evoke varying interpretations of your data. By aligning audiences, goals and data viz formats, you can create compelling visual narratives that not only convey information but also inspire action. Let's dive deeper with some comparibles.
Is the data visualization clear? Can it be misinterpreted? Is there anything that distracts the audience from the point you want to make?
Selecting a visualization type that best suits your data and the story you want to tell is important. A bar chart is great for comparing categories, while a line chart is ideal for showing trends over time.
Remember, the right visualization can make complex data easy to understand. Compare and contrast effective and ineffective visualizations while you’re building to show key differences. A cluttered, overly colorful chart can be distracting, so strive for simplicity and clarity.
Test your visualization with your target audience to gather feedback on clarity, effectiveness and overall impact. Use this feedback to iterate and refine your design. A well-designed visualization should be easy to understand and visually appealing.
Data analysts often have strong opinions about pie or donut charts. Some can't stand them; others don’t… mind them as much. Pie/donut charts may be great for comparing two or three categories, but beyond that, they lose their impact. For instance, compare these pie charts representing the breakdown of device categories used to interact with the Google Demo Store:
When comparing these pie charts, you can see that when there are 2-3 data points (chart 1), it’s easier to show how they compare against each other as part of a whole. If there are more than 3 data points (chart 2), it becomes more difficult to see differences in the data - how one sliver is slightly larger/smaller than the other.
While well-crafted visualizations can illuminate insights and drive informed decisions, common mistakes can obscure your message and mislead your audience. By identifying and addressing these errors, you can enhance the clarity and impact of your visualizations, ensuring that your audience receives the insights you intend to convey. Here are seven common mistakes to keep an eye out for:
Let’s look at two example charts to illustrate how these mistakes (and solutions) come to life in real-world scenarios:
Can you spot what’s problematic with chart A? Next, let's compare it to the one below. What are some differences? Look for some of the mistakes we listed above—too much information, cluttered layout, unclear metrics, etc.
This improved version corrects many of the issues seen in Chart A. Notice how it uses clear labels, focused metrics, and a more cohesive color palette.
In our next data visualization blog post, we’ll dive deeper into leveraging Adswerve’s expertise to get started with data visualization. Once your reporting needs are in order, the real fun begins: uncovering and activating insights.
Contact us if you have any questions or would like to consult with one of our experts. We offer Data Visualization Sessions to all current and new clients to determine ways to make the tech stack you’ve already invested in work for you or recommend changes that can empower you and resolve reporting problems.