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4 ways data visualization can help new online marketers (and 3 mistakes to avoid)

(MARKETING) Data visualization has become an important part of any marketer’s job, despite being somewhat new to the scene. Here’s why, and some quick tips to help you avoid failure.

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You’ve got enough to worry about

When you first enter the online marketing world, especially as a new entrepreneur, managing a new campaign can seem intimidating. There are hundreds of potential variables and metrics to consider; modern technology makes it possible to pull tons of new data from even basic user interactions, but when you see that data all at once, it becomes almost impossible to make sense of it. Data visualization is a relatively new trend, focused on providing this information in a more intuitive, visual way.

At its most basic, data visualization is an automated process that converts numerical information into visual information, such as translating a complex web of statistics into a straightforward series of charts and graphs. According to data visualization experts at datapine, data visualization “offer(s) a more dynamic approach to presenting data compared to the rigid, linear nature of Powerpoint or the numbers-without-a-story approach of Excel.”

But what is it, exactly, about data visualization that’s so beneficial?

How data visualization helps new online marketers

These are just some of the most important benefits:

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  1. Data consolidation. First, data visualization gives you the ability to consolidate complex patterns of data, sometimes collected over many years or across many different dimensions, into singular, all-in-one projections. If you can combine these visual aids into a single dashboard, this factor of consolidation increases further, making your job as a data analyst or marketer that much more streamlined.
  2. Identifying high-level trends. Next, visualizing data in simplified shapes and constructs helps marketers identify high-level trends they may miss when scrutinizing individual figures. For example, it’s one thing to look at a series of alternating numbers and make a guess about how they relate to each other, and another to take a step back and see a linear growth pattern develop over several bars in a graph. Visuals, especially ones that incorporate shapes and colors, give you the 10,000-foot view, which you can’t see getting lost in the weeds.
  3. Time savings. Using data visualization software saves you time as well. Rather than consulting multiple individual sources, or sorting through individual data points on your own, you can take a glimpse at your projections at a distance, forming a conclusion relatively quickly. The more time you spend involved in data visualization, the easier it will become, and your efficiency will grow even further.
  4. Communicating data more efficiently. Finally, data visualization isn’t just for you. It will also help your clients, partners, teammates, and bosses understand your work better. Think of it as a communicative tool that helps you translate the fruits of your labor to outside parties in a more efficient, apparent way.

Top 3 mistakes to avoid

However, data visualization isn’t perfect. When you use it, you’ll need to be wary of these three critical mistakes:

  1. Ignoring fine data points and outliers. One of the biggest mistakes people make in data visualization is ignoring fine data points and outliers. Visuals help you identify high-level trends, but high-level trends don’t always tell the full story. For example, your “average” user might spend a minute on each page of your site, but that doesn’t tell you about the polarization between users who bounce almost immediately and users who stick around indefinitely.
  2. Becoming over-reliant on visual projections. Visual projections are nice, but if you become over-reliant on them, you’ll lose your ability to see data on a ground level. You may end up forgetting what data points feed into what charts and graphs, or you may start neglecting certain data points altogether. It’s important to use visual projections as a tool to help you understand your data, not as a total replacement.
  3. Neglecting qualitative factors. Most data visualization programs rely on quantitative inputs to make their projections. Quantitative data is good—it’s objective, it’s measurable, and it’s easy to categorize—but it isn’t the only type of important data you’ll need to consider. Qualitative data should be just as big a part of your marketing efforts. Qualitative data doesn’t rely on numbers, but instead relies on qualitative inputs from your target audience, such as open-ended survey responses or forms of user feedback. If you grow too accustomed to quantitative data visualization, you could end up neglecting these important forms of data.

No matter how you look at it, data visualization is a growing trend, both in popularity and importance. As we gather more data, it becomes increasingly necessary to understand that data and interpret it correctly. Visualization makes data more approachable for a wider range of business owners and marketers, and once you understand and compensate for its few weaknesses, it becomes an indispensable tool for growth in any industry or application.

This editorial was first published here in August 2016.

Larry Alton is an independent business consultant specializing in social media trends, business, and entrepreneurship. When he's not consulting, glued to a headset, he's working on one of his many business projects. Follow him on Twitter and LinkedIn.

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