Data Visualization Makes Complex Data More

Do you have a ton of data but aren’t quite sure what to do with it?

You’re not the only one. Modern marketers have an embarrassment of data riches at their disposal compared to the marketers of yesteryear.

Between machine learning, marketing automation, and data analytics, it’s easier than ever for your business to collate information on your customers.

If you can categorize and evaluate this information, it’s possible to obtain valuable insights about what your audience want and need. These data insights can transform your marketing strategy, ensuring your efforts are more relevant, more efficient, and ultimately, more rewarding for your bottom line.

But here’s the problem:

You have to know how to simplify complex data.

After all, what good is it to collect reams of data if you can’t present it in a way that is easily understood?

Ideally, marketers should be able to look at a visualization of complex data for just a few seconds and say, “I got it!”

In this article, we’ll explore data visualization, and show you how to illustrate trends in data to make analysis easier and more beneficial for your company.

How to Simplify Complex Data

One of the most basic ways of presenting data is in a simple table like the one below. However, not only is this somewhat dull, but it makes it more difficult to truly appreciate the scale and significance of your results.

Let’s look at some innovative charts that we can use to present the data from this table in a way that makes it easier to perform a variable comparison.

Visual Representation #1

The first of our charts is a standard dual axes bar chart.

The blue bars represent the impressions, while the orange bars are the average position. The marketer has to keep track of this abstraction in his or her mind, which requires brain processing.

While it certainly does the job, this data visualization is not without its issues. The main problem here is that both metrics are represented by bars, which could make things a little confusing for viewers.

Surely there is a more dynamic way to represent two variables.

This combination chart tackles the previous issue by using bars to represent one variable and a line for the other variable. This tackles the previous issue as it requires less brain processing, which is the objective

This combination chart tackles the previous issue by using bars to represent one variable and a line for the other variable. This requires less brain processing, which is the objective.

Another addition is the tiles in the top-left corner of the chart.

This style of variable comparison is a clever way to show high-level and low-level details in one visualization. The tiles provide the top-level data, allowing viewers to glean quick insights of the rolled up values with a glance, whereas the chart provides the detailed breakdown of the data.

However, one caveat with this chart is that the bars dominate the visualization. As a result, the line is difficult to see.

So, how can we use data visualization in the style shown above, but ensure that both variables are easy to read and discern from one another?

We found that it helps by adding a fill to the orange line (that represents avg. position) to make it more prominent. However, this overcompensates a little, which means that the fill is now obscuring the bars.

Naturally, our next move was to try placing the fill behind the bars. However, as you can see, this just puts the bars back on center stage once again.

The bars are overshadowing the orange metric here, and they completely obscure the line in some parts.

Who would have thought learning how to simplify complex data would be so complex?

Not to be deterred, PPCexpo continued until they found a solution.

With the previous iterations in mind, the solution is a clever combination of several key aspects, which come together to deliver a clear and coherent visual representation of the data.

Essentially, this idea is a dual axes line, bar, and tile chart, which comprises the following elements:

• The fill in the background
• The bars in the middle
• The line in the foreground

 
With these elements, this data visualization creates a kind of optical illusion.

The fill is in the background, although it doesn’t seem that way due to the line being placed in the foreground.

This clever arrangement makes it easy to see the line, the bars, and the fill, all with a single glance. This makes it much easier to analyze the data and take quick insights from the information.

When you compare this solution with the first attempt, there is a stark contrast.

It’s crucial that your business has the methods and means on hand for effective data analysis, especially when it comes to large-scale PPC advertising campaigns.

Without the right practices in place, companies will not be able to analyze their campaigns efficiently. They could waste resources with poor methods, and could end up making poor decisions based on an inaccurate analysis.

By using data visualization, it’s possible for marketers to present their findings in a way that everyone can understand. Not only is it easy to process these combination charts, but it is a more engaging and effective way to capture the magnitude and variety of results.

Learning how to simplify complex data in this way won’t just impress the senior execs in your company, but it will help in the decision-making process, which will help your company tailor marketing and advertising campaigns for greater success. If the problem is clearly defined and the solution is well-communicated and understood by everyone, then there is a greater probability that your company will make the right decision.

As marketers invest more time and money into paid advertising, they will find themselves inundated with more data than ever before. Collecting that data is not cheap, and so it is imperative that marketers maximize the value of their data to bolster their marketing efforts with useful information on their customers. In doing so, companies can become more knowledgeable about their market and audience.

Most businesses understand the potential of data insights by now, but only the wise ones will truly profit before their competition.