At some point, it became nearly impossible to discuss marketing without mentioning data. Even in areas like content marketing, influencer marketing, and offline marketing—which were once considered difficult to quantify—attempts to measure performance are steadily increasing, even if they aren’t strictly performance marketing campaigns that track results daily. Consequently, marketers are also facing a growing number of tasks that require them to prepare reports (such as performance reports and proposals) that include data.
According to arecent study by UC Berkeley, people tend to accept visualized data as objective truth. While we all know how powerful data visualization can be, many of you are probably wondering if the approach you’re currently using is the right one, aren’t you?
For B2B marketers facing challenges, Elephant Company has prepared four essential elements every marketer should know when visualizing data, answers to frequently asked questions, and tips for creating reports.
1. Data Visualization: Here’s What You Must Keep in Mind…!
Think data visualization looks complicated? Just follow these tips and you’ll have the basics down! Actually, these are such basic concepts that you probably already know them. But let’s start by looking at four essential elements that are easy to forget once you actually start creating charts.
4 Essential Elements for Creating Charts
① A title that summarizes the chart's content
First of all, the title. It’s surprisingly easy to forget to include a title when creating a chart. You might think, “Everyone knows what it’s about anyway, so does it really matter?” But without a title, viewers of the data will be confused about what exactly you’re trying to convey.
② Axis labels that explain the data represented in the chart
Next, let’s look at the axes. We need to label the horizontal and vertical axes so we can see what data the chart represents.
③ A legend that distinguishes between different types of data
If your graph includes two or more categories, you must include a legend. A legend explains which specific colors or symbols represent which categories. Without a legend, it may be impossible to interpret the graph.
④ Unit notation that clearly indicates the data value
Finally, it’s essential to include units. Charts tell a lot through numbers, but the meaning behind those numbers isn’t always the same. Sometimes they represent time, sometimes the number of people, and sometimes a ratio. Without units, the information you’re trying to convey could be misinterpreted.
2. Frequently Asked Questions About Data Visualization
Now that we’ve covered the basics of data visualization, let’s dive a little deeper by answering some frequently asked questions.
Q. Can't you show everything in a single chart?
If you try to show too much data, you might end up failing to convey the most important message effectively.
This is a common mistake we often make when visualizing data. It’s easy to feel the urge to cram all our data into a single chart. While this has the advantage of making comparisons easier and allowing you to see everything at a glance without having to create multiple charts, trying to display too much data in a single chart often results in a situation where neither approach works well.
To avoid this problem, you should first clearlydefine your objective—what you want to convey with the chart—before creating it. For example, you might wantto “show the upward trend in organic traffic” or “allow users to compare traffic across different channels at a glance.”
Q. Bar charts, line charts, pie charts… When should I use which type of chart?
There’s a chart that works well for every type of data.
Even if you’ve clearly defined your objective, it can be difficult to convey your message effectively if you don’t choose the right type of chart. When writing a report, it’s easy to unconsciously choose a chart simply because it looks nice or because you’re familiar with it. Did you know that there’s a specific chart that works best for each type of data?
① When showing changes over time, use a line graph
Line graphs are well-suited for illustrating trends because the line extends continuously from the beginning to the end of the chart. Conversely, if you use a line graph to display values for different categories, it can easily create the illusion that they are part of a continuous trend.
② When showing proportions, a pie chart
Pie charts are ideal when you want to emphasize the proportion each value represents within the whole, rather than the individual values themselves. If you want to display each value and compare them accurately, it’s better to choose a different type of chart, such as a bar chart, rather than a pie chart.
③ When displaying category breakdowns, use a bar chart
If your data is organized into multiple categories and you want to show that structure, try using a stacked bar chart.
④ Scatter plots for showing the correlation between variables
A scatter plot is a good way to check for correlations between multiple variables. Adding a trend line allows you to visually assess the relationship between the two variables.
⑤ A 3D chart to illustrate the relationship between three variables
In other words, if you want to display only two variables instead of three, you shouldn’t use a 3D chart. As the name suggests, a 3D chart is designed to represent three variables. If you leave one dimension unused and assign it an arbitrary value, it can confuse the viewer.
💡 The simplest visualization is the best!
Just because you can create a nice graph doesn't mean you're an expert
There are many types of charts—such as violin plots, box plots, and box-and-whisker plots—that look and sound impressive and can convey a wealth of information at a glance. However, if the reader doesn’t understand these charts, they’re often worse than not using them at all. After all, the explanation of the chart might end up being longer than the actual report itself.
Don’t forget that the purpose of data visualization is to convey data more clearly and effectively!
"Charts" are also an excellent way to visualize data.
Sometimes a simple table is better than a hundred charts. For example, this is the case when you have a lot of data to present or want to compare multiple values across different items all at once.
In particular, when you use features like Google Sheets’ “Conditional Formatting” or the sparkline function to visualize the relative sizes of specific items at a glance, the results often rival those of most charts.
Q. How should I choose colors for data visualization?
Since color is also an important element in presenting data, we need to approach it according to established principles.
Color is another area where people often make mistakes in data visualization. As you’re creating a chart, the urge to choose colors that look nice to you starts to creep in. Even those who’ve managed to stay focused right up until they reach the chart type often crumble completely when it comes to color.
To avoid common mistakes, just keep these three things in mind!
① Choose colors consistently
If you’ve chosen blue as the main color, please keep blue as the default color throughout the report. If the color changes, it instinctively feels like something has shifted. If there are multiple charts comparing data across categories, please consistently use the same color to represent data within the same category. Once you recognize that a particular category is represented by red, you’ll be able to distinguish it easily without having to look closely from then on.
② Use gradients only where absolutely necessary
It’s much more soothing to look at a graph with a beautiful gradient of colors within the same color family than one painted in a haphazard array of colors. However, the situations where gradients can be used are very limited. For example, they work well when there is a clear order or hierarchy among data values, such as 0, 1, 2, 3, and so on. If there is no order among the values, using a gradient can actually make it easier to misinterpret the data. You’ve probably also seen rainbow gradient (!) graphs. You really need to be careful with these. In a chart, nothing should be used carelessly. Since every color has a meaning, it’s easy to cause misunderstandings.
If you use a gradient to represent unrelated items, as shown in the graph on the left, it can cause confusion.
Values that are unrelated to one another, such as “traffic sources,” should be represented in different colors, as shown in the graph on the right.
③ Avoid color choices that go against your intuition
Finally, it’s best to avoid choosing colors that go against people’s intuitive associations. Colors are often intuitively categorized into positive, neutral, or negative, or as feminine or masculine. Even if you provide additional explanations, viewers may still find it confusing, so it’s best to avoid such choices unless there’s a specific reason to do so.
Q. What should I do if I’ve plotted a chart but the growth trend isn’t clear?
If you simply crop the graph or change the scale without thinking, you risk distorting the data, so you need to approach it the right way.
It’s a moment that really gives you pause. You’ve finished drawing the graph, but the message isn’t coming across as strongly as you’d like. A common mistake people make in this situation is adjusting the vertical axis, which distorts the data. Even if the values aren’t clearly visible, you should never change the axis scale. Doing so can lead to serious misinterpretations among your audience.
I recently checked the subscriber growth trend for the YouTube channel run by Elephant. I was thrilled to see that the subscriber count had more than tripled recently. Just as I was thinking, "Wow, this is huge...!" and celebrating, I glanced at the vertical axis and felt like I’d been hit over the head. It turned out the vertical axis didn’t start at zero. You have to be extremely careful when adjusting the axis scale like this, as it can cause confusion for viewers.
① Make it clear that only a portion of the vertical axis is shown
If you really want to emphasize it, we can design it so that the graph starts at 0 and includes a highlight.
② Apply a logarithmic scale to the vertical axis
A more mathematical approach involves using a logarithmic scale. This is often used to represent data that rises gradually at first but increases exponentially over time.
3. Tips for Reporting for Top-Performing Marketers
I think we’ve covered the basics of data visualization. There are other aspects of data reports that require attention besides visualization. Finally, I’d like to share some tips on how to add that extra touch to your reports.
Every number needs an explanation
When writing a report, you shouldn’t just present numbers on their own. Every number needs an explanation. You need to interpret whether the number is good or bad, and if it’s good, how good it is.
If you find it difficult to interpret the data, start by comparing it to figures from last week, last month, or last year. You don’t need to go as far as comparing it to industry averages—if you’re making progress day by day compared to where you were yesterday, you’re doing just fine.
Let’s write with the reader in mind
It’s important to tailor your writing to the reader and their level of understanding.
If you’re reporting KPIs to the head of the internal marketing team, you can probably skip some of the details about the metrics. However, if it’s for an external proposal, you’ll need to include additional details explaining how we defined the metrics, where the data came from, the time frame covered, and the calculation method used.
A conclusion is needed
Just because it’s called a data report doesn’t mean it’s any different from a regular report. If you just throw out the raw data, your team lead will probably ask, “So what are you trying to say?”
Once you’ve analyzed the current situation using data, you should include the lessons learned from that analysis and recommendations for how to proceed.
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That wraps up today’s discussion on data visualization. I hope this has been of some help to B2B marketers who are looking to improve their data reporting skills!
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