Data visualization is a powerful way to communicate data, particularly when conveying complex information. As such, those who produce data visualizations should follow Spider-Man’s example and embrace that “with great power comes great responsibility.” Poorly executed visualizations are regularly used either due to carelessness or to author bias and can lead to cause false conclusions and even widespread panic. At HelloInfo, we specialize in visualizing data for our clients and are happy to share a few best practices.
Visualizations, such as bubble charts and heat maps, add visual interest and are an easy snapshot of the data presented. The selection of a visualization should first and foremost promote an accurate interpretation of the analysis in question, rather than a flashy but confusing narrative. Honest and clear reporting builds trust with information users and can be maintained by avoiding the following critical mistakes:
- Using the wrong type of chart or graph for the type of data
- Having too many variables
- Inconsistent and unclear axis or scales
- Poor color choices
These common mistakes and the power of data visualization will be discussed below, using data inspired by aforementioned Spider-Man.
Too much of the wrong thing
IMDB.com lists 10 Spider-Man movies (recognizing that there are earlier renditions that date back to the 70s) and provides a star rating for each. A Spider-Man enthusiast may want to visualize these data to help other enthusiasts see how their own preferences compare to popular opinion. The pie chart below (poorly) illustrates the star rating for the nine movies:
Figure 1. A pie chart of IMDB star rating for Spider-Man movies

Data source: IMDB
A pie chart is not the right choice for this data. The pie chart makes it difficult to quickly differentiate between the movie ratings and it is easy to see how it gets worse with more data points added. The pie chart also gives the incorrect impression that the ratings are parts of a whole. Therefore, pie charts should be reserved for data types that do add-up to a whole (i.e., 100%), such as illustrating the proportion of time that Spider-Man spends saving Mary Jane versus the rest of the world.
A bar graph is a much better choice to illustrate the star rating results. As evident below, this format helps to quickly examine how one movie is doing relative to the other. A line chart would be equally appropriate. However, using the correct chart/graph could still result in an ineffective data visualization if too many data points are used, creating a cluttered and overwhelming appearance.
Figure 2. A bar graph of IMDB star rating for Spider-Man movies

Data source: IMDB
It is all relative
The axis used in a visual has a direct impact on what viewers gain from it. Using uneven axis or scales can inflate small disparities and vice versa, misleading the reader into incorrect conclusions. For example, Figure 3 below portrays a sharp drop in the ratings for the Spider-Man 3 movie. However, a closer examination reveals that the y-axis ranges from 6.2 to 7.6, creating a visual effect that exacerbates the rating difference between the third movie to its predecessors. A more balanced y-axis that ranges from zero to 10 (in-line with the available star rating range) as in Figure 4 below demonstrates the same data in a more accurate way.
Figure 3. A line graph with y-axis ranging from 6.2 to 7.6, illustrating IMDB ratings of three Spider-Man movies

Data source: IMDB
Figure 4. A line graph with y-axis ranging from 0 to 10, illustrating IMDB ratings of three Spider-Man movies

Data source: IMDB
Color me pretty
The use of color is a powerful tool to draw the eye to the highlighted data. However, issues such as using too many colors, using too little contrast, and using familiar colors in unfamiliar ways, can create confusion for the reader. There is a preexisting relationship between certain colors, or shades of colors, to the nature of the data presented and any deviation from that would leave the reader either confused or misled. For example, charts tend to utilize darker shades to indicate larger numbers than lighter shades. Consider Figure 5 below, detailing lifetime box-office gross revenues for the 10 Spider-Man movies:
Figure 5. A table illustrating lifetime box-office gross revenues of 10 Spider-Man movies, using misleading coloring

Data source: Box Office Mojo
At first glance, it appears that Spider-Man: Into the Spider-Verse has the highest lifetime box-office gross revenues and Spider-Man: No Way Home has the lowest. This first impression is guided by the color choices, automatically associating darker shades with higher numbers. A closer examination of the actual values reveals that in fact Spider-Man: No Way Home grossed the highest. The figure below illustrates the same chart, recolored to better align with the data:
Figure 6. A table illustrating lifetime box-office gross revenues of 10 Spider-Man movies, using intuitive coloring

Data source: Box Office Mojo
Another example is that green colors are typically used to highlight positive or successful outcomes versus red colors for negative or unsuccessful ones. It is important to note that any report or presentation should consider the needs of those who are visually impaired and provide a verbal description of the data differences, rather than relying on the visualization alone.
How can HelloInfo help?
At HelloInfo, we specialize in providing clients with market and competitive intelligence, which includes insights on competitors’ pricing models, strengths and weaknesses, and more. We regularly create data visualizations that appear both polished and crystal clear, leaving no room for misinterpretation.
Whether your spider sense tells you that your data is weaving a web of lies or you are fighting off the real-world super-villain named “uncertainty,” schedule a call with HelloInfo to explore how we can help.