How To Build Reports Using Data Visualization Best Practices

June 28, 2016

Using illustrative charts is a great way to depict the narrative that your data trying to tell, but it’s essential to ensure you’re using data visualization best practices in your reporting.

Fortunately, Alchemer makes this easy with standard reports.

Generated automatically, a standard report presents your data with bold, bright visuals so you can slice, dice, and analyze your findings more effectively (and present those findings to stakeholders like your boss or professor)

When you first open your standard report, you may be surprised at what you find. Depending on which question types you use in your survey, there can be as many as 17 different charts and graphs in your report.

In this post, you’ll find out how each question type reports (and why), so you can start reporting using data visualization best practices.

Single Versus Multiple Versus Specialized

Before diving into each reporting chart type, the general guiding principle behind why a question reports the way it does comes down to single select, multiple select, or advanced.

Single select questions, like radio buttons, are those that require respondents to choose just one response. These questions report as pie charts because the percent of answers will always add up to 100%.

Multiple select questions, like checkboxes, give respondents the option of selecting multiple answers. In the case of these question types, the percentage of answers could, and usually does, add up to more than 100%. In these situations, a vertical or horizontal bar chart is the best, most flexible way to display your data.

Other report chart types, which I’m collectively referring to as specialized types, are tailored to the specific question type or group of types. These charts are customized to be the best visualization of a particular style of question. Read on to find out more.

Pie Chart

data visualization best practices - using pie charts

Like its culinary cousin, pie charts are versatile reporting visualizations.

While making an accurate pie chart by hand can be a bit of a nightmare, Alchemer takes all of the math and guess-and-check work out of creating beautiful, accurate pie charts.

Pie charts are the default in reports for several single-select questions, including:

  • Radio buttons
  • Dropdown menus
  • Ratings (Likert Scales)
  • Image Selects (Single)

If you like this visual style, you can also set the following to display as pie charts:

  • Rows of a Radio Button Grid
  • Rows of a Dropdown Menu List

It’s important to note that when using segmentation, all question types that normally default to pie charts will be displayed as bar graphs so that you can more easily determine relationships.

Hate pies? All question types that default to pie charts can also be displayed as vertical or horizontal bar charts. This, along with other editing options like filtering and statistics, can be customized by clicking the pencil icon on your report.

Vertical Bar Chart

data visualization best practices - using vertical bar charts

Vertical bar charts are used to report on multi-select questions, and question types that include a discrete list of answer options.

You are sure to be familiar with this chart style, as it is one of the easiest ways to compare multiple values at a glance.

You will find vertical bar charts as visualization for these question types:

  • Checkboxes
  • Rating (Likert Scale)
  • Image Select (Multi)

Other questions types that can be displayed using a vertical bar chart are:

  • Radio Buttons
  • Dropdown Menu
  • Rows of a Dropdowns Menu List
  • Rows of a Checkbox Grid
  • Rows of a Radio Button Grid

Horizontal Bar Chart

data visualization best practices - using horizontal bar charts

This is the first chart type in this list that does not appear as a default, but that doesn’t mean you should avoid using it!

Horizontal bar charts can help break up the monotony of multiple bar charts, but more importantly, for some data they are the more compelling visualization.

Experiment to see which type of bar chart is most interesting and representative for your data.

You can set the following question types to display as horizontal bar charts:

  • Radio Buttons
  • Dropdown Menu
  • Rating (Likert Scale)
  • Checkboxes
  • Rating (Likert Scale)
  • Image Select (Single)
  • Image Select (Multi)
  • Rows of a Radio Button Grid
  • Rows of a Dropdown Menu List


data visualization best practices - using histograms

Although easily confused with a vertical bar chart, histograms are their own unique reporting chart type. This visualization is used for questions that report a series of discrete variables. In this sense, “discrete” means a limited number of defined values, like 1 through 5. A respondent can select only one of the available digits, not, for example, 6 or 0.

Histograms illustrate how often a given variable is selected compared to the other options.

Default question types include:

  • Number
  • Percent
  • Slider
  • Slider List

Word Cloud

data visualization best practices - using word clouds

Word clouds are used to report on unvalidated open-text questions. Text questions are notoriously difficult to analyze, but word clouds are a great, simple way to display a quick overview of responses to stakeholders.

The following question types will populate a word cloud automatically:

  • Textbox (excluding number, email, percent, date and currency)
  • Essay/Long Answer
  • Textbox List

Collapsed Response List

Collapsed response lists are used to report on validated text question types where you want to have access to all exact answers without taking up pages and pages of space.

This reporting visualization is similar to the drop down menus you’ll find on websites.

Simply click “show responses,” and the section will expand. You can view all responses in this view, then click “hide responses” when you want to move on.

This reporting type is the default for validated text questions like:

  • Textbox (email and date validated)
  • Email
  • Date
  • Signature
  • File Upload


data visualization best practices - using grids

Some question types have multiple answer options in two or even three dimensions. These question types collect data that is much more complicated than the simple one-or-the-other response you get from a single select question type. To reflect this, dropdowns, sums, and grids will report as grids, showing you the number of responses for each question and the percentage of respondents who made that selection.

To make it even easier for you to review results at a glance, Alchemer automatically generates a color-coded heatmap.

In the example above, the heatmap is displayed in green. Darker shades represent a more popular answer, whereas lighter shades indicate fewer responses.

Below are the question types that report as a grid. Each question’s table format will look a little different.

  • Dropdown Menu List
  • Continuous Sum
  • Star Rating Grid
  • Checkbox Grid
  • Radio Button Grid
  • Dropdown Menu Grid
  • Textbox Grid

Diverging Stacked Bar Chart

data visualization best practices - using diverging bar charts

The diverging stacked bar chart shows four sets of ranking categories side-by-side, allowing you to dive deep into the results of your questions that ask respondents to rank items. These are: overall Rank, an automatically calculated weighted Score, the Number of Rankings, and the overall pattern of Distribution.

There are just two question types that will report in this way. They are:

  • Drag & Drop Ranking
  • Ranking Grid

Net Promoter Score

data visualization best practices - using net promoter scores

To get the most out of your NPS survey questions, our net promoter score reporting chart breaks down the distribution of responses in two ways.

The first shows you the overall distribution of detractors, passives, and promoters in relation to each other.

The second shows distribution by number and percent of respondents.

This reporting chart is used only for NPS question types.

Contact Cards

data visualization best practices - reporting on contact cards

When you are collecting personal information, from email addresses to physical addresses, that data needs to be linked to ensure that the information stays together. Contact cards are our solution, which present collected contact information in an easy to organize, easy to reference business card style.

This reporting type works with the contact form question type.

DIY Table

data visualization best practices - using diy tables

To organize text information by respondent without using a contact form question, choose the DIY table. This allows you to group data together. It does require a little set up, so be sure to check the DIY Table Tutorial.

Customizing Reports While Maintaining Data Visualization Best Practices

These reporting charts are just the beginning. Each reporting chart includes multiple options for fine tuning and customizing how your data is presented. This goes far beyond color palette.

For a full look into each chart type, see our Help Documentation, which includes details and instructions for customization.

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