Following our User Group events in Norway, we often conduct a survey to evaluate the success of the event and gather feedback for future improvements. This time, the survey was created using Microsoft Forms and achieved a response rate of 26%. To present the findings in a clear and engaging format, we leveraged Visual Analytics to transform the raw data into an interactive report. This approach allowed us to highlight key metrics and showcase participant engagement through dynamic and visually compelling dashboards.
The survey comprised 11 questions, including five rating score questions accompanied by follow-up prompts intended to encourage participants to reflect more deeply on their responses. Toward the end, respondents were presented with an optional field to enter their name for a prize draw.
Survey questions:
The survey responses were exported from Microsoft Forms as an Excel file. Before uploading the data to Visual Analytics, minor adjustments were made such as renaming questions for easier reference and navigation. Below is a snapshot showing a selection of records from the Excel file:
During the layout process, we chose to structure the report so that each rating score question was paired with its corresponding reflection question on the same page. This resulted in five dedicated pages, each following a consistent format. Additionally, we created a page displaying all submitted names for the prize draw. As this page was used as a Pop-up window, the finalized Visual Analytics report comprised five pages.
To structure the page layout, it was decided to use the default Standard container. This method results in a clean, organized and visually balanced design.
To effectively visualize the rating score question on each page, a Gauge was used to provide a clear and intuitive representation of the data. After dragging the Gauge from the Objects in the left pane onto the canvas, the relevant rating score question was selected as the Measure beneath Data Roles in the right pane.
To establish a benchmark, we created a target variable by assigning the maximum possible rating score across all respondents. This target helps compare the rating score against the highest achievable rating. The new target variable was assigned as Target beneath Data Roles in the right pane.
To enhance visual impact and maintain consistency throughout the report, we applied formatting rules using the Display Rules available in the right pane. When configuring rules, it’s important to choose colors that complement each other well, as the same palette is applied across all visual elements. A cohesive color scheme not only improves the overall aesthetic, but also reinforces visual consistency across the report. The formatting rules were configured as follows:
To ensure each visualization in the report is clearly understood, we added custom titles that reflect the original survey questions. By labeling each object with its corresponding question, viewers can immediately grasp the purpose of the visualization without needing to refer back to the survey. The object titles were added by navigating to the Options in the right pane, then selecting Custom Title under the Object section and entering the original survey question text.
This setup generated the following Gauge visualization:
To visualize the reflection responses alongside the rating scores, a Treemap from Objects was placed next to the Gauge. In the Data Roles pane on the right, the Tile was assigned to the variable containing the reflection responses and Size was linked to the corresponding rating values.
To improve readability, the Text Style for Data Labels was adjusted under Options in the right pane, setting the font size to 10. Since some responses included missing values, a filter was applied to the reflection variable by unchecking the Include missing values option in the Filters pane. This ensured that only complete responses are displayed.
Finally, to maintain visual consistency with the rest of the report, we applied these Display Rules on the Treemap:
Below is the Treemap created from this setup:
Thanks to the use of Display Rules, it's easy to distinguish which reflections correspond to each rating level.
To visualize how many respondents that selected each rating, a Bar chart object was placed directly beneath the Gauge. This visualization requires a character variable, so the original rating variable was duplicated and converted into a character format. The new variable was then assigned as Category beneath Data Roles in the right pane. For the Measure, the Frequency Percent was selected to display the distribution of responses across rating levels.
To maintain visual consistency with the Gauge and Treemap, the Display Rules was applied to ensure a harmonious color scheme and aligned thresholds:
The Bar chart was displayed like this:
To make the report dynamic, we wanted to be able to see which individuals provided the different ratings in the Bar Chart. While not all respondents chose to include their names, it was still valuable to highlight those who did. To achieve this, a separate page was needed for each of the five rating questions.
Each Pop-up page was built by dragging a List table from Objects onto the canvas, then assigning the relevant rating and name variable as Columns beneath Data Roles in the right pane. To ensure visual harmony with the rest of the report, we also applied consistent Display Rules on the table:
The result looked as follows:
Once the page was finalized, we clicked the three dots next to the page name, selected Page Type and chose Pop-Up for this setup. The final step was to link each Pop-Up page to its corresponding Bar Chart. This was done by right-clicking on the Bar Chart, selecting Add Link and then Page Link, before selecting the appropriate page. As a result, when a bar is clicked in the Bar chart, a Pop-Up window appears showing the names of respondents who selected that specific rating:
Creating this report based on the survey results was a rewarding process. With just a few thoughtful steps, the visual elements began to harmonize and interact seamlessly and making the data both engaging and easy to explore. I'm especially pleased with how the use of consistent colors and design rules brought everything together, giving the report a cohesive and professional look that enhances both clarity and impact.
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