Best Charts for Survey Results

What are the best charts for survey results?
The chart options are Bar, Stacked Bar, Line, Histogram, Pie, Funnel, Scatter, Heat, Radar and Treemap. There are lots of ways you can visualize your survey data. The best type of chart to use depends on the type of data you're working with, and the insights and underlying messages you want to present.

If you need a survey and charting app, feel free to try PageCaddy for free. Build a survey using our easy-to-use survey builder and generate charts with many customizations. Share the form and charts anywhere using the embed link and QR code. Contact our customer service team if you need to ask a question.

Creating great forms and surveys with engaging questions are the beginning to getting the useful insights.

We'll try to breakdown some of the most common and effective charts for different survey results and research projects.

You should be able to find most these charts available in most chart and dashboard apps.

1. Bar Chart

Great for	Categorical or discrete values.
When to use	If you have categories (e.g., responses like "Excellent", "Very Good", "Just OK", "Bad", and "Not Sure") and want to show how many people chose each option.
Example	Feedback survey responses about customer experience, where you want to show how many people picked each level of satisfaction.

2. Stacked Bar Chart

Best for	Multiple categories within a category (e.g., breaking down the responses by demographic group).
When to use	If you want to compare multiple categories across a few groups or conditions.
Example	Customer satisfaction levels differ among different age groups or regions.

3. Line Chart

Best for:	Time-series data.
When to use	If you are tracking changes in survey responses over time.
Example	A customer satisfaction survey conducted monthly, with a line chart showing satisfaction trends and levels over several months.

4. Histogram

Best for	Distribution of continuous data.
When to use	If your survey includes numeric data (e.g., age, income, or other continuous measures) and you want to show the distribution of responses.
Example	Showing the distribution of ages of respondents.

5. Pie Chart

Great for	Displaying proportions of the total survey
When to use	If you want to show how each response (usually in percentages) contributes to the total.
Example	Proportion of respondents who prefer different product features.
Tips	If you have continuous values eg. if you ask how many hours of exercise per week and people responded with a number, you can group the numbers into "bins" like "1-3" hours before creating the pie chart. Try to avoid using too many categories in pie charts otherwise it becomes hard to interpret.

6. Funnel Chart

Best for	Visualizing stages in a process, especially when data shows different quantities at each stage.
When to use	If you're analyzing a survey where respondents move through different stages or filters (e.g., marketing funnel).
Example	Showing the number of respondents who move through the sales funnel such as enquiry, email brochure, first phone call, demo, quotation, and sale.

7. Scatter Plot

Best for	Showing relationships between two continuous variables.
When to use	If you have two numeric survey questions and want to see if there is any correlation between them.
Example	Showing a relationship between the age of respondents and their satisfaction rating.

8. Heat Map

Best for	Displaying correlations between multiple variables or cross-tabulated data.
When to use	If you have a large dataset with multiple factors and want to show the intensity of responses or patterns.
Example	Survey results broken down by both age and satisfaction level, where color intensity indicates frequency or strength of the response.

9. Radar Chart

Best for	Comparing multiple variables (e.g., satisfaction with different aspects of a product).
When to use	If you want to show how and quantity of respondents feel about multiple dimensions at once.
Example	Comparing satisfaction levels across different features of a product (e.g., ease of use, design, price, etc.).

10. Treemap

Best for	Visualizing hierarchical data and their proportions.
When to use	If your survey responses are hierarchical (nested categories), and you want to see proportions of each category relative to the whole.
Example	A survey with multiple factors and sub-categories where you want to show relative proportions.

Final Tips

1. Know your audience: Some charts are easier and faster for non-technical audiences to understand (e.g., pie charts) while others are better suited for deeper analysis (e.g., heat maps, scatter plots).
2. Consider what insight and outcomes you want to present: Use charts to present the most significant insight you got from the survey, and communicate to your audience what actions or outcomes can improve your school, business, research project, organization, etc.
3. Know your data type: Categorical, discrete, or continuous data will determine the chart choice.
4. Simplicity : Avoid overcomplicating the visualizations, or having too many fancy formatting that may confuse the audience.

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