Customer satisfaction is a valuable customer feedback metric. Here are the four visualizations to find stories in your customer satisfaction data.

Measuring customer satisfaction only requires a single customer feedback survey question. Something as simple as, “On a scale of 1-10, how satisfied are you with this product?’ can open you to a world of information about your customers and how they interact with your product.

Customer satisfaction data is especially useful when analyzed alongside geographic, market, or time series data. You can analyze how your numbers have developed over time, compare your scores with industry competitors, and measure how satisfaction varies across the world. But in order to do this, you need to know the correct graph or chart to use. Using survey data from the tech industry, we'll show you the top four visualizations for customer satisfaction data.

Pictograph bar chart

A customer satisfaction score doesn’t tell you much about the distribution of responses. An average of 3.5 on a 7-point scale usually means that the majority of responses are scattered around the average, but it could also be that the responses are equally scattered around the two extremes. It's important to find out what is actually going on. A pictograph bar chart is a great way to visualize the distribution of your customer satisfaction numbers.

The chart above shows the distribution of customer satisfaction responses for a tech company. We can see from the visualization that the responses are distributed around the mean, which is generally what we expect to see. There are no unusual clusters or oddities within the data. If the responses contained clusters around the two extremes, then we would conclude that there are distinct groups within the customer base that are unlike the rest.

The distribution of your responses should inform your decision making. If the responses are clustered around the average, then incremental improvements to your product or service should increase future satisfaction scores. However, if there are clusters around the lower tail of the distribution, then you should try to pinpoint exactly why a subset of your customer base is so dissatisfied.


Time series line chart

If you are working with data from multiple surveys collected over a period of time, then a simple pictograph bar chart will not suit your needs. Instead, you will want to use a visualization that can track how customer satisfaction has varied over time. The results from a single survey could be an anomaly and therefore unreliable, but results over an extended period tend to be far more trustworthy.

A time series line chart is a great way to visualize your customer satisfaction results over time. It’s always a good idea to send out customer feedback surveys in regular intervals, and including an unchanged customer satisfaction question is a great way to track how satisfaction rates are trending. From the chart, we can see that the average scores fluctuate between 6.5 and 7.5, but there isn't a clear upward or downward trend.


Geographic map

It's often useful to see how your customer satisfaction numbers vary across geographic regions. A geographic map that color-codes countries based on their average scores can describe how language and cultural factors are influencing customer satisfaction rates.

The chart above shows the average customer satisfaction of respondents for each country.  Most countries do not have enough users to make meaningful inferences from the data, so we'll have to limit our analysis to only a handful of countries. Despite the limited data set, there are still a few useful insights to be found. One interesting observation is that English-speaking countries generally have higher rates of customer satisfaction than non-English speaking countries. This is a particularly useful insight if the company is looking to expand into foreign markets.


Stacked bar chart

Customer satisfaction data is always more useful when placed in the context of the overall market. Average satisfaction rates can vary wildly across industries, and so an individual statistic can be misleading if interpreted within a vacuum. For this reason, it's important to establish industry benchmarks and compare your results with your competitors.

The stacked bar chart above shows the distribution of customer satisfaction scores for the wider tech industry. We can see that there is enormous variation within the industry. Companies like Google have a satisfaction rate of over 75% among survey respondents, while Yahoo barely breaks 20%.


Try it yourself

Want to start creating insightful customer satisfaction visualizations? Click the links within this blog post for simple step-by-step guides on how to recreate the data visualizations!