CSAT Data Insights

To explain the thought in this article, we're going to present a hypothetical scenario. You run a customer satisfaction survey with a sample of 1000 people and you are analyzing overall satisfaction. You see the results of your survey, and find that you have an average score of 6.6 out of 10, for slightly above average.

You also find that 80% of your respondents answered with an 8, while 10% answered with a 1. Should you consider this a success or a failure? While rarely will you see a scenario quite this extreme, it does bring about an interesting question – which should be considered more successful, a high average or a high number of people providing a very positive answer? The answer is probably both.

When you complete your analysis, you should absolutely look at the average score, since average score tells you a lot about the health of your organization as a whole. But the distribution of the answers matters also, because average score doesn't tell the whole story. From the example above, you can probably make the following assumptions: Your loyalty is likely very high, because you have a high number of people that rate you an 8/10.

Something in your company seems to have a very profound negative effect on those that don't have as good an experience. You have no 10's, which means your company can absolutely improve. Had you looked only at the average, you would have missed this information.

Looking at the distribution allowed you to learn more from the data. However, you shouldn't just look at the distribution either. The 6.4 average is indicative of a business that isn't necessarily on the path to long term success.

While loyalty is currently high, the ability to cause that many "1's" absolutely is going to affect the future of your company, and could have a profound negative effect. The average does matter, and in a more realistic scenario, the average may be necessary to really understand the data distribution. So rather than look at just the average or just the distribution, take time to look at both.

We have charts available on SurveyMethods that make it easy to view the data distribution and analyze the data, and you'll often find that within that analysis you can learn even more about how your company truly feels, and where it can improve.