How to Estimate with a Confidence Interval
Rarely will you be able to survey every customer. Instead you need to take a sample of customers and use this sample to make inferences about all customers. You have to accept that the sample estimate has a risk of being inaccurate.
Even if your sample size is small, you can still use it to make sound decisions, especially when you use techniques like confidence intervals.
You can measure the amount of error with a confidence interval. Confidence intervals tell you how much you can expect sample estimates to fluctuate based on sample size. They provide you with the most likely range for the unknown customer population numbers you’re trying to predict.
The larger the sample size, the better the estimate is. By building a 95% confidence interval around a sample, you can expect that 95% of the time your interval will contain the actual customer population average.
Confidence intervals and all data you collect will only accurately predict the customer population if your sample is representative of the actual customer population. If you sell products mostly in Europe but most of your survey data comes from the U.S., it’s unlikely your estimates will be accurate (unless U.S. customers respond similarly to European customers).