What is a sample size?
A sample size is the total number of data points you collect in a study. For example, the number of survey responses you gather from customers.
Why is having a sample size important?
Having a big enough sample size is key for determining whether your data accurately reflects the population as a whole. A larger sample size generally means greater accuracy.
For example, let’s imagine you’re a car manufacturer and want to determine what the most in-demand color for cars is. If you asked 5 people which color car they prefer, you’d have some data—but it clearly wouldn’t be enough data to make a business decision on. You’d need a much bigger sample size.
What calculator do you use?
We recommend using a free tool like this one from TGM Research.
What is Slovin’s Formula?
Slovin’s formula helps you determine how many people to include in a sample when you want to study a large group (but don’t know much about it).
Researchers use this formula when they can’t guess how people in the group behave, or how their opinions are spread out.
The formula looks like this:
n = N / (1 + N × e²)
Here’s what the letters mean:
n is the number of people or items you need in your sample
N is the total number of people or items in the whole group
e is the margin of error you’re willing to accept (like 0.05 for 5%)
Because this formula includes a margin of error, you can choose a value that matches the confidence level you want. For example, using a 5% margin of error usually lines up with a 95% confidence level. So if you repeated the study many times, your results would fall within that margin 95 times out of 100.
How a sample size calculator works
A calculator tells you how many people you need to survey based on how accurate you want your results to be. Three main variables determine this accuracy:
Don’t know your numbers?
If you don’t know your numbers, use the default settings. The calculator starts with industry-standard values:
Population size: 20,000
Confidence level: 95%
Margin of error: ±5%
Other useful resources:
The ultimate guide to surveys: benefits, types, and tips
External factors that affect your survey’s accuracy
No random sample perfectly represents an entire population, but you can get close. The following factors affect your accuracy, so understanding them helps you create better customer research projects.
3 things to remember when calculating your sample size
It’s fine to change your settings when calculating sample size, but keep in mind that:
1) The bigger your sample, the better the results (up to a point)
2) A smaller margin of error requires a larger population size
3) A higher confidence level requires a larger sample size
3 surveys you can use to learn about your customers’ experiences
Collecting accurate survey data helps you better understand your users and improve your products and messaging. Here are 3 great survey types to get started with (you can create all of them with Contentsquare).
