When you’re asking “how many survey respondents do I need?”, what you’re really asking is, “how big does my sample need to be in order to accurately estimate my population?” These concepts are complex, so we’ve broken the process into 5 steps, allowing you to easily calculate your ideal sample size and ensure accuracy in your survey’s results.

By population we mean the entire set of people who you want to understand (your sample is going to be the people from this population who end up actually taking your survey).

So, for example, if you want to understand how to market your toothpaste in France, your population would be residents of France. If you’re trying to understand how many vacation days people who work for your toothpaste company would like to have, your population would be employees of your toothpaste company.

Regardless of whether it’s a country or a company, figuring out what population you’re trying to understand is a vital first step. Once you know what your population is, figure out how many people (roughly) make up that population. For example, roughly 65 million people live in France and we’re guessing that your toothpaste company has fewer employees than that.

Got your number? Okay then let’s keep going…

Think of this step as an assessment of how much of a risk you’re willing to take that the answers you get to your survey will be off by a little bit due to the fact that you’re not surveying your entire population. So here are your two questions to answer:

*How sure do you need to be that the answers reflect the views of your population?*

This is your margin of error. So if, for example, 90% of your sample likes grape bubble gum. A 5% margin of error would add 5% on either side of that number, meaning that actually 85-95% of your sample likes grape bubble gum. 5% is the most commonly used margin of error, but you may want anywhere from 1-10% for a margin of error depending on your survey. Increasing your margin of error above 10% is not recommended.*How sure do you need to be that the sample accurately samples your population?*

This is your confidence level. A confidence level is the likelihood that the sample you picked mattered in the results you got. The calculation is usually done in the following way. If you picked 30 more samples randomly from your population, how often would the results you got in your one sample significantly differ those other 30 samples? A 95% confidence level means that you would get the same results 95% of the time. 95% is the most commonly used confidence level but you may want a 90% or 99% confidence level depending on your survey. Decreasing your confidence level below 90% is not recommended.

Using the chart below, select your approximate target population, then choose your margin of error to estimate the number of completed surveys you’ll require.

Now that you have your numbers from Step #1 and Step #2 check out this handy chart below to figure out how big a sample you’ll need…

Population | 10% margin of error | 5% margin of error | 1% margin of error | 90% confidence level | 95% confidence level | 99% confidence level |

100 | 50 | 80 | 99 | 74 | 80 | 88 |

500 | 81 | 218 | 476 | 176 | 218 | 286 |

1,000 | 88 | 278 | 906 | 215 | 278 | 400 |

10,000 | 96 | 370 | 4,900 | 264 | 370 | 623 |

100,000 | 96 | 383 | 8,763 | 270 | 383 | 660 |

1,000,000+ | 97 | 384 | 9,513 | 271 | 384 | 664 |

*Note*: These are intended as rough guidelines only. Also, for populations of more than 1 million you might want to round up slightly to the nearest hundred.

We’re sorry to say that not everybody you send your survey to will fill it out.

The percentage of people who do actually fill out a survey that they receive is known as the “response rate”. Estimating your response rate will help you determine the total number of surveys you’ll need to send out to obtain the required number of completed surveys.

Response rates vary widely depending on a number of factors such as the relationship with your target audience, survey length and complexity, incentives, and topic of your survey. For online surveys in which there is no prior relationship with recipients, a response rate of between 20-30% is considered to be highly successful. A response rate of 10-15% is a more conservative and a safer guess if you haven’t surveyed your population before.

Just divide the number you got from Step #3 by the number you got from Step #4. That’s your magic number.

So, for example, if you need 100 women who use shampoo to fill out your survey and you think about 10% of these shampoo-using women that you send the survey to will actually fill it out, then you need to send it to 100/10% women – 1000!

SurveyMonkey Audience has millions of survey respondents ready to provide the answers you need to make critical decisions. Each survey taker has been profiled against hundreds of demographic, lifestyle, occupation and geographic data points, so that you can survey the exact group whose feedback matters to you. In as quickly as two days, a project can be launched, the full set of data can be collected, and the results ready made for analysis — all within your existing SurveyMonkey account.

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