Survey the right people
Google's People Analytics team constantly thinks about survey fatigue and the target population. Does everyone in the target group need to receive the survey? Sometimes it makes sense to do this, like when the group is fairly small, or if you are explicitly seeking high participation (as in an annual company survey that goes out to all employees). However, many times surveying a sample of respondents yields data that is just as powerful and informative as surveying an entire population.
Simple random sampling is a low-effort approach that we sometimes use as it gives everyone in the target population an equal, non-zero chance of being asked to participate. A very basic approach to simple random sampling is:
- Get a list of the people in your target population.
- Use a random number generator to assign numbers to the list of names of people in your target audience.
- Pick the top "n" number of people.
The main drawback to the simple random approach is the risk of drawing too few participants from a small portion of the company and not being able to make conclusions about that population. For example, in a global survey you could use a more advanced technique called stratified random sampling. In this form of sampling, you draw a random-but-proportionate number of people from each group in your target population (e.g., 10% of Sales in North America, 10% of Sales in Europe). It takes more effort, and you may have trouble identifying the appropriate groups, but this approach ensures that your sample includes people from all the important sub-groups of your target population.
You can learn more about survey sampling methodologies from the Harvard University Program on Survey Research.