Get prepared with your survey

Identify goals and purpose of the survey.

If you have decided to do a survey, you must be sure exactly why you're doing it. The first step in any survey is deciding what you want to learn.
What questions do you want to answer? Is it to get a general idea of the demographics of your area? To find out what people think about a particular issue or idea? Or is there another reason you're considering a survey?

The goals of the project determine whom you will survey and what you will ask them. If your goals are unclear, the results will probably be unclear. Some typical goals include learning more about:

  • The potential market for a new product or service
  • Ratings of current products or services
  • Employee attitudes
  • Customer/patient satisfaction levels
  • Reader/viewer/listener opinions
  • Association member opinions
  • Opinions about political candidates or issues
  • Corporate images

These are only general areas. The more specific you can make your goals, the easier it will be to get usable answers.

In any case, you will need to keep the purpose of the survey in mind throughout the process, as it will influence the choice of questions, the survey population, and even the way the survey is delivered (e.g., a computer-savvy population can be surveyed over the Internet; a population that is largely illiterate shouldn't be asked to take a written survey, and so forth).

Identify whom you will survey

The next step is finding out who has the answers to your question or questions. In other words, it's time for you to determine your audience -- the people who can best answer the questions your initiative needs to ask. Who will you survey? Is it the general public? The current program beneficiaries? People in a specific neighborhood or segment of the community? Potential members?

There are two main components in determining whom you will interview.

  • The first is deciding what kind of people to interview. Researchers often call this group the target population. If you conduct an employee attitude survey or an association membership survey, the population is obvious. If you are trying to determine the likely success of a product, the target population may be less obvious. Correctly determining the target population is critical. If you do not interview the right kinds of people, you will not successfully meet your goals.
  • The next thing to decide is how many people you need to interview. Statisticians know that a small, representative sample will reflect the group from which it is drawn. The larger the sample, the more precisely it reflects the target group. However, the rate of improvement in the precision decreases as your sample size increases. For example, to increase a sample from 250 to 1,000 only doubles the precision. You must make a decision about your sample size based on factors such as: time available, budget and necessary degree of precision.

Almost all surveys rely on sampling, i.e.: identifying a section of your population that satisfies the characteristics you try to survey, rather than doing a census.
For a truly representative sample, you must be sure that every member of the group you want to survey has an equal chance of being in the sample, and/or you must have a fairly large sample. It's important to make sure that the sample size you choose is adequate and not excessively large or small. If too large, it may be impossible to survey everybody effectively and within your budget; if too small, your credibility may suffer. A general rule to keep in mind is that the larger the sample size, the more accurate a reflection of the whole it will be.

You can figure out how big your sample should be by using a sample size calculator, such as:

  • ResearchInfo's Sample Size Calculator allows you to decide whether you want to calculate for 95% or 99% confidence level (the statistical term for the amount of certainty you have about the accuracy of your results).
  • UCLA's Sample Size Calculator from the online statistics textbook is a bit more advanced.

You might also need to give some thought to the design of your sample, especially if you are hoping to get representative responses from two or more groups; you need to come up with separate population counts for each of these groups and then select a sample from each. The samples should be large enough to represent the group it is drawn from, but the sample sizes should be proportional to the groups they represent.

Potential sampling pitfalls
Sampling is a challenge to conducting good surveys, but there are other pitfalls. For example, when people volunteer to respond to a survey, we say they are self-selected. These people may have a special interest in answering your survey, so their answers may not be truly representative of the group you're interested in. There are ways of dealing with self-selected audiences, such as only using a random selection of their surveys when only self-selection is involved. For example, if you get back 300 completed surveys, you might decide to only use every third one in order to randomize the results.

Avoiding a Biased Sample
A biased sample will produce biased results. Totally excluding all bias is almost impossible; however, if you recognize bias exists you can intuitively discount some of the answers. The following list shows some examples of biased samples.

 Example of Biased Sample 
Sample  Probable bias  Reason 
Your Customers  :-) favorable If they were unhappy, they wouldn't be your clients. The important point is to know why they are happy. 
Your Ex-customers  :-( unfavorable  If they were happy, they would still be your clients. The important point is to know why they drop you. 
Phone-in :-$ Extreme view Only people with a strong concern (For or Against) are likely to phone in. In addition, they may phone several time to load the votes/poll.
Daytime :-? Non-working Most of the people at home during the days do not work. Their interview/opinion at that occasion may not reflect the working people.
Internet :-@ Atypical people Not the majority of people do have/are used to internet. These users are representative fo the general population, even more when matching sampling on gender, age... 
Another issue, respondents may complete several forms to bias results (except if the software can prevent that).

The consequences of a source of bias depend on the nature of the survey. For example, a survey for a product aimed at retirees will not be as biased by daytime interviews as will a general public opinion survey. A survey about Internet products can safely ignore people who do not use the Internet.


A Quota is a sample size for a sub-group. It is sometimes useful to establish quotas to ensure that your sample accurately reflects relevant sub-groups in your target population. For example, men and women have somewhat different opinions in many areas. If you want your survey to accurately reflect the general population's opinions, you will want to ensure that the percentage of men and women in your sample reflect their percentages of the general population.

If you are interviewing users of a particular type of product, you probably want to ensure that users of the different current brands are represented in proportions that approximate the current market share. Alternatively, you may want to ensure that you have enough users of each brand to be able to analyze the users of each brand as a separate group. If you are doing telephone or Web page interviewing, The Survey System's optional Sample Management or Internet Module can help you enforce quotas. They let you create automatically enforced quotas and/or monitor your sample during interviewing sessions.