What is quota sampling?

Quota sampling is defined as a non-probability sampling method in which researchers create a sample involving individuals that represent a population. Researchers choose these individuals according to specific traits or qualities. They decide and create quotas so that the market research samples can be useful in collecting data. These samples can be generalized to the entire population. The final subset will be decided only according to the interviewer’s or researcher’s knowledge of the population.

For example, a cigarette company wants to find out what age group prefers what brand of cigarettes in a particular city. He/she applies quotas on the age groups of 21-30, 31-40, 41-50, and 51+. From this information, the researcher gauges the smoking trend among the population of the city.

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Types of quota sampling:

Quota sampling can be of two kinds – controlled quota sampling and uncontrolled quota sampling. Here’s what they mean:

Controlled quota sampling:

Controlled quota sampling imposes restrictions on the researcher’s choice of samples. Here, the researcher is limited to the selection of samples.

Uncontrolled quota sampling:

Uncontrolled quota sampling does not impose any restrictions on the researcher’s choice of samples. Here, the researcher chooses sample members at will.

Quota sampling example:

Let’s look at a basic example of quota sampling:

A researcher wants to survey individuals about what smartphone brand they prefer to use. He/she considers a sample size of 500 respondents. Also, he/she is only interested in surveying ten states in the US. Here’s how the researcher can divide the population by quotas:

  • Gender: 250 males and 250 females
  • Age: 100 respondents each between the ages of 16-20, 21-30, 31-40, 41-50, and 51+
  • Employment status: 350 employed and 150 unemployed people.
    • (Researchers apply further nested quotas . For eg, out of the 150 unemployed people, 100 must be students.)
  • Location: 50 responses per state

Depending on the type of research, the researcher can apply quotas based on the sampling frame. It is not necessary for the researcher to divide the quotas equally. He/she divides the quotas as per his/her need (as shown in the example where the researcher interviews 350 employed and only 150 unemployed individuals). Random sampling can be conducted to reach out to the respondents.

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How to perform quota sampling:

Probability sampling techniques involve a significant amount of rules that the researcher needs to follow to form samples. But, since quota sampling is a non-probability sampling technique, there are no rules for formally creating samples. Usually, there are four steps to form a quota sample. Here are the steps:

  1. Divide the sample population into subgroups: With stratified sampling, the researcher bifurcates the entire population into mutually exhaustive subgroups, i.e., the elements of each of the subgroups becomes a part of only one of those subgroups. Here, the researcher applies random selection.
  2. Figure out the weightage of subgroups: The researcher evaluates the proportion in which the subgroups exist in the population. He/she maintains this proportion in the sample selected using this type of sampling method.
  3. For example, if 58% of the people who are interested in purchasing your Bluetooth headphones are between the age group of 25-35 years, your subgroups also should have the same percentages of people belonging to the respective age group.
  4. Select an appropriate sample size: In the third step, the researcher should select the sample size while maintaining the proportion evaluated in the previous step. If the population size is 500, the researcher can pick a sample of 50 elements.
    The sample chosen after following the first three steps should represent the target population.
  5. Conduct surveys according to the quotas defined: Make sure to stick to the predefined quotas to achieve actual actionable results. Don’t survey quotas that are full and focus on completing surveys for each quota.

Characteristics of quota sampling:

Here are the top ten characteristics of quota sampling

  1. Aims to get the best representation of respondents in the final sample.
  2. Quotas replicate the population of interest in a real sense.
  3. The estimates produced are more representative.
  4. The quality of quota samples vary.
  5. Saves research data collection time as the sample represents the population.
  6. Saves research costs if the quotas accurately represent the population.
  7. It monitors the number of types of individuals who take the survey.
  8. The researcher always divides the population into subgroups.
  9. The sample represents the entire population.
  10. Researchers use the sampling method to identify the traits of a specific group of people.

Advantages of quota sampling

Here are the top four advantages of quota sampling

  1. Saves time: Because of the involvement of a quota for sample creation, this sampling process is quick and straightforward.
  2. Research convenience: By using quota sampling and appropriate research questions, interpreting information and responses to the survey is a much convenient process for a researcher.
  3. Accurate representation of the population of interest: Researchers effectively represent a population using this sampling technique. There is no room for over-representation as this sampling technique helps researchers to study the population using specific quotas.
  4. Saves money: The budget required for executing this sampling method is minimalistic.

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Applications of quota sampling:

Below are the instances where quota sampling is applied and used.

  • In situations where researchers have specific criteria for conducting research, it allows the selection of subgroups, due to which it becomes extremely convenient for researchers to obtain desired results. A trait or characteristic can be the filter for subgroup formation.
  • The researcher uses this method when he/she has time constraints. Applying quotas gives the researcher an idea of the whole population of interest in very little time.
  • Quotas are applied when the researcher is on a tight budget. Instead of researching a large population, the researcher saves money by using a few quotas to get the whole picture of the population.
  • Some research studies do not require pinpoint accuracy due to the nature of the research project. It is ideal for applying to quota sampling for these studies.

Sampling with QuestionPro Audience

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