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Quota Sampling quota sampling

Quota Sampling: Behind the Scenes of Market Research

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Surveys are the most popular method to gather insights from the target population. Whether it is the fans of Disney movies or customers of a beauty brand, you cannot survey the entire population at the same time. So, the researchers found ways to create samples from the target population to gather representative data – i.e. the data that represents the entire target population. 

One such popular method is quota sampling. So before you go about creating samples of your target market, you must understand what is quota sampling, its benefits, weakness, and how it works. And, this blog will help you learn all that. 

We will start with the definition of quota sampling and how researchers create quota samples to conduct surveys. 

What is Quota Sampling?

By definition of quota sampling, it is a type of non-probability sampling method. In this sampling process, the elements from the population are chosen non-randomly, and all members of the population don’t have an equal chance of being a part of the sample group.

In this method of sampling, researchers typically use market research software to create two stages to acquire their quota sample. 

1. First, they list relevant control characteristics and their distribution in the target population. 

This is done to ensure that the composition of the selected sample group is representative of the composition of the target population (in regard to the listed control characteristics). 

These “control characteristics” can be variables such as age, race, and sex. Researchers create these groups based on their own judgment.

2. The second stage is to select elements for the sample group based on the convenience and/or judgment of the researcher. 

This is what differentiates this type of sampling from stratified sampling, as stratified sampling uses SRS (simple random sampling) or other probability sampling methods to choose elements for the sample group once the strata are divided. 

To define quota sampling precisely, it is a two-stage non-probability sampling method that assigns quotas to the population in order to ensure that when elements of the population are selected, the sample group is representative of the population’s characteristics. After quotas are assigned, researchers choose elements from the subgroups using convenience or judgment. 

Now that we have established the quota sampling definition, we will move on to its two types. 

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What are the types of quota sampling?

With the definition of quota sampling out of the way, we can now focus on the two types. For market research tools, it can be divided into two broad categories. 

  1. Controlled sampling: This type imposes certain limitations on the researcher’s choice of samples.
  2. Uncontrolled sampling: It does not impose any limitations or restrictions on the researcher’s choice of samples.

The absence of random selection is what separates this sampling method from the rest. This is an ideal sampling method when the goal is to gather insights about certain characteristics of a particular sample group. 

We will now look at the four simple steps to build your quota sample. 

Quota Sampling quota sampling

How to perform quota sampling?

Let’s assume that a researcher wants to study the buying habits of the people in New York depending on their gender and employment status. In this example, gender and employment status will be the “relevant control characteristics”, using which the quotas will be decided.

Let’s consider the following factors for the quota sampling example. 

  • Employment Status
    • 10% of New York’s workforce is unemployed
    • 90% of New York’s workforce is employed
  • Gender 
  • 40% of New York’s population identifies as male.
  • 60% of New York’s population identifies as female.

Researchers will then use this information to reflect similar proportions of male/female and employed/unemployed in their sample group. 

Let’s say a sample size of 100 people is decided upon. Researchers will use market research tools that have quotas to decide how many males and females are chosen in regard to their employment status. 

Therefore, they may choose to include 60 females and 40 males, 10 of which are unemployed. These elements will be chosen by the researcher on the basis of convenience or judgment.

Here we have shared some examples of how quota sampling can be used in different research areas: 

  1. A company conducting market research on the use of digital novels can set quotas based on age group, gender, geographic location, and income level to ensure the sample represents various customer segments. 
  2. Social researchers studying the impact of educational attainment on socioeconomic status can use variables like income levels and educational background. 
  3. A healthcare organization researching the perception of different ethnic groups towards healthcare services can set quotas based on ethnicity, religion, and country. 

The next question that comes up often is when can you use this sampling method. 

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Example of Quota Sampling

Let’s assume that a researcher wants to study the buying habits of the people in New York depending on their gender and employment status. In this example, gender and employment status will be the “relevant control characteristics”, using which the quotas will be decided.

Let’s consider the following factors for the quota sampling example. 

  • Employment Status
    • 10% of New York’s workforce is unemployed
    • 90% of New York’s workforce is employed
  • Gender 
    • 40% of New York’s population identifies as male.
    • 60% of New York’s population identifies as female.

Researchers will then use this information to reflect similar proportions of male/female and employed/unemployed in their sample group. 

Let’s say a sample size of 100 people is decided upon. Researchers will use market research tools that have quotas to decide how many males and females are chosen in regard to their employment status. 

Therefore, they may choose to include 60 females and 40 males, 10 of which are unemployed. These elements will be chosen by the researcher on the basis of convenience or judgment.

The next question that comes up often is when can you use this sampling method.

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When can quota sampling be used?

With this type of sampling, you can select subgroups, which makes it ideal for research. You can gather desired results from your surveys. 

Here are five scenarios when you can use this type of sampling method to study the population. 

  1. You can use it to compare two subgroups and determine the distinguishing features among the shared characteristics. For example, the use of social media of boomers vs millennials. 
  2. When researchers have a limited time frame, they can use quota sampling method as it is a relatively quick method of sampling. This is because it uses convenience or judgment sampling to select elements once quotas are assigned.
  3. This method of sampling is also relatively cheaper than other methods, hence, it is also used when researchers have a limited budget.
  4. When the researcher is interested in studying certain subgroups of the population, this is the next best option after stratified sampling. It aims to select sample groups that are representative of the population but is also not as expensive and time-consuming as stratified sampling. 
  5. You can use this sampling approach when you have predetermined criteria to survey. It is very convenient because you can filter the characteristics to create a quota sample. 

What are the advantages of quota sampling?

It is a popular choice among researchers for many reasons. We have listed down some of these reasons that explain the advantages of the sampling method. 

  1. Can accurately represent the target population as quotas are assigned in order to ensure the final quota sample is representative of the population.
  2. Is a quicker and cheaper method of sampling in comparison to probability sampling methods as elements are chosen using convenience or judgment after quotas are assigned.
  3. Useful when minority participation is critical in the study as all targeted groups will be represented in the sample group. 
  4. You have control over the survey. Quota sampling allows you to monitor who takes the survey and also the number of participants for each quota sample. 

Affordability and ease are enough advantages to categorize it as an effective sampling method. However, there are some challenges that we will discuss next. 

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What are the disadvantages of quota sampling?

Here are some limitations of this type of sampling you need to keep in mind when you conduct research. 

  1. Not easily generalizable to the population as elements are chosen from the subgroups based on judgment/convenience hence not taking into account the standard deviation of characteristics among these subgroups.
  2. The inability to calculate sampling error is a disadvantage of all non-probability sampling methods.
  3. High potential for sampling bias with the use of convenience or judgemental sampling to pick the final sample group.
  4. You may have to create additional quota samples to ensure each group is exclusive and there is overlap. However, this can increase the sample size, which will result in more time, resources, and money spent on the research. 

What are some best practices for conducting quota sampling?

When you want to conduct quota sampling for your research, it’s important to follow some best practices to maintain the integrity and ensure the reliability and quality of research data. 

  1. Define the target audience.
  2. Determine quotas.
  3. Randomize within the quotas.
  4. Adjust quota.
  5. Use multiple variables.
  6. Validate your research sample.

Let’s look into these in detail. 

  1. Define the target audience: 

Identify the demographic that you intend to represent in your research sample. Define the target market segment based on the factors or characteristics. 

  1. Determine quotas: 

Set proper quotas for each segment based on their proportion in the target population. Each quota should establish the importance of each sub-group and ensure representation. 

  1. Randomize within the quotas: 

It’s best also to introduce randomization within each quota in quota sampling techniques. This enables you to minimize bias as it ensures that the selection is not influenced by subjective judgment. 

  1. Adjust quotas: 

For reliable research results, monitor the sample recruitment process and track the process of data collection. Adjust the quotas when certain quotas fill up quickly or slowly to main balance and ensure generalization.  

  1. Use multiple variables: 

While demographic variables are the general choice in the quota sampling process, it’s best to use other variables as well. For example, in market research, use variables such as purchase history, product usage, etc. This will help you gather nuanced data. 

  1. Validate your research sample: 

Evaluate the representativeness of the sample by comparing its characteristics to those of the target population. 

Wrapping up;

This sums up all about this sampling method. To recap, as the definition of quota sampling method goes, you use your personal judgment to select the final quota sample for the project. While this may create sampling error, you can always examine it using online survey software. 



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