The most popular technique for learning about a target audience is to conduct a survey. You can’t possibly poll every person who likes Disney movies or uses a certain beauty product all at once. This necessitated devising strategies for drawing up samples from the intended population to collect representative data. Quota sampling is one of the most widely used techniques for collecting data in surveys and scientific studies.
To make sure that quota sampling is the best strategy for your objective, you must first understand what it is, its strengths, and weaknesses.
Definition of “Quota Sampling” in simple terms
Quota sampling is a subset of non-probability sampling in which a representative cross-section of the target demographic is used to populate a sample. These people are chosen according to quotas or categories that ensure they reflect your target audience’s demographics.
The ideal final sample would reflect the target audience’s demographics in terms of the distribution of these traits.
Samples for quota purposes are collected in two phases with the help of market research software.
- To begin, they summarise the distribution of the primary control factors among the study population.
- After that, the researcher chooses the aspects that will comprise the sample population based on their own preferences or investigation constraints.
For instance, a beauty product manufacturer may like to know which cosmetic brands are more prevalent among people of different ages in a given metro area. All respondents aged 21–30, 31–40, 41–50, and 51–plus are subject to a survey quota. The researcher uses these responses to infer a trend in cosmetic products used by the city’s population.
An overview of types of quota sampling
There are two distinct varieties of quota sampling: controlled quota sampling and random quota sampling. What they imply is as follows:
- Controlled quota sampling: Sample selection criteria are limited by controlled quota sampling. In this case, the researcher can only do so much through sample selection.
- Uncontrolled quota sampling: There is no constraint on a researcher’s ability to conduct research using uncontrolled quota sampling systems. In this scenario, researchers are given complete leeway in selecting their sample members.
Quota sample characteristics
Listed here are the top ten features of quota sampling:
- Assures that the sample composition is optimal in terms of the types of respondents.
- Estimates are generated with greater accuracy.
- Samples used for quotas can vary in quality.
- It helps researchers save time because the data they get from the sample is representative of the whole.
- Research budgets are spared if the quotas are representative of the population.
- Every study involves a subset of the whole population created by the researcher.
- This sample is statistically valid for the total population.
Tips for Taking Quota Samples
Probability sampling approaches, such as quota sampling, are subject to a large number of regulations. Due to the fact that quota sampling is not chance-based, there are no hard and fast guidelines for selecting samples. However, there are four steps to the production of a quota sample.
Make subgroups from the sample population
A researcher uses stratified sampling to divide the entire population into smaller groups based on shared characteristics. Members of each subgroup are then only included in one of the groups. Random sampling is used here by the researchers.
Calculate the relative importance of each subgroup
The researcher calculates what percentage of the population falls into each class. In the sample drawn using this procedure, he keeps the proportion constant.
For instance, a subgroup of people aged 25 to 35 should include 58% of those who are interested in buying your Bluetooth headphones.
The sample number should be sufficient
The third stage is for the researcher to choose the sample size, keeping the evaluated proportion in mind. It is possible to take 50 people as a representative sample of a population of 500 people.
Until your sample size is satisfied, survey your audiences
Gather data from surveys according to the predetermined limits. Keep to your goals to see tangible outcomes. Refrain from surveying already-filled quotas; instead, give your complete attention to filling out the surveys for each available quota.
Big room for error in terms of objectivity
This method’s potential for biased samples due to its reliance on non-random sample selection makes the data less trustworthy.
Not applicable across the population
This method of sampling has the potential to be highly representative of the quota-defining features, but it may underrepresent other relevant characteristics.
Not Possible to Determine Sampling Error
Researchers can’t determine the sampling error while using quota sampling because it’s not a probability sampling method.
Learn to work smarter, not harder!
Explore our solutions that help researchers collect accurate insights, boost ROI, and retain respondents.
Heena Shah – Content Writer at Sambodhi