Purposive Sampling 101: Definition, Types, And Examples

Data is the new oil. We believe in that, don’t we? Well, not exactly. Raw data can never be fuel unless it’s structured – and the sampling method we choose affects that structure. One such sampling technique is purposive sampling (also known as purposeful sampling). 

If used correctly, the purposive sampling method generates high-quality data fairly quickly. In this article, we will:

• Purposive sampling definition
• Seven types of purposive sampling
• Examples of purposive sampling
• How to do purposive sampling
• When to use purposive sampling
• Advantages of purposive sampling

Just get yourself a cuppa and dive deep into Purposive Sampling 101.

What Is Purposive Sampling? 

The purposive sampling method is about selecting samples from the overall sample size based on the judgment of the survey taker or researcher.

In other words, a purposive sample is collected according to the requirements of the test, survey, or research that it’ll be used for.

To explain it better:

• Let’s say you have to collect purposive samples of ‘businesses started in 2025 that require a chatbot for the website’.
• The key part here is ‘businesses started in 2025’. So you’ll automatically discard from your sample any business that started before 2025.
• Next, you’ll see who already has a chatbot on their website. The ones that have it are also out of your final sample – leaving you with businesses that started in 2025 and don’t have chatbot support.

Voila! That’s your purposive sample for this case.

Researchers use survey software like SurveySparrow to easily collect and visualize data from any size of sample. Sign up below to try all of our features for FREE.

7 Different Types of Purposive Sampling Techniques

1. Maximum Variation Sampling

Also known as heterogeneous sampling, maximum variation sampling is a purposive sampling technique that captures a wide range of perspectives on your topic.

In this way, we can search and form samples for different perspectives, ranging from typical attributes to the more rare or extreme ones about the ‘total population’ that provide a diverse range of cases for an experiment or event.

These attributes can be of the people, businesses, events, or raw data in the sample, depending on the researcher’s or survey taker’s requirements. They can also be behaviors, incidents, qualities, traits, experiences, or situations.

2. Homogeneous Sampling

Homogeneous sampling is a purposive sampling method that’s precisely the opposite of the maximum variation method. With homogeneous sampling, a group of people of the same age, gender, background, or occupation will be chosen.

Researchers often use homogeneous purposive sampling when the research is about a specific trait, feature, or area of interest. This type of purposeful sampling is common in survey research – a methodology to study specific areas of interest.

3. Typical Case Sampling

Typical case purposive sampling is used when the researcher or evaluator wants to study a phenomenon related to the parent sample’s typical (average) members.

For example, if a survey taker wants to understand how inflation affects people with average income, then only average income earners will be selected from the overall sample.

4. Extreme Case Sampling

We use extreme case sampling to study the outliers from a set norm for a particular phenomenon or trend.

So, we will choose those not falling within the norm for an experiment’s requirement from the total sample. The reason behind this is to find why such anomalies occur and whether there is a pattern to them.

5. Critical Case Sampling

Critical case purposive sampling chooses one information-rich case to represent the population. The researcher expects it to reveal details that apply to other similar cases by studying it.

For example, to study crop patterns at different times of the year, a single village with frequently harvested land, a good water supply, moderate temperature, and adequate sunlight can be chosen instead of roping in multiple cases.

6. Total Population Sampling

Total population sampling is a way of carrying out purposive sampling where the entire population (parent sample) carrying one or more shared characteristics are examined or surveyed. These characteristics can be some specific experience, knowledge, or skills.

We use this method when the parent sample is small, and it’s easy to recognize at least one similar trait among them.

7. Expert Sampling

Expert sampling is used when the researcher needs to glean knowledge from individuals with particular expertise. This expertise may be necessary during the starting phase of qualitative research because it can help highlight new areas of interest.

The investigated expertise later forms the basis for further sampling and evaluation. Expert samples are helpful when there is a lack of evidence or prior knowledge in an area with high levels of uncertainty.

Purposive Sampling Examples and Use Cases

We know the definition of purposive sampling and different ways of carrying out purposive sampling. Now, let’s check out some examples of where it’s used.

Use Case #1: Choosing a Candidate

The first and most obvious example of purposive sampling is choosing skilled candidates for a vacancy.

One can call it a classic case of expert sampling; a panel of seniors who are themselves experts/adept at the role select a suitable sample to get the necessary result – hiring the best candidate for that role.

Use Case #2: New Product Launch

An organization trying to launch a new food product will first survey a few food scientists about it. They’re the subject-matter experts; hence their opinions will shape the final product.

So, this is a case where the company doesn’t know much about a subject but creates a sample of people who do. That’s again a great example of purposive sampling.

Use Case #3: Religious Beliefs

Suppose you’re studying Buddhism as a religion. So you select people from Malaysia, where nearly a fifth of the population practices the religion. The reason is that while China has the highest Buddhist population at 18.2%, it’s too large compared to Malaysia and therefore isn’t easy to sample accurately.

So here, we have an example of critical case purposive sampling, where a country or a particular city is selected for better and more accurate research. Since religion is a sensitive topic, this type of sampling is ideal for a more thorough study.

Use Case #4: Educational Research

Purposive sampling is used extensively for educational research. For example, using a Student Feedback Survey to collect the students’ inputs about the education system, their choice of subject, the content, and literally anything else.

We form purposive samples of the relevant students for this kind of survey. Sometimes, only consistently high-scoring students are included. In other cases, average students are included in the sample, depending on the experiment or research.

How to Do Purposive Sampling?

The following six simple steps you can follow to properly do a purposive sampling.

Step 1 - Define your Objectives

As it is for any process, you have to have a clear idea of what you need to achieve. In other words, define your goal. This will help you identify specific characteristics needed in your sample.

For example, you might need to understand the factors that influence the satisfaction levels of customers.

Step 2 - Identify the Population

Once you have decided on the goal/s, determine the population to draw the sample from. This should be a group that possesses the attributes relevant to your research question.

Step 3 - Choose a Purposive Sampling Method

We have already discussed the different types of purposive sampling you can choose from. go through it and choose the one that best fits your needs.

Step 4 - Select Your Participants

The next step is to choose your participants. They have to meet the necessary attributes to be eligible for selection.

Pro Tip: One of the best way towards this is conducting targeted surveys.

You can tailor your surveys with targeted questions and segment those who fit your needs.

With a proper tool like SurveySparrow by your side, you will be able to create surveys within seconds using AI. Moreover, it offers advanced AI-powered analysis to get proper deeper, granular insights.

Step 5 - Data Collection and Analysis

Here also, one of the best ways to collect feedback is through surveys. Other data collection methods include interviews, focus groups, and so on. Include the questions such that to collect both quantitative and qualitative feedback.

Give more importance to qualitative, since it can provide richer insights.

Step 6 - Understand Your Limitations

The last step is to reflect on the limitations. Acknowledge any biases that may arise due to the nature of purposive sampling. afterward, consider how it may affect the generalizability of your findings. 

When to Use Purposive Sampling

Knowing how to do it is necessary, but understanding when to use them is the key. Ever heard of the phrase, "Right time at the right place"? That's what you have to do.

So, here are the right times you should use purposive sampling.

When You Want Focused Results

Use them when you want to understand specific characteristics within a population.

For example, suppose a study aims to explore the opinions of expert users about a new technology. Then, selecting participants with significant experience in that area is crucial, and for that use this sampling.

When You Have a Small Sample Size

When in case of having small sample size, purposive sampling can help with exploration of particular traits or phenomenon. Researchers can select individuals who are likely to have rich, relevant data for this purpose. Also, it can be helpful with qualitative research.

Related Read: How to calculate sample size?

When You Have a Unique Use Case

When research involves unique cases, other sampling methods like random or cluster sampling might not be enough. However, purposive sampling can be really helpful.

Consider this example - you want to study the effects of rare medical conditions. With purposive sampling, you can select individuals who specifically have that condition. Ergo, better and richer results.

When You Have Exploratory Research

To be exact, you use purposive sampling, where exploratory studies have very little prior knowledge of the topic. How? It allows researchers to gather preliminary insights from participants to guide the research.

When You Have Information-Rich Cases

In the case where you have information-rich purposive sampling, it can provide deep insights related to research questions. This approach helps in maximizing the quality of data collected. 

The Benefits Of Purposive Sampling

Purposive sampling gives us the freedom to decide what data points to include in a sample and do in-depth analysis. But that’s not all. Let’s talk about the less obvious benefits:

• Foremost, purposive sampling is a highly cost-effective sample selection method. Here, the researcher chooses the participants or data points based on their knowledge. So, if the researcher is correct, the sample collection will be accurate.
• Purposive sampling works with many populations. But it works especially well with a smaller total sample. The researcher can analyze all data points for unique attributes, which leads to better data.
• Purposive sampling allows for qualitative response collection. That gets better insights and more precise results in the end.
• There is no randomness in this sampling method. The samples formed are highly suitable for the context of the research, survey, or experiment.
• Targeting niche demographics becomes easy with purposive samples.
• The margin of error here is low, as they’re selected based on the attributes fitting the requirement.
• It’s the best method to find averages in the data, which is of high value in many experiments.
• When conducting human experiments, purposive samples can produce a substantial result in real-time, as these people already have some specific knowledge about the research topic.

Purposive sampling is not the only sampling method; there are four more: random, stratified, systematic, and multistage sampling methods.

So while we’re discussing purposive sampling here, it makes sense to talk briefly about the other four, too. On we go.

Wrapping Up

We’re a 7.9 billion strong community, and we all produce data. There’s an explosion of data everywhere. The area we live in, language, shopping, and eating habits are all data points. We can go on, but you get the point – it’s practically impossible to find relevant information from data unless you sample it correctly.

So coming back to our opening statement, we would say that well-structured data is the new oil! While purposive sampling has many benefits, the data won’t yield the information you need based on subjective assumptions and generalizations.

Looking for subject matter experts for your sample? SurveySparrow Audience offers custom audience panels to suit your requirements perfectly. Get in touch for a quote or contact us for custom requirements.