Industry Insights

Snowball Sampling: How to Do It and Pros & Cons


Snowball sampling is a non-probability sampling method that is commonly used in social science research to identify and recruit hard-to-reach populations. This method is particularly useful when studying populations that are difficult to access. In this blog post, we will discuss how to do the snowball sampling method, and its pros and cons. 

Snowball Sampling

How to Do Snowball Sampling 

Snowball sampling is a type of chain-referral sampling, which means that participants are recruited through a chain of referrals from other research participants. 

Here are the basic steps for conducting the snowball sampling method: 

  1. Identify the population of interest: The first step is to identify the population of interest that you want to study. This could be a specific group of people who share a common characteristic or experience, such as victims of domestic violence or people with a particular medical condition. 
  2. Identify initial participants: The next step is to identify a few initial participants who fit the criteria for the population of interest. These participants are often referred to as “seeds.” Seeds can be recruited through various methods, such as through community organizations, social media, or personal networks. 
  3. Ask initial participants for referrals: Once you have identified your initial participants, ask them to refer other people they know who may fit the criteria for the population of interest. You should provide the participants with a set of criteria to help them identify potential referrals. 
  4. Repeat the process: As you recruit more participants through referrals, ask them to also refer others they know who fit the criteria for the population of interest. Repeat this process until you reach a sample size that satisfies your research needs. 

Pros and Cons of Snowball Sampling 

Like any research method, snowball sampling has its advantages and disadvantages. While it can reach difficult target audiences through referrals and is a cost-effective way to recruit, it could lead to sample bias and become representative of smaller networks rather than the larger population. Here are some of the pros and cons of the snowball sampling method: 


  • Access hard-to-reach populations: Snowball sampling is particularly useful when studying populations that are difficult to access. Because participants are recruited through referrals, it can be easier to establish trust and rapport with these populations for more accurate and honest data. 
  • Cost-effective: The snowball sampling method can be a cost-effective way to recruit participants, as it relies on referrals rather than expensive recruitment methods such as advertisements or mailings. 
  • Good for exploratory research: Snowball sampling can be a good method for exploratory research, as it allows researchers to study populations that have not been extensively studied before. 


  • Sample bias: Because participants are recruited through referrals, the snowball sampling method can lead to sample bias. Participants may be more likely to refer people who share their characteristics or experiences, which can skew the sample. 
  • Difficult to estimate sampling error: Because snowball sampling is a non-probability sampling method, it can be difficult to estimate sampling error or calculate statistical significance. 
  • Limited generalizability: Because snowball sampling often relies on referrals from participants’ personal networks, the sample may not be representative of the larger population. As a result, findings may not be generalizable to other populations. 

The snowball sampling method is incredibly useful for studying hard-to-reach populations, but it has its limitations. Researchers should carefully consider the steps to execute snowball sampling as well, as the pros and cons of snowball sampling before choosing to use this method. When using snowball sampling, researchers should also take steps to minimize sample bias and ensure that findings are accurately reported and interpreted.

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