How to use snowball sampling for research

Blocksurvey blog author
Written by Wilson Bright
Jul 7, 2023 2 mins read

Snowball sampling is a methodology you can use to allow people you already know to spread the word for you about your research topic. Instead of a top-down approach where you鈥檇 begin with random strangers and ask them to spread wide and far about your research, snowball sampling allows the people who are actually interested in a topic to spread word about it. Read more to know about what is Snowball sampling, its advantages, disadvantages, and how to implement one for your research.

What is snowball sampling?

Snowball sampling is a recruitment method in which research participants are often required to assist researchers in recognizing and distinguishing other possible subjects. Here's a fun fact about snowball sampling is its term "snowball sampling" mirrors a parallel resemblance to a snowball increasing in size as it keeps on rolling downhill. Want to read more about it in detail, check here 馃憠snowball sampling.

How many types of snowball sampling are there?

There are three types of snowball sampling methods.

  1. Exponential non-discriminative snowball sampling: In exponential non-discriminative snowball sampling, the first subject generally get recruited, and once they're recruited, they provide multiple referrals. Every new referral then provides more knowledge and data for referrals, so on and so forth, until there are enough subjects for the required samples.
  2. Linear Snowball sampling: Moving on, in the case of linear snowball sampling, the formation of a sample group generally starts with each subject providing information about the other subject, and it carries on with one referral to another subject. This pattern gets continued till enough subjects are there for the sample.
  3. Exponential discriminative snowball sampling: The last one, exponential discriminative snowball sampling, is where every subject gives several referrals, whereas only one subject gets recruited from each referral.

Advantages of snowball sampling

There are various advantages when one starts using the snowball sampling techniques, to mention a few.

  1. An easier and quicker way of finding samples: Referrals make it simple and fast to discover subjects really dependable sources. An extra task is put aside for a researcher, this time can be utilized in directing the investigation.
  2. Cost savings: This strategy is practical as the references are gotten from an essential information source. It's is advantageous and not so costly when contrasted with different techniques.
  3. Sampling hesitant or not reachable subjects: Some individuals would prefer not to approach and take part in research examines, in light of the fact that they don't need their character to be uncovered. Snowball examining helps for the present circumstance as they request a reference from individuals known to one another. There are a few areas of the objective populace which are difficult to contact.

Disadvantages of the snowball sampling

Even though snowball sampling is truly amazing though there are a few drawbacks to it and it is only fair we talk about it! Here are the three most common disadvantages or drawbacks one might face while using the snowball sampling method.

  1. The researcher has little command over the sampling method technique. The subjects that the researchers can acquire depend for the most part on the past subjects that were noticed.
  2. Representativeness of the sample isn't ensured and guaranteed. The analyst has no clue about the genuine appropriation of the populace and of the given sample.
  3. Sampling bias happens to be an additional dread for the researchers when utilizing this inspecting method. Initial subjects will nominate or choose the general names of individuals that they know well. Along these lines, it is profoundly conceivable that the subjects share similar attributes and qualities, in this manner, it is conceivable that the example that the researcher might or will acquire is just a little subgroup of the whole populace.
Also Read: A/B Testing Calculator for Statistical Significance.

Examples of snowball sampling

For some populations, snowball sampling is the only way out for collecting pieces of information and data. Given below are the instances where snowball sampling can be used:

  • No authority/official names are provided: This sampling technique can be utilized for a populace where there is no effectively accessible information like their segment data. For instance, destitute or rundown of individuals from a world-class club, whose individual subtleties can't be gotten without any problem.
  • Individuals who are not willing to be recognized: If a researcher鈥檚 doing an examination that includes gathering data/information from sex laborers or survivors of rape or people who would prefer not to uncover their sexual directions, these people will fall under this class.
  • The identity is kept a secret: Individuals who have a place with a clique or are strict radicals or programmers typically fall under this class. A researcher should utilize snowball sampling to recognize these people and concentrate data from them.

How to implement Snowball Sampling in a survey?

The first step in snowball sampling is to identify people who can refer you to other people. You can start with your personal network or your professional network. Identify people who know you, know your work, and are willing to refer you to their peers. Then, reach out to them and ask if they have time to chat. Ask them about their work, talk about the industry you are interested in, and if they know anyone in the field. If they do, ask them to refer you.

If you are using professional networks, you can use LinkedIn as a platform to find people who can refer you to others. You can also pay for LinkedIn鈥檚 premium services like InMail or Sales Navigator. Depending on your budget, you can use one of these tools to reach out to people who have more authority than you do. If you are using personal networks, you can use Facebook or Instagram to find people who can refer you to others. You can also reach out to your friends via email or phone. After you have identified people who can refer you to others, you can craft a message to ask for a referral.

Using BlockSurvey, you can implement a 'Thank you' screen with a message asking for referrals. Sample below. You can request the subjects to share using the social icons as well to share in their network.

Blocksurvey is a significant improvement over traditional snowball survey tools. With its easy to use interface, it dramatically reduces the time and effort required in data collection, yet still allows users to generate valuable insights about their user base. Give BlockSurvey a try to create your first snowball sampling survey.

How to use snowball sampling for research FAQ

When is snowball sampling used?

Snowball sampling is used when the population being studied is hard to reach or is not well-defined. It is often used in social science research and in studies of hidden or marginalized populations.

What are some advantages of snowball sampling?

Advantages of snowball sampling include the ability to reach hard-to-reach populations, the ability to recruit participants quickly, and the potential for the recruitment of participants with similar characteristics or experiences. Snowball sampling can also be cost-effective and can help establish trust between the researcher and the participants.

How is snowball sampling different from other sampling techniques?

Snowball sampling is different from other sampling techniques in that it does not require a sampling frame or a random selection of participants. Instead, it relies on the participants to identify other individuals who meet the criteria for participation in the study.

How do I ensure the validity of my results using snowball sampling?

To ensure the validity of your results using snowball sampling, it is important to clearly define the inclusion and exclusion criteria for participation in the study, to establish trust with the participants, and to use a variety of methods to verify the information provided by the participants.

Like what you see? Share with a friend.

blog author description

Wilson Bright

Wilson Bright is the co-founder of BlockSurvey. He is an avid crypto enthusiast, and his vision is to make BlockSurvey a go-to infrastructure for data collection with a focus on privacy and security.