This article describes the most common non-probability sampling methods used for the primary market research purposes.
Sampling exists and is necessary because surveying the entire population (all the potential customers of a particular market) is neither practical nor possible due to lack of resources. Besides, this would be too expensive and extremely time-consuming.
What should the sample look like?
Businesses select a sample for a particular market – a small group of people that is truly representative of the whole population. The population is all the potential customers of a product, or the overall target market.
A sample size of approximately 1,000 respondents is sufficient as it will very likely produce fairly accurate results.
When designing a sample, the business organization needs to consider the sample frame, a list of all people in the target population from which the sample is drawn, and the sample size, the number of people to include in the research.
Sampling results must be statistically accurate as determined by the confidence level of the results of .95 (95%) or higher.
The two broad categories of sampling include:
1. PROBABILITY SAMPLING METHODS:
a. Simple random sampling
b. Systematic sampling
c. Quota sampling
d. Stratified sampling
e. Cluster sampling
f. Multistage sampling
2. NON-PROBABILITY SAMPLING METHODS:
a. Convenience sampling
b. Snowballing sampling
c. Judgmental sampling
When choosing between different sampling methods, market research specialists need to determine who and what needs to be asked in the research. Then, when a chosen sampling method allows to generate statistically valid representative responses to the research question in a cost-effective way, this confirms that the choice was right.
2. NON-PROBABILITY SAMPLING METHODS
The probability of each respondent being selected into the sample cannot be calculated. Sample results will not allow for making judgment about the total population as must be analyzed by market researchers very cautiously.
All of the following non-probability samples are likely to lead to less accurate results – which are less representative of the whole population – than probability sampling techniques.
The most common non-probability sampling methods include the following three methods.
a. Convenience sampling
Convenience sampling selects for the sample members of the population based on relative easiness of accessing them. Simply, all those people that happen to come your way will be included in the sample. Or, anyone who is easy for the market researcher to reach in one place at the certain time when the research is being conducted.
How to conduct convenience sampling?
Convenience sampling mainly relies on ease of reach sampling friends and family members, fellow employees, shoppers in just one particular location, passers-by on the busy street and so on. Volunteers are also often used in a research study because of their availability. Researchers will be observing employees sitting in the same office, surveying all university students in the same lecture hall, interviewing customers in the coffee shop or restaurant, etc.
When to use convenience sampling?
The convenience sampling is particularly useful when short-time and low cost of research are important factors to the business. In urgent situations where samples are expensive and time-consuming to make such as medical emergencies or during natural disasters, convenience sampling may contain useful information which would be irresponsible to ignore. Additionally, when a business organization wants to quickly determine whether more detailed market research is necessary, it should use convenience sampling.
Advantages of convenience sampling
Convenience sampling ensures the availability and quickness of data collection when time and money are the issues.
Disadvantages of convenience sampling
Convenience sampling inadvertently excludes a large proportion of the population causing the research findings to be highly unrepresentative of the population. For instance, customers will spend different amount of time on average on entertainment during weekdays and weekends. Sampling people during those times will produce two different samples with completely different respondent profiles; hence the research would be producing totally different results.
b. Snowballing sampling
Snowballing sampling is a ‘word of mouth’ type approach to generating a sample. It chooses one highly knowledgeable respondent at the beginning. This person is then asked by the interviewer to recommend other people specializing in the researched subject to be included next in the sample.
How to conduct snowballing sampling?
Samples are developed from contacts of existing customers growing like a snowball. The first respondent refers an acquaintance, a friend, family member or colleague who then refers another friend. And, so the process continues to increase the sample size. Here are a few steps how to carry out snowballing sampling in practice:
- Start the process within one individual.
- Use the network of this person to enlarge the sample.
- Expect the ‘snowball effect’.
TIP: In order to avoid heavy bias, only use snowballing sampling when other sampling methods are not available.
When to use snowballing sampling?
Snowballing sampling is commonly used in situations when the research subject requires advanced expert knowledge. It is often used by businesses in the healthcare and pharmaceutical industries; wealth management and personal finance planning; car, medical and life insurance, for science and engineering projects, etc. Firms can gain easy access to a large number of people for market research purposes from an individual’s colleagues, acquaintances or even competitors. Snowballing sampling can also be used by businesses when it is difficult to get hold of appropriate respondents because the population is not clear or hidden.
Advantages of snowballing sampling
Snowballing sampling is a cheap and quick method of obtaining sample details as getting hold of relevant contact for enlarging a sample is fairly easy. In general, people tend to be very helpful when asked politely or when the purpose of reaching out the following respondents is clearly explained to them.
Disadvantages of snowballing sampling
Snowballing sampling is biased, hence cannot be representative as it is a heavily respondent-driven sampling method. Findings from the sample will never be unbiased because each respondent’s recommendation for the following person to be included in the research sample will not be objective as both will have similar lifestyles, values or opinions. In addition, snowballing sampling is usually restricted to highly-specialized one-off products such as medications, airplanes, buildings and other civil engineering projects, scientific research, etc.
c. Judgmental sampling
Judgmental sampling, also called authoritative sampling, selects the sample members solely based on the researcher’s intentions who has deep knowledge and understanding both about the research subject as well as who would be the most appropriate for the study.
How to conduct judgmental sampling?
In judgmental sampling, researchers are carefully picking and choosing each individual to be a part of the sample while ensuring that there are no errors. It is a critical intellectual challenge for the researcher to undertake. That is why the researcher is instrumental in creating a sample to maximize chances that results obtained will be highly accurate with a minimum bias involved.
When to use judgmental sampling?
Situation 1: Restricted number of people. Judgmental sampling is the most effective where only limited number of people own qualities that a researcher expects from the population. This includes highly intellectual individuals such as university professions or rare scientists who cannot be chosen by using any other sampling technique.
ADVICE: Judgmental sampling could be possibly replaced with convenience sampling. However, it is more probable to gather 100% feedback about the topic from known and trusted respondents rather than unknown random individuals who just happen to show up where the research takes place.
Situation 2: Limited time. Judgmental sampling is also used where there is time-constraint for sample creation and other sampling methods would consume more time. Researchers may be required to product a final report quickly. Therefore, those researchers who thoroughly understand the research topic are be able to quickly decide who should form the sample and easily filter out those participants who are not eligible to be a part of the research sample.
Situation 3: Sensitive topics. Certain topics such as religious beliefs, military conflicts, ethical differences or human value systems are highly sensitive among different cultures around the world. These topics ought to be studied by experienced researchers with expert knowledge. Hence, if samples of those who also have appropriate knowledge are created and research is properly conducted with those samples, final results will be highly accurate.
Advantages of judgmental sampling
Judgmental sampling is convenient as it consumes minimum time for preparation and execution. Researchers rely on their own expertise without any other barriers involved. Because there are no criteria involved for choosing the sample (except the researchers’ own judgments), it allows them to directly approach the target audience of their choice. Additionally, by communicating directly with the target market, researchers can obtain instant results through a quick survey or phone interview. The members of the sample all possess appropriate knowledge and understanding of the research subject.
Disadvantages of judgmental sampling
The two main weaknesses of judgmental sampling lie with the authority and in the sampling process leading to potential issues with reliability and bias. The first problem is with the researcher. Because each sample in judgmental sampling is based on the decisions of the researcher, it is extremely prone to human error. Experimenter bias happens when the people performing the research end up influencing the data and results of a study – the validity of a study. While it is difficult to evaluate the reliability of the expert who may lack proficiency in conducting an effective sampling process, every researcher has to be confident in own research skills and understanding of the research subject.
RECOMMENDATION: The best way to avoid sampling errors related to the expert is to choose the best and the most authoritative person in the field of research.
The second problem is with the sampling process itself as the sample is not representative of the whole population. And, the members of the population did not have an equal chance of being selected. This may result in the misrepresentation of the entire population, or superficial generalizations of the results of the study.
In conclusion, sample is a small group of people chosen either in the probability way or non-probability way aiming to represent the entire population – the target market. Researching everyone in the total population would be too costly and time-consuming. Hence, market researchers will be testing on a sample to understand how the population will react to a product being marketed.
Each non-probability sampling method has its advantages and disadvantages, and each one will be suitable for a different business situation. The choice of the best sampling method will mainly depend on the purpose of the market research, the population and financial resources of the business organization.
While disadvantages of sampling include issues with data reliability and bias, it can save time as fewer resources are required and aid marketing decision-making. Cost-effectiveness is always important in all market research decisions.
