A sample is a section of the population for a particular market

The term “population” refers to all members of a particular group. In Business Management, the term specifically refers to the total group of all potential customers in a particular market. However, it is often unrealistic for market researchers to conduct research on an entire population; it would be too time consuming and expensive to do so.

Instead, a subgroup is used. A sample refers to the proportion or subgroup of the population selected for market research purposes.

There are three sampling methods featured in the IB Business Management syllabus that can be used for market research purposes:

1. Quota

2. Random, and

3. Convenience

An issue with any sampling method is that the sample size, and hence the results, may not be representative of the entire population. Ideally, the sample chosen is representative of the overall target market (population). If a statistically valid sample size is chosen, it is not necessary to include the entire population for research purposes.

If the sample size is too small, the results are unlikely to be statistically valid (representative of the population). However, very large sample sizes increase the costs and complexities of market research.

1.  Quota sampling

Quota sampling refers to the sampling technique where researchers select a number of candidates from different market segments and then group them together according to various characteristics. Unlike random sampling, quota sampling requires the selection of representative people chosen from a specific sub-group. Examples of such sub-groups could include: age, gender, ethnicity, educational attainment level, income levels or religion. For example, a researcher might choose to use a sample consisting of 100 females and 50 males, or choose to interview people between the ages of 30 and 50.

 Advantages of quota sampling

• Unlike random sampling, quota sampling enables researchers to gather representative data from sub-groups.
• It is suitable when researchers want to detect possible relationships between sub-groups.
• It enables researchers to investigate particular traits (characteristics) of a certain sub-group in order to improve its marketing strategies.
• The researcher has control of who is included in the sample.
• The findings are usually more reliable than those collected from random sampling, especially where the proportions of the different sub-groups of the population are known in advance.

 Disadvantages of quota sampling

• Researchers need time to determine the characteristics on which they will base the quota sample in order to generate representative results.
• Selection is not random, so can be subject to researcher bias and sampling errors. This means that results might not be statistically representative.

2.  Random sampling

As the name suggests, researchers using random sampling select anyone in the population for market research. It is based on an arbitrary method, allowing all respondents the same equal chance of being selected. For example, if a sample of 20 employees are needed to gather some feedback, then a list of all workers could be entered into a random name generator, with the first 20 names listed being selected for interviews to determine their opinions on work-related matters.

To avoid or minimise potential, a variation is to use a systematic method, sampling every nth person from a list. This can improve the randomising in order to get a good mix of participants, and therefore more representative views.

 Advantages of random sampling

• Results are, in theory, random as everyone in the population has an equal chance of being selected for research.
• Results are therefore (in theory) free from researcher bias and sampling errors, so are more likely to be accurate and representative.
• It is a quick and simple method of sampling, particularly if research participants are freely available.

 Disadvantages of random sampling

• Random sampling only tends to work well if members of a population are likely to have similar views or characteristics.
• The sample, being just random, could be very skewed, so is not necessarily representative of the population.
• The sample needs to be large enough to generate results consistent with the opinions and views of the target population, but this can be time consuming and costly to implement.

3.  Convenience sampling

Convenience sampling refers to the practice of using people that are within easy reach, in an unplanned way, to conduct market research. The sample is simply made up of whoever is willing to participate in the research. Therefore, it is the least representative method of sampling. Unless very large sample sizes are used, convenience sampling is of limited use. However, as the name suggests, convenience sampling makes it simple for market researchers to carry out the study.

 Advantages of convenience sampling

• Samples are created by using research subjects who are easily and readily accessible.
• It is the quickest, easiest, and cheapest method of sampling.

 Disadvantages of convenience sampling

• As the least representative method of sampling, the results may be biased and atypical. Hence, the research findings may be of limited use.
• Therefore, it is unlikely the convenience sample will accurately represent the views of the wider target population.

Sampling errors

When a researcher inappropriately designs market research, this is referred to as a sampling error. Such errors are caused by poor sample design or methodology. For example, a group of students doing research for a school project may find convenience sampling easier than stratified sampling. Sampling errors can also be caused by the sample size being too small or having bias built into the research.

When an inappropriate sampling methodology is used, this causes a non-sampling error. These mistakes are not attributed to human errors. For example, untruthful answers by respondents distort the results and findings.