Principles of Marketing: Marketing Research - Sampling Techniques, Probability vs. Nonprobability

Sampling Techniques (Probability vs Non-Probability)

What It Is

Sampling techniques are methods used to select a subset of a larger population to represent the whole group. This is crucial in marketing research to make informed decisions about product development, pricing, and advertising. For instance, Coca-Cola uses sampling techniques to test new flavors and packaging designs before launching them globally.

Key Concepts & Frameworks

• Probability Sampling: A method where every member of the population has an equal chance of being selected. Example: Randomly selecting 100 customers from a database of 10,000 to participate in a survey.
• Non-Probability Sampling: A method where not every member of the population has an equal chance of being selected. Example: Selecting customers who have purchased a product online in the past month to participate in a focus group.
• Stratified Sampling: A method where the population is divided into subgroups (strata) and a random sample is taken from each subgroup. Example: Dividing a city into different neighborhoods and selecting a random sample of customers from each neighborhood to participate in a survey.
• Cluster Sampling: A method where the population is divided into clusters and a random sample of clusters is selected. Example: Selecting a random sample of 10 stores from a list of 100 stores to participate in a survey.
• Systematic Sampling: A method where every nth member of the population is selected. Example: Selecting every 5th customer from a database of 10,000 to participate in a survey.
• Convenience Sampling: A method where the sample is selected based on ease of access. Example: Selecting customers who are already in a store to participate in a survey.
• Snowball Sampling: A method where existing participants recruit new participants. Example: Asking existing customers to refer their friends to participate in a survey.

How to Apply It

• To segment a market, start with geographic, then add psychographic like lifestyle.
• To select a sample for a survey, use a combination of probability and non-probability sampling methods.
• To ensure a representative sample, use stratified sampling and cluster sampling methods.

Common Mistakes

• Mistake: Assuming that a non-probability sample is representative of the population.
• Correction: Non-probability samples are not representative of the population and should be used with caution.
• Mistake: Not considering the bias in a sample selection method.
• Correction: Always consider the bias in a sample selection method and take steps to minimize it.
• Mistake: Using a convenience sample as a representative sample.
• Correction: Convenience samples are not representative of the population and should not be used as a substitute for a probability sample.

Exam / Interview Tips

• Be able to explain the difference between probability and non-probability sampling methods.
• Be able to identify the bias in a sample selection method.
• Be able to describe the steps involved in stratified sampling and cluster sampling methods.

Quick Practice

Scenario: A market researcher wants to select a sample of customers to participate in a survey. The researcher has a list of 10,000 customers and wants to select a random sample of 100 customers.

Question: What sampling method should the researcher use?

Answer: Probability Sampling. Explanation: Probability sampling ensures that every member of the population has an equal chance of being selected.

Scenario: A marketing manager wants to select a sample of customers to participate in a focus group. The manager has a list of customers who have purchased a product online in the past month.

Question: What sampling method should the manager use?

Answer: Non-Probability Sampling. Explanation: Non-probability sampling is used when not every member of the population has an equal chance of being selected.

Scenario: A researcher wants to select a sample of stores to participate in a survey. The researcher has a list of 100 stores and wants to select a random sample of 10 stores.

Question: What sampling method should the researcher use?

Answer: Cluster Sampling. Explanation: Cluster sampling is used when the population is divided into clusters and a random sample of clusters is selected.

Last-Minute Cram Sheet

• Probability Sampling: A method where every member of the population has an equal chance of being selected.
• Non-Probability Sampling: A method where not every member of the population has an equal chance of being selected.
• Stratified Sampling: A method where the population is divided into subgroups (strata) and a random sample is taken from each subgroup.
• Cluster Sampling: A method where the population is divided into clusters and a random sample of clusters is selected.
• Systematic Sampling: A method where every nth member of the population is selected.
• Convenience Sampling: A method where the sample is selected based on ease of access.
• Snowball Sampling: A method where existing participants recruit new participants.
• Bias: A systematic error in a sample selection method.
• Representative Sample: A sample that accurately reflects the characteristics of the population.
• Sampling Frame: The list of individuals or units from which the sample is selected.
• Sampling Error: The difference between the sample estimate and the true population parameter.
• 'Marketing Myopia' = focusing on the product instead of the customer need.