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Quasi-experiments Definition

Studies in which the researcher lacks complete control over the scheduling of treatment or must assign respondents to treatment in a non-random manner.

Quasi-experiments are research designs that examine cause-and-effect relationships but lack random assignment of participants to conditions. In marketing research, they are often used in real-world settings – such as retail environments or digital platforms – where true experimental control isn't feasible.

What are the key aspects of quasi-experiments in marketing research?

• No random assignment to groups.
• Often conducted in naturalistic or field settings.
• Includes comparison groups or time-based measures.
• Seeks to determine causal impact of interventions or campaigns.
• May use methods like pre-post testing or matched groups.

Why are quasi-experiments important in market research?

Quasi-experiments are important because they provide a practical way to evaluate the effectiveness of marketing initiatives in real-world conditions. While they may not offer the rigor of true experiments, they can still yield valuable insights when randomization isn't possible.

Who relies on quasi-experiments in marketing research?

• Marketing and brand managers.
• Retailers and e-commerce teams.
• Advertising and campaign strategists.
• UX researchers.
• Data scientists and analysts conducting field-based studies.

How do market researchers use quasi-experiments?

Market researchers use quasi-experiments to test variables like pricing changes, promotional tactics or new product rollouts across different markets or timeframes. By analyzing outcomes in comparable groups or time periods, they can assess the impact of interventions while accounting for limitations in control or randomization.