Explore more resources
Industry-defining terminology from the authoritative consumer research platform.
Experimentation
Definition: What is Experimentation?
Experimentation is a research method in which one or more variables are manipulated to determine their effect on a dependent variable. This approach allows researchers to establish cause-and-effect relationships and measure the impact of specific changes.
Why is Experimentation Important?
Experimentation is widely used in marketing, product development, and consumer research to test the effectiveness of various strategies. It allows businesses to make data-driven decisions, optimize campaigns, and improve user experiences.
How Does Experimentation Work?
- Define the Hypothesis: Identify the relationship between variables.
- Select Test and Control Groups: One group experiences the change, while the other does not.
- Manipulate the Independent Variable: Introduce the change (e.g., new pricing, ad design, website layout).
- Measure the Dependent Variable: Analyze the results to determine if the change had an impact.
Types of Experimentation
| A/B Testing | Comparing two versions of an element to see which performs better. |
| Field Experiments | Conducted in a real-world setting to observe actual consumer behavior. |
| Laboratory Experiments | Conducted in a controlled environment to minimize external factors. |
| Quasi-Experiments | Similar to controlled experiments but without full randomization. |
What are Experimentation Best Practices?
- Ensure Statistical Significance: Use a large enough sample size for reliable results.
- Control External Factors: Minimizing external influences helps isolate the impact of the independent variable.
- Test Iteratively: Running multiple experiments refines insights and enhances accuracy.
- Clearly Define Success Metrics: Establishing clear goals ensures meaningful results.
Common Mistakes to Avoid with Experimentation
- Confusing Correlation with Causation: Just because two variables are related doesn’t mean one causes the other.
- Ignoring Control Groups: Without a control, it’s impossible to determine true impact.
- Drawing Conclusions Too Early: Statistical validation should confirm any observed trends.
Final Takeaway
Experimentation is one of the most effective methods for understanding causality and optimizing business strategies, but it requires careful planning, execution, and analysis.