What are the best practices for conducting a consumer behavior experiment?

1 Define your research question

Before you start planning your experiment, you need to have a clear and specific research question that guides your hypothesis, variables, and outcomes. Your research question should be relevant to your business goals, aligned with your existing data and insights, and focused on one aspect of consumer behavior that you want to understand or influence. For example, you might want to test how different prices affect the purchase intention of your target segment.

4 Measure your variables and outcomes

In an experiment, variables are the factors that you manipulate or observe, and outcomes are the results that you measure and analyze. It's important to define your variables and outcomes clearly and select appropriate methods and tools for collecting and recording data. Variables can include independent variables, which are the factors you change in your experiment that you expect to affect the outcomes; dependent variables, which are the factors you measure or observe in your experiment that you expect to be affected by the independent variables; control variables, which are the factors you keep constant or balance in your experiment; and extraneous variables, which are the factors that cannot be controlled or measured in your experiment. For example, independent variables could include changing the price, color, or name of a product, while dependent variables could be measuring customer sales, satisfaction, or loyalty. Control variables could include time, location, or mood of participants, while extraneous variables could be external events, noise, or errors that affect your data.

5 Test your experiment and analyze your data

Before launching your experiment, it is important to test it for any potential issues or errors that could compromise data quality or validity. Pilot testing can help you run a small-scale version of your experiment with a few participants and check for any technical, logistical, or ethical problems. Pre-testing involves measuring dependent variables before applying independent variables, and establishing a baseline for comparison. Post-testing requires measuring dependent variables after applying independent variables, and comparing results with the pre-test or control group. After collecting data, appropriate statistical methods and software should be used to analyze it. Descriptive analysis involves summarizing and presenting data using tables, charts, graphs, or measures of central tendency and variability. Inferential analysis tests hypotheses and draws conclusions about data using tests of significance, confidence intervals, or effect sizes. Exploratory analysis explores and discovers patterns, trends, or insights from data using visualization, clustering, or dimensionality reduction.

6 Report your findings and recommendations

The final step of your experiment is to report your findings and recommendations to your stakeholders, clients, or audience. You need to communicate these results clearly, concisely, and convincingly, using visual aids, narratives, and stories. Additionally, you should acknowledge the limitations, assumptions, and implications of your experiment while suggesting areas for further research or action. Your findings and recommendations can be reported using various formats such as reports, presentations, or dashboards. Reports are formal documents providing a comprehensive account of your experiment with background, objectives, methods, results, discussion and conclusion. Presentations are informal sessions highlighting the key findings, insights and recommendations. Dashboards are interactive tools displaying the data in a visual and accessible way for users to explore.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?