How do you design a marketing experiment with a clear hypothesis and measurable outcomes?

1 Define your goal

The first step in designing a marketing experiment is to define your goal. What are you trying to achieve or improve with your experiment? For example, do you want to increase your website traffic, conversions, retention, or revenue? Your goal should be specific, measurable, achievable, relevant, and time-bound (SMART). Your goal will guide your hypothesis and your outcome metrics.

2 Formulate your hypothesis

The second step in designing a marketing experiment is to formulate your hypothesis. A hypothesis is a statement that expresses your assumption or prediction about how a certain variable or factor will affect your goal. For example, if your goal is to increase conversions, your hypothesis might be: "Adding a testimonial video to the landing page will increase conversions by 10%." Your hypothesis should be based on data, research, or insights from your previous experiments or industry best practices.

3 Choose your method

The third step in designing a marketing experiment is to choose your method. How will you test your hypothesis and measure your outcomes? There are different methods for conducting marketing experiments, such as A/B testing, multivariate testing, or factorial design. Each method has its own advantages and disadvantages, depending on the complexity and scope of your experiment. You should choose the method that best suits your hypothesis, your goal, and your resources.

4 Set up your experiment

The fourth step in designing a marketing experiment is to set up your experiment. This involves creating and implementing the different versions or variations of your marketing element, such as your landing page, email, or ad, that you want to test. You also need to define and segment your target audience, decide how long you will run your experiment, and ensure that you have the tools and systems to track and analyze your results.

5 Analyze your results

The fifth step in designing a marketing experiment is to analyze your results. This involves comparing the performance of your different versions or variations against your outcome metrics, such as conversion rate, click-through rate, or revenue per visitor. You also need to check the statistical significance and validity of your results, and identify any confounding factors or sources of error that might affect your conclusions.

6 Apply your learnings

The sixth and final step in designing a marketing experiment is to apply your learnings. This involves interpreting and communicating your results, and using them to make data-driven decisions and actions. For example, if your experiment shows that adding a testimonial video to your landing page increases conversions by 10%, you might want to implement that change across all your landing pages, or test other types of testimonial videos. You should also document and share your learnings with your team and stakeholders, and use them to inform your future experiments and marketing strategies.

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?