Applying the scientific method to your marketing efforts can help provide data-driven, objective results. When you approach marketing as an experiment, you can make more accurate predictions about what could work, as well as learn why your efforts do work.
For those of us a little more removed from high school science fairs, the steps of the scientific method are as follows: First, ask a question. Then do background research and construct your hypothesis. Test your hypothesis with an experiment, then take the results and analyze them. From your analysis, draw conclusions and determine next steps.
The key to marketing success is to take what you’ve learned from analyzing your metrics and implement them in subsequent campaigns. Of course, the details to performing tests on your marketing are as important as the steps themselves: Your experiment must be controlled, and you should have measurable variables. In the infographic below, we outline how to apply the steps of the scientific method to your marketing campaigns, including a sample experiment that focuses on the call-to-action button on a landing page. Use these tips to improve your marketing efforts and get valuable, data-based answers for how to make your campaigns succeed.
The Scientific Method + Marketing = Data-Driven Results
- When you treat marketing like a science experiment, data reveals the levers you can pull to improve your metrics.
- You can make more accurate predictions about what’s most likely to work.
- With experimentation, you can answer important questions, such as:
- Which customers are best for your business?
- Which customer behaviours indicate buying intent?
- How can we use science to enhance our branding?
A Refresher: How the Scientific Method Works
- Ask a question.
- Do background research.
- Construct a hypothesis.
- Test with an experiment.
- Analyze the results of the experiment.
- If the test yields undesirable results, check your previous steps and try again.
- If the test goes well and gave you solid data, continue to the next step.
- Analyze your data and draw conclusions.
- If your results align with your hypothesis, report them and act accordingly.
- If your results are inconclusive or surprising:
- Report them and act accordingly, and
- This data now becomes background research for new and future tests — ask new questions, perform new tests, and continue analyzing results.
What Marketers Can Learn from Khan Academy’s Instructions for Conducting Experiments
- Each marketing experiment must be controlled.
- “A controlled experiment is a scientific test done under controlled conditions.”
- Just one (or a few) factors are changed at a time.
- All others are kept constant.
- In your controlled experiment, you need two groups:
- The group that receives the treatment in an experiment is called the experimental group.
- The group that does not receive the treatment is called the control group.
- The control group provides a baseline that lets you see if the treatment has an effect.
- The factor that is different between the control and experimental groups is known as the independent variable.
- In contrast, the dependent variable is the response that’s measured to see if the treatment had an effect.
- Sample size refers to the number of individual items tested in an experiment.
- Having more samples and repeating the experiment makes it less likely that you will reach a wrong conclusion because of random variation.
Putting It Together: How to Conduct a Marketing Experiment
- Ask a question: “Where should the call-to-action button be on a landing page to increase my click-through rate?”
- Do background research.
- Where have you put call-to-action buttons on landing pages in the past?
- In this experiment, we’ll say the CTA normally goes under the copy at the bottom of the page.
- How many views did each CTA get?
- How many clicks did each CTA get?
- What percentage of the views turned into clicks?
- Construct a hypothesis: “Putting the CTA immediately below the header on landing pages will increase conversions.”
- Test with an experiment.
- Change just one factor at a time: The location of the CTA.
- All others are kept constant:
- The wording of the CTA
- The design of the CTA
- The design of the landing page
- The experimental group: Landing pages that have the CTA immediately below the header
- The control group: Landing pages that have the CTA in your normal location, under the copy
- The independent variable: The location of the CTA
- The dependent variable: The click-through rate
- Sample size: 3 landing pages
- 2 versions of each, for a total of 6 landing pages
- The 2 versions only have the location of the CTA button different
- This type of test can be performed through marketing automation software as an A/B test.
- Analyze the results of the experiment.
- How many views did each CTA get?
- How many clicks did each CTA get?
- What percentage of the views turned into clicks?
- Analyze your data and draw conclusions.
- If the landing pages with the CTA button at the top had a better click-through rate, you likely need to use that format for all landing pages.
- If your results are inconclusive or surprising:
- Report them.
- Act based on the results: Leave the CTA in its original location or try a new location.
- Ask new questions:
- Should you design your CTA differently?
- What words should you use in your CTA?
How to Make Marketing Experiments Easier
- Be transparent with your data.
- Create public dashboards.
- Monitor stats.
- Share metrics in meetings.
- Save dashboards for future reference.
- Refer back to your data to see how your changes affect it.
- Measure what you can. Evaluate what you measure. And appreciate that you can’t measure the majority of what you do.
- Try to become agile.
- Agile marketing means making incremental experimentation and testing a fundamental part of your process as you run a campaign.
Conclusion:
Using the scientific method in your marketing efforts is easier than ever with marketing automation software. When you understand how to perform these tests effectively, you’ll be data-rich and can improve your campaigns.
