Want to keep learning?

This content is taken from the Darden School of Business, University of Virginia's online course, Marketing Analytics. Join the course to learn more.

Skip to 0 minutes and 1 second Hope you had a lot of fun learning about marketing experiments. I find this to be a very interesting topic and hope you did, too. And I’m sure this is something you will use a lot in your marketing analytics experience. Now, experiments are important because they assess cause and effect. They tell you whether marketing levels like advertising cause effects in sales. And when you do experiments, you need to pay attention to the design of the experiment. And even if you have a good designed experiment, you need to understand the gap between the test results and the field implementation. Like we saw Betty Spaghetty example, and also understand the difference between test and the campaign context.

Skip to 0 minutes and 46 seconds A lot can change, and this is where web experiments are getting very popular because they are cheap and fast. And the cost of experiments are now variable rather than fixed. Like we saw with the example of the Nanoblocks on the Amazon gold box. Now because of all of this, experiments provide forecasts of expected return on investments. And this is really important for marketers because it can help them determine the campaign budgets that are the best to maximize sales. Now that we’re done, I hope you should now be able to distinguish between correlation and causation. Design affective experiments to test marketing hypothesis. And also conduct basic experiments to assess the effectiveness of some of your marketing efforts.

Takeaways: Marketing Experiments

Reinforce your understanding of this week’s content with a summary of key takeaways about marketing experiments. Ask any questions in the comments and share your insights with your fellow learners.

Share this video:

This video is from the free online course:

Marketing Analytics

Darden School of Business, University of Virginia