Firms spend millions on branding for one reason: It allows them to charge more for their products and services. In this module, we'll explore this valuable, if intangible, asset. We'll discuss how to build and define a brand architecture and how to measure the impact of marketing efforts on brand value over time. By the end of this module, you'll be able to measure and track brand value. So let's get started!

How valuable are your customers? That's a tough question that we'll show you how to answer in this module where we'll explore Customer Lifetime Value, or the future net value of a customer relationship. This forward-looking measure of the customer relationship helps you connect marketing strategies to future financial consequences and invest marketing dollars in the right place to maximize return over a customer's lifetime. By the end of this module, you will know how to measure customer lifetime value and evaluate strategic marketing alternatives based on whether they improve customer retention and lifetime value.

Ever wonder how much you have to cut prices to drive the most sales? Or which advertisement copy is more effective in customer conversion? Do an experiment! Experiments allow you to understand the effectiveness of different marketing strategies and forecast expected ROI. This week, we'll explore how to design basic experiments so that you can assess your marketing efforts and invest your marketing dollars most effectively. We'll help you avoid a gap between your test results and field implementation, and explore how web experiments can be implemented cheaply and quickly. By the end of this module, you'll be able to design and conduct effective experiments that test your marketing campaigns--and then use the results to make future marketing decisions.

Ever wonder how variables influence consumer behavior in the real world--like how weather and a price promotion affect ice cream consumption? In this module, we will take a look at regression and how it's used to understand that relationship. We will discuss how to set up regressions and interpret outputs, explore confounding effects and biases, and distinguish between economic and statistical significance. We'll finish the week with a series of interviews with real marketing professionals who share their experiences and knowledge about how they use analytics on the job.