The abundance of data available to marketing professionals has pushed the definition of what it means to have a successful marketing strategy. Success can now be measured by the degree to which customers are not only brought into the funnel, but also engaged and retained without active intervention. In other words, your marketing strategy can now be adjusted so that your product sells itself. This course focuses on how to automate the design and processes of your marketing machine so it can pull customers organically. You will start by identifying which products can and would benefit from a growth marketing strategy, then learn how you can calibrate product, price, promotion, and place to create a self-sustaining chain reaction that enables your product to sell itself. You will then explore the three stages of AI — supervised learning, unsupervised learning, and reinforcement learning — and how you can leverage them in your growth marketing strategy. Ultimately, you will walk away with a clear view of what successful growth marketing implementation can look like in your own organization.
KEY COURSE TAKEAWAYS
Determine what products within your organization might benefit the most from growth marketing and set a growth marketing goal
Examine the 4Ps of marketing — product, price, place, and promotion — and determine where and how they can be enhanced by growth marketing
Examine the three stages of AI and how they could be applied to growth marketing
Identify what successful growth marketing implementation would look like in your organization, how it might best be measured, and how to mitigate potential obstacles
Assistant Professor of Marketing, Johnson Graduate School of Management, Cornell University
Professor Clarence Lee is an assistant professor at the Johnson Graduate School of Management, where he is a Breazzano Family Sesquicentennial Fellow. Professor Lee’s research examines the drivers behind consumer adoption, usage, and purchase dynamics of digital goods, where he models consumer behavior using Bayesian statistics, structural econometrics, and machine learning techniques. Digital products and platforms, such as the ones produced by many Silicon Valley and NYC tech start-ups, are increasingly present in almost all consumer interactions. In such settings, understanding consumer choice and the dynamics of engagement and usage become critically important in order to acquire, serve, and retain consumers. He currently teaches Digital Marketing and Data Analytics & Modeling at both the Ithaca and Cornell Tech campuses.
Professor Lee received his doctorate from Harvard Business School and holds undergraduate and graduate degrees in electrical engineering and computer science from MIT. Prior to pursuing graduate studies, he has conducted nanotechnology research at IBM and space system design at MIT Lincoln Laboratory.