Businesses today have access to an increasingly large amount of detailed customer data, and this influx of “big data” is only going to continue. Combined with a detailed history of marketing actions, there is a newfound potential for deriving actionable insights, but you need the tools to do so. Using real-world applications from various industries, this course will help you understand the tools and strategies used to make data-driven decisions that you can put to use in your own company or business.
This valuable data may include in-store and online customer transactions, customer surveys, web analytics, as well as prices and advertising. You’ll also learn how to assess critical managerial problems, develop relevant hypotheses, analyze data and, most importantly, draw inferences to create convincing narratives which yield actionable results. Artificial intelligence and machine learning will be explored as tools to deepen analytical skills and acumen and hone decision making.
This comprehensive exploration into digital marketing analytics tools and techniques is critical knowledge for any marketing influencers, digital marketing analysts and product and brand decision makers within small and medium businesses as well as larger organizations with international reach.
Overview
Syllabus
- Introduction to Digital Marketing Analytics
- In the first module, we will introduce you to the course and the objectives. You'll have the opportunity to meet your instructor, connect with your peers, and get familiar with the Coursera platform and support resources. We'll also explore the strategies for optimizing search engine visibility, analyzing the performance of paid search campaigns, and leveraging web analytics to track and improve digital marketing effectiveness.
- Online Testing and Recommendation Systems
- In this module, we will start with an exploration into Online Testing. Many managerial decisions are made based on professional knowledge and intuition, but often this knowledge is not sufficient enough to make the optimal decision. That's where testing comes in. Next, we will talk about Recommendation Systems. You may not realize it, but your internet experience is defined by recommendation systems. From music, games, videos, films, and what to buy, recommendation systems predict your preferences to suggest products or services that are likely to be of interest to you.
- End-of-Course Evaluation
- Congratulations! You've made it to the end of the course. As a final assessment, it's time to apply your learning.
Taught by
Michael Trusov
