Home Pennsylvania Customer Analytics

Customer Analytics

903
0
Online Course Highlights
  • University of Pennsylvania via Coursera
  • Learn for FREE, Up-gradable
  • 12 hours of effort required
  • 191,115 + already enrolled!
  • 4.6 ★★★★★ (9,525 Ratings)
  • Skill Level: Mixed
  • Language: English

Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts, to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions.

In this course, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices including Amazon, Google, and Starbucks to name a few. This course provides an overview of the field of analytics so that you can make informed business decisions. It is an introduction to the theory of customer analytics, and is not intended to prepare learners to perform customer analytics.

Course Learning Outcomes:

  • After completing the course learners will be able to…
  • Describe the major methods of customer data collection used by companies and understand how this data can inform business decisions
  • Describe the main tools used to predict customer behavior and identify the appropriate uses for each tool
  • Communicate key ideas about customer analytics and how the field informs business decisions
  • Communicate the history of customer analytics and latest best practices at top firms

Syllabus

WEEK 1: Introduction to Customer Analytics

  • 4 minutes to complete

What is Customer Analytics? How is this course structured? What will I learn in this course? What will I learn in the Business Analytics Specialization? These short videos will give you an overview of this course and the specialization; the substantive lectures begin in Week 2.

WEEK 2: Descriptive Analytics

  • 3 hours to complete

In this module, you’ll learn what data can and can’t describe about customer behavior as well as the most effective methods for collecting data and deciding what it means. You’ll understand the critical difference between data which describes a causal relationship and data which describes a correlative one as you explore the synergy between data and decisions, including the principles for systematically collecting and interpreting data to make better business decisions. You’ll also learn how data is used to explore a problem or question, and how to use that data to create products, marketing campaigns, and other strategies. By the end of this module, you’ll have a solid understanding of effective data collection and interpretation so that you can use the right data to make the right decision for your company or business.

WEEK 3: Predictive Analytics

  • 4 hours to complete

Once you’ve collected and interpreted data, what do you do with it? In this module, you’ll learn how to take the next step: how to use data about actions in the past to make to make predictions about actions in the future. You’ll examine the main tools used to predict behavior, and learn how to determine which tool is right for which decision purposes. Additionally, you’ll learn the language and the frameworks for making predictions of future behavior. At the end of this module, you’ll be able to determine what kinds of predictions you can make to create future strategies, understand the most powerful techniques for predictive models including regression analysis, and be prepared to take full advantage of analytics to create effective data-driven business decisions.

WEEK 4: Prescriptive Analytics

  • 2 hours to complete

How do you turn data into action? In this module, you’ll learn how prescriptive analytics provide recommendations for actions you can take to achieve your business goals. First, you’ll explore how to ask the right questions, how to define your objectives, and how to optimize for success. You’ll also examine critical examples of prescriptive models, including how quantity is impacted by price, how to maximize revenue, how to maximize profits, and how to best use online advertising. By the end of this module, you’ll be able to define a problem, define a good objective, and explore models for optimization which take competition into account, so that you can write prescriptions for data-driven actions that create success for your company or business.

Take This Online Course


More Related Courses:

Entrepreneurship 2: Launching your Start-Up

      • Wharton School of the University of Pennsylvania via Coursera
      • 8 hours of effort required
      • 39,453+ already enrolled!
      • ★★★★★ (1,649 Reviews)

Improving Communication Skills

      • Wharton School of the University of Pennsylvania via Coursera
      • 10 hours of effort required
      • 68,223+ already enrolled!
      • ★★★★★ (1,291 Reviews)

Your Feedback:

There are no reviews yet. Be the first one to write one.


0
0.0 rating
0 out of 5 stars (based on 0 reviews)
Excellent0%
Very good0%
Average0%
Poor0%
Terrible0%