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Customer Analytics

Eric Bradlow, Peter Fader, Raghu Iyengar, and Ron Berman

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.

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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

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What's inside

Syllabus

Introduction to Customer Analytics
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.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Taught by 4 top-tier Wharton professors, this course offers insights from experienced educators
Offers a comprehensive overview of customer analytics across descriptive, predictive, and prescriptive methods
Delves into real-world applications of customer analytics, providing industry context through examples from Amazon, Google, and Starbucks
Suitable for individuals seeking an introduction to customer analytics concepts and their practical implications
Focuses primarily on theoretical foundations and does not provide hands-on training in performing customer analytics

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Create your own learning path. Save this course to your list so you can find it easily later.
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Reviews summary

Overview of customer analytics concepts

According to learners, this course provides a strong theoretical foundation and an excellent overview of customer analytics. Many found the content, delivered by highly knowledgeable Wharton professors, to be clear and engaging, particularly the case studies applying concepts to real-world businesses. However, students repeatedly note that the course is strictly theoretical and does not teach practical skills like coding or using specific software. Those expecting to learn *how* to *do* analytics may be disappointed. It's best suited for those who need to understand analytics concepts for business decision-making or communication with analysts, not for becoming an analyst.
Ideal for understanding analytics for business use.
"This course is perfect for managers or decision-makers who need to understand what analytics can do and how to work with data scientists."
"If your job involves interpreting analytical reports or talking to analysts, this course will give you the language and context you need."
"Great for getting a business perspective on customer data and its potential."
"Highly recommend for anyone in a business role interacting with data or analytics teams."
Real-world examples enhance understanding.
"The application and case study module was the most helpful part, showing how companies like Amazon actually use these concepts."
"The real-world examples grounded the theory and made it much easier to grasp the practical implications, even without doing the analytics myself."
"Appreciated the case studies; they made the abstract concepts concrete."
"Seeing how top firms apply these analytics was very valuable."
Provides a solid understanding of key areas.
"This course is a fantastic overview of descriptive, predictive, and prescriptive analytics from a business perspective. It's great for managers."
"I now have a much better understanding of the different types of customer analytics and how they are used in companies."
"Provides a solid introduction to the frameworks and concepts. Good starting point if you're new to the topic."
"It covered all the main areas it promised in the syllabus and gave a good high-level view."
Professors are knowledgeable and engaging.
"The professors are incredibly knowledgeable and explain complex topics in a clear, understandable way. Their expertise shines through."
"Loved learning from the Wharton faculty. They bring a lot of real-world insight to the lectures."
"The instructors are top-notch. They are engaging and make the theoretical material interesting."
"The lectures are well-delivered by experts in the field."
Lacks skills needed to become an analyst.
"Do not take this course if you want to learn how to become a data analyst or customer analyst. You will not gain those skills here."
"I was hoping to learn how to use specific tools, but this course didn't cover any practical software or coding."
"If you want hands-on practice or technical skills, look elsewhere. This is purely conceptual."
"This won't teach you how to build models or run regressions."
Course provides concepts, not hands-on skills.
"This course is a strictly theoretical overview of customer analytics. It does not delve into the actual work of performing customer analytics, such as how to code and use statistical software."
"The course description and syllabus explicitly state that it provides an overview and is not intended to prepare learners to perform customer analytics. They mean it. You will not learn how to DO customer analytics."
"I wish there were more practical examples or demos instead of just concepts. It's hard to see how I'd apply this knowledge without hands-on practice."
"Expect to learn the 'what' and 'why' of customer analytics, but not the 'how'."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Customer Analytics with these activities:
Join a study group or online discussion forum
Engage with fellow learners to discuss course concepts, share insights, and support each other's understanding of customer analytics.
Show steps
  • Join an existing study group or online discussion forum dedicated to customer analytics or data science.
  • Participate in discussions, ask questions, and contribute your own insights to the group.
  • Collaborate on projects or assignments with group members to enhance your understanding and foster teamwork skills.
Review Data Collection Methods
Review the different methods of data collection in order to understand the basics of how businesses collect customer data.
Browse courses on Data Collection
Show steps
  • List the different methods of data collection.
  • Describe the advantages and disadvantages of each method.
  • Identify the most appropriate method for a given business objective.
Form a study group with other students in the course
Studying with other students can help you learn the material more effectively and improve your understanding of the concepts.
Show steps
  • Find a few other students in the course who are interested in forming a study group
  • Choose a time and place to meet regularly
  • Review the course material together
  • Work on practice problems together
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Review probability and statistics
Review the foundations of probability and statistics to enhance your understanding of customer analytics.
Browse courses on Probability
Show steps
  • Review notes from previous courses or textbooks on probability and statistics, focusing on concepts such as probability distributions, hypothesis testing, and regression analysis.
  • Practice solving exercises and problems to reinforce your understanding of probability and statistical principles.
Attend a regression analysis workshop
Regression analysis is a fundamental tool in predictive analytics. Attending a workshop will help you refresh your skills and gain a deeper understanding of the concepts.
Browse courses on Regression Analysis
Show steps
  • Find a regression analysis workshop in your area or online
  • Register for the workshop and attend all sessions
  • Participate in the hands-on exercises and ask questions
Attend a customer analytics conference
Customer analytics conferences are great opportunities to learn from experts in the field and network with other professionals.
Browse courses on Customer Analytics
Show steps
  • Find a customer analytics conference in your area or online
  • Register for the conference and attend all sessions
  • Network with other attendees and speakers
Practice Using Predictive Analytics Tools
Engage in hands-on practice to understand how to use predictive analytics tools to analyze customer behavior and make predictions.
Browse courses on Predictive Analytics
Show steps
  • Choose a predictive analytics tool.
  • Import customer data into the tool.
  • Build a predictive model using the data.
  • Test the model on a holdout dataset.
  • Deploy the model to make predictions on new data.
Create a visual representation of customer data
Develop your ability to interpret and present customer data through visual means, enhancing your understanding of customer behavior.
Browse courses on Data Visualization
Show steps
  • Use data visualization tools, such as Tableau or Power BI, to create charts, graphs, or dashboards that represent customer data.
  • Consider different types of visualizations, such as histograms, scatterplots, or heatmaps, to effectively convey various aspects of the data.
  • Communicate the insights gained from the visualizations to stakeholders, explaining the patterns and trends observed in customer behavior.
Practice building predictive models
Predictive models are a key component of customer analytics. Practicing building predictive models will help you develop the skills necessary to create accurate and effective models.
Browse courses on Predictive Analytics
Show steps
  • Find a dataset that you're interested in
  • Choose a predictive modeling technique
  • Build a predictive model using the technique you chose
  • Evaluate the performance of your model
Develop a customer analytics project
Apply your knowledge of customer analytics to a real-world problem, enhancing your ability to solve business challenges using data-driven insights.
Browse courses on Data-Driven Decision-Making
Show steps
  • Identify a specific business problem or opportunity that can be addressed using customer analytics.
  • Collect and analyze relevant customer data to understand their behavior and preferences.
  • Develop and implement a customer analytics model to predict future behavior or provide recommendations.
  • Communicate your findings and recommendations to stakeholders, including the potential impact and implications for business decisions.
Write a blog post about a customer analytics case study
Writing a blog post about a customer analytics case study will help you apply your knowledge of customer analytics to a real-world problem.
Browse courses on Customer Analytics
Show steps
  • Choose a customer analytics case study
  • Analyze the case study and identify the key insights
  • Write a blog post about the case study, highlighting the key insights

Career center

Learners who complete Customer Analytics will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts play an increasingly vital role in organizations, using their skills and expertise to analyze large amounts of data to uncover patterns and trends. With a course in Customer Analytics, you'll learn the latest techniques and methodologies for collecting, analyzing, and interpreting customer data to improve business outcomes. You will be better prepared to provide valuable insights to help your organization improve its customer service, marketing campaigns, and product development efforts, making you a valuable asset to any organization.
See salaries and explore the career path for Data Analyst
Market Research Analyst
Market Research Analysts play a critical role in helping organizations understand their customers and make informed decisions about their products and services. By taking a course in Customer Analytics, you'll gain a deep understanding of customer behavior and learn how to use data to conduct market research and identify trends. This will give you the skills you need to make informed recommendations to your organization on how to improve its products, services, and marketing strategies.
See salaries and explore the career path for Market Research Analyst
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns that attract and engage customers. By taking a course in Customer Analytics, you'll gain a deep understanding of customer behavior and learn how to use data to drive your marketing efforts. This will give you the skills you need to create more effective campaigns that will help your organization achieve its marketing goals.
See salaries and explore the career path for Marketing Manager
Product Manager
Product Managers are responsible for the development and launch of new products and services. By taking a course in Customer Analytics, you'll gain a deep understanding of customer needs and learn how to use data to inform product development. This will give you the skills you need to create products and services that meet the needs of your customers and achieve commercial success.
See salaries and explore the career path for Product Manager
Consultant
Consultants help organizations solve problems and improve their performance. By taking a course in Customer Analytics, you'll gain a deep understanding of customer behavior and learn how to use data to identify opportunities for improvement. This will give you the skills you need to help your clients achieve their business goals.
See salaries and explore the career path for Consultant
Data Scientist
Data Scientists use their skills in statistics, programming, and machine learning to extract insights from data. By taking a course in Customer Analytics, you'll gain a foundation in the principles of data science and learn how to apply them to customer-related data. This will give you the skills you need to build models that can predict customer behavior and help your organization make better decisions.
See salaries and explore the career path for Data Scientist
Business Analyst
Business Analysts help organizations improve their business processes and operations. By taking a course in Customer Analytics, you'll gain a deep understanding of customer behavior and learn how to use data to identify opportunities for improvement. This will give you the skills you need to help your organization make better decisions and achieve its business goals.
See salaries and explore the career path for Business Analyst
Customer Success Manager
Customer Success Managers are responsible for helping customers achieve success with a company's products and services. By taking a course in Customer Analytics, you'll gain a deep understanding of customer behavior and learn how to use data to identify opportunities to improve customer satisfaction. This will give you the skills you need to help your customers succeed and achieve their business goals.
See salaries and explore the career path for Customer Success Manager
Sales Manager
Sales Managers are responsible for leading and motivating sales teams to achieve their sales goals. By taking a course in Customer Analytics, you'll gain a deep understanding of customer behavior and learn how to use data to identify opportunities to improve sales performance. This will give you the skills you need to help your team achieve its sales goals and improve customer satisfaction.
See salaries and explore the career path for Sales Manager
Marketing Analyst
Marketing Analysts use their skills in data analysis and interpretation to help organizations understand their customers and develop effective marketing campaigns. By taking a course in Customer Analytics, you'll gain a deep understanding of customer behavior and learn how to use data to drive your marketing efforts. This will give you the skills you need to create more effective marketing campaigns that will help your organization achieve its marketing goals.
See salaries and explore the career path for Marketing Analyst
Operations Research Analyst
Operations Research Analysts use their skills in mathematics and modeling to help organizations improve their operations and decision-making processes. By taking a course in Customer Analytics, you'll gain a foundation in the principles of operations research and learn how to apply them to customer-related problems. This will give you the skills you need to help your organization make better decisions and achieve its business goals.
See salaries and explore the career path for Operations Research Analyst
Statistician
Statisticians use their skills in data analysis and interpretation to help organizations understand their customers and make informed decisions. By taking a course in Customer Analytics, you'll gain a deep understanding of statistical principles and learn how to apply them to customer-related data. This will give you the skills you need to help your organization make better decisions and achieve its business goals.
See salaries and explore the career path for Statistician
Software Engineer
Software Engineers design, develop, and maintain software applications. By taking a course in Customer Analytics, you'll gain a deeper understanding of the principles of software engineering and learn how to apply them to customer-related problems. This will give you the skills you need to help your organization develop software applications that meet the needs of your customers and achieve its business goals.
See salaries and explore the career path for Software Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines and databases. By taking a course in Customer Analytics, you'll gain a deeper understanding of the principles of data engineering and learn how to apply them to customer-related problems. This will give you the skills you need to help your organization build a data infrastructure that supports its customer analytics initiatives.
See salaries and explore the career path for Data Engineer
Database Administrator
Database Administrators design, build, and maintain databases. By taking a course in Customer Analytics, you'll gain a deeper understanding of the principles of database administration and learn how to apply them to customer-related problems. This will give you the skills you need to help your organization build and maintain a database that supports its customer analytics initiatives.
See salaries and explore the career path for Database Administrator

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Customer Analytics.
Cover image
Competing on Analytics: Updated, with a New...
Save
Provides a comprehensive overview of customer analytics in the digital age. It good resource for students who want to learn how to use data to improve customer experience.
Competing on Analytics: Updated, with a New...
Paperback
Check
Competing on Analytics: Updated, with a New...
Kindle Edition
Check
Cover image
Customer Behaviour in eCommerce
Save
Provides a practical guide to using customer analytics to improve e-commerce marketing efforts, with a focus on customer analytics.
Customer Behaviour in eCommerce: Case Studies from...
Kindle Edition
$$
Cover image
Data Analysis for Managers with Microsoft Excel
Save
Provides a comprehensive overview of business analytics. It good resource for students who want to learn how to use data to improve business performance.
Data Analysis for Managers with Microsoft Excel
Paperback
Check
Data Analysis for Managers with Microsoft Excel
Kindle Edition
Check
Cover image
Marketing Analytics
Save
Provides a practical guide to using predictive analytics to improve marketing efforts, with a focus on customer analytics.
Marketing Analytics: Based on First Principles
Paperback
$$
Marketing Analytics: Based on First Principles
Kindle Edition
$$
Cover image
Data Science for Business
Save
Provides a comprehensive overview of data science techniques. It good resource for students who want to learn how to use data to solve business problems.
Data Science for Business: What You Need to Know...
Paperback
$$
Data Science for Business: What You Need to Know...
Kindle Edition
$$
Cover image
Data Driven Business Transformation
Save
Provides a comprehensive overview of machine learning techniques. It good resource for students who want to learn how to use data to automate business processes.
Data Driven Business Transformation: How to Disrupt...
Hardcover
$$
Data Driven Business Transformation: How to Disrupt...
Kindle Edition
$$
Cover image
Machine Learning for Business Analytics
Save
Provides a comprehensive overview of data mining techniques. It good resource for students who want to learn how to use data to make better business decisions.
Machine Learning for Business Analytics: Concepts,...
Hardcover
$$$$
Machine Learning for Business Analytics: Concepts,...
Kindle Edition
$$$$
Cover image
Predictive Analytics For Dummies
Save
Provides a comprehensive overview of predictive analytics techniques. It good resource for students who want to learn more about how to use data to predict future behavior.
Predictive Analytics For Dummies
Paperback
$$
Predictive Analytics For Dummies (For Dummies...
Paperback
$$
Predictive Analytics For Dummies
Kindle Edition
$$
Cover image
Big Data
Save
Provides a comprehensive overview of big data technologies and their applications in business.
Big Data: A Revolution That Will Transform How We...
Kindle Edition
$$
Learning With Big Data (Kindle Single): The Future...
Kindle Edition
$
(Italiano) Big data. Una rivoluzione che trasformerà il nostro...
Hardcover
$$
(Español) Big data: La revolución de los datos masivos...
Kindle Edition
$$
(Deutsch) Lernen mit Big Data: Die Zukunft der Bildung
Paperback
$$
(Deutsch) Big Data: Die Revolution, die unser Leben verändern...
Hardcover
$$
(Español) Aprender con big data
Paperback
$$
Learning with Big Data: The Future of...
Hardcover
$$

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Course image
Effort
4 weeks of study, 5-6 hours/week
Via
Coursera
Institution
University of Pennsylvania
Instructors
Eric Bradlow
Peter Fader
Raghu Iyengar
Ron Berman
Language
English
Transcripts
Español Français Português Deutsch Italiano 中文 العربية 한국어 日本語 हिंदी Nederlands Svenska Pусский Türkçe Polski Ελληνικά українська мова magyar nyelv Bahasa Indonesia ไทย қазақша اُردُو, فارسی বাংলা tiếng Việt پښتو آذربایجان دیلی
This course belongs to a collection called Business Analytics. It's comprised of six courses:
  1. Accounting Analytics
  2. Operations Analytics
  3. People Analytics
  4. Business Analytics Capstone
  5. Customer Analytics (viewing)
  6. Analytics in Python
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Taught by 4 top-tier Wharton professors, this course offers insights from experienced educators
Offers a comprehensive overview of customer analytics across descriptive, predictive, and prescriptive methods
Delves into real-world applications of customer analytics, providing industry context through examples from Amazon, Google, and Starbucks
Suitable for individuals seeking an introduction to customer analytics concepts and their practical implications
Focuses primarily on theoretical foundations and does not provide hands-on training in performing customer analytics
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