You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering. However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data and explore new features and statistical functions in R.
Business Analytics, Big Data and Data Science are very hot topics today, and for good reasons. Companies are sitting on a treasure trove of data, but usually lack the skills and people to analyze and exploit that data efficiently. Those companies who develop the skills and hire the right people to analyze and exploit that data will have a clear competitive advantage.
It’s especially true in one domain: marketing. About 90% of the data collected by companies today are related to customer actions and marketing activities.The domain of Marketing Analytics is absolutely huge, and may cover fancy topics such as text mining, social network analysis, sentiment analysis, real-time bidding, online campaign optimization, and so on.
But at the heart of marketing lie a few basic questions that often remain unanswered: (1) who are my customers, (2) which customers should I target and spend most of my marketing budget on, and (3) what’s the future value of my customers so I can concentrate on those who will be worth the most to the company in the future.
That’s exactly what this course will cover: segmentation is all about understanding your customers, scorings models are about targeting the right ones, and customer lifetime value is about anticipating their future value. These are the foundations of Marketing Analytics. And that’s what you’ll learn to do in this course.
Who is this course for?
This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role, in particular in marketing.
This specialization is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. We recommend that you have some background in statistics, R or another programming language, and familiarity with databases and data analysis techniques such as regression, classification, and clustering.We’ll cover a wide variety of analytics approaches in different industry domains. You’ll engage in hands-on case studies in real business contexts: examples include predicting and forecasting events, statistical customer segmentation, and calculating customer scores and lifetime value. We’ll also teach you how to take these analyses and effectively present them to stakeholders so your business can take action. The third course and the Capstone Project are designed in partnership with Accenture, one of the world’s best-known consulting, technology services, and outsourcing companies. You’ll learn about applications in a wide variety of sectors, including media, communications, public service,etc. By the end of this specialization, you’ll be able to use statistical techniques in R to develop business intelligence insights, and present them in a compelling way to enable smart and sustainable business decisions. You’ll earn a Specialization Certificate from one of the world’s leading business schools and learn from two of Europe’s leading professors in business analytics and marketing.
Week 1: Module 0 : Introduction to Foundation of Marketing Analytics
Week 2: Module 1 : Statistical segmentation
Week 3: Module 2 : Managerial segmentation
Week 4: Module 3 : Targeting and scoring models
Week 5: Module 4 : Customer lifetime value
ENROLL IN COURSE