Об этом курсе
4.5
Оценки: 424
Рецензии: 120
Специализация
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100% онлайн

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Часов на завершение

Прибл. 8 часа на выполнение

Предполагаемая нагрузка: 7 hours/week...
Доступные языки

Английский

Субтитры: Английский...

Приобретаемые навыки

Market SegmentationCustomer Lifetime ValueMarketing AnalyticsMarketing Performance Measurement And Management
Специализация
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100% онлайн

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Гибкие сроки

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Назначьте сроки сдачи в соответствии со своим графиком.
Часов на завершение

Прибл. 8 часа на выполнение

Предполагаемая нагрузка: 7 hours/week...
Доступные языки

Английский

Субтитры: Английский...

Программа курса: что вы изучите

Неделя
1
Часов на завершение
26 минуты на завершение

Module 0 : Introduction to Foundation of Marketing Analytics

In this short module, we will introduce the field of marketing analytics, and layout the structure of this course. We will also take that opportunity to explore a retailing data set that we’ll be using throughout this course. We will setup the environment, load the data in R (we’ll be using the RStudio environment), and explore it using simple SQL statements. ...
Reading
2 видео (всего 16 мин.), 1 материал для самостоятельного изучения
Video2 видео
Setting up the environment and exploring the data (recital)12мин
Reading1 материал для самостоятельного изучения
.R files and dataset10мин
Неделя
2
Часов на завершение
1 ч. на завершение

Module 1 : Statistical segmentation

In this module, you will learn the inner workings of statistical segmentation, how to compute statistical indicators about customers such as recency or frequency, and how to identify homogeneous groups of customers within a database. We will alternate lectures and R tutorials, making sure that, by the end of this module, you will be able to apply every concept we will cover. ...
Reading
9 видео (всего 42 мин.), 2 материалов для самостоятельного изучения, 1 тест
Video9 видео
Hierarchical segmentation4мин
Selecting the "right" number of segments2мин
Segmentation variables1мин
Recency, frequency, and monetary value1мин
Computing recency, frequency and monetary value with R (Recital 1)8мин
Data transformation3мин
Preparing and transforming your data in R (Recital 2)3мин
Running a hierarchical segmentation in R (Recital 3)10мин
Reading2 материала для самостоятельного изучения
Acxiom URL10мин
Instructions before starting the quiz 110мин
Quiz1 практическое упражнение
Quiz module 1 - 20% of final grade10мин
Неделя
3
Часов на завершение
1 ч. на завершение

Module 2 : Managerial segmentation

Statistical segmentation is an invaluable tool, especially to explore, summarize, or make a snapshot of an existing database of customers. But what most academics will fail to tell you is that this kind of segmentation is not the method of choice for many companies, and for good reasons. In this module, you will learn to perform managerial segmentations, which are not built upon statistical techniques, but are an essential addition to your toolbox of marketing analyst. You will also learn how to segment a database now, but also at any point in time in the past, and why it is useful to managers to do so. ...
Reading
7 видео (всего 47 мин.), 1 материал для самостоятельного изучения, 1 тест
Video7 видео
Developing a managerial segmentation3мин
Coding a managerial segmentation in R (Recital 1)17мин
Describing segments2мин
Segmenting a database retrospectively in R (Recital 2)6мин
Segments and revenue generation2мин
R tutorial (Recital 3)12мин
Reading1 материал для самостоятельного изучения
Instructions before starting quiz 210мин
Quiz1 практическое упражнение
Quiz module 2 - 20% of final grade10мин
Неделя
4
Часов на завершение
1 ч. на завершение

Module 3 : Targeting and scoring models

How can Target predict which of its customers are pregnant? How can a bank predict the likelihood you will default on their loan, or crash your car within the next five years, and price accordingly? And if your firm only has the budget to reach a few customers during a marketing campaign, who should it target to maximize profit? The answer to all these questions is… by building a scoring model, and targeting your customers accordingly. In this module, you will learn how to build a customer score, which in marketing usually combines two predictions in one : what is the likelihood that a customer will buy something, and if he does, how much will he buy for? ...
Reading
4 видео (всего 29 мин.), 1 материал для самостоятельного изучения, 1 тест
Video4 видео
What you need to develop a scoring model2мин
Calibration data and statistical model5мин
Building a predictive model in R (Recital)18мин
Reading1 материал для самостоятельного изучения
Instructions before starting quiz 310мин
Quiz1 практическое упражнение
Quiz module 3 - 20% of final grade10мин
4.5
Формирование карьерного пути

17%

начал новую карьеру, пройдя эти курсы
Карьерные преимущества

83%

получил значимые преимущества в карьере благодаря этому курсу
Продвижение по карьерной лестнице

25%

стал больше зарабатывать или получил повышение

Лучшие рецензии

автор: TBDec 2nd 2017

Lectures were insightful and very applicable. Learning was reinforced with well documented R scripts. After this course I feel capable of applying these concepts to my own company.

автор: MKFeb 8th 2016

I was expecting a lot from this course. from basic to advanced fundamentals. this course should be floated as full specialization rather than as a part of other specialization.

Преподаватель

Avatar

Arnaud De Bruyn

Professor at ESSEC Business School
Marketing department

О ESSEC Business School

For over a century, ESSEC has been developing a state-of-the-art educational program that gives the individual pride of place in its learning model, promoting the values of freedom, openness, innovation and responsibility. Preparing future managers to reconcile personal interests with collective responsibility, giving consideration to the common good in their decision-making, and weighing economic challenges against the social costs are some of the objectives ESSEC has set for itself. Its ultimate goal? To create a global world that has meaning for us all. ...

О специализации ''Strategic Business Analytics'

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....
Strategic Business Analytics

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