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Foundations of marketing analytics · LearnSpace
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Foundations of marketing analytics

Курс от ESSEC Business School
Уровень не указан≈ 5.5 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

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. 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.

Навыки, которые вы освоите

Customer AnalysisPredictive ModelingPredictive AnalyticsR ProgrammingStatistical AnalysisCustomer Data ManagementMarketing StrategiesStatistical ModelingMarketing AnalyticsBusiness MarketingCustomer InsightsStatistical ProgrammingAdvanced AnalyticsData-Driven MarketingTarget MarketData-Driven Decision-MakingR (Software)Data Analysis SoftwareBusiness AnalyticsStatistical Methods

Программа курса

5 модулей · 39 учебных материалов

01Module 0 : Introduction to Foundation of Marketing Analytics3 материалов

Welcome to the course

Foundations of Marketing AnalyticsВидеоSetting up the environment and exploring the data (recital)Видео.R files and datasetЧтение
02Module 1 : Statistical segmentation12 материалов

Statistical segmentation: lectures and recitals

Учитесь у экспертов

Arnaud De Bruyn

Professor at ESSEC Business School

Foundations of marketing analytics
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≈ 5.5 ч

5 модулей

Язык: Английский

Субтитры: Арабский, Французский, Бенгальский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Урду, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Дари, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
IntroductionВидео
Acxiom URLЧтение
Hierarchical segmentationВидео
Selecting the "right" number of segmentsВидео
Segmentation variablesВидео
Recency, frequency, and monetary valueВидео
Computing recency, frequency and monetary value with R (Recital 1)Видео
Data transformationВидео
Preparing and transforming your data in R (Recital 2)Видео
Running a hierarchical segmentation in R (Recital 3)Видео

Statistical segmentation: Graded Assessment 1

Instructions before starting the quiz 1ЧтениеQuiz module 1 - 20% of final gradeЗадание
03Module 2 : Managerial segmentation9 материалов

Managerial segmentation: lectures and recitals

Limitations of statistical segmentationВидеоDeveloping a managerial segmentationВидеоCoding a managerial segmentation in R (Recital 1)ВидеоDescribing segmentsВидеоSegmenting a database retrospectively in R (Recital 2)ВидеоSegments and revenue generationВидеоR tutorial (Recital 3)Видео

Managerial segmentation: Graded Assessment 2

Instructions before starting quiz 2ЧтениеQuiz module 2 - 20% of final gradeЗадание
04Module 3 : Targeting and scoring models6 материалов

Targeting and scoring models: lectures and recitals

Can Target predict a customer is pregnant?ВидеоWhat you need to develop a scoring modelВидеоCalibration data and statistical modelВидеоBuilding a predictive model in R (Recital)Видео

Targeting and scoring models: Graded Assessment 3

Instructions before starting quiz 3ЧтениеQuiz module 3 - 20% of final gradeЗадание
05Module 4 : Customer lifetime value9 материалов

Customer lifetime value: lectures and recitals

What is customer lifetime value and why it mattersВидеоTransition probabilities and transition matrixВидеоHow to compute a transition matrix in R (Recital 1)ВидеоUsing the transition matrix to estimate how customers will evolveВидеоUsing the transition matrix to make predictions in R (Recital 2)ВидеоAssigning and discounting revenueВидеоComputing customer lifetime value in R (Recital 3)Видео

Customer lifetime value: Graded Assessment 4

Instructions before starting the quiz 4ЧтениеQuiz module 4Задание