This course introduces students to customer satisfaction measurement through a wide range of analytical approaches. We will discuss the components of customer satisfaction, major issues in measuring customer satisfaction, statistical methods in analyzing customer satisfaction influence, sentiment analysis with social media data, influence analysis with social media data, and text summarization with social media data. This course aims to provide the foundation required to make better marketing decisions by analyzing multiple types of data related to customer satisfaction.
Offert par
Spécialisation Business AnalyticsUniversité de l'Illinois à Urbana-ChampaignÀ propos de ce cours
28 249 consultations récentes
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 5 sur 6 dans le
Niveau intermédiaire
A basic familiarity with R is recommended.
Approx. 12 heures pour terminer
Anglais
Sous-titres : Anglais
Compétences que vous acquerrez
- Data Analysis
- Analytics
- Marketing
- Marketing Analytics
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 5 sur 6 dans le
Niveau intermédiaire
A basic familiarity with R is recommended.
Approx. 12 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Université de l'Illinois à Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
Commencez à travailler pour obtenir votre master
Ce cours est lié au diplôme Master of Business Administration (iMBA) intégralement en ligne de Université de l'Illinois à Urbana-Champaign. Il vous donnera un aperçu des sujets, des contenus et des enseignants afin que vous puissiez décider si le programme intégralement en ligne vous convient.
Programme de cours : ce que vous apprendrez dans ce cours
5 heures pour terminer
Course Introduction and Module 1: Customer Satisfaction
With the first module, we begin by looking at some definitions of customer satisfaction. Then, we explore some major issues we have to consider. These issues include the psychological constructs of customer satisfaction, proper measurement of those constructs, varying targets of satisfaction, differences in the impact of individuals' expressions, and changing satisfaction over time. We will then introduce you to a new tool that you can use to conduct various data science methods on social media data. We conclude the module with a short primer on R and RStudio.
5 heures pour terminer
14 vidéos (Total 76 min), 6 lectures, 2 quiz
3 heures pour terminer
Module 2: Customer Satisfaction Analysis
We will begin our second module with a discussion on different types of data for customer satisfaction analysis. We first focus on survey data and look at different ways to analyze them. Next, we will provide a simple primer on linear and logistic regression. We will wrap up this module with a guided demo of utilizing sentiment analysis on tweets using the Social Media Macroscope.
3 heures pour terminer
6 vidéos (Total 45 min), 2 lectures, 2 quiz
2 heures pour terminer
Module 3: Customer Satisfaction Influence Analysis
We will introduce a method to analyze customer satisfaction influence using social media data. Social networks are the perfect dataset to utilize network analysis to understand how people are interacting with other people and forming networks. Identifying a pattern in social media relationships can be useful when making marketing decisions. We will also review influencer brand personality analysis that can be used as a method for brands to find influencers similar in personality to themselves.
2 heures pour terminer
5 vidéos (Total 34 min), 2 lectures, 1 quiz
3 heures pour terminer
Module 4: Text Summarization
We will learn about the various methods of text summarization. We begin by discussing the pre-processing steps required to bring the text to an analyzable form. Next, we look at how the frequency counts of multi-word phrases of pre-processed text can reveal the common terms being discussed. Building on top of the n-grams, we move onto a more intelligent method to automatically detect quality phrases. We will also discuss the LDA Topic Modeling - a very popular way to detect topics in a body of texts. We will wrap up this module with a highlight on supervised machine learning and an example of its application.
3 heures pour terminer
7 vidéos (Total 56 min), 4 lectures, 1 quiz
Avis
Meilleurs avis pour APPLYING DATA ANALYTICS IN MARKETING
par YH26 nov. 2020
This course is really insightful. Explanation done very well, quizzes is related and challenging. Although I suggest you have a statistical background before taking this course
par MY2 nov. 2019
it was a perfect course , which gave me the full picture of how to make a marketing testing and evaluation
par S3 janv. 2021
Very informative. Good beginning to start the journey into analytics for marketers.
par KK25 août 2020
Very informative and nice presentation and interactive sessions.
À propos du Spécialisation Business Analytics
Our world has become increasingly digital, and business leaders need to make sense of the enormous amount of available data today. In order to make key strategic business decisions and leverage data as a competitive advantage, it is critical to understand how to draw key insights from this data. The Business Analytics specialization is targeted towards aspiring managers, senior managers, and business executives who wish to have a well-rounded knowledge of business analytics that integrates the areas of data science, analytics and business decision making.
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