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.
von
Applying Data Analytics in Marketing
University of Illinois at Urbana-ChampaignÜber diesen Kurs
19.730 kürzliche Aufrufe
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Stufe „Mittel“
A basic familiarity with R is recommended.
Ca. 12 Stunden zum Abschließen
Englisch
Untertitel: Englisch
Kompetenzen, die Sie erwerben
Data AnalysisAnalyticsMarketingMarketing Analytics
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Stufe „Mittel“
A basic familiarity with R is recommended.
Ca. 12 Stunden zum Abschließen
Englisch
Untertitel: Englisch
von
University of Illinois at 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.
Beginnen Sie damit, auf Ihren Master-Abschluss hinzuarbeiten.
Dieses Kurs ist Teil des reinen Onlineabschlusses Master of Science in Accountancy (iMSA) von University of Illinois at Urbana-Champaign.
Wenn Sie in das komplette Programm aufgenommen werden, werden Ihre Kurse auf Ihren Abschluss angerechnet.
Lehrplan - Was Sie in diesem Kurs lernen werden
5 Stunden zum Abschließen
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 Stunden zum Abschließen
14 Videos (Gesamt 76 min), 6 Lektüren, 2 Quiz
3 Stunden zum Abschließen
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 Stunden zum Abschließen
6 Videos (Gesamt 39 min), 2 Lektüren, 2 Quiz
2 Stunden zum Abschließen
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 Stunden zum Abschließen
5 Videos (Gesamt 34 min), 2 Lektüren, 1 Quiz
3 Stunden zum Abschließen
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 Stunden zum Abschließen
7 Videos (Gesamt 56 min), 4 Lektüren, 1 Quiz
Bewertungen
Top-Bewertungen von APPLYING DATA ANALYTICS IN MARKETING
von 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
von MY2. Nov. 2019
it was a perfect course , which gave me the full picture of how to make a marketing testing and evaluation
von S3. Jan. 2021
Very informative. Good beginning to start the journey into analytics for marketers.
von KK25. Aug. 2020
Very informative and nice presentation and interactive sessions.
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