课程大纲
COURSE SYLLABUS
1.
课程代码/名称
Course Code/Title
数据驱动的营销科技（Data-driven Marketing Analytics)
2.
课程性质
Compulsory/Elective
专业选修课 Major Elective Courses
3.
课程学分/学时
Course Credit/Hours
3
4.
授课语言
Teaching Language
英文 English
5.
授课教师
Instructor(s)
郭悦 （信管系 guoy@sustech.edu.cn）
6.
是否面向本科生开放
Open to undergraduates or not
否
7.
先修要求
Pre-requisites
无
8.
教学目标
Course Objectives
In this digital age, there is an unprecedented volume, velocity, and variety of marketing data available to
firms. User characteristics and behaviors are tracked in detail for websites, social media pages, and ad
campaigns, and information-rich user-generated content is contributed at breakneck speed throughout the web.
The marketing world is a-buzz with excitement about using this “big data” to increase profits – yet, many
marketers find real, measurable value-gain to be elusive. It is all too easy to suffer “analysis paralysis” in the
face of a sea of metrics; to make misinformed recommendations based on flawed data or analytics; or in invest
in an analytics tool that makes strong promises but doesn’t deliver actionable insights. At present, Internet
marketing is in the ascendant, and many enterprises are accelerating into this emerging field. For network
marketing, which indicators should we focus on? To what extent has it increased the marketing effect of the
company? Through this lesson, students can clearly understand this knowledge.
9.
教学方法
Teaching Methods
Students will learn to evaluate different analytics approaches and will gain hands-on practice gathering and
analyzing large digital data sets containing both structured and unstructured data.
Students will gain experience addressing questions such as: “What is the ROI of my social media initiative?”,
“How should I target my paid ads?”, “What are users saying about my brand?”, and “Should I invest in this
new analytics tool?” In the online marketing budget, nearly 50% is invested in search engine marketing.
How much user attention did these marketing investments bring? To what extent has it increased the
marketing effect of the company?
10.
教学内容
Course Contents
（如面向本科生开放，请注明区分内容。 If the course is open to undergraduates, please indicate the
difference.）
Week 1
Introduction to the Digital Marketing Landscape
Week 2
What is Artificial Intelligence?
Search Engine Optimization (SEO)
Week 3
Paid Advertising
Week 4
Ad Effectiveness Testing
Website Analytics
Week 5
Social Media Marketing and Data Collection
Week 6
Mining User-Generated Text 1
Mining User-Generated Text 2
Week 7
Data Cleaning
Week 8
Exploring Data; Frequencies; Descriptive Statistics
Crosstabulations; Independent Samples t-Test; One-Way ANOVA
Week 9
Scatterplots & Correlation Analysis
Week 10
Linear Regression
Causal Analysis
Week 11
User behavior and characteristics analysis
Week 12
Loyalty marketing
The power of the brand
Week 13
Precision marketing information push support
Week 14
Competitor monitoring and brand communication
Market forecast and decision analysis support
Week 15
Brand crisis monitoring and management support
Week 16
Course wrap-up and review
Group Presentation
11.
课程考核
Course Assessment
考核形式 Form of examination
分数构成 Grading policy
出勤 Attendance
20%
课堂表现 Class Performance
20%
期末报告 Final Presentation
60%
12.
教材及其它参考资料
Textbook and Supplementary Readings
