Xi Li

Xi Li

Professor of Marketing, Innovation and Information Management

Welcome to the Digital Marketing class! This is the semi-official website for the course.

  • Instructor: Xi Li
  • Class 1A: Monday 9:30–12:20 (KKLG106)
  • Class 1B: Friday 9:30–12:20 (KKLG106)
  • Sept 12 class (1A) will be cancelled (Public Holiday)
  • To make the teaching schedule consistent, Sept 9 class for Class 1B will be not be delivered in the classroom. Students can use the time to form their groups and discuss their research projects, and the instructor will stay in the office (KKL 836) to answer questions from students.
  • You can download the software for the course here: R, R Studio and Tableau Public
  • Note: When installing R/Rstudio, make sure your path does not contain any non-english characters. (安裝路徑必須為純英文，否則運行可能出錯)
  • No textbooks for the course. You may find this free ebook helpful.

Grading

  • 10%: In class participation: Based on your in class participation (e.g., answering questions in class)
  • 15%: Group Data Project (start in class; no presentation).
    For details, see Lecture 7. Deadline: Nov 4 (Class B) or Nov 7 (Class A)
  • 25%: Group Project (in class presentation + report) Details
    You need to present your projects by Nov 25 (Class B) or Nov 28 (Class A), and the order of presentation will be determined by a lucky draw.
    Duration of in-class presentation: 18 min + 2 min Q&A
    Deadline for reports: Nov 27 (Class B) or Nov 30 (Class A). The maximum length of your report is 12 pages (double space)
  • 50%: Final Example (Open-notes; Multiple Choice Questions Only)

Lecture 1: Introduction to Digital Marketing

Slides (With Answer Keys)
Submit your group information (your group name, your own name, and your student numbers) to Yana (yanalo@hku.hk).
Deadline: Sep 17 (Class 1B) and Sep 20 (Class 1A).
Install R and RStudio and bring your laptop with you for the next class.

Lecture 2: Data Analysis with R

This class introduces some basic R operations. The lecture is designed for students with zero background in computer programming/R. We will explore how to use R to conduct simple data analysis.
Note: Please get R installed on your laptop and bring it with you.
Slides (With Answer Keys)
Teaching materials: A beginner’s guide to R
Troubleshooting for package installation: Here

Lecture 3: Introduction to Data Scraping

Note: Please get R and Chrome browser installed on your laptop and bring it with you.
Slides (With Answer Keys)
Teaching materials: Scraper (HKU), Scaper (Marketing Science Journal), Scraper (Harvard), Scraper (Photo)

Lecture 4: Data visualization: A Tableau approach

This class introduces Tableau Public, a power data visualization software. It is simple and you will have fun using it.
Note: Please get Tableau Public installed on your laptop and bring it with you.
Slides
Data files: Superstore Data, Movie Data Tableau Public Gallery
Example of Word Cloud: Word Cloud Tagul for generating Word Cloud: Tagul

Lecture 5: Search Engine Optimization (SEO)

Slides (With Answer Keys)
Tools: ahref for checking backlinks; HubSpot

Lecture 6: Paid Search

Slides (With Answer Keys)

Lecture 7: Data Workshop

Note: Please get R installed on your laptop and bring it with you.
Slides (With Answer Keys)
Dataset: CSV
Sample Data Analysis with R: Sample

Lecture 8: Display Advertising

Slides (With Answer Keys)

Lecture 9: Social Networks

Slides (With Answer Keys)

Lecture 10: Social Media Marketing

Slides (With Answer Keys)
Final Review: Slides
Tools: Google Alert, TweetDeck, RivalIQ