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

  • Instructor: Xi Li
  • Class 1A: Monday 14:30–17:20 (MB256)
  • Class 1B: Friday 14:30–17:20 (MB141) — Oct 1 class will be cancelled (Public Holiday)
  • You can download the software for the course here: R, R Studio and Tableau Public
  • No textbooks for the course. You may find this free ebook helpful.

Grading

  • 5%: In class participation: Based on your in class participation (e.g., answering questions in class)
  • 10%: Group Paper Presentation (~12 minutes, in class). Details
    Paper selection for class B; class A
  • 15%: Group Data Project (start in class; no presentation).
    For details, see Lecture 7. Deadline: November 5
  • 25%: Group Project (in class presentation + report). Details
    You need to get your presentation ready by Nov 22 (Class A) or Nov 26 (Class B), and the order will be determined by a lucky draw. For class A, groups will present on either Nov 22 or Nov 29 (according to the lucky draw); for class B, all groups will present on Nov 26.
    Duration of in-class presentation: 25 min + 5 min Q&A
    Deadline for reports: Nov 29 (Monday). The maximum length of your report is 12 pages (double space)
  • 45%: Final Example (Open-notes; Multiple Choice Questions Only)
    14:30–16:00, December 7 (Tuesday), KB223

Lecture 1: Introduction to Digital Marketing

Slides (Without Answer Keys) Slides (With Answer Keys)
You need to form groups for your course project. Deadline: Sep 12 for 1B and Sep 15 for 1A.

Lecture 2: Data Analysis: An R Approach

Note: Please get R installed on your laptop and bring it with you.
Slides
Teaching materials: A beginner’s guide to R
Trouble shooting for package installation: Here

Lecture 3: Introduction to Data Scraping

Note: Please get R installed on your laptop and bring it with you.
Slides
Teaching materials: Scraper (HKU), Scaper (Marketing Science Journal), Scrape (MIT)

Lecture 4: Data Visualization: A Tableau Approach

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)

Keywords: Crawler, on-page optimizing, off-page optimizing, backlinks, page ranking, website evaluation
Slides (Without Answer Keys) Slides (With Answer Keys)
Tools: ahref for checking backlinks; HubSpot

Lecture 6: Paid Search

Keywords: Google analytics, second-price auctions, ad practices, keyword matches, measurability.
Slides (Without Answer Keys) Slides (With Answer Keys)
Tools: Google Analytics

Lecture 7: Data Analysis Workshop

Note: Please get R installed on your laptop and bring it with you.
Slides
Dataset: XLSX, CSV
Sample Data Analysis with R: Sample

Lecture 8: Display Advertising and Content Creation

Keywords: Tagreting, direct buying, real-time bidding, ad networks, ad exchange, persona, click and like fraud.
Slides (Without Answer Keys) Slides (With Answer Keys)
Tools used: followerwonk, Klear, BuzzSumo, Trendspottr

Lecture 9: Social Networks and Mobile Marketing

Note: Please get R installed on your laptop and bring it with you.
Keywords: Web 2.0, centrality, mobile, location-based targeting and geofencing.
Slides (Without Answer Keys) Slides (With Answer Keys)

Lecture 10: Social Media Marketing

Keywords: Social media, guideline, crisis, content, “Contagious”, AB tests, Texual listening, visual listening, influencer, UGC and WOM.
Slides (Without Answer Keys) Slides (With Answer Keys)
Tools: HootSuite, Google Alert, TweetDeck, Socialmention, RivalIQ

Lecture 11: Project Presentation

Review and Information About Final
Slides (Without Answer Keys) Slides (With Answer Keys)