SEARCH ENGINE OPTIMIZATION AND ANALYTICS
2017/2018, Semester 1
School of Computing (Information Systems & Analytics)
Modular Credits: 4
This course teaches the concepts, techniques and methods to analyse and improve the visibility of a website or a web page in search engines via the “natural” or un-paid (“organic” or “algorithmic”) search results. Students will be taught concepts and knowledge in terms of how search engines work, what people search for, what are the actual search terms or keywords typed into search engines, which search engines are preferred by their targeted audience, and how to optimize a website in terms of editing its content, structure and links, and associated coding to both increase its relevance to specific keywords and to remove barriers to the indexing activities of search engines. Importantly, the module will emphasize the relationship of search engine optimization to digital marketing in terms of building high quality web pages to engage and persuade, setting up analytics programs to enable sites to measure results, and improving a site's conversion rate.
Completed 80 MCs
Week 1 (August 15) Overview of SEO and Course Logistics,
Overview of BT4212
Basics of Internet Marketing
What is SEO?
Three major search engines: Google, Bing, and Yahoo
Assignment => :
Maximum 5 students in one group before Week 2’s class. Group of 4 is strongly preferred and group of 5 is only allowed for assigning the few students who cannot find a group to join.
When you form a team, it is better that you have at least one teammate who has stronger technical expertise, including Python programming, HTML and blogging.
It is also better that at least some of your team members use Windows, rather than all of you use Mac.
Week 2 (August 22) On-Page SEO
What is “Keywords Research” and how to conduct keywords research?
What is the well-known long tail concept and how it relates to SEO?
One-Page SEO Factors
H1 H2 paragraphs
“Similarity” to Keywords in Search Phrases
Length of Articles
Google Pagespeed Test
Team Assignment 1 => (1) Conduct your keyword research and decide the topic of your blog, (2) publish your first article on 2-3 blogging sites, (3) setup Google analytics and Rank Tracker tools to track your blog’s search ranking.
It is fine that you use non-traditional blogging sites or your personal website if you have one.
Week 3 (August 29) The most important off-page SEO: Link Building Strategies
White Hat Link Building Strategies
Black Hat Link Building Strategies: Link pyramid, Link circle, Article directories, and Spams.
History of Google Updates
Week 4 (September 5) Analytics: Causality, Randomized Experiment, Field Experiment, and other methods.
This week’s class is more about analytics and is less about SEO. I will cover important foundations and methods for field experiments or other methods that provides much stronger empirical evidence of causality than OLS you have used many times.
Randomized experiment and procedure of conducting field experiment will be covered. If the time allows, I will cover the following subjects: (1) instrumental variables (2) regression discontinuity.
Team Assignment 1 . Before the class of Week 4, I will ask TA to check the keywords performance of your blogs. More details will be announced later.
Team Assignment 2 => (1) Finishing up Week 2 assignment, (2) Also post at least one article per week. (3) Prepare a proposal of field experiment.
Week 5 (September 12) Other Factors of SEO,
Top Social Network Sites: although not that critical for SEO, but this is important for you to learn about digital/social marketing and it will be fun. Facebook, Twitter, Google Plus, Pinterest, Stumbleupon, among others.
(fake) Social sharing.
Week 6 (September 19) Online Advertising
Pay-per-click versus pay-per-impressions and other advertising metrics.
Example: Return of advertising investment of Facebook and Gogoogle Ads, experience from a
Preschool in Singapore
Recess Week (September 26) Team Assignment 2
Field Experiment Proposal Due
. I will try to provide feedback asap and you can start conduct experiment asap you hear from me. We will have about 1.5 months to see the treatment effect and SEO efforts.
Week 7 (October 3) More on Related Statistical Models
Predicting the ranking by Tobit regression and other regression methods.
Predicting the traffic of your blogs.
Applying on your dataset and compare the estimated treatment effects with treatment effects from randomized experiment.
Propensity Score Matching (if we have time).
Week 8 (October 10) Case Studies of Analytics based on SEO and traffic, Part I
Because BT4212 is only for BA students, I will cover more about the analytics and decision making models, less about the traditional technical aspects of SEO. So I plan to use the following three weeks to cover case studies or academic studies related to SEO and online advertising. The exact topics will be announced later.
Team Assignment 3 => Applying analytics for prediction. For example, predicting the page ranking of search results of your focal keywords by OLS or PSM…etc.
Week 9 (October 17) Case Studies of Analytics based on SEO and traffic, Part II
Week 10 (October 24) Case Studies of Analytics based on SEO and traffic, Part III
Week 11-12 (October 31 and November 7) Non-traditional and Multimedia SEO
Non-traditional SEOs on websites such as Youtube, Instagram, Taobao (merchant results), Chinese SEO on Baidu, and others.
Week 13 (November 14) Final Group Project Presentation of Your Advertising and Experimental Results. Final Report Due.
Workload Components : A-B-C-D-E
A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of lab hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week