SEARCH ENGINE OPTIMIZATION AND ANALYTICS
2016/2017, 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.
Understand the conceptual foundations of search engine optimization and analytics
Apply technical and analytic tools, techniques and methods for search engine optimization and analytics
Learn how to conduct field experiments and analytics.
Decision making and analytics based on search results.
Completed 80 MCs
Week 1 (August 9 National Day Holiday)
Week 2 (August 16) Overview of SEO and Course Logistics,
Overview of BT4212
Basics of Internet Marketing
What is SEO?
Three major search engines: Google, Bing, and Yahoo
Learn how to use Google and Bing Analytics
Blogging Basics: Setup a blog for SEO experiments later
SEO Tools and Rank Trackers
Assignment => : maximum 5 students in one group before Week 3’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 HTML and blogging. No programming is needed but HTML skills will be quite useful.
Week 3 (August 23) Keywords Research, Long Tail Concept, and Key Factors of 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?
Key factors of SEO Part I
“Similarity” to Keywords in Search Phrases
H1 H2 paragraphs
Keywords? <= surprisingly, keywords in HTML do not matter.
Keywords location, density, and Topics Modeling of your content?
HTML Links and Page Rank Algorithm (more in Week 5)
Team Assignment 1 => (1) Conduct your keyword search 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.
Week 4 (August 30) Analytics: Causality, Randomized Experiment, Field Experiment, and other methods.
This week’s class is more about analytics and 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 (3) propensity score matching (<= this does not really help much but is similar to experiment).
Team Assignment 2 => (1) Finishing up Week 3 assignment, (2) Also post at least one article per week. (3) Prepare a proposal of field experiment.
Week 5 (September 6) The most important factor of 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
Team Assignment 1 . Before the class of Week 5, I will ask TA to check the keywords performance of your blogs. More details in Section 6.
Week 6 (September 13) 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.
Embedding multi-media files (images, videos, audios, …etc.) into your page.
Others minor SEO factors: Google Speed Test, internal Links, Mobile view.
Recess Week (September 20) 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. More details in Section 6.
Week 7 (September 27) More on Related Statistical Models
Predicting the ranking by Tobit regression and other regression methods.
Predicting the traffic of your blogs.
Propensity Score Matching (if not covered in Week 4).
Applying on your dataset and compare the estimated treatment effects with treatment effects from randomized experiment.
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 8 (October 4) Online Advertising
Google Adwords, Bing Ads, and other (novel) advertising platforms.
Amazon Affiliated Marketing.
Pay-per-click versus pay-per-impressions and other advertising metrics.
(Maybe) studies and algorithms of personalized advertising.
Example: Return of advertising investment on Facebook and Gogoogle, experience from a
Preschool in Singapore
Week 9 (October 11) 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 or papers based on the search engine results, or web traffic. The exact topics will be announced later.
Team Assignment 3 Due.
Team Assignment 4 (Tentative) Decision Making and Optimization => Draft an online advertising plan with some basics of optimization in math. I am considering give each team 10SGD for trying out on Google Ads to advertise your webpage. You need to come up a plan first to maximize the expected traffic drawn to site, the number of users who clicked on your other pages and/or ads,, given the budget constraint of ads.
Week 10 (October 18) Case Studies of Analytics based on SEO and traffic, Part II
Week 11 (October 25) Case Studies of Analytics based on SEO and traffic, Part III
Team Assignment 4 Due. Start conducting your advertising experiment.
Week 12 (November 1) Non-traditional and Multimedia SEO and/or Multimedia Data Mining
Non-traditional SEOs on websites such as Youtube, instagram, Taobao (merchant results), Chinese SEO on Baidu, and others.
I may also find some interesting related methods of multimedia data mining to be covered in this week’s class.
Week 13 (November 8) Final Group Project Presentation of Your Advertising and Experimental Results. Final Report Due.
Group Project (Tentative and more details to be announced)
This is a preparation assignment. You need to conduct keywords research by the steps I teach in class. Identify the theme for your blogs. Grading will depend on your keywords performance and the completeness of your blogs. You may need to submit screen shots of Google analytics page and ranking tracking results.
You need to identify a SEO factor of interests and conduct a field experiment to check the impact of this SEO factor. So you need to explain what is the factor? Why is that interesting and worthy of studying? Explain the details of procedure of conducting the experiment. How are you going to control/exclude confounding factors?
Run OLS, Tobit, PSM, Logistic models on the top 20 search results of a chosen keyword. Each team will analyze two different keywords. The DV is search results ranking. The IVs include SEO factors chosen by you. One additional requirement is you need to conduct text mining analysis on those top 20 pages to create a variable called
between the focal page and the keyword.
In this assignment, you need to build a mathematical model that uses the real-world data as the input. Input data means the price of each keywords advertising. Make some assumptions of the behavior of those users. Then write an optimization program and really solve the problem numerically to decide the set of keywords and the price of keywords you want to bid so to maximize several different metrics. Metrics include: number of unique visitors, the number of page views, the length of visitors staying on your site, and if we have ads, the number of ads clicked on your site.
Final Report and Final Presentation
The report and presentation will cover
(1) The experiment settings you conducted.
(2) The treatment effects identified.
(3) The advertising experiment results.
(4) Summary of discussion of your findings.
(5) Lessons learned: challenges throughout the semester and if you can redo the experiment, what will you do differently?
Class Participation: 5%
4 Team assignments: 35%
Group Project: 20% (1
0% final report, 10% presentation)
Final Exam: 40% (Open Book, 2 hour)
In order to have more individual components
A1 (2 students for one submission): 5%
A2 (one team for one submission): 10%
A3 (2 students for one submission): 10%
A4 (one team for one submission): 10%
A group of 4 students is expected. 2 students for submission mean each team will submit two related but different submissions and each is written up by 2 team members.
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