CIS 3650 Web and Mobile Analytics Spring 2026

Fully Asynchronous Course | Spring 2026

1. Instructor

• If you email me, please use “CIS 3650” in the subject line, spell your full name in the email body, and send it from your cpp.edu account.
• Please do not submit any homework to me via email – it will not be accepted or graded. All homework should be submitted to either Canvas or Cengage as instructed.
• I typically aim to reply to emails within 24 hours. However, please note that this timeframe does not include weekends, as we are advised not to work on weekends or outside the 8-hour weekday limit according to university policy. Therefore, I recommend emailing on Thursday or early Friday if you would like to receive a response before the weekend.
• Office hours and the instructor’s Zoom link are provided in Canvas – Modules – Welcome to Class.

2. Class meetings

This course is fully asynchronous, with no scheduled class meetings. All learning materials and activities are available in Canvas -> Modules. The instructor posts weekly announcements to remind students of upcoming assignment deadlines. Students can contact the instructor with questions via email or during office hours.

3. Course Description

Web and mobile analytics, including the collection, analysis, and reporting of the audience, acquisition, behavior, and conversion data from websites and mobile applications to understand and optimize digital design, use, and performance. Advanced topics include data visualization, search engine optimization, attribution model, regular expression, tag management, conversion optimization, and preparing for professional certification exams such as the Google Analytics certification assessment.

4. Learning Objectives

Students completing this course should have acquired the ability to:

1. Describe how web and mobile analytics can provide business insights that help the business optimize its digital presence and performance.
2. Analyze and interpret User (including User Attributes and Tech), Acquisition, Engagement, and Monetization reports.
3. Create data-driven insights and recommendations.
4. Apply filters, dimensions, metrics, event tracking, tag management, configurations, and segmentation.
5. Develop custom dashboards and reports.
6. Describe and explain analytics-driven optimization.
7. Prepare and take the Google Analytics certification exam.

5. Textbook and Software

Required Resources

• Google Analytics 4 training and resources (free with a Google account)
• Access to a computer and the Internet

Required Software (all software is browser-based and free with a Google account)

• Google Analytics
• Google Tag Manager
• Google Looker Studio (previously Google Data Studio)

6. Exams, Projects, and Assignments

All weekly learning modules are published and all assignments are available from day one of the class so you can work ahead. I will send a Canvas announcement every Monday and a reminder every Friday. Weekly learning activities and assignments are due Friday at 11:59 p.m.

• Google Analytics 4 Reading Assignments: Students will engage with online materials to learn about Google Analytics 4, and complete readings, activities, and assessments.
• Hands-on Exercises: Students will apply their knowledge and skills in hands-on exercises using the GA 4 demo account, Google Tag Manager, and Looker Studio.
• Quizzes: Based on lecture videos and readings, students will take quizzes (time-limited multiple-choice questions).
• Google Analytics certification exam: After learning the knowledge and skills through Google Analytics 4, Google Tag Manager, Data/Looker Studio modules, and various web analytics relevant topics, including SEO, SEM, Dimension and Metrics, Attribution Models, etc., students will take the Google Analytics certificate exam to assess their web analytics proficiency. This timed- Google-hosted exam must be taken during the assigned week (Week 10).
• Group project: Students will apply the comprehensive knowledge and skills learned in class to analyze digital data for a real website using Google Analytics and provide business insights and/or recommendations. The deliverables include a written report (.docx), slide deck (.pptx), and a presentation video (.mov or .mp4). The instructor will assign students to groups after add/drop period (Week 3).

Make-up policy: Make-up exams are not offered except for serious and compelling reasons substantiated by formal and authoritative documents.

Late submission: Late assignments or projects will incur a 50% penalty if submitted within 24 hours after the deadline, and no late work will be accepted afterward.

Plagiarism: Students’ written assignments will be checked for plagiarism detection through AI software and Turnitin, which will check against not only Internet sources but also previous students’ work submitted to Canvas. Plagiarism activities will be reported to the university’s Student Conduct Office.

AI Use Policy:

Generative AI tools such as ChatGPT, Gemini, Claude, Perplexity, and Copilot may be used for brainstorming, code, image or video generation, creating study materials, and text editing. However, you must clearly indicate what the AI produced and what you contributed, and you must disclose your use of AI in the assignment (e.g., in a note or footnote).

I expect you to be the author of all work you turn in. If I ask about your assignments and projects, you should be able to explain them in depth and demonstrate mastery of the material without assistance.

AI tools may support your analysis, but they cannot replace your own reasoning or interpretation. You are responsible for explaining results and showing your understanding.

Reflections on readings and assignments must be written entirely by you without AI assistance. These are meant to demonstrate the quality of your own ideas and the personal nature of your reflection.

Student Responsibilities:

• Each student is responsible for completing and submitting all assignments and projects. Corrupted files or incomplete submissions will not be credited. Students are also responsible for keeping a backup copy of each submission.
• To ensure fairness, the instructor will NOT review, debug, or fix problems in student assignments and projects BEFORE grading the entire class. The instructor will, however, help students understand expectations, clarify requirements, provide guidance, help students gain knowledge and skills in analysis, design, and problem-solving, and answer specific questions on course topics.
• Students must have spent a significant and reasonable amount of time and effort researching and working on the issue independently BEFORE asking for help.

7. Grading

8. Course Schedule

Week	Learning Activities	Assignments Due
Week 1	Introduction to Web and Mobile Analytics	Quiz 1 Introduction Hands-on exercise 1: Access the Google Analytics Demo Account
Week 2	Google Analytics 4 Getting Started Search Engine Optimization (SEO)	GA4 Reading Assignment 1 Quiz 2 SEO
Week 3	Manage GA4 Data and Learn to Read Reports Search Engine Marketing (SEM)	GA4 Reading Assignment 2 Quiz 3 SEM
Week 4	Dive Deeper into GA4 Data and Reports Dimensions and Metrics	GA4 Reading Assignment 3 Quiz 4 Dimensions and Metrics
Week 5	Use GA4 with Other Tools and Data Sources Attribution Models	GA4 Reading Assignment 4 Quiz 5 Attribution Models
Week 6	Study Google Tag Manager (GTM)	Quiz 6 Google Tag Manager Hands-on exercise 2: Google Tag Manager
Week 7	Study Looker Studio	Quiz 7 Looker Studio Hands-on exercise 3: Looker Studio Report
Week 8	Mobile Analytics	Quiz 8 Mobile Analytics
Week 8	Regular Expression Analytic-driven Optimization	Quiz 9 Regular Expression Quiz 10 Analytic-Driven Optimization
Week 10	Google Analytics Certification exam	Google Analytics Certification exam
Week 11-15	Group project	Group project

9. University Policies

Accessibility: Cal Poly Pomona is committed to student success as a learning-centered university. Students with disabilities are encouraged to contact the instructor privately or to visit the Disability Resource Center to coordinate course accommodations.

Computing Resources: At Cal Poly Pomona, computers and communications links to remote resources are recognized as being integral to the education and research experience. Every student must have access to a computer with all the required software for this course. Contact I&IT if you need help.

Academic Integrity: The University is committed to maintaining academic integrity throughout the university community. Academic dishonesty is a serious offense that can diminish the quality of scholarship, the educational environment, the academic reputation, and the quality of a Cal Poly Pomona degree. Plagiarism or cheating will not be tolerated in this course. 

Copyright Policy: Copyright laws and fair use policies protect the rights of those who have produced the material. The copy in this course has been provided for private study, scholarship, or research. Other uses may require permission from the copyright holder. The user of this work is responsible for adhering to the copyright law of the U.S. (Title 17, U.S. Code). The course website contains material protected by copyrights held by the instructor, other individuals, or institutions. Such material is used for educational purposes following copyright law and/or with permission given by the owners of the original material. Students may download one copy of the materials on any single computer for non-commercial, personal, or educational purposes only, provided that (1) do not modify it, (2) use it only for the duration of this course, and (3) include both this notice and any copyright notice originally included with the material. Beyond this use, no material from the course website may be copied, reproduced, republished, uploaded, posted, transmitted, or distributed in any way without the original copyright holder’s permission. The instructor assumes no responsibility for individuals who improperly use copyrighted material placed on the website.