UCSD MGT 100: Customer Analytics

Prepared by Kenneth C. Wilbur and Dan Yavorsky

Navigation Guide : Tap to expand

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Readings, Class Slides, R Scripts and Class Videos: The links below provide the latest versions of all class content.

Study Groups and Grades: Available on Canvas.ucsd.edu

Asynchronous communication: Piazza--linked from Canvas--for all student questions, comments, requests, etc. After class or office hours are for discussions. Please, no emails or Canvas messages.

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2025 Syllabus | Data | Past Exams

Week 1: Visualization, Intro
Before class: Read the syllabus
Slides: Web, PDF | R Script | Class Video

Week 2: Segmentation, Mapping, Text
Before class: Read and watch
Slides: Web, PDF | R Script | Class Video

Week 3: Demand Modeling
Before class: Read sections 3.1, 3.3 & 3.9. Read other sections if they interest you.
Slides: Web, PDF | R Script | Class Video

Week 4: Midterm 1

Week 5: Heterogeneous Demand Modeling
Before class: Watch and Read sections 6.1, 6.2 & 6.8. Read other sections if they interest you.
Slides: Web, PDF | R Script | Class Video

Week 6: Pricing
Before class: Read
Slides: Web, PDF | R Script | Class Video

Week 7: Branding
Before class: Read
Slides: Web, PDF | R Script | Class Video

Week 8: Midterm 2

Week 9: Predictive Customer Analytics
Before class: Read
Slides: Web, PDF | R Script | Class Video

Week 10: Customers+Finance
Before class: Read
Slides: Web, PDF | No R Script or Homework | Class Video

Final Exam: In Person at the UCSD-appointed time and place

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Materials linked below are from 2024.

Week 6: Demand Modeling: Heterogeneous Logit
Slides | R Script | Class Video

Week 7: Pricing & Optimal Pricing
Slides | R Script | Class Video

Week 8: Branding
Slides | R Script | Class Video

Week 9: Market Size & Customer Lifetime Value
Slides | R Script | Class Video

Week 10: Marketing+Finance
Slides | No R Script & No Homework | Class Video

Why do we share these class materials? Tap to expand

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1. We are public employees, so we like to make our work products publicly accessible when possible.

2. We want as many people as possible to be as good at analytics as possible. We hope that sharing these materials could encourage that.

3. We hope our materials could help other teachers in their analytics course designs. The github repository contains .qmd Quarto source files to modify presentation pages. We invite others to remix or extend these materials. Please share any revisions or corrections back with us, so we can consider incorporating them with attribution into our next iteration.

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For students who consider registering : Tap to expand ================================================ here and sections 2-10 here. 5. We will post 2025 revisions to all course materials as they become available. All required materials will be provided here. 6. We look forward to meeting you soon! ================================================>