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AINS6200 AI for Marketing & Customer Insights

  • AINS6200: AI for Marketing & Customer Insights
  • Syllabus: AINS6200 AI for Marketing & Customer Insights
  • How to Use AINS6200
  • Technical Requirements and Setup
  • Authoritative Readings and Resources
  • Module 1: Customer data and segmentation
    • Module 1 Book Prose
    • Module 1: Customer data and segmentation
    • Module 1 Narrated Study Guide
    • Module 1 Rubric
  • Module 2: Recommendation systems
    • Module 2 Book Prose
    • Module 2: Recommendation systems
    • Module 2 Narrated Study Guide
    • Module 2 Rubric
  • Module 3: Campaign optimization
    • Module 3 Book Prose
    • Module 3: Campaign optimization
    • Module 3 Narrated Study Guide
    • Module 3 Rubric
  • Module 4: Customer journey analytics
    • Module 4 Book Prose
    • Module 4: Customer journey analytics
    • Module 4 Narrated Study Guide
    • Module 4 Rubric
  • Module 5: Generative AI for marketing operations
    • Module 5 Book Prose
    • Module 5: Generative AI for marketing operations
    • Module 5 Narrated Study Guide
    • Module 5 Rubric
  • Module 6: Measurement, attribution, and incrementality
    • Module 6 Book Prose
    • Module 6: Measurement, attribution, and incrementality
    • Module 6 Narrated Study Guide
    • Module 6 Rubric
  • Module 7: Privacy, consent, and trust
    • Module 7 Book Prose
    • Module 7: Privacy, consent, and trust
    • Module 7 Narrated Study Guide
    • Module 7 Rubric
  • Module 8: AI customer insights portfolio
    • Module 8 Book Prose
    • Module 8: AI customer insights portfolio
    • Module 8 Narrated Study Guide
    • Module 8 Rubric
  • .md

Module 7: Privacy, consent, and trust

Contents

  • Theme
  • Essential Question
  • Module Components
  • Module Artifact
  • Professional Setting
  • Use This Module in Order

Module 7: Privacy, consent, and trust#

Theme#

Privacy, consent, and trust

Essential Question#

How do marketing AI systems respect customers?

Module Components#

  • Book prose: conceptual framing, domain scenario, methods, and failure modes

  • Assignment: evidence-backed production of a specific artifact

  • Slides: presentation sequence for seminar or lecture delivery

  • Narration: spoken version of the slide flow

  • Rubric: criteria for evaluating the module artifact

  • Notebook: executable lab aligned with the module theme using synthetic customer records with engagement, recency, spend, channel preference, and consent state

Module Artifact#

customer insights package with segmentation, measurement design, and consent constraints focused on privacy, consent, and trust: Draft a consent and data-use review.

Professional Setting#

Students work as if advising a growth team deciding how AI-generated customer insights should guide campaign targeting. Their work must be intelligible to marketing lead, analytics manager, privacy counsel, and customer experience owner.

Use This Module in Order#

  1. Read the learning chapter.

  2. Review the slide deck with the matching narration.

  3. In Populi, open the private student-repository link for this course and enter modules/module-7.

  4. Clone the repository once or open its Codespace/Colab copy; run lab.ipynb and complete exercise.ipynb there.

  5. Self-check with the rubric, commit and push the work, then submit exactly what Populi requests.

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Module 6 Rubric

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Module 7 Book Prose

Contents
  • Theme
  • Essential Question
  • Module Components
  • Module Artifact
  • Professional Setting
  • Use This Module in Order

By Castalia Institute

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