Module 6: Measurement, attribution, and incrementality

Module 6: Measurement, attribution, and incrementality#

Theme#

Measurement, attribution, and incrementality

Essential Question#

What evidence shows marketing impact?

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 measurement, attribution, and incrementality: Compare attribution and incrementality approaches.

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-6.

  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.