Skip to content

A 5-year marketing simulation using A/B testing, regression analysis, and multi-channel strategy to optimize ROMI, CLV, and customer growth for a fictional fitness brand.

License

Notifications You must be signed in to change notification settings

maddoMaddz/exerciseMinder-digital-marketing-simulation

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

4 Commits
Β 
Β 
Β 
Β 
Β 
Β 

Repository files navigation

ExerciseMinder: Customer Acquisition & Retention Simulation

πŸ“Š Overview
This project explores a 5-year marketing strategy simulation for a fictional fitness tracker brand, ExerciseMinder, using real-world frameworks like RACE and See–Think–Do–Care. The goal: optimize customer acquisition, retention, and ROMI across digital channels using A/B testing, regression analysis, and campaign iteration.


🧠 Key Learnings

  • A/B testing revealed value-driven messaging outperforms short-term discounting for retention.
  • Email and branded search consistently delivered the highest ROI.
  • Regression analysis uncovered underperforming channels (e.g., TV) and improved spend allocation.
  • Lifetime value (CLV) doubled over time by shifting from high-churn acquisition to loyalty campaigns.

πŸ“ˆ Results

  • πŸ§β€β™‚οΈ Customer Base: Grown from 2M to 3.97M
  • πŸ’° Cumulative Revenue: $900M+
  • πŸ“Š ROMI: Improved from 1.42 β†’ 2.7 β†’ 3.5 peak

πŸ§ͺ Tools & Methods

  • Regression analysis
  • A/B testing
  • Customer segmentation
  • Attribution modeling
  • Channel performance metrics

πŸ“„ Deliverables


πŸ“¬ Contact

Madeleine Benna
LinkedIn | GitHub

About

A 5-year marketing simulation using A/B testing, regression analysis, and multi-channel strategy to optimize ROMI, CLV, and customer growth for a fictional fitness brand.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published