Investigate Churn Drivers for NordicGlow Cosmetics Customers
Overview
What this challenge is about.
Investigate Churn Drivers for NordicGlow Cosmetics Customers. Intermediate challenge in analysis. Analyzing real datasets and building models that drive deci...
The Brief
What you'll do, and what you'll demonstrate.
Identify which NordicGlow customers are likely to stop purchasing within the next 30 days and determine the cost-effective retention actions most likely to keep them.
This is not a data exercise. It is the work an analyst does when stakeholders need answers from messy data. That distinction matters to every hiring manager who has seen candidates describe statistical methods and none who have extracted insight from messy, real-world data.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Profile and clean a multi-signal customer dataset, handling missing values and outliers defensibly
- Engineer behavioural features (recency, frequency, monetary, engagement decay, support friction) from raw records
- Train and validate an interpretable churn classifier and evaluate it honestly on held-out data
- Use model interpretation methods to identify and evidence the leading drivers of churn
- Translate technical findings into costed retention actions and communicate them to a non-technical executive
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Data Preprocessing
Apply data preprocessing to solve real industry problems and demonstrate production-level capability.
- Feature Engineering
Apply feature engineering to solve real industry problems and demonstrate production-level capability.
- Classification
Apply classification to solve real industry problems and demonstrate production-level capability.
- Model Interpretation
Apply model interpretation to solve real industry problems and demonstrate production-level capability.
- Business Communication
Apply business communication to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Customer Analytics Data Scientist
This challenge mirrors the core loop of a customer analytics role: turning messy first-party behaviour data into a validated churn model and retention recommendations that a business can fund and act on within budget.
This challenge sharpens
- feature-engineering
- classification
- model-interpretation
Growth / Retention Analyst
Retention analysts must diagnose why customers leave and propose cost-effective interventions. Here you practice evidencing churn drivers from data and pricing retention actions against a real budget constraint.
This challenge sharpens
- data-preprocessing
- model-interpretation
- business-communication
Analytics Consultant
Consultants deliver decisions, not just models. This challenge builds the consulting muscle of scoping an investigation, validating results honestly, and communicating recommendations to a non-technical executive audience.
This challenge sharpens
- classification
- business-communication
- feature-engineering