Customer Segmentation & Growth Analytics
From raw transactions to a boardroom-ready growth story
Northbridge Retail Group — an illustrative company sponsor — wants to understand which customer segments create the most value and where its next wave of growth will come from. Over six weeks you'll move from raw purchase data to a clear, defensible recommendation, working the way a professional analyst actually works: framing the question, interrogating the data, and translating findings into decisions.
This is Industry Project Experience — a mentored, company-sponsored problem that mirrors real analytics work. You'll build every deliverable in professional tools and defend your thinking in a live final presentation.
What you'll deliver
- Customer Segmentation Analysis (RFM + clustering)
- Interactive Growth Dashboard
- Executive Recommendation Deck
- Professional Portfolio entry with verified completion
- StartedJul 28, 2026
- Current week endsAug 17, 2026
- Final presentationSep 5, 2026
Customer Behavior Analysis
Understand purchasing behavior across customer groups.
Build an RFM view — Recency, Frequency, and Monetary value — for each customer, surface the patterns that separate your best customers from the rest, and visualize what you find. This week's analysis becomes the foundation for next week's segmentation.
Drag & drop your notebook here
or — .ipynb, .pdf, .csv up to 25 MB
Once you submit, Amina is notified and typically returns written feedback within 2 business days. You can keep editing until she opens the review.
Strong start on frequency analysis — add recency and monetary value to complete an RFM view. Let's review Thursday.
Thanks! I've added a recency column and I'm calculating monetary value now — I'll push the updated notebook before Thursday.
Agenda: review your RFM approach and plan Week 4 segmentation.
Everything you need for this project
Datasets, starter templates, and reference material curated by your mentor — organized so you always know where to look next.
Datasets
Customer Transactions (CSV), Product Catalog, and a Data Dictionary describing every field.
Starter templates
Python and SQL starter notebooks with the project scaffold and helper functions ready to run.
Guides & references
RFM primer, windowed-aggregate SQL guide, and a Tableau style guide for polished dashboards.
Worked examples
An anonymized example RFM dashboard and analysis so you can see the standard you're building toward.
Deliverables across the project
Every weekly notebook and final artifact lives here. Submitted work is reviewed by your mentor; approved work flows straight into your Professional Portfolio.
Feedback history
Every review Amina leaves is kept here so you can act on it, reply, and track how your work is improving week over week.
Strong start on frequency analysis — add recency and monetary value to complete an RFM view. Let's review Thursday.
Thanks! I've added a recency column and I'm calculating monetary value now — I'll push the updated notebook before Thursday.
Excellent cleaning log — documenting every assumption is exactly how professional analysts build trust. Your distribution plots made the outliers obvious. Approved.
Average mentor rating across submitted work.
- 2 deliverables approved
- 2 mentor sessions completed
When you present findings, lead with the decision it enables — not the method you used to get there.
Mentor meetings
Weekly 45-minute check-ins with your Industry Mentor, plus notes and recordings from every past session.
Present your recommendation like a professional
In your final session you'll walk your mentor — and an illustrative company sponsor panel — through your growth recommendation: who the highest-value segments are, why, and what the business should do next. This is where six weeks of analysis becomes a story that drives a decision.
Your final presentation will include
- Executive Recommendation Deck (10–12 slides)
- Live walkthrough of your interactive dashboard
- Q&A defending your methodology and assumptions