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Programming & Development Math / Algorithms / Analytics

Customer Segmentation & LTV Analysis

$30/hr Starting at $300

Not all customers are worth the same to your business


Most brands treat every customer the same in their marketing and retention spend.


In reality, a small segment usually drives most of your revenue, and knowing exactly who they are changes how you spend on retention, advertising, and loyalty.


What this analysis delivers


  • RFM segmentation — Customers grouped by how recently, how often, and how much they buy.


  • Lifetime value gaps — How much more your best customers are worth compared to your average ones.


  • At-risk identification — High-value customers showing signs of drifting away before you lose them.


  • Underused segments — Customer groups with real upgrade potential that are currently being ignored.


A finding from a past project


On a £17.3M UK retail dataset:


  • The top 20% of customers generated 77.2% of total revenue.


  • There was a 40× lifetime value gap between the highest-value and at-risk customer segments.


Deliverable


You receive an interactive dashboard/model together with a concise written summary containing:


  • Segment breakdown with customer counts and revenue share.


  • Quantified $ or £ impact of protecting your highest-value customer segments.


  • Specific recommendations for each segment—not generic "improve retention" advice.


Turnaround5–8 business days.
See it here.

About

$30/hr Ongoing

Download Resume

Not all customers are worth the same to your business


Most brands treat every customer the same in their marketing and retention spend.


In reality, a small segment usually drives most of your revenue, and knowing exactly who they are changes how you spend on retention, advertising, and loyalty.


What this analysis delivers


  • RFM segmentation — Customers grouped by how recently, how often, and how much they buy.


  • Lifetime value gaps — How much more your best customers are worth compared to your average ones.


  • At-risk identification — High-value customers showing signs of drifting away before you lose them.


  • Underused segments — Customer groups with real upgrade potential that are currently being ignored.


A finding from a past project


On a £17.3M UK retail dataset:


  • The top 20% of customers generated 77.2% of total revenue.


  • There was a 40× lifetime value gap between the highest-value and at-risk customer segments.


Deliverable


You receive an interactive dashboard/model together with a concise written summary containing:


  • Segment breakdown with customer counts and revenue share.


  • Quantified $ or £ impact of protecting your highest-value customer segments.


  • Specific recommendations for each segment—not generic "improve retention" advice.


Turnaround5–8 business days.
See it here.

Skills & Expertise

AnalyticsData AnalysisData ModelingData VisualizationMicrosoft ExcelPower BISpreadsheetsStatistical Analysis

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