Rohan Verma
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Analytics project / RFM

Diagnose value before you reallocate the budget.

A commercial analytics project linking sales and profitability diagnostics with RFM segmentation to make retention, upsell, and budget decisions more targeted.

150K+transactions analysed across pricing tiers and promotions
15-20%improvement in profitability visibility
3budget-reallocation recommendations developed

The business question

Which commercial levers are leaking value, and which customers should get more attention?

Commercial performance can look healthy at an aggregate level while discounted products, low-value customers, or retention gaps erode contribution. This project paired margin diagnostics with RFM segmentation to make the next actions specific.

The work

Connect profitability visibility with customer value.

I analysed 150K+ transactions across pricing tiers and promotions to pinpoint discounted SKUs eroding contribution margin. I then built scenario-based discount-rationalisation models, improving profitability visibility by 15-20%, and segmented 100K+ records through RFM analysis to surface high-value and at-risk customer cohorts.

Diagnose

Find leakage

Connect discount depth and price tiers with contribution-margin risk.

Segment

Classify value

Use recency, frequency, and monetary value to distinguish customer needs.

Prioritise

Direct the budget

Translate behavioural clusters into specific retention and upsell actions.

The decision support

Make every recommendation traceable to a commercial signal.

Pricing & promotionsMargin leakage isolated across 150K+ transactionsImproved discount-rationalisation visibility
Customer value100K+ records segmented into high-value and at-risk cohortsEnabled retention and upsell strategy
Resource allocationThree prioritised budget-reallocation recommendationsOptimized expected campaign ROI

Portfolio note

This is a summary of project-level outcomes. It intentionally excludes underlying records, model logic, source data, and any figures beyond the approved resume-level metrics.