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Programming & Development Math / Algorithms / Analytics

Ecommerce Profit Leak Diagnostic

$35/hr Starting at $500

Find out which products are quietly bleeding your profit


Most D2C brands look profitable on the sales report and lose money in practice.


The gap hides in a handful of places nobody checks: SKUs that cost more to fulfill than they earn, shipping tiers that eat your margin, and discount habits that became permanent without anyone deciding that on purpose.


I run a full profitability and operational-risk audit on your actual order data and deliver a plain-English report showing exactly where the money is leaking and what to do about it.


What this diagnostic uncovers


  • Profit concentration — Which products actually drive your bottom line (often a small handful, not your top revenue sellers).

  • Zombie SKUs — Products draining warehouse and support time while contributing almost nothing to revenue or profit.

  • Revenue traps — Items that look like winners by sales volume but are quietly losing money on every order.

  • Shipping risk — Which delivery methods are costing you in late deliveries, refunds, or poor customer experience.

  • Discount dependency — Whether your discounting is a lever or has become your default price.


Example finding from a past audit


In one dataset containing 180,000+ orders:


  • Just 8 products drove 84.5% of total profit.

  • 28 zombie SKUs consumed significant operational resources for almost no return.

  • One shipping method failed to arrive on time 100% of the time.


What you get


1. A clean, client-facing PDF report (not a raw data dump).


2. A ranked list of findings by dollar impact.


3. A short set of concrete next steps with no generic advice.


Process


1. Data access

You share a read-only export or database access. No admin permissions required.


2. Analysis

I build the profitability model and run the audit.


3. Delivery

You receive the report along with a walkthrough call to discuss the findings.


Turnaround: Typically 7–10 business days, depending on data size.


See the full methodology and a real project write-up on my Website and GitHub.GitHub

About

$35/hr Ongoing

Download Resume

Find out which products are quietly bleeding your profit


Most D2C brands look profitable on the sales report and lose money in practice.


The gap hides in a handful of places nobody checks: SKUs that cost more to fulfill than they earn, shipping tiers that eat your margin, and discount habits that became permanent without anyone deciding that on purpose.


I run a full profitability and operational-risk audit on your actual order data and deliver a plain-English report showing exactly where the money is leaking and what to do about it.


What this diagnostic uncovers


  • Profit concentration — Which products actually drive your bottom line (often a small handful, not your top revenue sellers).

  • Zombie SKUs — Products draining warehouse and support time while contributing almost nothing to revenue or profit.

  • Revenue traps — Items that look like winners by sales volume but are quietly losing money on every order.

  • Shipping risk — Which delivery methods are costing you in late deliveries, refunds, or poor customer experience.

  • Discount dependency — Whether your discounting is a lever or has become your default price.


Example finding from a past audit


In one dataset containing 180,000+ orders:


  • Just 8 products drove 84.5% of total profit.

  • 28 zombie SKUs consumed significant operational resources for almost no return.

  • One shipping method failed to arrive on time 100% of the time.


What you get


1. A clean, client-facing PDF report (not a raw data dump).


2. A ranked list of findings by dollar impact.


3. A short set of concrete next steps with no generic advice.


Process


1. Data access

You share a read-only export or database access. No admin permissions required.


2. Analysis

I build the profitability model and run the audit.


3. Delivery

You receive the report along with a walkthrough call to discuss the findings.


Turnaround: Typically 7–10 business days, depending on data size.


See the full methodology and a real project write-up on my Website and GitHub.GitHub

Skills & Expertise

AnalyticsData AnalysisData ModelingData VisualizationE CommerceMicrosoft ExcelPower BIStatistical Analysis

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