Amazon FBA Financial Due Diligence Framework
Developing a rigorous financial and operational analysis model for evaluating Amazon FBA acquisitions.
Challenge
Evaluating an Amazon business for acquisition is notoriously difficult due to messy seller central reporting, hidden operational costs, and the volatility of platform-dependent businesses. Buyers need a reliable way to verify true profitability beyond the top-line revenue numbers presented in a seller's prospectus.
Approach
We built a comprehensive, data-driven analytical framework that cross-references multiple Amazon reports to reconstruct accurate profit and loss statements, identify listing vulnerabilities, and assess true operational health.
Technology
Work Completed
The core of the project involved designing a financial model capable of ingesting raw Amazon Seller Central data—specifically the transaction, advertising, and return reports. By normalizing this data, we created a system that accurately maps Cost of Goods Sold (COGS), inbound shipping, and Amazon FBA fees down to the individual SKU level.
We developed metrics dashboards to evaluate critical health indicators: True ACOS (Total Advertising Cost of Sales) versus traditional ACOS, organic-to-paid sales ratios, and refund rate trends. This granular view helps identify products that are artificially propped up by heavy ad spend versus those with genuine organic traction.
Operationally, the framework includes assessment protocols for account health warnings, supplier concentration risk, and review velocity analysis to check for potential black-hat tactics that could result in suspension post-acquisition.
Outcome
We structured a robust, repeatable due diligence framework that allows potential acquirers to cut through inflated broker numbers. The model provides clear visibility into True Seller Discretionary Earnings (SDE), highlighting operational inefficiencies and exposing hidden risks before capital is deployed, ensuring data-backed acquisition decisions.
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