Sample report

Profit Forensics Report — Demonstration

This is an illustrative report for a fictional store. It shows the structure and depth of a real engagement using invented numbers.

Demonstration using synthetic data. Not a real merchant.

Gross sales traced: $420,000
Contribution profit: $123,400
Findings surfaced: 8
Classes represented: 4

Northbound Goods (fictional) · Core Profit Forensics Audit · trailing 12 months · illustrative figures, verified separated from modeled.

Section 1

The Dollar Trail

Gross sales traced to contribution profit. In this synthetic store, contribution profit lands at roughly 29% of gross — and three steps account for most of the erosion.

The Dollar TrailSynthetic example

Gross sales$420,000
Discounts9.1% of gross−$38,400
Refunds5.4% of gross−$22,600
Net sales$359,000
Processing & app fees−$14,800
Shipping (net of charged)−$19,300
Product costs (COGS)−$201,500
Contribution profit
$123,400

Illustrative figures. Your report separates verified amounts from modeled estimates.

How to read the findings

Five classifications, in plain English

Each finding is tagged so you know how much weight to give it and what to do next.

Verified loss: Confirmed against source records (such as payout statements). The money difference is documented, not estimated.
Modeled loss: Calculated from your costs and order data. It is an evidence-based estimate, clearly labeled as modeled rather than directly confirmed.
Suspected anomaly: A pattern that looks wrong and warrants review — for example a possible duplicate refund. Flagged for your confirmation, not asserted as fact.
Missed opportunity: Profit you are likely leaving on the table, such as a strong product that keeps going out of stock.
Data blind spot: Information that is missing or incomplete, which makes standard platform reporting misleading until it is filled in.

Section 2

Findings & evidence appendix

Verified figures are confirmed against records; modeled figures are estimated from supplied costs and clearly labeled.

Modeled lossConfidence: Medium

$3,140 across 41 orders (modeled)

Negative-margin orders

Evidence: Contribution model applied per order using supplied product costs. 41 orders returned negative contribution after discounts, fees, and shipping. Figures are modeled from costs you provide, not confirmed bank movements.
Recommended action: Raise the free-shipping threshold, cap stackable discounts on low-margin SKUs, and exclude unprofitable bundles.

SourceOrders export · your cost inputs

FormulaF-CONTRIBUTION-MARGIN v1.0

Suspected anomalyConfidence: Medium

4.07% effective (vs 3.31% standard)

Processing fees settle at two different rates

Evidence: About half of card charges match the standard 2.9% + $0.30; the rest settle higher, lifting the true blended processing cost. This is a margin-accuracy insight — a descriptive true-cost figure, not a recoverable saving — and the underlying cause (often foreign-issued cards) cannot be confirmed from the export alone.
Recommended action: Price and set COGS against the true blended rate, and investigate why the higher-rate cohort pays more.

SourcePayment processor transactions export

FormulaF-FEE-COHORT v1.0

Suspected anomalyConfidence: Low

$420 (pending confirmation)

Possible duplicate refund

Evidence: Two refunds of equal value posted to the same order within 36 hours. Could be intentional (partial + adjustment) or a duplicate. Flagged for merchant confirmation.
Recommended action: Confirm with your team; if duplicated, request a reversal.

SourceRefunds export

Suspected anomalyConfidence: Medium

18% refund rate on 1 product

Refund concentration on one SKU

Evidence: One product accounts for a disproportionate share of refunds versus the store average, suggesting sizing, quality, or expectation issues.
Recommended action: Review product detail accuracy, sizing guidance, and supplier quality for the affected SKU.

SourceOrders export · order-level refunded amounts

FormulaF-REFUND-RATE v2.0

Data blind spotConfidence: High

27% of SKUs lack cost data

Missing product costs

Evidence: Cost-of-goods values are absent for a quarter of active SKUs, which makes your platform's built-in profit reporting incomplete and potentially misleading.
Recommended action: Populate cost-per-item for all active SKUs so margin reporting becomes trustworthy.

SourceProducts export · cost-per-item field

Data blind spotConfidence: High

Needs the payout summary export

Payout-to-bank reconciliation not yet possible

Evidence: The transactions export lists per-transaction charges and fees, but a bank-verified payout total needs the separate payout summary export from your processor. Until it is provided, payout reconciliation is reported as a blind spot rather than a verified figure.
Recommended action: Add the payout summary export from your processor so deposits can be reconciled to the cent.

SourcePayment processor transactions export (summary not provided)

Missed opportunityConfidence: Medium

$11,500 retail value

Slow-moving inventory tying up cash

Evidence: A cohort of SKUs has not sold in 90+ days while consuming storage and working capital.
Recommended action: Bundle, discount strategically, or liquidate to free cash for high-margin restocks.

SourceInventory export · sales history

Missed opportunityConfidence: Medium

$6,800 (modeled forgone profit)

Profitable product repeatedly out of stock

Evidence: Your highest contribution-margin SKU was out of stock for 34 days during a strong demand window.
Recommended action: Set reorder points and safety stock for top-margin SKUs.

SourceInventory history · contribution model