Maison Loft Co.

The Challenge
Revenue recorded at gross with no separation of platform fees, refunds, or returns
Cost of goods sold never properly configured — inventory purchases mixed with operating expenses
Three sales channels with different payout schedules, all reconciled manually and inconsistently
No visibility into which products or channels were actually driving profit
The PrecisionPenny Solution
Maison Loft Co. partnered with PrecisionPenny to rebuild their books from the ground up and establish a monthly reporting structure that reflected the true economics of a multi-channel e-commerce business. Within the first month, PrecisionPenny:
Completed a full catch-up and clean-up of 8 months of disorganized records
Set up proper COGS tracking with inventory-matched expenses in QuickBooks
Separated revenue, fees, and returns by platform — Shopify, Amazon, and Etsy
Reconciled all payment processor payouts against actual sales figures
Built a monthly P&L showing net margin by channel and product category
Key Outcomes
Multi-Channel Clarity: By separating revenue streams and reconciling platform fees individually, Maison Loft Co. got a true picture of what each channel was actually contributing — not just in revenue but in net profit after every cost.
COGS Accuracy: Proper cost of goods tracking revealed that several high-volume SKUs had margins under 15% after fulfillment — information that directly shaped the next buying cycle.
Amazon Reallocation: Amazon, previously assumed to be the strongest channel, was identified as the least profitable after fees and returns. Ad spend was reallocated to Shopify where margins were 22% higher.
Tax-Ready Books: Year-end financials were delivered to the CPA three weeks ahead of schedule — the first time in the business's history.
Future Action Plan
Introduce product-level margin tracking to evaluate every SKU individually at reorder
Add ad spend as a direct cost of sale per channel to calculate true ROAS monthly
Build a 12-month cash flow forecast based on seasonal sales patterns now visible in the data
