Scaling prospecting spend was losing money on every sale.
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DTC · Beauty & personal care

Scaling prospecting spend was losing money on every sale.

This marketing & margin audit priced a loss on two prospecting campaigns at its readout, 6 days from kickoff; the after results review a year later read $134k a year of improved contribution on them, in a DTC / Ecommerce business.

$8M to $20M annual revenue Beauty & personal care Focus: Paid social mix
+$134k
margin improvement / yr
+16pts
contribution margin swing
6 days
to findings
Contribution margin on the two top campaigns
2023 window
−7%
→
2024 window
+9%

The business

This was a direct to consumer beauty and personal care brand. Its finance lead framed the brief in one line: revenue is growing, but cash is not keeping up. The question was whether the two prospecting campaigns the brand was preparing to scale, Prospecting A and B, still made money after refunds, product cost, fulfillment and payment fees.

What triggered the audit

The finance lead commissioned the audit to rebuild contribution per order on Prospecting A and B before any budget increase, loading in the shipping, returns and payment costs that gross ROAS left out. The campaigns were judged against a platform ROAS target of 2.0; the audit asked what each order earned after those costs.

What the audit found

Rebuilt order by order, the picture inverted. The two prospecting campaigns the brand was preparing to scale were buying revenue below break even once shipping, returns and payment fees were charged against each order. Gross ROAS looked healthy because it stopped measuring at the sale; it never followed the order through fulfillment or the high return rate on color cosmetics. On average, the spend on those two campaigns was losing margin: in the six month before window the loss was $28,735. The brief had named platform ROAS as the metric the finance lead trusted least; the campaigns were judged against a target of 2.0 and showed 2.49.

◉ How we produced this finding

The paid social mix finding was produced by a cost loading reconciliation: every store order assigned to the two campaigns, followed through refunds, product cost, fulfillment, payment fees and return handling to its contribution, then compared with the platform’s own credit. What you’re reading isn’t an opinion. It is an evidenced read: every figure traces to the working paper.

Data sources: Daily media spend by campaign, joined to the order and return records, with payment fees, fulfillment charges and product cost applied from the client’s rate cards and cost sheet, and reconciled to the prepared cohort P&L.

Key frameworks: Cost loading reconciliation, platform credit versus store sales, a mature cohort comparison with a 35 day lag, annualization and a retained demand sensitivity.

Human validation gate: Every read is rerun against the client’s own data and reviewed before it ships. No automated output leaves the building unreviewed.

Read from
Ad platform daily spend Order and return records Payment rate card Fulfillment rate card Prepared cohort P&L

The margin improvement / yr was compared like for like over two matched six month windows, reconciled to a cohort P&L built from the order, return, payment, fulfillment and cost records. Client identity redacted to protect their commercial position.

WORKING PAPER ████████ Beauty & personal care
Both windows Redacted
CampaignContribution margin
Retargeting
+12%
Google Shopping
+8%
Prospecting camp. A & B
−7%
margin improvement / yr +$134,240
Annualized: twice the six month improvement on the two campaigns, an annual run rate.
Working paper: the rows are the before window margins, from the client’s order and return records, with payment fees, fulfillment and product cost applied from its rate cards and cost sheet, campaign names redacted and figures scaled down by one factor for anonymity, then the six month totals rounded; margins are campaign averages, not every order. The total is the annualized improvement on Prospecting A and B across both windows, twice the six month difference.
What the audit proposed
✓

Rebuild both campaigns around contribution margin measured after shipping, returns and payment fees, so success is defined by profit per order rather than gross ROAS.

✓

Cut or rework the audience and creative combinations that converted below break even on average, while protecting the pockets that paid back.

✓

Install a margin after returns guardrail in the media plan, so no campaign scales past the point at which each extra order starts losing money.

✓

Give finance and marketing one shared view of contribution after returns, closing the gap between the ad dashboard and the P&L.

The result

$134k a year of improved contribution, read a year after the audit, an annual figure equal to 23× the $5,950 Audit + Sprint fee. It is read on the two campaigns, over matched windows.

From kickoff to the readout: 6 days.

Portrait photograph of Victoria Miller
Lead auditor:
Victoria Miller
Senior Auditor · MarginFix · 10+ years of auditing experience
✓Anonymized to protect the client · senior reviewed findings · Audit completed February 2024, contracted through Cristian Bragau's practice before the MarginFix name existed · Published in the MarginFix library · Last reviewed

What the client said

DTC / ECOMMERCE

$134k a year, read a year after a 6 day audit

Contribution margin on the two top campaigns: −7% → +9%

“Revenue grew and cash didn't. Victoria rebuilt margin per order after shipping, returns and payment fees, and our two biggest prospecting campaigns were losing money on every sale. We stopped scaling them.”

Founder & CEO · DTC · Beauty & personal care
Client approvedUnder NDA6 days to findings
Portrait photograph of Victoria MillerVictoria MillerLead auditor on this audit
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The full Strategic Audit behind this case, anonymized: read the sample report.