ProblemsWe Do Not Know Which Products Make Money › E-commerce & DTC

We Do Not Know Which Products Make Money
in E-commerce & DTC

Every business has a line that everyone assumes is profitable, and it is usually the one being subsidised. This page works through it for e-commerce and DTC brands specifically — including an unedited excerpt from a real analysis of a DTC brand.

The short answer

Every business has a line that everyone assumes is profitable, and it is usually the one being subsidised. For e-commerce and DTC brands, this shows up in a particular place. The numbers that carry the answer are LTV/CAC and contribution margin, and the complication specific to this industry is that retail distribution fixes the customer-acquisition cost but needs working capital the runway cannot fund. The general version of this problem and the one you are actually in have different first moves.

Product-level profit is genuinely hard because most costs are shared, and the usual allocation — by revenue — quietly guarantees the answer. Allocating overhead in proportion to revenue makes high-revenue lines look expensive and low-revenue lines look efficient, which is precisely backwards when the low-revenue line consumes disproportionate attention.

A workable approach allocates only what is genuinely traceable and leaves the rest unallocated. You end up with contribution by line and one honest pool of shared cost, which is far more useful than a fully-absorbed number that nobody trusts.

The result is usually uncomfortable. In most portfolios a minority of lines carries the whole thing, and at least one long-standing line has been losing money for years with everyone assuming otherwise.

How to tell this is actually your problem

These three together are the signature. One on its own usually points somewhere else.

✓ Product profitability is quoted as a company-wide gross margin
✓ Nobody has discontinued anything in years
✓ Two people give different answers about the same product line

The move that usually makes it worse. Fully absorbing overhead into product lines, which produces a precise number built on an arbitrary rule and gets defended because it looks rigorous.

Who this is for — and who it is not

It is for you if you run or finance a DTC brand and product profitability is quoted as a company-wide gross margin. It is the situation where the numbers are available but nobody has put them in an order that produces a decision.

It is not for you if Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.

Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.

What this looks like when the analysis is actually run

Below is an excerpt from a real run of this analysis on a DTC brand. It is a sample profile rather than a customer, and it is unedited engine output — this is the format you get, on your own numbers.

The subject is Northaven Goods, a sample company profile used for testing rather than a customer — $62M revenue, 95 people.

Excerpt from a real Percision run · Quick Market Scan · sample company profile

The move. Turn one-time lifetime-guarantee buyers into recurring 55%-margin members before wholesale consumes runway.

The leak it closes. Reduces paid-media CAC reliance by 8-12% via member referral loop

The assumption it rests on. Pilot cohort of 500 customers achieves ≥35% 12-month repeat-rate — the engine put the probability at 0.7.

What the run committed to
Investment required$180-250K total — $120K platform build (internal dev) + $60-130K pilot marketing and inventory
Expected return23.3× — $42M upside / $1.8M investment; ROI based on actual $72M revenue base
Revenue, year 1$1.8M incremental (8,000 members × $49 × 55% GM × 12 months)
Revenue, year 2$5.4M incremental (18,000 members)
Revenue, year 3$11.2M incremental (25,000 members)

This is one move out of a full analysis. Read a complete report — every page, no email required.

What the engine does with this question

This question routes to Matrix Strategy, one of 29 engagements the platform runs. For e-commerce and DTC brands it works through LTV/CAC, contribution margin, paid media as % of revenue and repeat purchase rate, then produces the sequence rather than a list of options — which move first, what it funds, and the observation that would say the sequence is wrong.

You watch the analysis get built before paying anything. Read a complete report here if you would rather see the depth first.

Questions people ask about this

Do I need activity-based costing?

Almost never for the decision at hand. Traceable costs plus an unallocated pool gets you the ranking, and the ranking is what you act on. Full ABC is a project that frequently outlives the decision that prompted it.

What about products that support others?

Say so explicitly and price the support. A loss-making line that genuinely pulls profitable revenue is a marketing cost with a name, which is a fine thing to be — as long as somebody decided it.

How often should this be redone?

Annually, and after any significant mix change. The ranking is more stable than the numbers, so the exercise gets cheaper each time.

Is this different in e-commerce & dtc than in other industries?

Materially, yes. Retail distribution fixes the customer-acquisition cost but needs working capital the runway cannot fund — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are LTV/CAC, contribution margin, paid media as % of revenue, and an answer built on industry-general benchmarks will usually point at the wrong one first.

What data do I need before this analysis is worth running for a DTC brand?

Less than most people expect. Your last twelve months of revenue and cost split the way you already split it, plus whatever you hold on LTV/CAC and contribution margin. The analysis is explicit about what it is assuming where your data stops, which is more useful than waiting for numbers you may never have.

When is Percision the wrong tool?

Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.

Does Percision replace a lawyer, tax advisor, auditor, or AI implementation team?

Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.

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