ProblemsWe Have Too Many Products › E-commerce & DTC

We Have Too Many Products
in E-commerce & DTC

Proliferation costs are real, mostly invisible, and land on the products that were paying for everything. 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

Proliferation costs are real, mostly invisible, and land on the products that were paying for everything. 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 lines accumulate because each addition is individually justifiable and nothing is ever removed. The cost is not in any one of them; it is in the complexity they collectively impose — inventory, changeovers, support knowledge, sales attention, forecasting error.

That cost is borne disproportionately by the profitable core, because that is where the capacity being fragmented lives. Which is why rationalisation often increases total profit even when the removed lines were nominally contributing.

The analysis worth doing ranks lines by contribution against the constraint they consume, then asks which of the tail exists for a reason — a strategic customer, a channel requirement — and which exists because nobody has looked.

How to tell this is actually your problem

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

✓ A minority of lines produces the large majority of revenue
✓ Nothing has been discontinued in several years
✓ Operations complexity is rising faster than volume

The move that usually makes it worse. Cutting the tail by revenue rank alone, which removes lines that were cheap to carry and keeps ones that quietly consume the constraint.

Who this is for — and who it is not

It is for you if you run or finance a DTC brand and a minority of lines produces the large majority of revenue. 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

How do I decide what to discontinue?

Contribution per unit of the binding constraint, then a check on strategic dependencies. Revenue rank alone gets this wrong in both directions.

Will customers leave if I discontinue products?

Some will, and the analysis should price that before the decision rather than after. Usually the revenue at risk is smaller than the complexity cost being removed, but it should be a finding rather than an assumption.

How much complexity cost is normal?

It is rarely tracked, which is why it grows. A workable proxy is the trend in operating cost per unit of volume; when that rises while volume rises, complexity is the usual explanation.

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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