Shopify DTC Analytics

You're not scaling customers.
You're scaling losses.

Contribution LTV runs 30-40% below what Shopify shows — after COGS, fulfillment, and discounts. Most brands find out when the cash stops keeping up with revenue.

Start the conversation No form. One email.

The typical gap

30–40%

lower than your dashboard shows after COGS, fulfillment & discounts

Revenue LTV

3:1

Contribution LTV

1.4:1

After COGS, fulfillment & discounts

31%

Discount churn order 3

62%

Cancel before ship 3

74%

Never placed order 2

Example audit finding

What the real numbers
look like.

Revenue LTV $140

— COGS (48%) — $67

— Fulfillment — $12

— First-order discount — $18

— Transaction fees — $3

Contribution LTV $40

CAC $48

Real profit per customer — $8

This brand was scaling.

Revenue LTV:CAC showed 2.9:1. Dashboard looked healthy. They were reinvesting into acquisition every month.

After COGS, fulfillment, and the first-order discount — every new customer cost $8 more than they returned. Growth was accelerating the loss.

Blended reporting made it invisible.
Cohort analysis made it obvious.

Why this audit

Most brands are scaling
unprofitable customers.

Before the audit

Blended LTV hides which cohorts are unprofitable

CAC payback calculated on revenue, not contribution margin

Discount and full-price customers reported as one number

Scaling spend into channels that destroy unit economics

After the audit

You know exactly which acquisition month is destroying LTV

Real CAC payback per cohort — after all costs

Discount vs full-price cohort split — separate curves

30-day action plan based on your specific data

Stop scaling losing channels

Know which acquisition channels produce profitable cohorts vs which ones look fine in Shopify but destroy contribution margin.

Fix retention before it compounds

Find the exact shipment or order where your cohort drops — before CAC payback extends to 14+ months and the math becomes unfixable.

15 minutes of your time

You export the Shopify order data. I build the model. No API, no integrations, no lengthy onboarding. Report in 5-7 days.

Operator, not just analyst

I ran supplements affiliate at $3.5M in 4 months. I've been on your side of the dashboard. The analysis reflects that.

Real example — supplements brand

Revenue LTV:CAC (dashboard) 3:1

Contribution LTV:CAC (real) 1.4:1

Discount cohort churn, order 3 31%

Full-price cohort churn, order 3 11%

Action taken Stopped discount acquisition for low-LTV channel

All case studies are anonymized. Data reflects real audit findings.

What you walk away with

A working Excel cohort model, a written report identifying specific gaps, and a 30-day action plan ranked by impact. Not a deck. A file you keep and act on.

Case studySupplements · US

Revenue LTV:CAC looked fine.
Contribution didn't.

A supplements brand ran a 20% first-order discount on subscriptions. Revenue LTV:CAC: 3:1. Looked healthy on the dashboard.

After separating cohorts, contribution LTV:CAC on the discount group dropped to 1.4:1 — after COGS, fulfillment, and the discount itself. 31% of discount subscribers churned before order 3. Full-price subscribers at 11%.

Both cohorts were being reported as one blended number.

3:1

Revenue LTV:CAC

1.4:1

Contribution LTV:CAC

31%

Discount churn order 3

Churn rate by order number

Discount cohort vs full-price cohort

Based in

United States

Who runs this

Alex Viktorov

LTV & Retention Analyst · US/UK/EU brands

I ran supplements affiliate in the US market. $3.5M revenue in 4 months. I know what blended LTV looks like when you are scaling fast — and why it hides the problem until it is expensive.

I also know what it costs when the math is wrong. A bank withheld $600,000 in a single freeze. The project ended. You learn differently when the downside is real.

Now I do the cohort analysis most operators skip. Not because they do not care — because Shopify does not show it by default.

The pattern

Shopify shows one number.
The cohorts show three.

Most brands have seen #1. Almost none have looked at #3.

Revenue LTV

What the dashboard reports. Blended across all customers, all acquisition months, all channels. The number founders cite when explaining business health.

Contribution LTV

Revenue LTV minus COGS, fulfillment, discounts, and transaction fees. Typically 30-40% lower. Almost never calculated at the cohort level.

Cohort LTV

Contribution LTV broken out by acquisition month. Where the actual gap lives. This is what most Shopify dashboards do not show by default.

Case studyPet Supplements · UK

62% of subscribers cancelled
before shipment 3.

A pet supplements brand had healthy subscription signup rates. Blended cancel rate looked acceptable in the dashboard.

Broken out by shipment: 62% of first-time subscribers cancelled between shipment 2 and 3. The spike was concentrated in a single acquisition window — invisible in aggregate.

CAC payback extended to 14 months on a contribution basis.

62%

Cancel rate, shipments 2-3

14 mo

CAC payback, contribution

Cumulative cancel rate by shipment

First-time subscribers, pet supplements brand

Case studySkincare · US

First order AOV: $94.
Month-two reorder rate: 22%.

A skincare brand had strong first-order AOV and acceptable blended retention metrics. The dashboard showed healthy numbers.

74% of customers never placed a second order. On a contribution basis — after COGS and acquisition cost — the brand was losing money on every customer who did not reorder.

The cohort that did reorder was profitable. It was 22% of buyers.

$94

First order AOV

22%

Month-two reorder rate

74%

Never placed order 2

Customer retention after first order

Skincare brand — all customers

74%

never
reordered

Never reordered

74%

Reordered at least once

26%

The 26% who reordered were profitable. The 74% who did not were not — after COGS and acquisition cost.

The audit

What the engagement looks like.

Three steps. No API access. 5-7 days from data to report.

STEP 01

You share the data

Shopify order export and subscription data. No API or integrations needed. 15 minutes on your end.

STEP 02

I build the cohort model

Retention tables, repeat purchase curves, contribution LTV by acquisition month and channel. Usually 5-7 days.

STEP 03

You get a working model

Excel cohort file, written report, and 30-day action plan. Not a deck. A file you keep and update.

$1,500–$2,500 depending on data complexity.

Ideal partners

This works for specific brands.

Replenishment categories only. Shopify only. Diagnosis, not execution.
If you already track LTV at contribution level by cohort — you don't need this audit. You need execution.

Good fit

Shopify DTC, $1M–$10M revenue
Supplements, skincare, wellness, pet, functional beverages
Subscription or replenishment model
You suspect retention is a problem but have not measured it at cohort level

Not a fit

Apparel, electronics, furniture, one-time purchase goods
No Shopify or not DTC
Looking for execution and implementation, not a diagnosis

What you get

You'll know exactly
where the money goes.

Which cohorts destroy your margin

Contribution LTV broken out by acquisition month. You see exactly which customers are unprofitable — and by how much — not as a blended average.

Real CAC payback after all costs

Payback period calculated on contribution margin — after COGS, fulfillment, discounts, transaction fees. Not revenue. The number that determines whether growth builds equity or burns cash.

Three specific changes ranked by impact

Not general retention advice. A 30-day action plan based on what your cohort data shows — ranked by financial impact, not effort.

$1,500–$2,500 depending on data complexity. Delivered in 5–7 days.

You're not scaling customers.You're scaling losses.

What the real numberslook like.

Most brands are scalingunprofitable customers.

Revenue LTV:CAC looked fine.Contribution didn't.

Shopify shows one number.The cohorts show three.

62% of subscribers cancelledbefore shipment 3.

First order AOV: $94.Month-two reorder rate: 22%.