Shopify DTC Analytics

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

Contribution LTV typically runs 30-40% below what Shopify shows, after COGS, fulfillment, and discounts. Most brands find out when 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
30–40%
Contribution LTV gap
5–7 days
Data export to report
$1,500
Starting price
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 where retention drops - before CAC payback stretches past 14 months and the numbers stop working.
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 built and ran ecommerce brands before doing this. I've sat with the same Shopify dashboard and the same blind spots. The models I build are the ones I needed back then.
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 on what's off and by how much, 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
Alex Viktorov
Working with
US · UK · EU brands
Who runs this
Alex Viktorov
LTV & Retention Analyst · US/UK/EU brands

Before this, I built and ran ecommerce brands. Supplements, affiliate, DTC in the US market. At one point we were doing $3.5M in four months and the Shopify dashboard looked healthy the whole way through.

A bank froze $600,000 in one day. The project shut down. After that I spent a long time building the cohort models that should have been there from the start. Turned out the real numbers looked nothing like what the dashboard was showing.

That's what I do now for other brands. Not as someone who read about it - as someone who ran the numbers too late once and knows what that costs.

The pattern

Shopify shows one number.
The cohorts show three.

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

01
Revenue LTV
What the dashboard reports. Blended across all customers, all acquisition months, all channels. The number founders cite when explaining business health.
02
Contribution LTV
Revenue LTV minus COGS, fulfillment, discounts, and transaction fees. Typically 30-40% lower. Almost never calculated at the cohort level.
03
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. Blended retention numbers looked fine on the dashboard.

74% of customers never placed a second order. 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. · Your data is never shared with third parties. NDA available on request.
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.

01
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.
02
Real CAC payback after all costs
Payback period calculated on contribution margin, after COGS, fulfillment, discounts, and transaction fees. Not revenue. The number that tells you whether growth builds equity or burns cash.
03
Three specific changes ranked by impact
Not general retention advice. A 30-day action plan based on your cohort data, ranked by financial impact.
$1,500–$2,500 depending on data complexity. Delivered in 5–7 days.
FAQ

Common questions.

What data do I need to share?
A Shopify order export (.csv) and subscription history if you use ReCharge, Bold, or Stay.ai. No API access, no integrations. Takes about 15 minutes on your end.
Is my order data safe?
Your data is never shared with third parties. Files are deleted after the report is delivered. NDA available on request before you share anything.
I use ReCharge / Bold / Stay.ai - does that change anything?
No. The cohort model is built from Shopify order data, not subscription platform data. Any standard order export works.
I'm not on Shopify - can you still help?
The model is built for Shopify. If you're on another platform with exportable order-level data, reach out and I'll confirm if it's workable.
I already track LTV - do I still need this?
If you're already tracking contribution LTV at cohort level by acquisition month - you don't need this audit. Most brands who reach out are working from blended revenue LTV shown in Shopify.
Get in touch

If retention is a gap,
let's look at the data.

No discovery call required. Fill the form or write directly. One message is enough to start.

Email alex@ltvaudit.com
LinkedIn linkedin.com/in/auditltv
Send a message
I'll respond within 24 hours.
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