Unit Economics — October 20266 min read

You’re Paying ₹1,400 to Acquire a Customer Worth ₹800. And Your Dashboard Looks Green.

Here’s a story I hear more than I should.

D2C brand. 18 months old. Revenue growing 30% month-on-month.

The dashboard looks green but CAC of ₹1,400 exceeds LTV of ₹800

The founder is proud, rightly so. It’s not easy to build that kind of growth.

Then we run the numbers.

True new customer CAC

₹1,400

Return-adjusted, prospecting spend only

12-month LTV

₹800

From cohort data, margin-adjusted

LTV : CAC

0.57x

−₹600 on every new customer

The brand is spending ₹1,400 to acquire a customer who will contribute ₹800 in gross profit over 12 months.

Every new customer costs them ₹600 more than they’ll ever contribute. Revenue grows. Cash disappears. The business is structurally loss-making, and has been for months.

No one told them. Because no one was measuring the right things.

How This Happens

It’s not carelessness. It’s what happens when you measure the wrong CAC and the wrong LTV.

The CAC problem

How most brands calculate CAC

Total marketing spend ÷ Total orders

This blends new and returning customers. Returning customers convert at a fraction of the cost of new ones: they already know you, they’re already warm.

When you blend them together, your CAC looks lower than it is.

Take it further: “total orders” includes returns. Customers who returned their product were never acquired. But they’re in the denominator.

True new customer CAC

Prospecting spend only ÷ (Net new first-time buyers × (1 − return rate))

In practice, this number is typically 50–100% higher than what brands report as their CPA.

The LTV problem

How most brands calculate LTV

AOV × Purchase Frequency × Gross Margin × Lifespan

Three problems:

Purchase frequency is usually measured on the full customer base (including highly engaged loyalists who inflate the average)
Gross Margin, not effective margin (ignores shipping, returns, payment fees)
Lifespan is estimated, often optimistically

LTV method	Result
Standard formula	₹1,800
Cohort data (observed purchase behaviour, 12 months)	₹800

The brand in our story: the formula was off by 2.25x.

Stop estimating, measure the cohort: observed LTV versus projected LTV

The Calculation That Reveals the Truth

Pull your cohort data from Shopify.

Specifically: take every customer who made their first purchase exactly 12 months ago. Calculate their total gross margin contribution since then (all orders × effective margin %).

That number is your 12-month observed LTV.

Not projected. Not modelled. Observed.

Compare it to your true new customer CAC.

LTV < CAC

Model doesn’t work

Your business model doesn’t work at current scale. Revenue growth is accelerating the problem, not solving it.

Below 2 : 1

Technically positive

LTV is above true CAC but your payback period may be creating a working capital problem.

Above 3 : 1

Healthy

You have healthy unit economics. Scale aggressively.

What the Dashboard Shows Instead

Green arrows.

The standard performance report

Revenue: Up
ROAS: 3.8x, above category benchmark
CPA: ₹620, looks reasonable
Orders: Growing

Nothing in standard performance reporting shows that the LTV:CAC ratio is 0.57x.

Because the standard performance reporting doesn’t calculate LTV. It doesn’t calculate true new customer CAC. It doesn’t separate prospecting from retargeting. It doesn’t adjust for returns.

The dashboard is built to show campaign performance. Not business health. And those are different things.

The Fix: Three Numbers You Need to Know

1
True New Customer CAC
Prospecting spend ÷ return-adjusted new first-time buyers
Calculate monthly. Track the trend. If it’s rising, either your prospecting is becoming less efficient or your new customer return rate is climbing.
2
Observed 12-Month LTV (Margin-Adjusted)
Pull from Shopify cohort data. Calculate at 3, 6, and 12 months. Use effective margin (gross margin minus shipping, returns, payment fees) not gross margin.
3
LTV:CAC Ratio and Payback Period
LTV ÷ True New Customer CAC = sustainability ratio (target above 3:1).
True New Customer CAC ÷ Monthly Gross Profit per Customer = payback period (target below 6 months for most D2C categories).

These three numbers together tell you whether the business model works. Nothing else does.

LTV:CAC moving from 0.57x towards 1.8x: from loss-making to viable

What Happened to the Brand

We found the problem. That’s the good news.

We restructured their campaigns, separating prospecting from retargeting, removing high-return campaigns, focusing prospecting spend on the audience segments that were generating the highest 90-day repeat purchase rates.

Over 90 days:

Metric	Before	After 90 days
True new customer CAC	₹1,400	₹890
90-day repeat purchase rate	12%	21%
12-month LTV	₹800	Tracking toward ₹1,600 (projected)
LTV : CAC	0.57x	Approaching 1.8x

LTV:CAC ratio went from 0.57x to approaching 1.8x, still below the 3:1 target but no longer structurally loss-making.

Revenue growth slowed slightly. The business became structurally viable.

That’s the trade. And it’s always worth making.

The Question to Ask Right Now

1
Take your true new customer CAC
Prospecting spend ÷ return-adjusted new buyers.
2
Take your 12-month observed LTV from cohort data
Not the formula, the actual numbers from 12 months ago.
3
Divide LTV by CAC.

Above 3

You have a scalable business. Go.

The economics support growth.

Below 2

You have a business model problem.

No amount of campaign optimisation will fix it. Fix the economics first.

Revenue doesn’t lie. But revenue without LTV:CAC context is just an incomplete sentence.

Frequently Asked Questions

What is true new customer CAC?

Prospecting spend only ÷ (net new first-time buyers × (1 − return rate)). It excludes returning customers and customers who returned the product. In practice it is typically 50–100% higher than the CPA most brands report.

Why is the standard LTV formula often wrong?

AOV × Purchase Frequency × Gross Margin × Lifespan usually measures frequency on the full customer base (inflated by loyalists), uses gross margin instead of effective margin (ignoring shipping, returns and payment fees), and estimates lifespan optimistically. In the example the formula said ₹1,800 while cohort data showed ₹800.

How do I calculate observed 12-month LTV?

Take every customer who made their first purchase exactly 12 months ago and calculate their total gross margin contribution since then: all orders × effective margin %. That is observed, not projected or modelled.

What is a healthy LTV:CAC ratio for a D2C brand?

Above 3:1 means healthy unit economics. Between 1:1 and 2:1 you're technically positive but payback may create a working capital problem. Below 1:1 the business model doesn't work at current scale.

How can a brand fix an LTV:CAC ratio below 1?

Separate prospecting from retargeting, remove high-return campaigns and focus prospecting spend on segments with the highest 90-day repeat purchase rates. In this case true CAC fell from ₹1,400 to ₹890 and 90-day repeat rate rose from 12% to 21% within 90 days.