ROAS is the curse of e-commerce

The real core of an e-commerce business isn't ROAS.

It's lifetime value (LTV).

As long as you keep reading the business off the immediate return of a campaign, you're using the wrong metric.

ROAS only tells you how much attributed revenue you generated against your ad spend. That's it. LTV, on the other hand, tells you how much economic value a customer really produces over time. And that's the difference between someone who buys orders and someone who builds a business.

An e-commerce business doesn't win when it gets a profitable order on a single click. It wins when it acquires customers who pay back the customer acquisition cost (CAC), come back, buy again, raise overall margin and let you reinvest more aggressively.

That's why ROAS on its own can even become dangerous. It pushes you to optimize the short term, while the real economic engine of an e-commerce business is the ability to monetize the customer over time.

An example?

Store A has a ROAS of 4 on the first purchase. Looks great in the dashboard. But that customer buys once, comes in on a discount, has a low repeat rate and compressed margin.

Store B has a ROAS of 1.8, or even 1.4, on the first order. Plenty of people would say straight away that it doesn't add up. But that customer comes in on an aggressive offer, maybe close to break-even or slightly negative, and then buys again two, three, four times over the following months. Average order value (AOV) grows, the second purchase costs zero in average acquisition, payback improves and cumulative margin explodes.

Which of the two has the better business? The one with the prettier short-term ROAS, or the one building more value per customer over the medium term?

The real competitive advantage of an e-commerce business isn't having clean campaigns in the dashboard. It's being able to afford to buy customers more aggressively than everyone else, because you know their value doesn't run out with the first order.

And that's why you can have a low ROAS, or in some cases even a negative one on the first order, and still have a far healthier business than someone defending a high ROAS with no economic depth.

ROAS looks at the snapshot of a transaction. LTV looks at the economics of the relationship.

A serious e-commerce business doesn't live on isolated transactions. It lives on the ability to turn the first purchase into a repeatable economic machine.

So don't just ask yourself whether the campaign closed positive today. Ask yourself what that customer is worth at 30, 60, 90, 180 days, how long it takes to earn back CAC, which products drive the second order, which cohorts actually turn profitable and whether you're acquiring customers or just orders.

Weak e-commerce businesses run paid to defend ROAS. Strong e-commerce businesses run customer acquisition to maximize LTV.

And that's the difference that changes everything.

If you only look at ROAS, you protect the campaign. If you look at LTV, you start building the business.

Store A vs Store B: the comparison in numbers

The abstract comparison is easy to grasp. The concrete one is what changes decisions.

Store A looks like the winner in every paid dashboard. Store B looks like the loser. But at 12 months, Store B has customers with 2.5x higher LTV, a repeat-buyer base that lowers the real average acquisition cost, and the ability to scale ad budget without compressing margins.

Store A, on the other hand, is forced to defend its ROAS because it doesn't have the economic depth to lower it. Every time it scales, ROAS drops and profit collapses.

I've worked on real cases with this dynamic. In the case of a premium food brand, monthly revenue went from €22,000 to €119,000 — not by optimizing ROAS, but by restructuring the offer, killing across-the-board discounts and building cohorts of high-LTV customers. Blended ROAS was 6.2x — but that was a consequence of the system, not the goal.

How to calculate the LTV of your e-commerce business

You don't need a sophisticated tool to start. You need to be honest about the numbers you already have.

Base formula:

LTV = AOV × average number of orders per customer in the first 12 months

A practical example. AOV €68. Shopify tells you that 32% of the customers acquired in January buy again within 6 months, with an average of 2.1 additional orders. Your 12-month LTV on that cohort is:

LTV = €68 × (1 + 0.32 × 2.1) = €68 × 1.67 = €113.5

Your average CAC is €40 (with a ROAS of 1.7x on an AOV of €68). The LTV:CAC ratio is 2.8x — in the acceptable zone for a mid-market brand, with room for improvement.

CAC payback: if gross margin on the first order is 35% of €68 = €23.8, you earn back the €40 CAC in about 1.7 orders — meaning 2-3 months for the customers who buy again, never for the ones who don't come back.

This is the number that tells you whether you're building or burning.

You see a similar comparison in the beachwear fashion e-commerce case as well: 31% of revenue came from returning customers, with second-purchase AOV up 38%. It wasn't an aggressive retargeting campaign — it was a system built to grow the value of the right customers over time.

When a low ROAS is a healthy signal (and when it isn't)

Not all low ROAS is the same. There are cases where it's a deliberate strategic choice and cases where it's simply a campaign that doesn't work.

Healthy low ROAS:

• Repeat purchase rate within 90 days is above 25% on recent cohorts
• Projected 12-month LTV:CAC ratio is above 3x
• CAC payback doesn't go beyond 4 months
• You have cohort data confirming the pattern — it's not a hypothesis, it's a trend verified across several acquisition cycles
• The entry offer is designed to attract the high-LTV customer profile, not to do volume with deep discounts

Problematic low ROAS:

• You have no cohort data. You're betting without evidence, and the low ROAS is just a badly optimized campaign
• Repeat purchase rate is below 15% at 90 days. Customers come in, buy once and disappear
• Payback goes past 6 months on a brand with no retention history. You're burning cash without the financial depth to sustain it
• First acquisition only happens with 30-40% discounts. You're buying orders, not customers

The question isn't "is ROAS high or low?" but "do I know why ROAS is what it is, and do I know what happens after the first order?"

The metrics that actually matter

If ROAS is the wrong metric, these are the right ones. Not all of them from day one — pick the three you can measure today and start there.

Repeat purchase rate at 30/60/90 days — by acquisition cohort, not aggregated. The aggregate number hides everything. You want to know whether the customers acquired in January with campaign X behave differently from the ones acquired in March with campaign Y.

LTV:CAC ratio — minimum target 3x for mid-market brands, 5x+ for premium brands with high margins. Below 2x you're destroying value with every acquisition.

CAC payback period — how many months it takes to recover the acquisition cost from gross margin. Above 5 months for a brand with no financial backing is a structural problem.

Repeat purchase rate — percentage of customers who place more than one order within 12 months. Industry benchmark: 25-35% for consumer e-commerce, 40%+ for subscription or consumables.

AOV by cohort over time — high-LTV customers tend to increase AOV after the first purchase. If AOV stays flat or drops, there's a problem with the offer or with post-purchase communication.

How to find them: Shopify Analytics for repeat purchase rate and AOV by cohort. Klaviyo for post-purchase behavior. GA4 with cohort analysis for return patterns. Triple Whale, Northbeam or Polar Analytics if you have the budget for an attribution tool that unifies everything.

If you have none of this data, the first step isn't optimizing campaigns. It's building the ability to measure.

Because without cohort data you're flying with your eyes shut — and ROAS is the only light you can see, even if it's taking you in the wrong direction.

Read also

More notes on ROAS, offer and margin in e-commerce:

• Why ROAS is a dangerous metric
• Low ROAS is an offer problem
• Selling at full price without discounts
• Brand or ad budget dependency

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If you want to understand where your acquisition model breaks and how to restructure your Meta campaigns starting from the real LTV of your e-commerce, book a strategy session.