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2026-08-23 · 6 min read · Selvra OS Team

LTV:CAC Ratio for Ecommerce: Formula and Benchmarks

LTV:CAC compares what a customer is worth to what it costs to acquire them. The formula, a worked example, and what counts as a healthy ratio.

LTV:CAC ratio compares customer lifetime value to customer acquisition cost — how much a customer is worth over time against how much it costs to acquire them. It's one of the highest-level health checks available for whether growth spend is actually building a sustainable business.

The formulas

LTV = Average order value × Purchase frequency × Customer lifespan
CAC = (Ad spend + Sales/marketing expenses) ÷ New customers acquired
LTV:CAC = LTV ÷ CAC

LTV estimates the total revenue a typical customer generates over their relationship with your store. CAC captures what it costs, in total marketing spend, to acquire one new customer in a given period — not just ad spend, but the full cost of acquisition if you want an accurate number.

Worked example

A Shopify store with a $60 average order value, where customers purchase 3 times per year on average and stay active for 2 years:

LTV = $60 × 3 × 2 = $360

That same store spent $5,000 on marketing last month and acquired 50 new customers:

CAC = $5,000 ÷ 50 = $100
LTV:CAC = $360 ÷ $100 = 3.6:1

A 3.6:1 ratio sits comfortably within the healthy range for ecommerce, discussed below — this store is generating meaningfully more value per customer than it costs to acquire them.

What's a good LTV:CAC ratio for ecommerce?

According to Shopify's own published guidance, a good LTV to CAC ratio sits around 3:1, with ecommerce brands typically ranging between 2:1 and 4:1. A ratio at or below 2:1 suggests you're close to break-even on acquisition once lifetime value is factored in — every new customer is barely paying back what it cost to acquire them, let alone generating a meaningful return.

Counter-intuitively, a very high ratio isn't automatically better. Shopify's guidance flags ratios above roughly 8:1 as a signal of underinvestment in marketing rather than efficiency — if customers are worth far more than it costs to acquire them, there's likely room to spend more and grow faster while remaining well within a healthy ratio.

What actually moves the ratio

Both sides of the ratio are levers, not fixed facts about your business. On the LTV side, the three inputs — average order value, purchase frequency, and customer lifespan — respond to different things: AOV moves with pricing, bundling, and upsell tactics; purchase frequency moves with retention efforts like email flows and loyalty programs; lifespan moves with overall product satisfaction and how replaceable your category is by competitors. A store trying to improve its ratio by cutting CAC alone, without also working retention or AOV, is only pulling on one of three available levers.

On the CAC side, the ratio is sensitive to which channels and campaigns are actually acquiring customers, not just the blended account-wide average. A store with an overall CAC of $80 might have one channel acquiring customers at $50 and another at $150 — the blended number hides that spread entirely, and reallocating budget toward the cheaper, equally effective channel improves the ratio without cutting total spend at all.

The mistake most ecommerce LTV calculations make

The formula above uses revenue — average order value — not profit. That's a reasonable starting point, but it silently assumes every dollar of revenue converts to the same value, which isn't true once cost of goods sold enters the picture. A store with a 60% margin and one with a 20% margin can post an identical revenue-based LTV and have wildly different actual customer value once COGS is subtracted.

A more accurate version replaces average order value with average order profit (order value minus COGS), producing a profit-based LTV that reflects what a customer is actually worth to the business, not just what they generate in top-line sales. This mirrors the same revenue-vs-profit distinction we cover throughout this blog for ad spend — see what is POAS for the ad-spend-specific version, and Shopify COGS setup for where to find the margin data needed to make this calculation accurate.

How this connects to your Google Ads spend specifically

CAC and cost-per-acquisition are closely related ideas, and the same margin-blind trap that affects break-even ROAS affects CAC: a channel or campaign with a low, efficient-looking CAC can still be a poor use of budget if it's acquiring customers who buy low-margin products and don't come back. Conversely, a higher CAC channel can be worth the spend if it reliably acquires high-LTV customers. Treating CAC as a number to minimise in isolation, without checking it against actual customer value, leads to the same kind of misallocation covered in our complete guide to Google Ads for Shopify.

Our CLV/LTV calculator estimates customer lifetime value from your own average order value, purchase frequency, and retention — useful for getting a working LTV number before deciding what CAC you can actually afford to pay.

FAQ

What is a good LTV to CAC ratio for ecommerce?

A commonly cited benchmark is 3:1, with ecommerce brands typically ranging between 2:1 and 4:1. A ratio at or below 2:1 suggests you're close to break-even on customer acquisition once lifetime value is accounted for; a ratio above roughly 8:1 can actually signal underinvestment in marketing rather than efficiency, since it implies room to acquire more customers profitably than you currently are. Where your store should sit within that range depends on your margins, repeat purchase rate, and how much of your growth you want to fund from acquisition spend versus organic and retention.

How do I calculate customer acquisition cost (CAC) for a Shopify store?

CAC = (total ad spend + sales and marketing expenses) ÷ number of new customers acquired in that period. The most common mistake is scoping this too narrowly — including only ad spend and excluding agency fees, tools, or other marketing costs — which understates true CAC and makes the ratio look better than it actually is. It's worth deciding on a consistent scope up front and applying it the same way every time you calculate the number, rather than adjusting what counts period to period.

Related reading

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