Last Updated: October 13, 2025
Monthly P&L review. Your CFO slides the report across the table.
Revenue: €620,000
Ad spend: €180,000
New customers: 2,400
Quick math: €180,000 ÷ 2,400 = €75 CAC
CFO asks: "Is €75 per customer good or bad?"
You pause. You know your average order value is €95. Gross margin is 60%. So you're making €57 per order, spending €75 to acquire the customer.
You're losing €18 on every new customer.
"But they'll buy again," you say. "Customer lifetime value is €280."
CFO: "How long until we break even?"
You don't know. You've never calculated payback period.
This is the CAC problem.
Most e-commerce brands know their CAC. Few know if it's profitable. Even fewer know how to optimize it without killing growth.
Let's fix it.
Simple definition: How much you spend to acquire one new customer.
Basic formula:
CAC = Total Marketing Spend ÷ Number of New Customers
Example:
Sounds simple. It's not.
Question 1: What counts as "marketing spend"?
Question 2: What counts as a "new customer"?
Question 3: How do you attribute the customer?
Different answers = different CAC. Your €62.50 might actually be €45 or €95 depending on methodology.
Blended CAC = (Total Marketing Spend) ÷ (Total New Customers)
What to include in marketing spend:
Example:
Why this matters: Most brands only count ad spend (€62.50 CAC) and wonder why they're not profitable. The real cost is €75.
Channel CAC = (Channel Ad Spend) ÷ (New Customers from Channel)
Example:
ChannelAd SpendNew CustomersCACMeta Prospecting€20,000350€57Google Search€15,000280€54TikTok€10,000140€71Meta Retargeting€5,00030€167
Wait, retargeting CAC is €167?
Yes. Because retargeting mostly converts existing site visitors (not new customers). This is why you can't just look at ROAS (return on ad spend)—you need to track new customer acquisition (with proper channel attribution) separately.
Key insight: Different channels have different roles. Prospecting acquires new customers (lower CAC). Retargeting converts existing traffic (higher CAC but higher conversion rate and attribution accuracy).
Incremental CAC = (Channel Ad Spend) ÷ (Incremental New Customers)
What's "incremental"? Customers you wouldn't have acquired WITHOUT the marketing.
Example:
Google Branded Search:
But wait—run an incrementality test:
The insight: 87% of those "new customers" would have found you anyway (organic search, direct). You're paying €15K to acquire 35 incremental customers, not 280.
This is why your CFO is confused about profitability.
Industry benchmarks (2025):
IndustryAverage CACGood CACExcellent CACBeauty & Skincare€45-75€30-45<€30Fashion & Apparel€35-60€25-35<€25Supplements€50-90€35-50<€35Home & Lifestyle€40-70€28-40<€28Jewelry€60-100€40-60<€40
But benchmarks don't tell you if YOU'RE profitable.
What matters is the relationship between CAC and customer lifetime value (LTV).
CAC:LTV Ratio = Customer Lifetime Value ÷ CAC
What it means:
RatioInterpretationAction<1:1Losing money on every customerEmergency—fix immediately1:1 to 2:1Breaking even to slight profitNot sustainable—optimize2:1 to 3:1Decent, but could be betterRoom for improvement3:1 to 5:1Healthy and scalableThis is the target zone>5:1Excellent (or under-investing)Consider scaling spend
Example:
Scenario A: Unprofitable
Scenario B: Barely Profitable
Scenario C: Healthy
Scenario D: Excellent
Target: 3:1 to 5:1 ratio with payback period under 6 months.
CFO asks: "Which channels should we invest in?"
You pull up channel CAC:
ChannelCACLTVCAC:LTVPaybackTikTok Prospecting€71€2954.15:13.2 monthsMeta Prospecting€57€2684.70:12.8 monthsGoogle Shopping€62€2453.95:13.5 monthsGoogle Branded€429€2800.65:1Never (unprofitable)
Obvious decision:
Now you're making budget decisions based on profitability, not vanity metrics.
You can't optimize CAC without knowing LTV. Here's how to calculate it.
LTV = (Average Order Value) × (Average # of Orders) × (Gross Margin %)
Example:
How to find these numbers:
In Shopify:
Limitation: Doesn't account for time value of money or customer retention over time.
LTV = Σ (Revenue per customer in each month) × (Gross margin %)
How it works: Track a cohort of customers acquired in a specific month, measure their purchases over 12-24 months.
Example cohort (January 2024 customers):
MonthCustomersOrdersRevenueRevenue/CustomerMonth 0 (Jan)1,0001,000€95,000€95.00Month 1 (Feb)1,000180€17,100€17.10Month 2 (Mar)1,000140€13,300€13.30Month 3-121,000420€39,900€39.90Total (12 months)1,0001,740€165,300€165.30
LTV calculation:
Why this is more accurate: Accounts for actual retention and purchase behavior over time, not just averages.
Use machine learning to predict future customer value based on early behavior.
Tools: Causality Engine, Lifetimely, Peel, Fairing
What they do: Analyze first purchase behavior (AOV, product, channel, time to purchase) to predict 12-month LTV.
Why it matters: Know which customers are high-value within 30 days, not 12 months later.
Impact: 10% conversion rate improvement = 10% CAC reduction
How:
Example:
Impact: Better targeting = higher conversion rate = lower CAC
How:
Example: Beauty brand switched from broad targeting to lookalike audiences based on customers with €200+ LTV. CAC dropped from €68 → €52 (-24%).
Impact: Better creative = higher CTR = lower CPC = lower CAC
How:
Example: Fashion brand tested UGC video ads vs. professional product shots. UGC had 2.3x higher CTR, 35% lower CPC, 28% lower CAC.
Impact: Dedicated landing pages convert 2-5x better than homepage
How:
Example: Supplement brand created dedicated landing page for "sleep support" campaign. Conversion rate: 1.8% (homepage) → 4.2% (landing page). CAC dropped 57%.
Impact: Convert browsers into leads, nurture via email, reduce CAC by 30-50%
How:
Example:
Impact: Stop paying multiple channels for the same customer
How:
Example: Brand discovered 87% of Google branded search conversions had prior Meta touchpoint. Cut branded search budget 70%, CAC dropped from €75 → €58.
Impact: Higher AOV = more revenue per customer = can afford higher CAC
How:
Example:
Impact: Higher LTV = can afford higher CAC = more budget to acquire customers
How:
Example:
Starting point:
Actions taken:
Month 1:
Month 2:
Month 3:
Final result:
Most brands optimize for ROAS and wonder why they're not profitable.
The brands that win? They optimize for CAC:LTV ratio and payback period.
Your choice.
CAC is how much you spend to acquire one new customer. Formula: Total marketing spend ÷ Number of new customers. Example: €50,000 ad spend ÷ 800 new customers = €62.50 CAC. Include all marketing costs (ads, agency, software, content) for accurate calculation.
Depends on your customer lifetime value (LTV). Target CAC:LTV ratio of 3:1 to 5:1. Example: If LTV is €180, aim for €36-60 CAC. Industry benchmarks: Beauty €30-45, Fashion €25-35, Supplements €35-50. But your profitability matters more than benchmarks.
Simple method: LTV = (Average order value) × (Average # orders) × (Gross margin %). Example: €95 AOV × 2.2 orders × 60% margin = €125.40 LTV. Accurate method: Track cohort revenue over 12 months, multiply by gross margin.
How long it takes to recover your customer acquisition cost. Formula: CAC ÷ (Monthly profit per customer). Example: €75 CAC ÷ €25/month profit = 3 months payback. Target: <6 months. Longer payback = cash flow problems.
8 levers: 1) Improve conversion rate (landing pages, checkout), 2) Better targeting (lookalikes, exclusions), 3) Better creative (UGC, testing), 4) Email capture (nurture leads), 5) Reduce channel overlap, 6) Increase AOV (bundles, upsells), 7) Improve retention (increase LTV), 8) Cut low-incrementality channels.
CAC = cost to acquire a NEW customer. CPA (cost per acquisition) = cost per conversion (includes repeat customers). Example: €50K spend, 1,000 conversions (800 new, 200 repeat) = €50 CPA but €62.50 CAC. Track both, but optimize for CAC.
Common reasons: 1) iOS 14 broke tracking (can't optimize), 2) Ad fatigue (creative needs refresh), 3) Increased competition (CPMs rising), 4) Poor targeting (reaching wrong audience), 5) Low conversion rate (site experience issues), 6) Retargeting exhausted (need more prospecting).
No. 2:1 is barely profitable. Target 3:1 minimum before scaling. At 2:1, focus on: 1) Reducing CAC (conversion rate, creative, targeting), 2) Increasing LTV (retention, AOV, subscriptions). Once you hit 3:1+, then scale aggressively.
Struggling with attribution discrepancies? If you're spending €100K+ per month on ads and can't tell which channels are actually driving sales, you're not alone. Learn how leading Shopify beauty and fashion brands are solving attribution challenges to scale profitably.
Ready to optimize your customer acquisition? Causality Engine tracks CAC, LTV, and payback period by channel—showing you exactly where to invest for profitable growth.
