Written by: Aaron Rovner, Founder, Saas Hero | Last updated: August 31, 2026
Key Takeaways
- Paddle calculates CAC by dividing total sales and marketing expenses by new customers acquired, using a fully loaded approach that includes salaries, tools, and program spend.
- The Paddle CAC formula is CAC = Total Sales and Marketing Expenses ÷ Number of New Customers Acquired, with a worked example of $36,000 spent yielding a $36 CAC for 1,000 customers.
- Channel-level CAC segmentation reveals which channels actually work, and Paddle’s cross-domain checkout requires customData or passthrough parameters to maintain accurate attribution.
- Key benchmarks include a 3:1 LTV:CAC ratio and CAC payback periods under 12 months for SMB, 18 months for mid-market, and 24 months for enterprise accounts.
- Building a CAC calculation your board can trust requires connecting ad spend to CRM revenue data, which SaaSHero can help with.
The Paddle CAC Formula, Explained
Paddle’s official CAC formula is: CAC = Total Sales and Marketing Expenses ÷ Number of New Customers Acquired. Paddle’s own resources describe the calculation in two steps: add every expense from your P&L that contributes to winning new business, then divide by the exact count of new customers gained during that same timeframe.
Paddle’s worked example is $36,000 spent in a month divided by 1,000 new customers, yielding a CAC of $36. The key distinction Paddle draws is that this is a fully loaded calculation, which goes beyond ad spend. For SaaS companies with long sales cycles and multiple touchpoints, a fully loaded CAC produces a true picture of acquisition efficiency rather than a flattering one.
The formula itself is simple. The discipline sits in what goes into the numerator and what counts in the denominator.
Which Costs Paddle Puts in Your CAC
Paddle’s guidance is to include every expense from your profit and loss statement that contributes to acquiring new customers. Costs that belong in the numerator include:
- Salaries and commissions for sales and marketing personnel, consistent with the fully loaded CAC methodology that also incorporates payroll taxes and benefits.
- Software and tools such as CRM platforms, email automation, analytics, and attribution software.
- Program spend such as paid advertising across search, social, and display, plus content creation, events, webinars, and agency fees.
- Founder or executive time when leadership is actively involved in selling, in line with Paddle’s fully loaded approach.
Paddle generally excludes the following:
- Customer success costs, which are post-acquisition and belong in retention or expansion metrics, not new logo CAC.
- Free trial signups, because Paddle counts customers when they convert to paid, not when they start a trial.
- Repeat customers and reactivations, since the denominator is net-new paying customers only.
The most common failure is counting only media spend. Excluding salaries, tools, and overhead understates CAC by 40–70% for most teams. A CFO and VP of Sales at the same company can arrive at materially different CAC figures, one using fully loaded acquisition cost including SDR salaries and allocated marketing time, the other using direct sales commissions and program spend only. The gap exists because no one has agreed on what goes in the numerator.
Want to see how this looks with your own numbers? Schedule a working session with SaaSHero to map your P&L into a fully loaded CAC model tied to CRM revenue.
How to Segment CAC by Channel on Paddle
Blended CAC, the total across all channels, works for board reporting but hides which channels actually perform. Paddle supports channel-level CAC segmentation, but only under specific conditions. You must connect its payment data to external analytics tools or use its passthrough/customData parameter to carry channel context across the cross-domain checkout. Paddle’s built-in reporting does not natively attribute customers to acquisition channels.
To see how blended CAC hides channel efficiency, consider this example. $20,000 on paid search acquiring 200 customers yields a channel CAC of $100. $5,000 on content acquiring 100 customers yields a channel CAC of $50. The blended number obscures a 2:1 efficiency gap between the two.
The operational challenge on Paddle is attribution, and that challenge determines whether you can see gaps like this. Paddle’s checkout runs on checkout.paddle.com, which breaks standard cookie-based channel attribution for 100% of Paddle transactions unless the passthrough (customData) parameter is used to carry the session ID across the domain boundary. Without a passthrough handshake, channel-level CAC is a guess.
The fix requires carrying a visitor ID through checkout using customData in Paddle Billing (v2) or passthrough in Paddle Classic. Mixing them up is the most common silent attribution failure. Attribution should fire on transaction.completed, not payment.created, which fires before the charge succeeds, or subscription.created, which misses all subsequent renewals.
The customData set on the first checkout sticks to the subscription for its entire lifetime, so every renewal auto-attributes to the original channel without additional code. Without this plumbing, you have the formula but lack the data to feed it accurate channel-level inputs.
When platform-reported conversions are summed across channels, the total is typically 2–3 times the actual conversion volume recorded in the CRM, due to overlapping attribution windows and view-through attribution. CRM closed-won data should be treated as authoritative. Platform-reported conversion counts are directional at best.
CAC Payback Period and LTV:CAC Benchmarks
CAC alone does not tell you whether acquisition is sustainable. Paddle pairs it with two benchmarks.
CAC Payback Period = CAC ÷ (Monthly Recurring Revenue per Customer × Gross Margin). ProfitWell/Paddle research found a median CAC payback period of 15–18 months for B2B SaaS companies, not 11 months. Bessemer Venture Partners recommends targeting a CAC payback period of under 12 months for SMB-focused cloud companies, under 18 months for mid-market-focused accounts, and under 24 months for enterprise-focused accounts. For bootstrapped founders funding growth from cash flow, a CAC payback period over 18 months is the canonical danger zone where paid acquisition stops being self-funding.
LTV:CAC Ratio = Customer Lifetime Value ÷ CAC. Paddle uses the 3:1 benchmark, where each acquired customer should be worth three times what it cost to earn their business. This benchmark traces back to David Skok’s SaaS Metrics 2.0. Below 2:1 is unsustainable, and below 1:1 means losing money on every customer. SaaS Capital’s 2024 Private SaaS Company Survey places top-quartile performance at 5:1 or higher.
These are the numbers a CFO or board uses to evaluate a channel. If your CAC calculation is understated because attribution is broken, your payback period and LTV:CAC will look better than they are. The board will eventually find out.
Common Mistakes When Calculating CAC with Paddle
Five errors repeatedly distort CAC for Paddle users:
- Counting only ad spend. This mistake understates CAC by the same 40–70% mentioned earlier because fully loaded CAC includes salaries, tools, content, and overhead. Learn more about fully loaded CAC.
- Using leads instead of customers. Counting free trial users instead of paying customers makes CAC appear lower than reality. Paddle counts paying customers, not form fills or trial signups.
- Mixing time periods. For B2B SaaS companies with longer sales cycles, calculating CAC on a single month of data mismatches expenses and customers. The calculation window should match the average sales cycle length.
- Ignoring channel segmentation. Blended numbers hide which half of your acquisition mix is working, and cuts made on a blended figure often hit the wrong channel.
- Not updating CAC regularly. CAC should be calculated monthly for operational monitoring and quarterly for strategic decision-making and investor reporting. Monthly numbers are noisy, and quarterly smoothing catches problems while remaining responsive.
Paddle vs. Stripe: How the Methodologies Differ
Paddle and Stripe both present the same core formula. Stripe’s SaaS metrics guide defines CAC as total sales and marketing costs divided by new customers acquired, with a worked example of $100,000 in spend and 100 customers yielding a $1,000 CAC.
Paddle’s cross-domain checkout creates an attribution gap that Stripe’s on-site checkout does not. Paddle’s methodology therefore emphasizes fully loaded costs and channel segmentation more explicitly, because the data required to do either accurately is harder to capture on Paddle without deliberate engineering. Stripe’s guidance is more focused on payment processing metrics, while Paddle’s is oriented toward unit economics for SaaS businesses selling globally. For a B2B SaaS company, Paddle’s framework is the more comprehensive of the two when the attribution layer underneath it is built correctly.
Step-by-Step Example Using Paddle’s Methodology
To see how the formula, segmentation, payback period, and LTV:CAC ratio work together, consider this scenario. A B2B SaaS company on Paddle with $50,000 in monthly sales and marketing expenses acquires 500 new customers.
Step 1: Calculate blended CAC. $50,000 ÷ 500 = $100 blended CAC.
Step 2: Segment by channel.
- Paid search: $30,000 spend, 200 customers = $150 CAC
- Organic/content: $10,000 spend, 200 customers = $50 CAC
- Referrals/partners: $10,000 spend, 100 customers = $100 CAC
Step 3: Calculate payback period. Assume $50 MRR per customer and 80% gross margin. Payback = $100 ÷ ($50 × 0.80) = 2.5 months. This result indicates a strong payback profile.
Step 4: Calculate LTV:CAC. Assume $1,500 LTV per customer. LTV:CAC = $1,500 ÷ $100 = 15:1. This result is excellent and possibly a signal of under-investment in growth. A ratio well above 5:1, sustained for several quarters, more often signals under-investment in growth than exceptional efficiency.
This example shows why segmentation matters. The blended $100 CAC hides that paid search costs three times what organic costs per customer. Without channel-level data, no informed budget decision is possible.
Frequently Asked Questions
What is the average CAC for SaaS?
CAC varies widely by segment, sales motion, and average contract value. Self-serve SMB products typically see CAC in the $150–$500 range. SMB with inside sales runs $500–$2,500. Mid-market deals land between $1,000 and $8,000, though other benchmarks report narrower ranges such as $1,500–$5,000. Enterprise acquisition commonly runs $10,000–$250,000 or more in CAC, with enterprise accounts ($25K–$100K ACV) at a median of $24,500 and strategic accounts ($100K+ ACV) at a median of $68,000. These ranges reflect fully loaded costs. Companies that count only ad spend will report figures materially lower than their actual acquisition cost.
What is a good LTV:CAC ratio for SaaS?
As mentioned earlier, 3:1 is the widely accepted healthy benchmark. Below 2:1 is unsustainable. Below 1:1 means the company is spending more to acquire customers than those customers are worth. Top-quartile SaaS companies achieve 5:1 or higher, according to SaaS Capital’s 2024 Private SaaS Company Survey. A ratio above 5:1 sustained for several quarters often signals under-investment in growth rather than exceptional efficiency.
Does Paddle include founder salaries in CAC?
Yes, if the founder is actively involved in sales or marketing. Paddle’s fully loaded CAC approach includes all sales and marketing expenses, and while its guide does not explicitly list executive time, the broader industry definition of fully loaded CAC can include executive time spent on acquisition activities. Most private companies exclude this in practice, which understates CAC. The correct approach is to allocate the portion of executive time attributable to winning new business and include it in the numerator alongside sales and marketing salaries.
How often should I recalculate CAC?
Recalculate CAC monthly for operational monitoring and quarterly for strategic decision-making and investor reporting. Monthly numbers are noisy when sales cycles run 60 days or longer, because a single large deal or a delayed close can swing the figure significantly. Quarterly smoothing catches problems while remaining responsive enough to act on. For companies with very long sales cycles, matching the calculation window to the average cycle length produces the most accurate cause-and-effect relationship between spend and customers acquired.
Why does Paddle’s cross-domain checkout break attribution, and how do I fix it?
Paddle’s checkout runs on checkout.paddle.com, a separate domain from your marketing site. First-party cookies are scoped to the origin that set them, and browser settings and features can alter this behavior, such as blocking first-party cookies entirely or partitioning them by top-level site. Any visitor ID or UTM data stored on your domain is therefore invisible to Paddle’s checkout page. Every transaction passes through this domain, meaning 100% of your conversions lose their channel attribution unless you explicitly carry that data through.
The fix is to use the customData field in Paddle Billing or the passthrough field in Paddle Classic to carry a visitor ID through the checkout. Always attribute on the transaction.completed webhook event. Keep the payload flat and small, with a visitor ID plus up to three UTM keys. Once set on the first checkout, the customData sticks to the subscription for its lifetime, so renewals attribute automatically to the original channel.
Your CAC Is Only as Good as Your Attribution
Paddle gives you a clear formula: fully loaded sales and marketing costs divided by new customers. The benchmarks are equally clear. Aim for a 3:1 LTV:CAC ratio and a payback period under 12 months where your model allows.
What Paddle cannot give you is the attribution layer that makes the formula accurate. If your Paddle checkout breaks cookie tracking and you have not built the passthrough handshake, your channel CAC is a guess. Similarly, if your ad platforms optimize toward form fills while your board asks about revenue, your CAC is built on the wrong denominator. Both problems lead to the same outcome: making budget decisions from platform-reported numbers means optimizing based on what each channel claims, not what is actually driving revenue.
This gap is the problem SaaSHero exists to close. SaaSHero connects ad spend to CRM outcomes such as qualified pipeline, lifecycle stage, and closed revenue, so the CAC you report is the CAC your board can trust. The team owns paid media, creative, landing pages, and attribution end to end, and they optimize against CRM data rather than form-fill counts.
Want attribution that makes Paddle’s CAC framework reliable for board-level decisions? Schedule a demo with SaaSHero to see your ad spend tied directly to CRM revenue.