Hello and welcome back.

One of the consistent patterns in SaaS is that growth rarely stalls because of one dramatic problem. More often, it slows because of a collection of small operational failures that compound. Teams often don’t notice them until the numbers flatten out. The Cleverbridge Friction Report is interesting because it quantifies a set of issues that most teams feel anecdotally but rarely measure.

Over the last decade, SaaS moved from high-touch sales motions to product-led motions and now toward ecommerce-style revenue. More software is purchased with a credit card, inside the product, or through a lightweight “Buy Now” flow. The promise is obvious. Lower friction. Higher velocity. Fewer humans in the loop.

The reality is more complicated. Once you move revenue into these channels, you inherit the same complexity that ecommerce companies have dealt with for years. Local payments. Tax rules. Language expectations. Checkout conversions. Payment failures. Subscription logic. Support routing. It becomes a system. And when that system isn’t maintained, it creates friction that quietly removes revenue from the top line and churn from the bottom.

Here are the patterns that stood out.

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1. Going global is easy on a strategy slide and hard in practice

Every SaaS company eventually reaches a point where incremental US growth slows and international markets start to look appealing. The report shows that 83 percent of companies plan to expand internationally in the next year. Only 4 percent operate in more than 100 countries, and only a little more than half feel prepared to scale globally.

The missing piece is operational readiness. Global expansion looks like a distribution problem, but it behaves like an infrastructure problem. Payment preferences change by region. Tax requirements rarely match. Buyers expect currency familiarity and local language. People underestimate how strong that expectation is. Ninety six percent of buyers expect local currency. Forty three percent stop if checkout is not in their language.

This has measurable effects.

Take a PLG funnel with 10,000 monthly international visitors, a 3 percent pricing-to-checkout rate, and a 40 percent checkout completion rate.

Baseline revenue: 10,000 × 0.03 × 0.40 = 120 purchases

If missing local currency reduces conversion by only 20 percent: 40 percent × 0.80 = 32 percent checkout completion

New conversions: 10,000 × 0.03 × 0.32 = 96 purchases

A simple localization miss removes 20 percent of international revenue before product quality is ever evaluated. Add missing regional payment rails like Pix, OXXO, Alipay, or PayPal-preferring markets, and these drops multiply rather than stack.

Most teams focus on go to market strategy, hiring country managers, and adapting pricing. The real bottlenecks tend to show up later. A company enters a market, demand looks promising, but the conversion rate ends up lower than expected for reasons that feel disconnected from product. The friction lives in the revenue system, not the product itself.

This is a predictable pattern. Companies underestimate the operational surface area associated with “global.” The report’s data illustrates the gap clearly.

2. Sellers are optimizing the wrong parts of the purchase flow

Another recurring theme is the mismatch between what buyers actually care about and what sellers believe they care about. Many teams assume speed and security are the primary factors. The report shows that buyers consistently rank clear pricing and terms above both.

Nearly half of buyers cite unexpected taxes or fees as the reason they abandon a purchase. That number is unusually high, but it tracks with what teams often find when they finally run a detailed funnel analysis. Hidden fees work like small breaches of trust. They don’t generate complaints. They just reduce conversion quietly.

This reflects a simple utility model:

Late VAT reveals increase “uncertainty,” which reduces utility even if the price does not change.

Example

Price shown: 50 per month

Price at checkout with VAT: 59 per month

The nine dollar difference is small. The uncertainty penalty is large. That is why conversion drops sharply.

Sellers, on the other hand, tend to focus on reducing steps in the flow. Buyers do not rank this as highly. They care more about understanding what they are paying for and what will happen next. That pattern repeats in renewal flows. Sellers believe they are transparent. Buyers report confusion around pricing changes and renewal dates.

This is one of the subtle challenges of SaaS. Teams have strong product analytics, but far fewer have high quality analytics on pricing and checkout. Decisions end up centered on what feels intuitive rather than what the data suggests.

3. Cart abandonment has become a core revenue variable for SaaS

As more SaaS companies adopt PLG or ecommerce driven motions, abandonment rates matter more. Nearly half of companies in the report say they lose at least a quarter of potential orders during the purchase process. For a ten million dollar business, that translates into several million dollars of preventable loss.

Here is what the math looks like.

Assume

1 million site visits

2 percent start checkout = 20,000

27 percent abandonment = 5,400 lost purchases

300 average order value

Lost revenue: 5,400 × 300 = 1.62 million per month ≈ 19.4 million per year

If 30 percent of these failures are due to payment method gaps: 1.62M × 0.30 = 486,000 monthly revenue upside ≈ 5.83 million yearly upside

This is not a UX problem. This is a compounding revenue problem caused by missing ownership. No one inside the company “owns” checkout the way a PM owns onboarding.

The companies that perform best test the purchasing experience regularly. Most companies do not. They test it only when something breaks. This creates a long tail of small failures that persist for months or years without detection. The effect is cumulative. By the time leadership notices conversion softness, the underlying issues have already compounded.

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4. The post purchase experience influences retention more than most teams expect

Retention is rarely driven solely by product quality. The surrounding experience matters as well. Billing clarity. Renewal consistency. Support responsiveness. The report shows that ninety one percent of sellers believe they handle this well. Buyers report the opposite.

Difficulty canceling, unclear renewal timing, slow support, and surprise charges all contribute to churn that never shows up as a product problem. Many cancellations get attributed to “lack of fit” or “budget issues.” The true cause is often frustration with the billing or support process.

Involuntary churn is still a major driver of lost revenue. Failed cards and expired cards remove paying customers quietly. Less than half of companies use automated recovery systems. This is surprising given the direct impact on revenue.

Involuntary churn also has measurable impact.

100,000 paying customers

2.5 percent involuntary churn monthly

Automated recovery improves this by 50 percent

Saves

100,000 × 0.025 = 2,500 involuntary churn events

2,500 × 0.50 = 1,250 recovered customers

At 300 ACV, that is 375,000 recovered monthly ≈ 4.5 million annually

The companies that manage this layer well tend to treat billing and renewals as product responsibilities. They build clear explanations, predictable flows, and strong support loops. Companies that treat billing as an administrative function see higher churn.

5. The underlying revenue stack determines how quickly a company can scale

A final observation is the relationship between infrastructure and confidence. Companies with integrated revenue systems are more than twice as confident in scaling globally. Fragmented stacks reduce confidence because they require manual workarounds and coordination across multiple teams.

Most companies start with a modular stack because it is fast to implement. Over time those choices create integration debt. Tax systems, payment processors, subscription tools, and localization layers accumulate. The system works, but only because people inside the company hold it together.

Fragmentation also reduces iteration speed.

Integrated stack: One pricing or tax logic change = 5 engineering hours

Fragmented stack: Touch 5 to 6 systems

Total = 25 to 40 hours per change

If a company runs 25 experiments annually:

Integrated = 125 hours

Fragmented = 750 hours

Delta = 625 hours

At 150 dollars per engineering hour, that is 93,750 dollars of pure operational tax, before considering lost experiment velocity.

This creates drag. Launching in new countries takes longer. Investigating conversion issues takes longer. Reconciling payments takes longer. More engineering cycles go into maintaining the system rather than shipping product. The teams that shift to more integrated approaches usually do so because the operational load becomes unsustainable.

This mirrors patterns in other parts of SaaS. Infrastructure that works at one scale becomes a bottleneck at the next. The revenue system is now reaching that point across many companies.

The opportunity

The Friction Report is useful because it highlights something that is easy to overlook. As SaaS shifts further toward self serve purchasing and global reach, the revenue layer itself has become a growth system. It influences acquisition, conversion, retention, and expansion. Yet it is rarely treated with the same discipline as the product.

The companies that scale well tend to identify this early. They treat checkout, payments, pricing, and renewals as part of the customer experience. They invest in infrastructure before problems accumulate. They measure the entire funnel from first click to renewal, not only the usage metrics inside the product.

Nothing in the data is surprising. The value comes from seeing how consistent these patterns are. Most companies lose revenue not because the product is weak but because the system around the product introduces friction no one is accountable for.

P.P.S. If you know someone on a product, growth, or finance team who would find this useful, feel free to forward it. And if this was forwarded to you, you can subscribe here for more grounded analysis on how tech companies actually grow.