The ICONIQ Enterprise Five

YoY ARR Growth

YoY ARR Growth = (EOP ARR – Prior Year EOP ARR) / Prior Year EOP ARR

Year-over-year ARR growth reveals how quickly and consistently a company is growing and has historically been one of the top two metrics most correlated with software valuations across both the public and private markets.

Looking at top quartile growth rates over time, our data shows year-over-year growth declining over the last several years; however, ARR growth is now stabilizing across the software sector, with green shoots in mid-stage companies ($50-$100M). Meanwhile, we have also seen the entry of new AI-native companies in the last year that are growing exponentially, redefining the growth curve and time to key milestone ARR figures.

Based on our analysis, the observed overall decline in growth has primarily been driven by weakness in bookings with gross new logo ARR and gross expansion ARR dropping from peak levels in the high-growth environment of 2021 and now starting to level off this year. Meanwhile, churn has remained relatively stable over the last several years.

While top quartile growth rates have stabilized in aggregate in 2025, we are seeing subsets of companies out-perform historical benchmarks for best-in-class growth. Top quartile benchmarks for growth in the $1-$10M ARR stage have actually increased since we ran this analysis last year, from 485% year-over-year in our 2024 scorecard to 515% year-over-year in our 2025 scorecard. We predict that this upward trend will persist as AI-native companies continue to scale rapidly.¹

Net Dollar Retention

Net Dollar Retention = 1+ (expansion ARR - gross churn ARR) / average (BOP ARR + EOP ARR)

Net dollar retention (NDR) signals the efficiency and predictability of a company’s revenue generation by measuring its ability to retain and expand existing customers. NDR can be used to measure everything from product-market fit to customer satisfaction, making it, in our view, one of the most important gauges of business health and one of the strongest indicators of long-term success for B2B software companies. In an AI-transformed environment, product stickiness becomes even more important to evaluate. AI products are often adopted through trials or pilots, and we have observed a divergence between durable and “experimental” revenue. Experimental revenue (generally tied to free trials or paid pilots) is common in product-led growth or AI-native companies and can spike NDR in the short-term due to a higher risk of churn. Net dollar retention can help ground high-growth AI and software companies in reality and discern how durable revenue truly is. With new logo acquisition harder to come by, companies have doubled down on expansion through customer marketing, community, and realigned GTM incentives. Ongoing improvements in go-to-market efforts (find our latest go-to-market research here)² seem to be paying off as it appears expansion and churn have stabilized, allowing NDR to settle in the ~110-120% range in 2025.

Another major factor influencing NDR is the industry-wide shift in pricing strategies. As software companies prioritize delivering measurable outcomes for customers, we expect pricing based on value or usage, rather than pricing per seat, to become the norm. However, there is risk of volatility in customer expansion and churn when shifting away from traditional SaaS pricing, particularly in fluctuating macro environments.

We have observed that many software companies (38%³) have adopted hybrid models, blending elements from traditional subscription pricing with outcome-oriented pricing (check out our latest AI research here). These hybrid pricing models offer a soft “landing” spot, giving customers pricing flexibility tied to usage or success, while still providing companies with a predictable revenue base. However, as both AI-native and AI-enabled companies are in their early stages of developing and commercializing AI products, companies are still trying to figure out their pricing strategies. According to our latest research, 37% of companies building AI products reported they are considering changing their pricing model in the next year³. We will continue to keep a close eye on pricing models and their impact on retention in the coming year.¹

Rule of 40

Rule of 40 = YoY ARR Growth + FCF Margin

While the first two Enterprise Five metrics focus on top-line growth and health, Rule of 40 measures both growth and free cash flow (FCF) margin (a measure of working capital and profitability) in tandem. The combination of growth and profitability has become increasingly important in software markets over the last few years, with Rule of 40’s correlation to forward revenue multiples for public companies exceeding that of revenue growth alone for each of the last eight quarters, suggesting efficient growth is imperative.

The general rule of thumb for Rule of 40 is that a software company’s combined year-over-year growth and FCF margin should meet or exceed 40%. As exceptional year-over-year growth inflates Rule of 40 performance for early-stage companies, we typically only begin to place real weight against Rule of 40 for companies with at least $25M ARR.

As growth declined over the last several years, software companies showcased a deliberate shift towards efficiency over time, reversing the norm of “growth at all costs” in the pre-2020 era. These improvements in efficiency in 2025 have led to a gradual improvement in Rule of 40.

Looking ahead, we expect AI-native companies with high growth rates to outperform on Rule of 40, despite lower FCF margins. Additionally, we anticipate companies that adopt AI will have the potential to position themselves closer to Rule of 60 as they unlock material efficiency gains. However, AI adoption is likely to require significant upfront investments across data infrastructure, change management, upskilling, and the hiring of specialized roles which means that near-term benefits and efficiency gains may be marginal for many companies, but we predict that the long-term impact of AI on efficiency will be outsized.¹

Net Magic Number

Net Magic Number = Current Q Net New ARR / Prior Q S&M OpEx

The “magic” of this metric lies in its ability to measure revenue generation against sales and marketing spend while accounting for the lag in a typical sales cycle, signaling the efficiency of a company’s go-to-market motion (an important driver of overall efficiency). While there are multiple flavors of magic number, we believe net magic number (NMN) to be the most comprehensive, as it takes churn into account by calculating the ratio of a company’s net new ARR for every dollar spent on sales and marketing.

NMN is expected to decline as companies scale due to a relative decline in net new ARR growth, competitive dynamics, and shrinking headroom. However, top quartile companies have historically been able to maintain a net magic number above 1.0x - where revenue generation exceeds sales and marketing spend, regardless of scale.

Following years of decline, net magic number has begun to stabilize in 2025, although top quartile figures have not returned to pre-2020 norms, underscoring the headwinds software companies continue to face in driving net new ARR growth.

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According to our latest GTM research, companies that are embracing AI into their workflows are seeing early signs of improvement in sales productivity, notably in funnel conversion rates and sales efficiency. Though the up-front costs of investing in these technologies may be driving GTM efficiency down temporarily, we expect significant sales productivity and efficiency gains for AI-forward GTM organizations in the future.

However, net magic number alone may not tell the whole story in today’s age of AI. While many AI-native companies may be demonstrating a strong net magic number, these figures can be misleading without additional context. AI-native businesses often operate with compressed margins due to high infrastructure costs, so while they may seem to be running efficient GTM orgs, the actual contribution margin from ARR may be lower. To get a clear view of GTM efficiency, it may be beneficial to look at gross-margin adjusted net magic number to properly benchmark GTM organizational health.¹

ARR per FTE

ARR per FTE = EOP ARR / EOP FTEs

ARR per full-time employee (FTE) simply divides a company’s annual recurring revenue by number of employees to measure headcount productivity. As most of the typical software company’s operating costs are people-related, we have found headcount productivity to be a robust measure of overall growth and efficiency - especially when considered in tandem with total operational expenses per FTE.

In aggregate, ARR per FTE is the only Enterprise Five metric that has seen significant and consistent improvement over the last three years. While headcount productivity temporarily declined in 2022 as the market turned, companies adjusted to the market throughout 2023 and the technology ecosystem experienced a significant wave of workforce restructuring, performance management, and lay-offs, resulting in more productive, performance-driven cultures. Since then, rather than a short-term boost in productivity from headcount reductions (resulting from a smaller denominator), we’ve seen an increase in headcount productivity that has been sustained through 2025.

While headcount productivity has improved, there has also been an increase in OpEx per FTE over time. However, ARR per FTE has outpaced OpEx per FTE in 2025, resulting in an increase in overall headcount productivity ratio (ARR per FTE / OpEx per FTE). This increase could be the result of strategic headcount decisions (e.g., offshoring in low-cost geographies, organizational rightsizing, etc.) and/or AI implementation, helping create sustainable efficiency results for organizations.

Final Thoughts

2025 marks not only a stabilization in key growth and efficiency benchmarks but also may indicate a fundamental shift in how software companies achieve them. The playbook is evolving – and fast. AI-native and AI-forward companies are not just outperforming metrics like GTM efficiency and growth at scale; they are redefining what operational excellence looks like. In this new environment, hitting the benchmarks of the ICONIQ Enterprise Five still matters but understanding how you achieve them matters more.

As AI reshapes operating models, go-to-market motions, and pricing structures, the context behind each number is more important than ever. Metrics like Net Dollar Retention may mask short-term spikes from experimental revenue. Net Magic Number may appear strong but hide compressed gross margins. And ARR per FTE may rise on the back of smaller, leaner teams, but only some of that productivity gain will be sustainable.

In this era, leaders must pair quantitative performance with qualitative insight. The companies best positioned for long-term success will be those that stay grounded in fundamentals – durable growth, efficient operations, and strategic clarity – while adapting with agility to the changing terrain AI is creating.

We hope this offers both a compass and context: a benchmark for performance, and a lens for understanding it in today’s transformed software landscape.