Benchmarking SaaS metrics can be a bit of a pain. While great public sources exist (Bessemer’s scaling to $100M, Iconiq’s Compass), the numbers tend to be scattered and context dependent. VC benchmarks have selection bias based on the stage and check sizes they invest, operator benchmarks have very high variances and don't represent VC-backed, growth-focused businesses very well.
So we went ahead did the heavy-lifting of combining, contextualizing and triangulating across multiple, high-quality, publicly-available benchmarks to create a representative set for VC-backed SaaS.
Focused on 8 key metrics (to start with)
Split by ARR buckets
Representative of current market trends (we’ve weighted more towards recent numbers)
Clean visualizations to screenshot and share
Intended Use
Operators: See how your business stacks up vs benchmarks across key topline and unit economics metrics
Investors: Evaluate how one or more SaaS companies in your portfolio are doing and what they can improve.
Sources
ICONIQ Compass
Sapphire Ventures SaaS survey
BVP Scaling to 100M
ICONIQ Scaling SaaS report
High Alpha SaaS Benchmarks Report
Openview Partners SaaS Benchmarks Report
Benchmarkit 2025 Benchmarks
BVP Cloud 100 Benchmarks Report
BVP State of the Cloud
A16Z Growth Benchmarks
SaaS Capital 2025 Benchmarks
Benchmarks - ChartMogul
Triangulation Methodology
Different sources use different ARR buckets, vintages, and definitions. We stitched them together with a few simple ground rules:
Recency Bias: Across data sources, we weighted latest numbers higher to reflect today’s market reality.
Consistent Bucketing: ARR ranges don’t always line up across benchmarks, so we re-mapped them into consistent buckets ($1-10M, $10-25M, $25-50M, $50M+) using weighted averages.
Skew-adjusted medians: Across benchmarks, we took a weighted average for medians (based on the N) and adjusted for skew across the interquartile range (effectively, if variance is high a particular dataset, the median gets a lower weight)
Variance-adjusted quartiles: Interquartile ranges were adjusted to capture the variance not just within a dataset but across datasets, i.e. when benchmarks had vastly different values across sources, the interquartile ranges were adjusted to be larger.
Future Plans
We’re just getting started. The plan is to keep the dashboard up-to-date and add more functionality.
Latest Datasets: we will continuously find new public benchmarks and adjust numbers
More Qualifiers: beyond just ARR ranges, we will add more qualifiers to contextualize benchmarks better
GTM: Sales-led vs PLG
Tech: AI-natives vs AI-adoptersValuation metrics: we will bring in private and public valuation benchmarks
We’re working on dashboards for other sectors as well - ConsumerTech & FinTech are next. Stay Tuned!
Benchmarking SaaS metrics can be a bit of a pain. While great public sources exist (Bessemer’s scaling to $100M, Iconiq’s Compass), the numbers tend to be scattered and context dependent. VC benchmarks have selection bias based on the stage and check sizes they invest, operator benchmarks have very high variances and don't represent VC-backed, growth-focused businesses very well.
So we went ahead did the heavy-lifting of combining, contextualizing and triangulating across multiple, high-quality, publicly-available benchmarks to create a representative set for VC-backed SaaS.
Focused on 8 key metrics (to start with)
Split by ARR buckets
Representative of current market trends (we’ve weighted more towards recent numbers)
Clean visualizations to screenshot and share
Intended Use
Operators: See how your business stacks up vs benchmarks across key topline and unit economics metrics
Investors: Evaluate how one or more SaaS companies in your portfolio are doing and what they can improve.
Sources
ICONIQ Compass
Sapphire Ventures SaaS survey
BVP Scaling to 100M
ICONIQ Scaling SaaS report
High Alpha SaaS Benchmarks Report
Openview Partners SaaS Benchmarks Report
Benchmarkit 2025 Benchmarks
BVP Cloud 100 Benchmarks Report
BVP State of the Cloud
A16Z Growth Benchmarks
SaaS Capital 2025 Benchmarks
Benchmarks - ChartMogul
Triangulation Methodology
Different sources use different ARR buckets, vintages, and definitions. We stitched them together with a few simple ground rules:
Recency Bias: Across data sources, we weighted latest numbers higher to reflect today’s market reality.
Consistent Bucketing: ARR ranges don’t always line up across benchmarks, so we re-mapped them into consistent buckets ($1-10M, $10-25M, $25-50M, $50M+) using weighted averages.
Skew-adjusted medians: Across benchmarks, we took a weighted average for medians (based on the N) and adjusted for skew across the interquartile range (effectively, if variance is high a particular dataset, the median gets a lower weight)
Variance-adjusted quartiles: Interquartile ranges were adjusted to capture the variance not just within a dataset but across datasets, i.e. when benchmarks had vastly different values across sources, the interquartile ranges were adjusted to be larger.
Future Plans
We’re just getting started. The plan is to keep the dashboard up-to-date and add more functionality.
Latest Datasets: we will continuously find new public benchmarks and adjust numbers
More Qualifiers: beyond just ARR ranges, we will add more qualifiers to contextualize benchmarks better
GTM: Sales-led vs PLG
Tech: AI-natives vs AI-adoptersValuation metrics: we will bring in private and public valuation benchmarks
We’re working on dashboards for other sectors as well - ConsumerTech & FinTech are next. Stay Tuned!
Benchmarking SaaS metrics can be a bit of a pain. While great public sources exist (Bessemer’s scaling to $100M, Iconiq’s Compass), the numbers tend to be scattered and context dependent. VC benchmarks have selection bias based on the stage and check sizes they invest, operator benchmarks have very high variances and don't represent VC-backed, growth-focused businesses very well.
So we went ahead did the heavy-lifting of combining, contextualizing and triangulating across multiple, high-quality, publicly-available benchmarks to create a representative set for VC-backed SaaS.
Focused on 8 key metrics (to start with)
Split by ARR buckets
Representative of current market trends (we’ve weighted more towards recent numbers)
Clean visualizations to screenshot and share
Intended Use
Operators: See how your business stacks up vs benchmarks across key topline and unit economics metrics
Investors: Evaluate how one or more SaaS companies in your portfolio are doing and what they can improve.
Sources
ICONIQ Compass
Sapphire Ventures SaaS survey
BVP Scaling to 100M
ICONIQ Scaling SaaS report
High Alpha SaaS Benchmarks Report
Openview Partners SaaS Benchmarks Report
Benchmarkit 2025 Benchmarks
BVP Cloud 100 Benchmarks Report
BVP State of the Cloud
A16Z Growth Benchmarks
SaaS Capital 2025 Benchmarks
Benchmarks - ChartMogul
Triangulation Methodology
Different sources use different ARR buckets, vintages, and definitions. We stitched them together with a few simple ground rules:
Recency Bias: Across data sources, we weighted latest numbers higher to reflect today’s market reality.
Consistent Bucketing: ARR ranges don’t always line up across benchmarks, so we re-mapped them into consistent buckets ($1-10M, $10-25M, $25-50M, $50M+) using weighted averages.
Skew-adjusted medians: Across benchmarks, we took a weighted average for medians (based on the N) and adjusted for skew across the interquartile range (effectively, if variance is high a particular dataset, the median gets a lower weight)
Variance-adjusted quartiles: Interquartile ranges were adjusted to capture the variance not just within a dataset but across datasets, i.e. when benchmarks had vastly different values across sources, the interquartile ranges were adjusted to be larger.
Future Plans
We’re just getting started. The plan is to keep the dashboard up-to-date and add more functionality.
Latest Datasets: we will continuously find new public benchmarks and adjust numbers
More Qualifiers: beyond just ARR ranges, we will add more qualifiers to contextualize benchmarks better
GTM: Sales-led vs PLG
Tech: AI-natives vs AI-adoptersValuation metrics: we will bring in private and public valuation benchmarks
We’re working on dashboards for other sectors as well - ConsumerTech & FinTech are next. Stay Tuned!