B2B SaaS paid ads benchmarks
On Google Ads, the median B2B SaaS account pays $8.50 to $14.00 for a non-brand click and $800 to $2,500 for a sales-qualified lead (SQL). On LinkedIn Ads, a click costs $8 to $25 and an SQL $800 to $8,000. Both ranges move several times over with vertical and contract size, so the right benchmark is the row that matches the company, not the headline.
A Google Ads SQL costs a median $800 to $2,500. A LinkedIn SQL costs $800 to $8,000, by contract size.
Cost per SQL. It correlated with pipeline at 0.71, against 0.09 for click-through rate.
Averages across verticals. A cybersecurity SQL costs about five times a developer tools SQL.
Find the row for the right vertical and contract size before comparing any account number.
What are the paid ads benchmarks for B2B SaaS?
The table puts the two main channels side by side. The rows come from different publications with different methods, so they show scale and are not a controlled comparison.
| Metric | Google Ads | LinkedIn Ads |
|---|---|---|
| Cost per click | $8.50 to $14.00 median, non-brand search | $8 to $25 by vertical |
| Click-through rate | 2.8% to 3.5% median, non-brand search | About 0.4% to 0.65% on single-image ads, all industries, directional |
| Cost per lead | $180 to $350 median | About $80 to $200, all industries, directional |
| Cost per SQL | $800 to $2,500 median | $800 to $8,000 by contract value |
| Average wasted spend | 34.0% across 104 accounts | 32.0% across 56 accounts |
The Google Ads rows are from SaaS Google Ads Benchmarks 2026 and the 2026 Google Ads waste audit. The LinkedIn click and SQL rows are the ranges given in the 2026 LinkedIn audit report. The two rows marked directional are from LinkedIn Ads Benchmarks 2026, which its publisher describes as synthesized ranges and not a single dataset. That source adds that B2B SaaS sits at the higher end.
The channel pages give the context behind each column: Google Ads and LinkedIn Ads.
How do Google Ads benchmarks differ by vertical?
Widely. The same publication lists eight verticals, and cost per SQL runs from $650 to $3,500 across them.
| Vertical | Cost per click | Click-through rate | Conversion rate | Cost per lead | Cost per SQL |
|---|---|---|---|---|---|
| Developer tools | $7.50 | 4.1% | 4.8% | $130 | $650 |
| Project management | $9.00 | 3.8% | 4.2% | $170 | $900 |
| HR Tech | $11.50 | 3.2% | 3.5% | $280 | $1,400 |
| ERP | $12.00 | 2.8% | 2.8% | $290 | $1,600 |
| MarTech and Sales Tech | $13.00 | 3.0% | 3.0% | $310 | $1,800 |
| Healthcare | $14.50 | 2.6% | 2.4% | $380 | $2,200 |
| FinTech | $16.00 | 2.4% | 2.2% | $420 | $2,800 |
| Cybersecurity | $18.00 | 2.1% | 1.8% | $550 | $3,500 |
Clicks get more expensive down the table, and conversion rates fall in all but one step. A cybersecurity account with a $3,000 SQL is near its vertical's figure. A developer tools account at the same price is far from its own. The full set, with top and bottom quarter ranges, is in B2B SaaS Google Ads benchmarks 2026.
What should a qualified lead cost at each contract size?
More as the contract grows. SaaS Google Ads Benchmarks 2026 gives a target cost per SQL for four tiers of annual contract value.
| Annual contract value | Target cost per SQL | CAC payback | Typical monthly spend |
|---|---|---|---|
| $5K to $15K | $400 to $1,000 | 6 to 9 months | $10K to $30K |
| $15K to $50K | $1,000 to $3,000 | 9 to 12 months | $25K to $75K |
| $50K to $150K | $3,000 to $8,000 | 12 to 18 months | $50K to $150K |
| $150K and up | $8,000 to $20,000 | 18 to 24 months | $75K to $250K |
CAC payback is the time a customer takes to pay back the cost of acquiring them. The table explains why the same $2,000 SQL is a bargain for one company and a loss for another. How these tiers turn into a budget is on the budget and channel mix page.
What are normal funnel conversion rates?
They depend on the channel the lead came from. First Page Sage publishes stage-by-stage rates for B2B SaaS, last updated on June 11, 2025 and drawn from more than 50 clients.
| Stage | PPC | SEO | |
|---|---|---|---|
| Visitor to lead | 0.7% | 2.2% | 2.1% |
| Lead to marketing-qualified lead (MQL) | 36% | 38% | 41% |
| MQL to SQL | 26% | 30% | 51% |
| SQL to opportunity | 38% | 41% | 49% |
| Opportunity to close | 35% | 39% | 36% |
A second source gives a lower figure for one of these rows. SaaS Google Ads Benchmarks 2026 puts the median MQL to SQL rate at 13% to 18%, with the top quarter at 20% to 30%. The two publishers define their stages separately, so the gap is not a contradiction and the figures should not be averaged.
One audit figure belongs beside them. In the 2026 Google Ads waste audit of 104 accounts, 78% of form fills never became an SQL.
Which benchmark predicts pipeline?
Cost per SQL. The Paid Ads Pipeline Disconnect in B2B SaaS studied 1,412 ad variants across 96 accounts and ranked five metrics by how closely each tracked the pipeline an ad produced.
| Metric | Correlation with pipeline |
|---|---|
| Click-through rate | 0.09 |
| Cost per lead | 0.23 |
| Landing page conversion rate | 0.31 |
| ICP score of the lead | 0.66 |
| Cost per SQL | 0.71 |
ICP stands for ideal customer profile. The three metrics an ad platform shows by default sit at the top of the table with the weakest link to pipeline. The two that need CRM data sit at the bottom with the strongest. The study is covered in does CTR predict pipeline in B2B SaaS ads.
How much do B2B SaaS companies spend on marketing?
A median of 8% of annual recurring revenue. SaaS Capital published the figure on June 10, 2026, from a survey of more than 1,000 private B2B SaaS companies.
The same survey puts research and development at 22%, sales at 15% and customer support and success at 9%. It reports that equity-backed companies spend "100% more on marketing" than bootstrapped ones.
The survey treats marketing as one line and does not break out paid media. No study with a stated sample was found that does, so any single percentage quoted for the paid share should be treated as a guess.
What are the limits of these benchmarks?
Four limits apply, and each changes how a number should be used.
- Most are agency data. The Google Ads and LinkedIn figures come from accounts their publisher had access to. That is a convenience sample, not a random one.
- Some carry no per-row sample. The Google Ads benchmark tables state an overall base of more than $60M in managed spend across more than 300 accounts, and nothing for each vertical.
- Publishers define stages differently. An MQL or an SQL in one source is not the same event in another.
- A benchmark is a range to compare against. It is not a target every account should hit.
Frequently asked questions
What is a good click-through rate for B2B SaaS Google Ads?
The published 2026 median for non-brand search is 2.8% to 3.5%, and the top quarter of accounts reach 4.0% to 6.5%. Click-through rate is a weak guide to results. In a 2026 study it correlated with pipeline at 0.09, so it should not decide which ad wins.
What is a good landing page conversion rate for B2B SaaS?
The published 2026 median for B2B SaaS Google Ads traffic is 2.5% to 4.0%, with the top quarter at 5.0% to 8.0% and the bottom quarter at 0.8% to 2.0%. Developer tools average 4.8% and cybersecurity 1.8% in the same source.
What is a good cost per lead for B2B SaaS?
On Google Ads the published 2026 median is $180 to $350, and it runs from $130 in developer tools to $550 in cybersecurity. A low cost per lead is not proof of a good campaign. It correlated with pipeline at only 0.23 in a 2026 study.
Can Google Ads and LinkedIn Ads benchmarks be compared directly?
Only for rough scale. The figures come from different publications, samples and methods. A LinkedIn click and a search click also mean different things: one reaches a chosen role who is not looking, the other a person who typed a query. Cost per SQL is the fairest shared unit.
Are there benchmarks for Meta, Microsoft or ChatGPT ads?
None with a stated sample for B2B SaaS were found, so this site gives no figures for them. OpenAI publishes no prices for ChatGPT ads at all. For those channels the only dependable benchmark is a company's own cost per SQL on its main channels.
Why do benchmarks from different sources disagree?
Because they measure different accounts in different ways. One source may count every form fill as a lead and another only work emails. Samples differ in company size, country and vertical. Use one source for one comparison, and check how it defines each stage.
Figures on this page come from published studies and platform documentation. Where the numbers come from
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