SaaS Conversion Benchmarks 2026: Trial, Freemium, FinTech

If your trial converts at 5% and that feels like failure, you may be reading the wrong row of the benchmark. If it converts at 22% and that feels like success, the same is true.

The median B2B software product converts 8% of free signups to paid within six months (ChartMogul, February 2026). A trial without a card converts at 4% to 6% when it is good and 10% to 15% when it is great. A trial that asks for a card up front converts at 25% to 35%, and 50% to 60% at the top.

Most founders I talk to compare themselves with the wrong row of that table. Below is the full set, with sources, and the conversion gap calculator to turn your row into a revenue figure.

Trial-to-paid benchmarks by model

ChartMogul’s Conversion Report surveyed 200 B2B software companies in January 2026. “Good” is the median. “Great” is the 75th percentile. The window is six months from signup.

Entry model	Good	Great	Paying customers per 1,000 site visitors
Freemium	3–5%	8–12%	about 5.0
Freemium, ungated	7–9%	8–12%	about 5.6
Free trial, no card	4–6%	10–15%	about 3.6
Reverse trial	4–6%	8–12%	not reported
Free trial, card required	25–35%	50–60%	about 10.5

The last column is the one boards should look at. A card-required trial gets half the signups, so its conversion rate overstates the advantage. Per visitor, it still produces nearly three times the paying customers of a no-card trial.

By segment, the same report puts B2B at 6% to 10% good and 15% to 20% great. AI-native and AI-hybrid products sit at 6% to 8% and 15% to 20%.

Two more facts from the same survey: 62% of trials last 14 days, and only 20% ask for a card.

The wrong-row mistake

A founder with a no-card trial converting at 5% reads “30%” somewhere and concludes the product is broken.

It is not broken. It is in the good band for its model.

A founder with a card-required trial at 22% reads “8% median” and concludes the product is healthy.

It is below the good band for its model by 3 points or more.

The benchmark is not a number. It is a row. Pick the row first.

Activation benchmarks: read the definition first

Activation numbers disagree because nobody defines activation the same way.

Source	Sample	Definition	Figure
Lenny’s Newsletter, October 2022	500+ products	Milestone chosen by each company	SaaS median 30%
Userpilot, 2024	62 B2B companies	Milestone set in each company’s dashboard	Median 37%
Amplitude, November 2025	2,600+ companies	Time-bound, all new users	Top 10% of products activate about 12% by day 7

The first two let each company choose an easy milestone. The third holds every product to the same clock. Do not compare a number from one column with a target from another.

Userpilot’s industry cut is worth a look, with care: AI and ML products led at 54.8%, healthcare sat at 23.8%, and FinTech and insurance at 5%. The samples per industry are small.

FinTech onboarding: three numbers that don’t measure the same thing

68% of European consumers had abandoned a financial onboarding at some point (Signicat, The Battle to Onboard, 2022, 7,600 people in 14 markets). That is the latest edition.

38% of UK customers abandoned an account opening, against the 2% businesses expected (FullCircl, reported October 2024). Average onboarding took 35 minutes.

70% of financial institutions lost clients to slow onboarding in the past year, with average client abandonment of 10%, and UK corporate banks taking more than six weeks (Fenergo, reported October 2025, 600 firms).

The first is a share of people who ever quit. The third is an average rate inside institutions. Quote each one with its own definition, or a sharp investor will do it for you.

For B2B FinTech, the stronger evidence is about time, not steps. Weeks to onboard and clients lost to delay are the numbers to measure first.

AI-native products: high activation, low retention

AI products activate easily and leave easily.

ChartMogul’s retention study of about 3,500 companies (December 2025) puts AI-native gross revenue retention at 40% and net revenue retention at 48%. B2B SaaS net revenue retention sits at a median of 82%.

Price changes the picture. AI-native products above $250 a month retain 70% gross and 85% net. Below $50 a month: 23% and 32%.

A first output is cheap to reach. A habit is not. If your activation event for an AI product is “first prompt sent”, your activation rate is measuring curiosity.

What AI analytics will and won’t do for you

Analytics vendors now ship agents that watch funnels and session recordings and flag where people drop. Amplitude launched a set of them in February 2026.

That saves hours. It does not choose your benchmark row. An agent will tell you 40% of trials stall at the integration step. It will not tell you whether 4% trial-to-paid is a problem for a no-card trial with a $3,000 contract.

That decision is still yours, and it is the one that sets the budget.

Turn your row into a number

Annual gap = (target rate − current rate) × monthly volume × value per unit × 12

Illustrative inputs:

1,500 no-card trials a month

4% trial-to-paid today

6% target, the top of the good band

$2,400 annual contract value

(6% − 4%) × 1,500 × $2,400 × 12 = $864,000 a year

Assume a fix closes 30% to 50% of that:

$259,200 to $432,000 a year

Every input above is illustrative. The benchmark is the only real number in it, and it came from your row.

Is your benchmark for a card-required trial or a no-card trial?

Let’s run your real numbers. Try the conversion gap calculator, then book a discovery call at Spirixx.com.

Sources

B2B SaaS and FinTech Onboarding Conversion Benchmarks for 2026