Marketing Suite

Free Trial Conversion Rate Calculator

How many trial users become paying customers — and why the benchmark depends on your trial model far more than on your product.

Trial to paid rate

(paying customers ÷ trials started) × 100

Trial conversion verdict (opt-in model)

15 % 20 % 25 %
< 15 % (Low) 15–25 % (Solid) > 25 % (Strong)

Trials started, not signups: what the denominator decides

This rate measures what share of trial users become paying customers once the trial ends. In any product with a free trial it is the conversion number that matters, because it reads on two things at once: whether the product demonstrates real value inside the trial window, and whether onboarding gets people there fast enough. And it lives or dies on the denominator. Count trials actually started — people who used the product — and the figure means something. Count every registration, including the accounts that never opened anything, and you are measuring your signup form.

One division, and both figures from the same cohort

Trial to paid rate (%) = paying customers ÷ trials started × 100

Worked example: 500 trials, 100 conversions

A SaaS product records 500 started trials in a month, of which 100 take out a paid subscription when the trial expires:

Trials started500
Paying customers100
Trial to paid = (100 ÷ 500) × 100 = 20.0 %

Your trial model sets the benchmark, not your product

These three zones are rough orientation — and they describe an opt-in trial. Which model you run moves the whole scale:

Low< 15 %
Solid15–25 %
Strong> 25 %

Opt-in trials ask for no card, attract plenty of unqualified testers, and therefore sit at the lower end — 15–25 % already counts as solid. Opt-out trials take the card up front and start billing unless the user cancels, which puts them structurally higher, often 40–60 %. That is a difference in mechanics, not in product quality, so a rate is only comparable within the same model. What tells you the most is neither number in isolation but the direction your own rate moves over time.

Four levers, and the first one outweighs the rest

  • Time to value in the first days: the sooner a user reaches a genuinely useful result, the more likely they convert. Point onboarding at the one action that proves the product works, and treat everything else as optional.
  • Opt-in against opt-out: taking the card up front lifts conversion substantially and cuts the number of trial starts. Going without it does the reverse. Which trade is right depends on your audience and sales cycle, not on which number you would rather report.
  • Focus beats a feature tour: activation emails, in-app guidance and one clear first step outperform a complete walkthrough. A trial user who registers but never activates converts essentially never.
  • Test the trial length: shorter creates urgency, longer gives complex products room to demonstrate value. The right length is product-specific — test it rather than copying someone else's.

Background and sources

The widely used targets for trial conversion — the 25 %-plus mark for opt-in B2B SaaS among them — trace back to the much-cited benchmarks from Sixteen Ventures (Lincoln Murphy) on free trial conversion. They vary substantially by trial model, audience and price point, and are orientation rather than goals.

Frequently asked questions

What is the trial to paid conversion rate?
It is the share of trial users who become paying customers once the trial ends. Formula: paying customers ÷ trials started × 100. Example: 100 paying customers out of 500 trials is 20.0 %.
How do you calculate free trial conversion rate?
Divide paying customers by trials started and multiply by 100. Both figures have to come from the same cohort and the same period, otherwise the number compares two different groups of people.
What is a good trial conversion rate?
It depends heavily on the trial model. As rough orientation for opt-in trials: under 15 % is low, 15–25 % is solid, above 25 % is strong. Opt-out trials that take a card up front convert far higher — often 40–60 % — because billing starts automatically.
Opt-in or opt-out trial: which converts better?
Opt-out converts better and always will, because it asks for the card at the start and bills unless the user cancels. It also produces fewer trial starts, since the card is a barrier. Opt-in draws more users at a lower rate. The two are only comparable within the same model, never across.