Should Your Free Trial Be 7, 14 Or 30 Days?

Should my free trial be 7, 14 or 30 days?

Fourteen, unless you have a specific reason to differ, and the reason matters more than the number. ChartMogul's SaaS Conversion Report found that the most common trial length is 14 days, used by 62% of products, followed by 7 days and 30 days at 14% each. So the default is well established.

But defaults are not answers. The honest version of this decision starts with how long your product takes to show someone something useful, and ends with a length that fits that. Picking 14 because everyone picks 14 is how you end up with a trial that expires before the value lands.

What follows is the data that exists, the data that does not, and the way I would actually make the call.

What does the data actually say about trial length?

Less than you would hope. ChartMogul's report, produced with ProductLed, analysed conversion data from 200 B2B software products, so it tells you what companies do and how well they convert overall. What I have not found anywhere, in its published figures or elsewhere, is a clean comparison of conversion rate by trial length.

That absence is itself informative. If a 30-day trial reliably beat a 14-day trial, somebody would have published that chart by now. What the report does give you is the distribution above, which says the market has converged on two weeks without proving two weeks is optimal.

So treat 14 days as a convention rather than a finding. Conventions are useful because buyers recognise them, and that is a real advantage. It is just not the same as evidence that the length itself does the work.

The wider context is that trials dominate this stage of the funnel. The report found that 57% of products have a free trial as their primary landing point for new customers, more than twice the rate of freemium at 26%, and that among SaaS products specifically the figure is 61%.

Why is trial length the wrong first question?

Because the variation between products dwarfs the variation between lengths. ChartMogul reports a median free-to-paid conversion rate of 8% across all products, while also noting that very few products actually sit at 8%. The median is a landmark, not a description of anyone.

The spread is the real story. The report found a 10x conversion difference between the top 20% of self-serve products and the bottom 20%, and that roughly one in four products, 23%, convert above 25%. Nothing about trial duration explains a gap that size.

So the first question is not how many days. It is how many days until someone sees the thing they came for. I call that the time to first useful output, and it is the only input to this decision that is actually about your product rather than about the market's habits.

Measure it honestly. Not how long a demo takes when you drive, but how long it takes a real user who has a day job, has to find a password, and needs data from a colleague. In my experience that number comes back a good deal higher than the founder guessed.

Does asking for a credit card change the maths?

Dramatically, and this is the single biggest number in the report. ChartMogul found that free trials requiring a credit card see 30% free-to-paid conversion, more than five times the rate of trials that do not require one. It also found that only 20% of free trial products ask for a card upfront, with the remaining 80% not asking.

Read that pair carefully before you act on it. A 30% conversion rate among card-gated trials does not mean gating causes conversion. It means the people who hand over a card were already much closer to buying, and the gate filtered out everyone else before they counted as a trial at all.

That is a selection effect, not a growth tactic, and treating it as a tactic is how teams destroy their pipeline while improving their conversion rate. Your conversion percentage will rise and your number of new customers can easily fall.

The useful way to use this finding is as a choice about which problem you have. If you are drowning in unqualified signups and your team cannot keep up, a card requirement is a legitimate filter. If you are short of signups, it is the last thing you should add.

How do you pick a length from your own product?

Work backwards from first value and add a buffer for real life. If your product delivers something useful in an hour, a 7-day trial is plenty and a 30-day trial just gives people permission to forget you. If it needs a data import and a colleague's approval, 14 days will expire mid-setup.

Then check the buffer against your buyer's calendar rather than yours. Enterprise trials lose whole weeks to procurement, holidays and the one person who has the credentials. A trial that technically allows enough working hours can still fail because those hours are not consecutive.

ChartMogul's own history is a useful example of the logic. Its blog notes that at ChartMogul they extended the trial period from 14 days to 30 days when they released an Import API for their subscription analytics software. The product got a step that took longer, so the trial got longer. That is the right causal direction.

When should you extend past 14 days?

When setup is genuinely long, when your buying committee is large, or when the value only appears after a cycle your customer does not control. A payroll tool cannot prove itself in a fortnight if payroll runs monthly. That is a product fact, not a marketing preference.

Be suspicious of every other reason. Extending the trial because conversion is low is usually treating a symptom, since a user who was not activated in two weeks rarely becomes activated in four. Longer trials mostly buy you a longer wait for the same answer.

There is also a cost nobody accounts for. A 30-day trial lengthens your feedback loop on every change you make to onboarding, because you wait a month to learn whether it worked. If you are iterating quickly, a shorter trial is a faster instrument.

And extending is not the only lever. Extending the window while leaving onboarding untouched is a decision to hope, which is the opposite of the approach I argued for in designing an onboarding email sequence for trial users.

When is a shorter trial the honest choice?

When your product proves itself fast and your sales motion is self-serve. A 7-day trial creates real urgency, shortens your learning cycle, and gets a decision out of people while they still remember why they signed up. For a simple tool, 30 days is just a month of drift.

Short trials also expose weak onboarding immediately, which is uncomfortable and useful. If nobody reaches value in seven days, you now know that within a week instead of finding out next quarter.

The trap with short trials is assuming the clock does the persuading. Urgency only converts someone who already got value, so a 7-day trial with no activation support is a faster way to lose people. Length changes when you find out; it does not change what you find out.

How do you change trial length without wrecking your numbers?

Decide up front what would make you revert, and write it down before you ship. Most teams change trial length, watch the dashboard, and then argue about what they are seeing, because nobody agreed on the success condition while they were still impartial.

Compare cohorts, not calendar months. A trial length change contaminates any before-and-after read, because a 30-day cohort has not finished converting when a 14-day cohort has. Give the longer cohort the full extra time before you compare anything, and expect the first month of data to look worse than reality.

Count paying customers as your outcome, not conversion rate. Conversion rate is a ratio you can improve by shrinking the denominator, which is exactly what stricter trials do. Revenue and new customers are harder to fool.

And remember that length is only one dial on this stage of your go-to-market. Whether you offer a trial at all, and to whom, is the bigger decision, and I worked through that one in choosing between a self-serve trial and a demo request.

What should you do next?

Measure your time to first useful output with three real users this week, then set your trial to roughly twice that, rounded to a familiar number. If the answer lands near 14 days, you have the market's default and no argument to have. If it lands well outside, you have a reason to differ and you can defend it.

Then leave the length alone for a quarter and spend the effort on activation instead. Given a 10x spread between the best and worst self-serve products, your trial length is almost certainly not what is holding you back. How you package and price what happens next matters more, which is the question behind how many pricing tiers B2B software should have.

If you want a second opinion on your trial design, or you are about to change the length and want to get the measurement right first, reach out. I would rather help you set up the comparison properly than watch you guess from a dashboard.