Freemium vs free trial vs reverse trial: how to choose, with the evidence

Neither freemium nor a free trial wins on conversion alone. Free trials convert slightly better, but freemium makes up the gap with higher visitor-to-signup rates. In a January 2026 study of 200 business-to-business (B2B) software products, 57% led with a free trial and 26% with freemium. Choose on product conditions such as time to value, marginal cost and network effects, and compare models on visitor-to-paid conversion.

Freemium vs free trial, the short answer

Neither model wins on conversion alone. Free trials are the more common choice and they convert a little better, but freemium recovers the difference at the top of the funnel. Choose on product conditions, not on the headline conversion rate.

Free trials were the primary entry point for 57% of the products studied, against 26% for freemium and 7% for reverse trials.

Primary entry point for new customers, 200 B2B software products% of products

1. Free trial57 % of products
2. Freemium26 % of products
3. Reverse trial7 % of products
4. Interactive demo7 % of products
5. Paid trial4 % of products

Primary entry point for new customers, 200 B2B software products

Item	Value, % of products
Free trial	57 % of products
Freemium	26 % of products
Reverse trial	7 % of products
Interactive demo	7 % of products
Paid trial	4 % of products

The current numbers come from a Growth Unhinged study of business-to-business (B2B) software, which "was conducted in January 2026 and included 200 software products." It found that "57% of products have a free trial as their primary landing point for new customers, more than twice the rate of freemium (26%)." Only 7% ran a reverse trial, where, as Growth Unhinged describes it, new users start with a time-limited trial of paid features and then buy or drop to a free tier.

On conversion, the same study's finding is the short answer: "Free trials convert at slightly higher rates than freemium; however, this difference gets wiped out upon accounting for signup rates." It measured conversion as the percentage of leads or free signups that became paying customers within six months, and the median across all products was 8%. The signup side matters because freemium products tend to see higher conversion from website visitor to new sign-up.

Why the gap closes: a worked example

These are example inputs, not benchmarks. Two products each get 10000 visitors a month.

• Freemium: 20% of 10000 visitors sign up, which gives 2000 signups.
• Free trial: 10% of 10000 visitors sign up, which gives 1000 signups.
• Free trial converts 20% of its 1000 signups, which gives 200 customers.
• Freemium converts 10% of its 2000 signups, which gives 200 customers.

The trial looked twice as strong on signup-to-paid conversion and produced the same number of customers. When you compare models, track visitor-to-paid, not signup-to-paid. Our free-to-paid conversion benchmarks break the rates down further.

Which conditions point which way

Product condition	Leans toward (our reading)
Users reach value inside the trial window	Free trial
Value needs weeks of setup or team adoption	Freemium or reverse trial
You need cash quickly to fund paid acquisition	Free trial
The product gains value as more people use it	Freemium

Two inputs from your own data settle most of this table: your time to value and your target payback period. Pull both this week before you change your entry model.

What freemium, a free trial and a reverse trial mean

The three models differ in one thing: what the paywall is built on. David Sacks put the split simply: the choice is between a functionality-based or time-based paywall. A reverse trial uses both, in sequence.

Freemium: a feature paywall

Companies that run on a freemium model offer a version of their product for free, forever. Users pay to get past a feature, usage or support limit. Time never runs out. Elena Verna, writing for Amplitude, reported that she typically sees a ~5% conversion rate from the free plan to a paid plan.

Free trial: a time paywall

A trial gives the paid product for a fixed window. Verna noted that it assumes everyone needs the same amount of time (7, 14, or 30 days) to reach some value. There are two kinds, and they behave differently:

Trial type	What the user gives at signup	Trial-to-paid conversion reported by Verna
Card required	A credit card upfront before the ‘free’ trial starts	As many as 70-80%
No card	Nothing beyond an account	A 15% trial-start-to-paid conversion rate

The card version filters hard at the door. Verna wrote that as many as 80% of people will drop off at the credit card screen.

Here is a worked example with round inputs, not a benchmark. If 1000 people reach a card screen and 80% drop off, 200 start the trial. If 70% of those 200 convert, you get 140 paying customers. If the same 1000 people start a no-card trial and 15% of the 1000 convert, you get 150. In our reading, the two paths can land close together, so the card decision is mostly about funnel shape: fewer, higher-intent trialists versus more trialists who need onboarding work.

Reverse trial: time paywall first, feature paywall after

The reverse trial, defined in the short answer above, adds two details worth knowing.

Real setups vary:

• Asana lands profiled signups in a 30-day paid trial.
• Airtable drops users into a 14-day reverse trial for a team experience.
• Notion asks for a credit card as part of its reverse trial.

Write down which paywall you would run before you compare results. Then pick a trial length from your time to value, and see the reverse trial glossary entry for the terms.

What the product benchmarks report for each model

The two benchmark sets were built differently, so read them as separate snapshots. One is a 2022 survey of product-led companies. The other is the 2026 study introduced in the opening section.

Among free trial products in the 2026 study, 14 days was the most common length at 62%, with 7 days and 30 days at 14% each.

Free trial length, share of free trial productsPer cent

Free trial length, share of free trial products

Item	Value, %
14 days	62%
7 days	14%
30 days	14%

The 2022 picture: growth and the freemium funnel

OpenView's third annual Product Benchmarks Report found that product-led companies, especially freemium ones, were 2x more likely to grow revenue 100% year over year than sales-led models. That is a correlation across survey respondents. It does not show that switching to freemium causes faster growth.

The same report described the freemium funnel stage by stage. Top freemium businesses got most users from organic search (53%) and product-driven referrals (13%). Freemium businesses had a median visit-to-signup rate of 6%. At standout product-led companies, only 20 to 30% of new users reached activation.

Here is a worked example, not a benchmark. Suppose 10000 visitors arrive and convert to signups at 6%: that gives 600 signups. If 20% of those 600 activate, you have 120 activated users. At 30%, you have 180. In our reading, most of the loss happens before anyone sees a paywall, so start by measuring your activation rate.

The 2026 picture: trial lengths and spread

The 2026 study gave trial length as a share of free trial products: 14 days (62% of products), then 7 days (14%) or 30 days (14%). Model choice varied by product type. 61% of SaaS products led with a free trial, against AI-native (43%) products. Trials were also not purely self-serve: 80% of free trial products have human touchpoints when an enterprise user starts a trial.

The median conversion rate covered earlier hides a wide spread. The study found a 10x conversion difference between the top 20% of self-serve products and the bottom 20%. For the full rate bands by model, see our free-to-paid conversion benchmarks.

Report	What it measured	Headline figure
OpenView, 2022	Revenue growth by model	2x more likely to grow 100% year over year
OpenView, 2022	Freemium visit-to-signup	6% median
2026 study	Most common trial length	14 days, 62% of trial products
2026 study	Spread in conversion	10x, top 20% versus bottom 20%

In our reading, the 10x spread matters more than any single median. Compare your product with others of the same model and price band, then work on the funnel stage where your numbers fall furthest behind.

When does freemium make sense

Freemium earns its cost under a narrow set of conditions. Three cases show what those conditions look like in practice, and each one points to a check you can run on your own product this week.

Case 1: Yammer, where free users were the sales pipeline

Yammer's sales went from $1 million in 2009 to $56 million in 2012. Its co-founder's rule was that freemium is better for viral or networked products that depend on user-generated content, network effects or bottom-up adoption.

In our reading, the cost was urgency. Reps said their biggest competitor was “Yammer Free.”

Case 2: Slack against Stride

Atlassian priced Stride at $2 per user/month with a 30-day free trial. In our reading, a lower price does not offset a time limit when the product's value grows with the number of teammates using it.

Case 3: Tettra and Vidyard, where value took longer than the trial

In our reading, Tettra ran a 15-day free trial, but a knowledge base pays off only after documents pile up. Moving to freemium tripled the number of upgrades by the 5th quarter. A free Chrome extension then gained more than 100k users within a year.

A five-minute check

Condition	Case that shows it	What to check this week (our reading)
Each user brings in others	Yammer	Count invites sent per active user in the first month
Value grows with team size	Slack	Compare retention for solo accounts against accounts with teammates
Time to value exceeds the trial	Tettra, Vidyard	Measure days from signup to the first meaningful outcome
Market is large	All three	Size your total addressable market (TAM) before giving the product away

On the last row, one investor's view is that for a freemium model to succeed, a company needs a large TAM.

Here is a worked example, not a benchmark. If the median user takes 30 days to reach value and your trial lasts 14, the median user hits the paywall 16 days early. If two or more rows apply to you, we think freemium deserves a test. Track invite rates with a viral coefficient.

Should a free trial require a credit card, and how long should it run

In our reading, asking for a card up front is the single biggest lever on trial conversion, and the one most likely to mislead you. Growth Unhinged's 2026 report found that free trials that require a credit card see 30% free-to-paid conversion, more than 5x ones that don’t require one. Yet among free trial products, 20% require users to provide a credit card upfront.

Check the denominator before you copy that number. The report counts the percentage of leads or free signups that convert to become a paying customer within six months. Elena Verna's figures at Amplitude use trial starts instead: as many as 70-80% of users who start this trial will convert on card-required trials, while no-card trials typically see a 15% trial-start-to-paid conversion rate.

Run the funnel, not the rate

A high rate on a smaller pool can still produce fewer customers. Here is an example, not a benchmark.

Step	No card (example)	Card required (example)
Trial starts	1000	200
Conversion rate	10%	30%
Paying customers	100	60

1000 starts at 10% gives 100 customers. If the card screen leaves 200 of those 1000 starts, 200 at 30% gives 60. The card version wins on rate and loses on customers.

The cost that shows up later

Opt-out billing pulls in people who never meant to stay. Sixteen Ventures notes that customers who didn’t intend to continue will cancel immediately, often requesting refunds or initiating chargebacks. If 20 of the 60 card-trial customers in the example cancel after the first charge, 60 minus 20 leaves 40 who stayed on purpose.

So do not count a first charge as a win. Sixteen Ventures suggests observing customers over multiple billing cycles (ideally 90 days) to see who is staying intentionally. Report card-trial conversion as paid customers still active after that window, tracked by cohort on your retention curves.

We think a card wall makes sense when your product is high-intent and low-touch and you send a clear reminder before the charge. Otherwise, start without one and test the card as an experiment.

Set length by time to value

Trials assume time is the right value metric. Verna points out that in B2B companies, this favors smaller businesses and discriminates against larger enterprises.

Set the length this week:

1. Pick your activation event, the action that best predicts a user paying.
2. Pull the median days from signup to that event, split by company size.
3. Set the trial long enough for the slower segment to reach it, starting from the 14-day default covered earlier.
4. If enterprise users need far longer, offer extensions through sales rather than lengthening everyone's trial.

What is a reverse trial, and who has run one

A reverse trial starts every new signup on the paid plan for a fixed window. After the trial ends without a payment being made, users are smoothly transitioned to a freemium plan. The user gets the full product first and loses part of it later, which is where the upgrade pressure comes from.

Two preconditions

Elena Verna lists two requirements. First, your product has a freemium plan to fall back to. Second, it must be possible for a free customer to try some version of the paid plan without bankrupting your business. Her sample offer gives users all premium features for the next 7 days. No credit card required.

She reports that reverse trials usually result in ~20% lift in conversion, with one condition: assuming high utilization of paid functionality within the reverse trial window. If users never touch the paid features, there is nothing to take away. That makes activation inside the window the metric to watch.

How four products set it up

Product	What the signup sees
Canva	Canva profiles every new signup for intent, and there is no way to start here without a trial
Asana	A splash modal letting them know about their 30-day paid trial
Notion	Asking for a credit card as part of their reverse trial
Airtable	A 14-day Reverse Trial for a team experience after profiling

In our reading, the common step is profiling. Ask what the user is there to do, then decide which plan to trial: team or individual, and how long.

Reverse trials as cost control in AI products

For artificial intelligence (AI) products, every free session costs compute. Writing on GTM Strategist, the author argues reverse trials are essential if you’re running an AI product and want to control costs while still driving activation. The window caps how long expensive access stays open.

A worked example, not a benchmark: if full access costs you 10 dollars per user over a 14-day window, 1000 signups cost 10000 dollars before anyone pays. If 100 of those 1000 signups would convert anyway, a 20% lift adds 20 conversions, for 120. Run the same arithmetic with your own compute cost and conversion rate before you choose the window length.

Run it more than once

Verna writes that on average, it takes 2-3 trials to upgrade a free customer to paid. One cadence she suggests: every six months or so, reverse trial your entire user base. Treat each round as a growth experiment with its own cohort.

A decision table for choosing your model, with a worked example

The earlier sections covered what each model is and what the benchmarks show. This one is our method: five questions, one table, and a worked example you can copy into a planning doc this week.

The table below is our reading. It draws on two published trade-offs. Free trial products often see 2-3x the free-to-paid conversion rates of freemium ones. Their median time-to-purchase might be 14 days compared to 60 or 90 days for a freemium one. ProductLed frames the split as freemium giving away beginner milestone features permanently and a trial giving away intermediate/advanced features temporarily.

Factor	Points to freemium (our reading)	Points to free trial (our reading)	Points to reverse trial (our reading)
Time to value	Value builds over weeks of use	Value shows inside the trial window	Setup is long, but paid features show the payoff early
Marginal cost of a free user	Close to zero	High on every feature	High on paid features, low on the core
Network effects	Strong: each user brings in others	Weak or none	Strong, and you also need conversion
Price point	Low, and you accept price anchoring	Higher, where anchoring would hurt	Low to mid, self-serve
Sales motion	User growth first	Revenue and cash first	Both at once

How to score it: mark one column per row, then count. Three or more marks in one column is your starting model. A split usually lands on the reverse trial.

Two rows need care. On network effects, Growth Unhinged notes that in these cases product owners inherently prioritize acquisition over conversion and revenue. On price, a free version can anchor users on a lower price point.

Worked example

Take a team tool priced at $30 a month. Treat every number here as an example, not a benchmark. Setup takes about 20 days, and AI features cost about $10 a month per active user in model calls, rising.

• Time to value. A 14-day trial ends 6 days before setup finishes (20 minus 14). Some users can’t experience real value in only a 14-day or 30-day period. Mark: reverse trial with a 30-day window.
• Marginal cost. Freemium with AI included at 1000 free users and $10 each costs $10,000 a month. Mark: reverse trial, with AI kept in the paid tier.
• Network effects. Teams invite teammates. Mark: freemium or reverse trial.
• Price point. At $30, anchoring risk is small. Mark: freemium or reverse trial.
• Sales motion. Self-serve, with cash needed for paid acquisition. Mark: reverse trial.

The result is a reverse trial. Users get 30 days of full access including AI. After that, they drop to a free tier with sharing and core features but no model calls. We think this keeps the invite loop alive without paying token bills for users who never convert.

To test the result, plug your own signups and costs into the growth model template. Then check the cash timing against your payback period.

How to test a switch without breaking the funnel

A model switch changes the whole funnel at once, so test it as a cohort holdout rather than a page-level A/B test. The steps below are our method. Agree on them in writing before any traffic moves.

Step 1: Split by signup cohort

Assign each new account at signup, at random, to the current model or the new one, and keep it there for the whole test. Existing users stay where they are. Each arm becomes a clean cohort you can follow week by week. If you run it as a growth experiment, write the hypothesis down first. A good hypothesis names the metric expected to rise and the one expected to fall.

Step 2: Size the test on the slowest metric

Free-to-paid needs far more signups to read than visitor-to-signup does, so size on conversion to paid. Use the sample size calculator. Here is an example, not a benchmark: if 10000 visitors reach pricing and 10 percent sign up, each month gives you 1000 signups to split. If the calculator asks for more than that, the test runs longer. You can also accept a larger detectable effect.

Step 3: Watch six metrics, each with a fixed window

Expect a trade-off. Growth Unhinged reports that freemium products tend to see higher conversion from visitor to signup. It also notes that PLG companies typically have two competing north star metrics, one for users and one for revenue. Track both sides.

Metric	Window (example)	Guardrail, our reading
Visitor-to-signup	14 days	Pause if the new arm falls 20 percent below control
Activation	14 days from signup	Must not fall below control
Free-to-paid	Same fixed window for both arms, say 30 days	Primary success metric
Time to purchase	Median days, signup to first payment	Report, do not optimize alone
Cash payback	Months to recover acquisition cost	Must not lengthen
Month-two retention	Paid accounts active in month two	Must not fall below control

Use the same window for free-to-paid in both arms. A trial arm buys at expiry, a freemium arm buys later, and an open window flatters whichever arm has run longer.

Step 4: Set stop rules before launch

• Stop early if a guardrail breaks for two consecutive weekly reads.
• Do not stop early for a winning free-to-paid number. Wait for the planned sample.
• Check the trial clock. Trials run commonly ~14 days. If activation in the trial arm lands after expiry, fix onboarding with an email sequence before you judge the model.
• Read month two before you roll out. A conversion lift that churns out later costs more than it earns.

What this page does not cover

This page does not cover how to set price levels, how to package specific features into tiers beyond the examples shown, or sales-led enterprise contracts. It is not financial or legal advice, including on billing, refund or chargeback practices for card-required trials.

Related on Race to Scale: Free-to-paid conversion rate benchmarks for freemium, opt-in trials and card-required trials; Pricing page examples from six SaaS companies and what each one does; Growth loops explained, with the four loop types and a template to draw your own.