Trial-to-paid conversion rate measures how many trial users go on to pay. Every dollar spent upstream is priced against it, because a trial signup is only worth what its conversion probability says it is worth.

How to calculate trial-to-paid conversion rate

Trial-to-paid conversion rate = (Trials converted to paid / Trials started) x 100

Trial-to-paid conversion rate = (Trials converted to paid / Trials started) x 100

Trial-to-paid conversion rate = (Trials converted to paid / Trials started) x 100

A quick example

A campaign drives 4,000 trial starts in March. By the time every one of those trials has run its course, 1,100 have converted:

(1,100 / 4,000) x 100 = 27.5

(1,100 / 4,000) x 100 = 27.5

(1,100 / 4,000) x 100 = 27.5

If the campaign cost $40,000, the cost per trial was $10 but the real cost per subscriber was $36.36. The second figure is the one that has to clear LTV.

What counts as a good trial-to-paid conversion rate?

It depends almost entirely on the trial design, so benchmarks travel badly:

• Opt-out trials that take card details up front convert far higher than opt-in ones, often by a multiple, because the default is to be billed.

• Price point matters. Low-cost consumer subscriptions convert more freely than expensive ones with a purchase decision behind them.

• Traffic source matters more than most teams expect. Two channels delivering identical trial volume can differ threefold here.

• Your own trend is the benchmark. Compare against your previous cohorts, not against a figure from someone else's product.

Trial-to-paid vs. activation rate

Activation measures whether a user reached the product's first moment of value; trial-to-paid measures whether they paid for it. Activation is the leading indicator and usually the thing you can actually fix, since users who never activate almost never convert. Treating the two as the same number hides where the funnel is leaking.

How to improve it

• Shorten time to first value. Users convert on what they experienced, not on what the product could theoretically do.

• Remind before billing. It costs a little conversion and prevents the disputes and reversals that follow a surprise charge.

• Match trial length to the product. A window longer than the natural evaluation period adds delay, not persuasion.

• Segment by source. Cut the channels whose trials never convert rather than optimizing the average.

Common mistakes to avoid

• Measuring live instead of by cohort. Open trials in the denominator make the rate look worse early and better later, for no real reason.

• Optimizing the rate in isolation. Tightening the trial to raise conversion can shrink trial volume enough to lose subscribers overall.

• Ignoring what happens after the first payment. A high conversion rate followed by month-two churn is a refund pipeline, not growth.