# 7-Day vs 14-Day Free Trial A/B Test

Page: https://alidemirbas.com.tr/en/lab/ab-test-library/tests/7-day-vs-14-day-free-trial-ab-test

## Hypothesis

A seven-day trial may bring the decision forward while interest is still fresh, while a fourteen-day trial gives users more time to reach first value. If users reach first value in the first days, seven days could bring the higher trial-to-paid conversion rate; if first value takes longer, fourteen days could.

## When to run this test

If product analytics show active use falling after the first days, trials ending before users reach first value, or support requests asking for an extension, the trial length may not fit how people decide. If the shorter trial comes out ahead, users reach first value early and decide faster; if the longer trial wins, more users reach first value and go on to pay. If onboarding or the card requirement is about to change, finish that first, because a trial-length test can only be read while those conditions stay fixed.

## Primary metric

**Trial-to-paid conversion rate**: Measure paid starts among assigned trial users after each trial and the same post-trial follow-up window have matured; exclude immature cohorts.

## Other metrics

- **Activation rate**: Report activation at the same elapsed-day checkpoints and at the end of each trial.
- **Time to first value**: Use the same start and value events; report users who never reach the value event separately.
- **Three-month paid retention**: Compare users who complete the same three-month window after their first paid start.

## What to check before and during the test

- **Paid conversion**: Compare paid conversion after 7-day and 14-day trials.
- **Activation**: Compare how often users reach the predefined activation event.
- **Time to value**: Measure time to the same first-value event in each arm.
- **Trial usage**: Report active days and sessions while noting the different trial lengths.
- **Segment**: Review whether small and larger teams respond differently to trial length.

## What to watch when reading the result

- Read trial-to-paid conversion over a common follow-up window that starts at assignment, across all eligible assigned users. Compare three-month paid retention across all assigned users as well; if one arm brings more conversions but leaves fewer lasting customers, do not pick it on conversion alone.
- Read the result within this product access and onboarding. Keep trial scope the same across plans and warn users before an account closes at the end of the trial; otherwise the difference comes from the experience, not the length. Review small and larger teams separately.
- A longer trial delays when conversion shows up, so an early look can make the shorter trial seem ahead. Get the eligible users needed per arm for trial-to-paid conversion from the [sample size calculator](https://alidemirbas.com.tr/en/calculators/sample-size-calculator), then plan the run as the time to enroll them plus the time the longer trial needs to mature. Keep each arm's trial length unchanged mid-test, and do not decide before both cohorts finish the follow-up window.

## Frequently Asked Questions

### When can I start interpreting trial-length results?

Use a common follow-up window beginning at assignment, long enough for the longer trial to mature. Report trial-end-aligned analyses separately. Use paid conversion per eligible assigned user as the primary outcome.

### How should trial usage be compared?

Account for unequal trial durations. Report activation at equal elapsed times and at trial end separately. Measure time to first value from the same start and event, and report users who never reach it.

### Does higher paid conversion mean the shorter trial won?

Compare retained paying-user contribution across all eligible assigned users. Retention among converters is diagnostic because the people converting may differ. Do not substitute that conditional rate for overall success.

### Which trial conditions should stay fixed?

Keep trial duration assignments, card requirements and feature scope stable. Do not close accounts at expiry without warning.