Soft launch testing

Roblox Soft Launch Experiment Planner

Turn a weak metric or creator hunch into a 7-day experiment that changes one variable and produces a readable decision.

7-day experiment schedule

1

Day 1

Record the baseline for play-through rate, average session, D1 retention, and current page assets.

Baseline note and screenshots of the current title, icon, thumbnail, and description.

2

Day 2

Prepare exactly one change: test a reward-focused thumbnail instead of the current danger thumbnail.

One finished change that fits 3-5 hours, with no extra gameplay or monetization edits.

3

Day 3

Publish the change and write down the exact time it went live.

Launch note with timestamp and what changed.

4

Day 4

Check early movement in play-through rate, but do not make another change yet.

Early read: up, flat, or down.

5

Day 5

Read comments, private feedback, and playtest observations for the same bottleneck.

Three user phrases that explain the metric movement.

6

Day 6

Decide whether the experiment needs one more day of data or is clearly failing.

Keep observing, revert, or prepare the next variable.

7

Day 7

Keep, revert, or iterate based on the decision rule.

Next experiment brief with one metric and one variable.

Prepare the experiment assets

How to run a useful soft launch test

A soft launch should reduce confusion. The goal is not to fix everything in one week, but to learn which lever actually moves.

How to use it

  • + Pick one metric: play-through, average session, D1 retention, payer conversion, or update return.
  • + Write one hypothesis.
  • + Change one variable.
  • + Record baseline and decision rule before publishing.

Example outputs

  • + Thumbnail test: change thumbnail only and watch play-through rate.
  • + First-session test: change spawn and first reward only, then watch average session.
  • + Retention test: add one daily reward and watch D1 retention.

Common mistakes

  • + Changing the thumbnail and tutorial and game passes on the same day.
  • + Judging a test without a baseline.
  • + Keeping a change because it looks better even when the target metric falls.

It is a small controlled test before or during early launch where you change one variable and watch one main metric.