Update Experiment
Updates the targeting rules, treatment allocation, metrics, or hypothesis of an existing experiment or feature flag. Weights and metrics can only grow, so enrolled users never change arms and an existing metric is never dropped. Lifecycle moves through the transition endpoints (activate, pause, end), never through this update. Requires the corresponding experiment permission on the owning account, or Whop internal access for internal experiments.
Authorizations
An Account API key, account-scoped JWT, App API key, or user OAuth token. Prepend the key or token with Bearer, for example Bearer ***************************.
Headers
Pins the request to a dated API version.
"2026-09-11"
Path Parameters
The experiment identifier — the expt_ id or the flag_key handle.
Query Parameters
Owning account or internal. Required when id is a flag key; optional for an expt_ ID.
Body
Omit to leave unchanged. Send an empty string to clear it. Not accepted on feature flags. When setting it, structure it as "If we [change] for [cohort], then [measurable behavior] will [increase/decrease], resulting in [business outcome], because [evidence]. Created by [name]." same as on create.
"If we send a blueprint nudge email 30 minutes after business creation, then GTV within 10 hours will increase among newly created businesses, resulting in more new business operators generating GTV within 10 hours, because operators currently land on an empty dashboard with no concrete next step. Created by Jane Doe."
Replace the targeting rules with this set. Omit to leave unchanged.
Grow treatment allocation. Pass every existing treatment with an equal-or-higher weight; append new names to add arms. Weights never decrease and arms are never removed. Omit to leave unchanged.
Response
metrics added
Owning account ID, or internal for Whop platform experiments.
"internal"
Assignment hashes UTF-8 seed + subject ID with CRC32 modulo 100 and selects the stored end-exclusive range.
"verb_end_exp1768435200"
Revision of the serving configuration. Does not change the assignment seed.
2
Developer-chosen handle referenced from code. Anywhere the API takes an experiment identifier, the expt_ id and the flag_key are interchangeable.
"verb_end_exp"
Unique identifier for the experiment, prefixed expt_.
"expt_xxxxxxxxxxxxxx"
Human-readable display name.
"Verb End"
Lifecycle state. draft — not yet live; active — currently running; paused — traffic paused; ended — concluded.
draft, active, paused, ended "ended"
Rules gating who is in the experiment at all. Conditions within a rule are AND-ed, rules are OR-ed, and exclude rules always win. Empty means everyone qualifies.
"2026-01-01T12:00:00.000Z"
Treatment arms. Users outside every arm's allocation form the implicit control group. Weights only ever grow and arms are never removed, so a user moves from control into a treatment at most once.
Randomization unit — user buckets each user independently, account buckets whole accounts (every user of an account gets the same arm). null for feature flags.
user, account, anonymous "user"
When the experiment was created, as an ISO 8601 timestamp.
"2026-01-01T12:00:00.000Z"
ID of the user who created the experiment, prefixed user_. null for experiments created before creators were recorded.
"user_xxxxxxxxxxxxxx"
When the experiment stopped collecting data, as an ISO 8601 timestamp. null while still running.
"2026-01-01T12:00:00.000Z"
true when this was created as a feature flag rather than a full experiment. Feature flags share the same evaluation API but do not collect metric results.
false
What was learned and why this outcome, recorded when the experiment was ended. null until then.
"Treatment lifted conversion 8%"
Hypothesis for this experiment. null when none is set, and always null for feature flags.
"Users will convert more"
When the experiment began collecting data, as an ISO 8601 timestamp. null for drafts.
"2026-01-01T12:00:00.000Z"
The treatment that won, set when the experiment was ended. Once set, every evaluation returns this arm to every caller regardless of targeting or allocation, and no further exposures are recorded. null means control won — an ended experiment with no winning arm evaluates to control for everyone. Always null for feature flags, which simply evaluate to disabled once ended.
"treatment"

