You can now map your identity provider's role names to Statsig roles without renaming anything in your IdP.
Create aliases on the Statsig side that translate your IdP's existing role names to first-class Statsig roles. Works with Okta, Microsoft Entra ID, and other SCIM-compatible identity providers with strict or unchangeable naming conventions.
Self-serve setup in a few clicks. No support ticket or manual intervention needed
Now, SCIM provisioning no longer requires your IdP group names to match an expected role format. You can define the translation on the Statsig side and let provisioning work with whatever names your IdP already uses.
Go to Settings in the Statsig console to configure SCIM role aliases for your organization.
Learn more in the Statsig SCIM docs.
You can now pull the data behind the Daily Checks column in the experiment list directly over the API.
One new endpoint is available on statsigapi.net/console/v1/:
GET /console/v1/experiments/{id}/diagnostics_checks?lastDays=30
Use lastDays (1-90) to set a lookback window without computing dates yourself
Use startDate / endDate if you need an explicit range instead
is_realtime tells you whether the final day is still filling, so you know not to treat it as a complete day
Warehouse Native experiments now return real data from the warehouse exposures summary, the same source the console list column uses
Before, the Daily Checks column in the experiment list flagged experiments that were "In Progress" after being pulled from code, or "Decision Made" while still serving traffic and catching those states meant querying your own warehouse. Now, you can surface that signal programmatically and build automated checks or alerts on top of it.
Review the full API reference in the Statsig Console API docs.
Statsig WHN queries now carry cost attribution tags in your warehouse, so you can see exactly what Statsig activity is driving your compute costs.
Every query is stamped with is_whn, a type (experiment, gate, etc.), the experiment or gate name, a job type, and the reload ID. Tags land natively in each warehouse β nothing leaves your account:
Snowflake β session QUERY_TAG in ACCOUNT_USAGE.QUERY_HISTORY and QUERY_ATTRIBUTION_HISTORY
BigQuery β job labels (type=whn_query) in INFORMATION_SCHEMA.JOBS
Redshift β query_group in SYS_QUERY_HISTORY.query_label
Databricks β statement comment in system.query.history
Before , you could see total spend but had no way to attribute it to a specific experiment or job type in Statsig. Now, you can point one query at your warehouse's usage view, filter to Statsig WHN queries, group by experiment, and get per-experiment reload cost, making it straightforward to spot expensive reloads and change your schedule.
Filter your warehouse usage view to is_whn:"True" (or type=whn_query on BigQuery) and group by experiment to see per-experiment reload costs.
Learn more in the Statsig Warehouse Native docs.
Setting up Layers when creating an experiment is now easier than ever.
See Layers as a top-level Targeting option alongside ID Type and Target Applications.
Pick a layer and have ID Type and Target Applications auto-fill and lock automatically.
Clear the layer to unlock those fields and keep your values.
See Target Applications displayed by name rather than a raw count

Layers keep experiments mutually exclusive, preventing cross-experiment contamination across your project. With Layers now a top-level option in the Create Experiment modal, setting them up correctly takes less effort from the start.
Open the Statsig console and create a new experiment to try it out.
View and manage values entered into freeform or custom-value fields when editing targeting rules, however many you want.
A new and improved StatsigValueMultiSelect component gives you:
A dropdown that makes the complete list easy to view and manage, including removing individual values
A dedicated input for adding or pasting values
Search across both added values and available autocomplete suggestions
Selected-value chips with an accurate +N more summary that includes only values not already visible
Clear sections separating search results and added values
A contextual empty state when no values have been added
Type-aware copy throughout, e.g. βAdd or search Unit IDs,β βAdded Unit IDs,β and βNo Unit IDs addedβ
Copy-all and remove-all actions
It can be reused across targeting rules and other custom-value workflows. Preset-only selectors such as Operating System and Device remain unchanged and will be updated to have a more consistent UI.
Previously, the targeting input displayed only a few values and hid the rest behind a popover, making values increasingly difficult to find and remove as lists grew. Adding new values was also cumbersome through the existing input field, and there was no way to search existing values.
If you have lots of values to add, that's easier now.
This is currently behind a feature gate, but will be released to all customers soon. If you want early access, reach out to your account team.
You can now give gates, experiments, and dynamic configs the same display name.
Use duplicate display names across feature gates, experiments, dynamic configs, and their templates.
When a name collision occurs, the ID auto-resolves to the smallest free suffix (checkout_flow becomes checkout_flow_1) and Create stays enabled with an info note instead of a dead-end error.
Edit the auto-generated ID inline by hovering or focusing the row and clicking the pencil icon.
Works across create, clone, and rename flows.
Before this, two entities with the same display name hit "ID already in use" and teams with naturally similar naming conventions had to add arbitrary suffixes just to get past the create step. Now display names can reflect what something actually is, while uniqueness is still enforced on the ID.
Open the Statsig console and create a new gate, experiment, or dynamic config with a name that already exists to see the new flow in action.
Managing targeting rule order is now faster and more intuitive.
Drag any rule by its IF / ELSE IF rail to reorder it inline β no more opening a separate Reorder Rules modal.
Hover on any rule to reveal an "Insert new rule" button and drop a new rule exactly where you want it, instead of adding to the bottom and dragging it up.
Precedence labels update live as you drag so you always know where a rule will land
Rule order matters in targeting. Before this, reordering required a separate modal. Now, you can build and adjust targeting logic directly in the editor without breaking your flow.
Open any feature gate, experiment, or dynamic config in the Statsig console and try dragging or inserting a targeting rule.
You can now remove an individual user from a Feature Gate override without touching the rest of the list.
One new endpoint is available on statsigapi.net/console/v1/:
DELETE /console/v1/gates/{gateName}/overrides/userID/{userID}
Before this, removing a single user override meant fetching the full override list, mutating it locally, and re-posting it, which could be risky when test runs are happening concurrently. Now, you can target and remove exactly one user, leaving every other override untouched.
Review the full API reference in the Statsig Console API docs.
Statsig Topline Alerts can now page PagerDuty directly.
Add PagerDuty services to the Integrations catalog once with a name and Events API v2 routing key.
Select one or more PagerDuty services per alert in the Notifications settings.
Test your wiring end-to-end before you rely on it β test pages are tagged [TEST] and never collide with real incidents.
Deleting a PagerDuty service that an alert still references is blocked, and disabled integrations are clearly flagged.

Topline Alerts catch anomalies in your most critical product metrics, but a notification in Slack or email isn't always enough when something is on fire. Now, the same alert that fires in Statsig can page your on-call team in PagerDuty, closing the gap between detecting a problem and fixing it quickly.
Go to Integrations in the Statsig console, add your PagerDuty service, then open any Topline Alert and configure PagerDuty under Notifications.
Learn more in the Statsig Topline Alerts docs.
You can now submit Autotune changes for review and manage the full review lifecycle across the console, Console API, and MCP.
Submit Autotune configuration changes for review before they reach production.
Approve, reject, or cancel in-flight Autotune reviews from the console, via CAPI, or through the MCP.
Teams with reviews required can now enforce that same approval workflow on Autotunes, the same way they do for gates and experiments.
Teams running Autotune for high-stakes decisions need the same guardrails they have everywhere else. Any change to a live Autotune can shift traffic allocation immediately, so being able to require an approval before it goes out matters. Reviews are now consistent across gates, experiments, and Autotunes.
If you have the Statsig MCP set up, try a prompt like:
"Using the Statsig MCP, open a review to update the winner threshold on
autotune_nameand submit it for approval."
Learn more in the Statsig Reviews docs.