Product Updates

🧪 Analyze Exposures in Metrics Explorer (Warehouse Native)

Experiment exposure events are now supported in Metrics Explorer on Warehouse Native. You can select them like any other event, filter or group by properties (variant, metadata), and tie rollout data directly to product metrics.

More details here: Exposures in Metrics Explorer

✅ Verified Cohorts and Dashboards

Admins can now mark specific cohorts and dashboards as verified. This signals that they are the trusted, official versions while also protecting them from accidental edits.

What You Can Do Now

• Mark cohorts and dashboards as verified to indicate they are the approved versions

• Prevent edits to verified entities unless you are an admin

• Clone verified cohorts and dashboards to create your own editable versions

How It Works

• Cohorts: Mark as verified when creating a new cohort or by editing an existing one

• Dashboards: Mark as verified from the settings cog in the top right of the dashboard page

Impact on Your Analysis

Teams can align on a single source of truth for key cohorts and dashboards while still allowing individuals to explore their own versions without risking changes to the verified originals.

This keeps shared analysis reliable and consistent.

Pre-Post Results on Feature Gates

Sometimes, you don’t have the luxury of launching a feature partially to your user population (e,g, X% of the users). Maybe you had to ship something immediately, rolled out a backend improvement to all users, or made a change you can’t ethically hold back from part of your audience. That’s where Pre-Post Results comes in.

With Pre-Post Results, you can:

• Compare metrics before and after a feature reaches 100% rollout

• See the directional impact on key outcomes, even without a control group

✨ How it works

Statsig automatically detects when a feature gate has been rolled out to all users (0 → 100% or started at 100% in the last 30 days). It then compares the same users’ behavior before and after rollout, showing you whether your feature moved the needle. To read more about our computational methodology, read Statsig Docs.

📍 Available now

Pre-Post Results is live for all Cloud customers in Statsig. You’ll see it automatically when your rollout qualifies - no setup required.

📈 Velocity Dashboard

Introducing the Velocity Dashboard, your new source of truth for understanding how fast your team is shipping. Built to bring visibility and alignment, this dashboard helps you track experiments and gates shipped over time, making it easier to highlight progress, spot trends, and share impact across your organization.

Highlights

• Unified view of experiment and gate velocity across teams

• Filter & group by team, tag, or status to focus on what matters

• Long-term trends at a glance — perfect for quarterly reviews

• Export to PDF for reporting, decks, or sharing with stakeholders

Available Now

Click on Dashboards → Velocity Dashboard to get started, or from the homepage widget.

📌 Default Dashboard Filters

You can now pin filters directly to dashboards, making it easier to analyze different views of your data without rebuilding filters from scratch.

What You Can Do Now

• Pin commonly used filters (e.g. “Company Name”) to any dashboard

• Quickly swap values to see how different users, cohorts, or properties impact the same set of charts

• Use pinned filters as a starting point for scoped analysis

How It Works

From any dashboard, go to dashboard settings and configure "default filters". The pinned filter will appear at the top of the dashboard and apply across all charts. When you change the value (e.g. from Company A to Company B), the charts update automatically with no need to reconfigure each one.

Impact on Your Analysis

This makes it faster to compare trends across dimensions like company, region, or platform. Instead of duplicating dashboards or editing individual filters, you can reuse the same dashboard with dynamic, scoped filtering.

Great for teams who want to keep a consistent dashboard layout while comparing key segments.

🔍 Conversion Drivers in Funnels

Pinpoint what’s helping or hurting your conversions. Conversion Drivers automatically highlight the most significant factors influencing whether users drop off or complete a funnel, so you don’t have to guess where to dig deeper.

What You Can Do Now

• Identify high-impact drivers of conversion or drop-off without needing a hypothesis in advance

• Analyze correlations across event properties, user properties, and intermediary events

• View performance summaries for each driver, including conversion rate and share of funnel participants

• Drill into a driver to access a conversion matrix and correlation coefficient

• Group the funnel by any surfaced driver with one click to explore broader trends

How It Works

When viewing a funnel, click on any step and select “View Drop-Off & Conversion Drivers.” A modal will appear showing a ranked list of the most statistically significant factors associated with conversion or drop-off at that step.

You can configure which types of data we analyze:

• Event properties like plan type, referral code, or platform

• User properties like country, account age, or signup method

• Intermediary events, which occurred between the two funnel steps

Each surfaced driver includes:

• How much more or less likely users with the factor were to convert, expressed as a multiple (for example, users with platform = Android were 1.2x as likely to convert)

• Conversion rate for users with the factor

• Share of funnel participants who had the factor

Clicking into a driver opens the drilldown view, where you can explore:

• A conversion matrix that compares outcomes for users who had the factor versus those who did not

• A correlation coefficient measuring how strongly the factor is associated with completing the funnel

If a pattern looks meaningful, you can group your funnel by that property with a single click. This reconfigures the chart to show step-by-step conversion performance broken down by the selected value.

Impact on Your Analysis

Funnels tell you what your conversion rate is. Conversion Drivers help explain why.

This feature is especially useful when:

• You are exploring a new funnel without a clear hypothesis

• You notice a drop-off and want to identify potential causes

• You want to validate whether specific user groups or behaviors are influencing conversion

• You are monitoring changes in funnel performance and need to explain what shifted

By surfacing statistically significant behaviors and attributes, Conversion Drivers gives you a starting point for deeper investigation and helps you move faster from observation to insight.

Available Now

Conversion Drivers are available on any funnel for customers on the Pro plan or Enterprise customers with the Advanced Analytics package. Click on a step and select “View Drop-Off & Conversion Drivers” to get started.

Multi-Variant Support for Dynamic Configs

Dynamic Configs just got more powerful. You’re no longer limited to a single config value and a fallback. With multi-variant support, you can define multiple named JSON variants and control which one is served - all from the Statsig console, no deploys required.

🧠 Real-world Example

Let’s say you’re using a third party messaging service. You use Twilio, but want a fallback in case it goes down, and you’re testing AWS SES for cost savings.

With Multivariate Dynamic Configs, you can:

• Define config variants for each provider

• Roll traffic to AWS SES for 5% of users to validate integration

• Failover to Sendgrid if Twilio has an outage

• Tune timeouts and retry logic on the fly - no redeploys

⚡️ Available Now

We will be rolling out Multivariate Dynamic Configs to all Statsig customers over the next few weeks. If you'd like to get an early access, please reach out.

📼 Playlists in Session Replay

You can now group replays into Playlists to curate and share the sessions that matter most.

What You Can Do Now

• Add a replay to an existing playlist or create a new one directly from the replay viewer

• Access all your saved playlists from the new “Playlists” tab next to “Sessions”

• Cycle through playlist sessions without returning to the full list view

How It Works

From any replay, click the “Add to Playlist” button to save it. You can either select an existing playlist or create a new one on the spot. The Playlists tab lets you view and play through a sequence of sessions in one place.

Impact on Your Analysis

Playlists make it easy to gather replays related to:

• Bugs or usability issues

• Experiment test groups

• Feature launches or onboarding flows

They’re ideal for sharing context across teams without needing to repeat yourself.

Try building a playlist for your next launch review or bug triage session.

🧑‍💻 Revamped Users Tab

We’ve redesigned the Users tab in Metrics Explorer to make it more useful out of the box and more powerful when you need to dig deeper.

What You Can Do Now

• View recent users instantly

  Landing on the Users tab now shows a live sample of recent users with basic info, so you can immediately start exploring.

• Filter to specific user sets

  Narrow the list by applying filters based on:

  • User properties (e.g. country, plan type)

  • Events performed (e.g. signed_up, clicked_button)

  • Experiment or feature gate group (e.g. users in treatment vs control)

How It Works

You’ll see a sample of recent users as soon as the tab loads with no query required. Use the filter panel to drill down into any segment you care about. For example:

• Find users who dropped out of a funnel after the second step

• See only users in the “new-nav-rollout” feature gate

• Inspect event history for users on a specific pricing tier

Impact on Your Analysis

Filtering to specific sets of users helps you move from high-level trends to concrete user behavior. You can:

• Debug feature exposure by confirming which users were actually in a gate or experiment

• Investigate drop-offs by checking what users did before and after a key event

• Validate hypotheses about certain user groups, like whether trial users behave differently than paid ones

🎯 Segments in Funnels and Metrics Explorer

You can now create and analyze Segments directly from Funnels and use them in Metrics Explorer for deeper, follow-up analysis.

What You Can Do Now

• From Funnels: Create a new Segment from users who did or didn’t convert at a given step.

• In Metrics Explorer:

  • Filter your chart to only include users in a Segment.

  • Break down results by whether users are in a Segment.

• Segment Type: Currently limited to ID List-based Segments (max size: 1000 users).

How It Works

When viewing a funnel chart, you’ll see a new option to “Create Segment” next to conversion results. Clicking it will generate an ID List-based Segment you can name and save.

In Metrics Explorer, you’ll find Segment filtering under the filter panel, and breakdown by Segment in the group-by dropdown. These options appear only when the Segment is based on an ID list.

Impact on Your Analysis

This gives you a fast, integrated way to dig deeper into interesting groups of users, like understanding what users who dropped off at step 2 did before or after, or comparing behavior between converters and non-converters over time.

Looking Ahead

We’re planning to:

• Support additional segment types beyond ID Lists.

• Remove the 1000-user limit for ID List-based Segments.