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Launch Intelligence

Stop flying blind on launches

Did our launch actually move the needle? Stop waiting on the data team, get answers in minutes.

Right now you're probably:

  • •Asking the data team to pull post-launch numbers, waiting days for a messy spreadsheet
  • •Presenting to the team with "we think it helped"
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Backed by

Nat Friedman
Daniel Gross
Nat Friedman & Daniel Gross
Shine Capital logo
Twine Ventures logo
Guillermo Rauch
Guillermo Rauch
Christina Cordova
Christina Cordova
Adrien Treuille
Adrien Treuille

Trigger insights from the tools you already use

Launch Tracker
Name
Status
Owner
Launch Date
Priority
Checkout Redesign
Launched
SC
Sarah
Jan 15, 2024
P0
Mobile App v2
In Progress
MK
Marcus
Feb 1, 2024
P1
Onboarding Flow
Planning
AR
Alex
Feb 20, 2024
P1
New

Analysis triggered

"Checkout Redesign" status changed to Launched

The Output

The answer to 'did it work?' — backed by the math

Every launch gets a structured report: what moved, by how much, and whether it's real signal or just noise.

Checkout Redesign Launch Analysis

Generated Feb 6, 2026

Published

Key Findings

Signal 1: Step‑change in daily active users

On Feb 6, 2026, daily active users break from the prior stable levels and establish a new level. Before launch, DAU hovered at a long‑run average of 217,444 users/day. Post-launch, DAU clears the upper limits of 303,792 users/day for over 4 consecutive days. This indicates a special cause variation with a new plateau forming at 295,000–300,000 users/day.

  • Peak DAU reaches 342,891, roughly 1.6× the pre‑launch mean
  • This pattern persists for 8 consecutive days above the upper limit
  • Timing aligns with the checkout redesign launch

This represents a statistically significant improvement where user engagement increased dramatically following the release.

Daily Active Users

Reproducible

Daily paid quota consumption Dec 15...

Succeeded

XmR analysis for paid quota consumption Dec...

Succeeded

Daily Active Users

Succeeded
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StarRocks Replica
Checkout Redesign Launch Analysis
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Semantic IndexConnects the codebase to analytics & business context

It already knows your stack

"How many users were exposed to the feature we just shipped?"

Indexes your data warehouse

Knows what data exists and how to query it

Reads your docs and notes

Gets the full context of your question from the PRDs, launch plans, and metric definitions in your connected apps

Scans your codebase repo

Understands *how* the data is actually generated in the code, not just the numbers

Your team ships constantly.
Now every launch gets measured.

See the analysis your last launch would have produced — with your actual data.

(we'll use your actual data)

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