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AI agent for product analysts

Experiment Ship Decision Follow-Up Agent

Confirm that shipped experiment wins hold up in production and flag them early when they do not.

Experiment Ship Decision Follow-Up Agent: what goes in, what the agent does and what you get

What it does

After a winning test ships, the team moves on and nobody checks whether the lift held. This agent tracks the live metric after rollout and compares it with the lift expected from the test. It checks for novelty decay, where the lift fades after a few weeks, and splits the result by segment, such as new and returning users or platform. If results drift from the test result by more than your threshold, it writes a follow-up note with the data. If needed, it proposes a holdout group to measure the true effect. You review the note and decide what goes to the product team. Edge case: the lift holds on web but is gone on Android, and the agent shows that split.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedYes, continueNoNo 1 STARTS WHEN Test is shipped to all users 2 USES A TOOL Pull the live metric since the rollout date 3 DOES Compare the live lift with the test result and range 4 USES A TOOL Split by segment and week 5 CHECKS THE RESULT Is the live lift inside the expected range? If not: Check for novelty decay, seasonality andtracking changes. Back to step 3. 6 DOES Rank the likely causes of the gap 7 USES A TOOL Draft a follow-up note with charts 8 YOU APPROVE Analyst approves the note and any holdout proposal 9 USES A TOOL Send the note to the product team 10 CHECKS THE RESULT Does the next week's data confirm the pattern? If not: Keep tracking and update the note. Back to step3. 11 RESULT Post-launch result summary
Read the steps as a list
  1. Test is shipped to all users
  2. Pull the live metric since the rollout date
  3. Compare the live lift with the test result and range
  4. Split by segment and week
  5. Is the live lift inside the expected range?If not: Check for novelty decay, seasonality and tracking changes. Back to step 3.
  6. Rank the likely causes of the gap
  7. Draft a follow-up note with charts
  8. Analyst approves the note and any holdout proposalThe agent waits here for your OK.
  9. Send the note to the product team
  10. Does the next week's data confirm the pattern?If not: Keep tracking and update the note. Back to step 3.
  11. Post-launch result summary

How it decides

It compares the live lift with the test's confidence range. A result outside the range for two weeks in a row counts as drift.

  • Two weeks outside the range counts as drift (default)
  • Segments with under 1,000 users are not reported alone
  • Always check tracking and seasonality before blaming the change
  • Recommend a holdout only when the cause is unclear

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Tracking period (default 8 weeks)
  • Drift rule
  • Segments to split by
  • Minimum segment size
  • Who receives the note

What keeps you in control

It always asks you first

  • Follow-up note before sharing
  • Holdout proposal

Hard limits

  • Never reverts a feature
  • Never reports a segment under the size limit
  • Shows the data behind every claim

It stops when

  • Done: eight weeks tracked and the result confirmed or explained
  • Stop: metric tracking is broken; analyst fixes the data first

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensA new checkout button showed +3.2% conversion in the test. In week 3 live data showed +1.1%, below the 2.0 to 4.4% range. The check failed, so the agent split by device. Desktop held at +3.0%, mobile fell to -0.4%, after an app update. It drafted a note, and the analyst sent it with a holdout proposal for mobile.

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