Testing Agent

Test, validate, act: automatically

The Testing Agent picks the geo-based incrementality test that would shrink the widest uncertainty in your MMM, monitors integrity in-flight, and pushes the lift result back into the model as a posterior update, so next week's allocation is grounded in causal truth. Have a channel you want to try out? The Testing Agent can handle that too.

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What changes

A ranked test queue. Live integrity reads. A posterior update to the MMM the day a test closes.

Which test to run next, ranked by information gain per dollar.
The agent computes expected information gain for every candidate test (how much it would shrink uncertainty about a specific channel), and divides by the foregone-spend cost of running it. Top of the queue is the test with the best information-per-dollar ratio. The math is transparent and overrideable.
A complete test design, ready for sign-off.
Geo splits, holdout share, target MDE, integrity checks — all set to hit 80% power at the channel's expected lift range. The agent produces a one-page brief any analyst on the team can review and approve, and the Execution Agent launches it on-platform once signed off.
Live integrity reads, flagged while the test is still fixable.
Daily reads on geo-pair balance, treatment-control baseline drift, contamination, and sample-size projection against the read date. You hear about integrity problems while the test can still be saved, not on the day you sit down to read it.
The details

Matched-market geo tests with a synthetic-control read: the cleanest causal evidence you can get without burning all your spend.

A geo-based incrementality test splits your markets into a treatment group and a control group, holds spend in one and runs spend in the other, then measures the difference in outcomes. The read isn't “how did the treatment group do?” It's “how did the treatment group do versus what a synthetic control built from the holdout markets would predict?” The gap is the incremental lift, with a confidence interval attached.

In production.
A consumer fintech client running ~$20M/yr in paid media. AppLovin's confidence interval was the widest in the MMM; the agent designed a geo holdout that would shrink it fastest. AppLovin's platform-reported ROAS was 4.77x. The actual incremental lift came in at zero. The posterior update collapsed AppLovin's contribution to near-zero and $500K/yr was reallocated to incremental channels. 16.7x ROI on the test alone.

Install the BlueAlpha MCP to query the Testing Agent from any AI assistant: pull the test queue, inspect any candidate design, check integrity status on a live test, and approve the next design straight from chat. Zero friction.

Installation Guide

Prompt Library

Frequently asked questions

  • We already run geo tests with [vendor]. What does the Testing Agent add?

    What about platform-side experiments (Meta lift tests, Google geo experiments)?

    Geo testing isn't possible for every channel. What about everything else?

    How does the agent decide a test is worth the foregone spend?

    Does the agent launch tests automatically?

Stop testing and forgetting.
Start running tests that change the next allocation.

30-minute walkthrough on your mix. We'll talk you through you the test we'd run first and the channel uncertainty it would shrink.

Book a demo

Stop testing and forgetting.
Start running tests that change the next allocation.

30-minute walkthrough on your mix. We'll talk you through you the test we'd run first and the channel uncertainty it would shrink.

Book a demo

Articles

Articles

Playbooks

Playbooks

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