---
title: "Transparent MMM — Question it. Trust it. Own it. | Thoughtful Robots"
description: "AI-orchestrated Bayesian MMM. Inspect the evidence, understand uncertainty and own a system built with your team."
source: "https://thoughtfulrobots.ai/transparent-mmm"
---
**Transparent MMM** — a Thoughtful Robots product
# Measurement you can *question, trust and own.*#
AI orchestrates the process using your business context. Tested, versioned statistical engines compute the results.
Assumptions, uncertainty and limits are explicit. Built with your team. Transferred to you. Not SaaS.
- 01 Humans lead Define the objective. Bring business context. Question the evidence.- 02 AI orchestrates Guide the process, translate context into model settings and explain the results.- 03 Statistical engines compute Fit Bayesian MMM, run diagnostics and model scenarios with tested, versioned code.
Tested · Versioned · Reproducible
## Rigorous computation#
Tested, versioned statistical engines.
## Honest uncertainty#
What the data supports—and what it cannot answer.
## No new dashboard#
ChatGPT or Claude, connected through MCP.
## A system you own#
Built with your team. Transferred to you.
## Measurement you can challenge is measurement you can trust.#
Every result includes its evidence trail.
### What went in#
Priors and business context.
### What the data supports#
Estimates, ranges and diagnostics.
### What remains unresolved#
Weak variation and correlated channels.
### What could answer it#
Lift, geo or holdout evidence.
## Where the data cannot answer, we say so—and tell you what could.#
### The channel can be separated.#
Spend varies enough and independently enough. ROI is estimated with uncertainty, supported by diagnostics and checks on assumptions.
### The channels move together.#
The result is marked as uncertain, not presented as a confident channel ROI. This can be a limit of the data rather than a modelling failure.
Conversion-lift study · Geo experiment · Holdout test
Core modelling choices are versioned before final results are interpreted. Changes remain visible.
## Ask any question about the model or its results.#
Probe assumptions, compare alternative media plans or ask how any metric was calculated. If the evidence cannot answer, Transparent MMM says so rather than inventing a misleading explanation.
- Assumptions- Alternative media plans- Metric calculations
Search ROI is estimated at 1.8×–10.4×. That range is too wide for a confident decision. Why is it so wide, and how can we narrow it?
### Why the range is wide#
Search spend varies little and moves closely with Facebook Performance (correlation coefficient r = 0.78) and Instagram (r = 0.72). The model therefore cannot cleanly separate Search’s effect.
### How to narrow it#
Use a geo holdout test, a conversion-lift test or deliberately vary spend to create independent evidence. I can help you design the geo holdout or conversion-lift test.
Facebook Brand ROI is 2.6×—well below what we expected. Why?
### What the evidence supports#
Facebook Brand ROI is estimated at 2.0×–3.2×. The evidence is strong enough to override the initial prior of 6×–12×.
### What the evidence cannot answer#
This data does not show why ROI is lower. I cannot reliably infer a cause, so I will not invent one. Answering that requires a carefully designed experiment.
## Not SaaS. Built with you. Transferred to you.#
- 01 Build A measurement system configured around your business, data and decision process.- 02 Transfer The working system, code and configurations—with knowledge transfer to your team.- 03 Advise Ongoing support when you need it, as your questions and measurement needs evolve.
### Your data does not leave your control.#
Runs inside your controlled environment. Nothing is pooled with another customer or locked inside a vendor portal.
## See what the data can answer—and what evidence to collect next.#
Bring your channels, data and the decision you need to make. We’ll shape the demo around your context.
## Bring us your measurement question.#
We’ll shape the demo around your channels, data and decisions.
## Transparent MMM — original report
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