SignalRig.

A media mix model that shows its work · $249 once

SignalRig turns spend and outcome CSVs into calibration curves, holdout accuracy, and plain-language budget verdicts. Fully offline on your Mac. No account. No cloud.

Download on the Mac App Store Watch the 50 second demo Try the live demo

Available now. $249 once, no subscription. Requires macOS 13 or later.

The receipts

2.6%

holdout error

92%

interval coverage

24 of 24

planted truths recovered

Results from the fully worked sample model that ships in the app. Your data earns its own receipts.

02 / Proof

Fig. 01 · MMM Lab

2480 × 1830 px

MMM Lab

Pull the slider. Fitted curves answer.

Move budget between channels and watch two fitted response curves answer back, in leads and in dollars, with a credible interval attached to every number. No adjective grades the trade; a probability does. Every scenario carries a plain-language verdict, not just a chart to decode.

Fig. 02 · Data Drop-In

Data Drop-In screen showing a failing 18 percent readiness score with named errors: missing spend column, malformed dates, and duplicate rows

Shown here: a failing package, on purpose.

1784 × 2340 px

Data Drop-In

Drop a CSV. Watch it get graded.

The screen above isn't the happy path, it's a package that fails on purpose, because that's the honest demo: specific, actionable errors instead of a vague "invalid file." Readiness is scored 0 to 100 against the same contract the model trains on, so the fix list is exact and the score never lies to make you feel better.

Fig. 03 · Model Card

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Model Card

The graded exam no vendor shows you.

Hidden true values, planted in advance, checked against what the model recovered. A twelve-week blindfold forecast, scored on weeks the model never saw. Sampler diagnostics translated out of jargon. Most vendors ask you to trust a score; this is the exam that produced it.

03 / Privacy

Your data never leaves your Mac.

No account No telemetry App Privacy: Data Not Collected Works with Wi-Fi off

Pricing

$249 once.

No subscription. No seats. No upsells inside the app.

The model core is open source under Apache-2.0. The app is the finished instrument built on it.

Available now on the Mac App Store.

Get SignalRig for Mac

Questions before you buy? Email joey@gearedlikeamachine.com.

Learn

MMM 101, the visual cheat sheet

A one-page primer on baselines, adstock, saturation, and marginal cost.

MMM software compared, honestly

Robyn, Meridian, PyMC-Marketing, subscription vendors, and SignalRig, side by side.

What media mix modeling costs

Four price tiers, what each includes, and the costs nobody itemizes.

Frequently asked

Does it fit a model on MY data yet?

Yes. Since 1.0.2 the Mac app fits a model on your own weekly spend and outcome CSVs, entirely on your Mac, and grades the result the same way it grades the sample: holdout error, interval coverage, and sampler diagnostics. If a fit fails its own checks, the app says so and withholds the budget recommendations instead of guessing. The browser demo on this site validates your CSVs and shows the sample model; fitting needs the app.

What data do I need?

A campaign export from Google Ads, Meta, TikTok, LinkedIn, or Microsoft Ads, plus any sheet with a date and an outcome number. SignalRig converts them into its weekly format on your Mac, shows each step it took, and tells you whether your history is deep enough to model honestly.

Is it open source?

The model is: the Stan model and the Swift fitting engine are public on GitHub under Apache-2.0, tests and synthetic fixtures included. The Mac app is the finished instrument built on that engine: the validator, the views, the graded exam presented so a room understands it.

Why offline?

Client spend data is confidential. Software that phones home is a procurement problem and a trust problem. SignalRig makes no network connections, ever.