SmartInferYour dashboard says Meta ROAS is 4.2. Is that enough to move next quarter’s budget?
Galileo combines an identifiability-aware marketing mix model with an evidence-grounded AI agent. The model estimates channel response, uncertainty, and budget scenarios from weekly spend and outcome data. Its credibility checks flag estimates the data cannot separate and distinguish actionable recommendations from decisions that require additional evidence or a test. The agent lets teams interrogate computed results and run model-backed scenarios while keeping quantitative answers bound to engine output.
Why not the dashboard you have
A recommendation you can interrogate before you act
- Independent. Galileo estimates channel response from weekly business data rather than accepting each platform’s self-reported attribution.
- Explicit about method. The model represents saturation, carryover, baseline demand, and uncertainty — and reports when the data cannot separate a channel effect.
- Traceable. Quantitative answers remain tied to computed model output rather than being invented by the language model.
- Bounded by evidence. When an estimate is too uncertain to support reallocation, Galileo recommends additional evidence or a test instead of presenting false precision.
How Galileo works
From model output to a justified decision
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Model
Galileo fits an identifiability-aware marketing mix model to weekly spend and outcome data. It estimates channel response, uncertainty, saturation, and budget scenarios under stated modeling assumptions.
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Credibility
Galileo checks whether the available data can separate the quantities required for the decision. It flags uncertain channel effects, states material caveats, withholds unsupported reallocations, and identifies where additional evidence or a test is required.
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Agent
Once the analysis exists, the Marketing Scientist agent lets a team interrogate it, run model-backed scenarios, and examine the evidence behind a recommendation. Quantitative answers remain bound to computed engine output.
A recorded session
What working with Galileo looks like
This replay uses captured engine output from a synthetic demonstration. The confirmation table, model-backed scenario, uncertainty interval, and refusal come from Galileo’s tools rather than being written as marketing examples.
The data
What Galileo reads
Galileo works from one row per week: the date, spend in each channel, and one business outcome. At least 26 weeks are required; 52 or more are preferable.
Revenue supports model-based ROAS, marginal-return estimates, and financial budget scenarios, subject to the credibility assessment. Orders or conversions support outcome-specific efficiency analysis. Sessions or clicks produce a traffic-response model only, without financial budget recommendations.
You provide one outcome for the business or product scope being modeled — not outcomes already attributed to individual channels. Galileo estimates channel-level contributions under the model, with uncertainty and credibility limits.
No tags, pixels, or platform integrations are required. The input is a weekly CSV.
Private pilots
What a Galileo pilot looks like
After an initial call, Galileo can be run on your data without a platform integration.
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Prepare the weekly data
Prepare the weekly dataset described above. Intake checks flag missing fields, insufficient history, and channel patterns the data may not be able to separate. See exactly what to send →
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Build the model and assess credibility
Galileo produces channel-response estimates, uncertainty ranges, saturation curves, and budget scenarios. The credibility assessment states which conclusions the evidence supports, which carry material caveats, and which require a test.
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Interrogate the analysis
The Marketing Scientist agent lets your team explore model-backed scenarios, inspect why a recommendation was made, and follow its evidence trace.
Evidence before confidence
Two different questions must be answered
Credibility
Can the available evidence support this conclusion or recommendation?
Galileo evaluates data sufficiency, uncertainty, separability, material caveats, and whether a recommendation should be acted on or resolved through additional evidence.
Report integrity
Does the report faithfully represent the computed model output?
Separate integrity checks compare totals, intervals, response curves, recommendation language, provenance, and other internal relationships before a report is released.
A report can be internally consistent while the underlying data remains insufficient for confident action. Galileo treats those as different conditions.
Bloom & Co. · Synthetic demonstration
52 weeks · 6 channels · Historical fit: R² 0.941
Despite the strong historical fit, all six channel coefficient intervals included zero. Galileo therefore marked every channel TEST rather than presenting a reallocation as supported.
Sample reports
- American Heritage Leather →Synthetic example with tighter channel estimates
- Bloom & Co. →Synthetic example where the data cannot support confident channel action
Evidence & research
Executive resource
Executive Capital Allocation Brief
A CFO-oriented guide to reading a marketing mix model. Delivered after a short form.
As new evidence arrives
A model that can refuse an update
Galileo is designed to compare new outcomes with the expectations of the existing analysis. When new weeks remain compatible with that analysis, the evidence can be updated and prior recommendations tracked as:
consistent · inconsistent · evidence accumulating
When new data crosses the drift gate, Galileo refuses an incremental update and calls for a full refit. The recorded session above shows that refusal.
Questions
FAQ
What is marketing mix modeling?
Marketing mix modeling examines how aggregate business outcomes varied with channel spend over time while representing saturation, carryover, baseline demand, and seasonality. It estimates channel response under stated assumptions; observational MMM does not by itself prove causal incrementality.
What data do I need?
Weekly channel spend and one business outcome. At least 26 weeks are required; 52 or more are preferable. See data requirements →
Can I try it on my data right now?
Not on this marketing site. Sample reports and a recorded session are here; your data runs in a private pilot after a call.
What if my spend has been flat?
If a channel has barely varied, the data may not be able to separate its effect from baseline demand or other channels. Galileo flags that limitation instead of presenting an unsupported channel estimate.
We sell several products and advertise them on different channels.
Model a product separately only when it has its own spend and outcome history. Otherwise, Galileo operates at the aggregate business scope represented in the input data.
Private pilots
Pilot pricing
Galileo is available through a limited number of private pilots. Each begins with a review of whether the available data can support the intended decision. Pricing and scope are set after that review.
If Galileo cannot serve the data honestly, SmartInfer will say so before the pilot proceeds.