After every analysis, MMM Pilot automatically generates an AI-powered evaluation report. This removes the guesswork of manual statistical inspection and provides a clear roadmap toward more accurate models with every iteration.
Automatic AI Evaluation
Once a run completes, the platform sends the model outputs—including fit statistics, contribution breakdowns, and visual data—to an AI model for structured analysis.
What the Evaluation Covers
The AI evaluation report translates technical data into actionable business intelligence:
| Section | What It Contains |
| Model Fit Assessment | An analysis of overall accuracy (such as R-Squared). It notes if the model is capturing market dynamics effectively or if it needs adjustment. |
| Contribution Breakdown | A review of whether channel impacts align with your actual spend and industry benchmarks. This flags results that don’t seem plausible. |
| Spend Efficiency Analysis | An assessment of your response curves to identify which channels are hitting diminishing returns and which have room to grow. |
| Budget Recommendations | A summary of suggested reallocations, highlighting where you can shift budget to maximize your total impact. |
| Overall Assessment | A high-level verdict on the model’s reliability, helping you decide if the results are ready for client presentation. |
Diagnostic Mode
For those who want to look under the hood, Diagnostic Mode provides deeper technical transparency:
- Summary of fields, paid channels, and processing iterations used.
- Detailed parameter analysis for every marketing channel.
- Observations on data quality, such as coverage gaps or variance issues.
AI-Generated Visual Insights
Every chart produced—from impact breakdowns to spend efficiency curves—includes an individual AI-generated description.
How It Works
- The AI analyzes the visual data alongside your specific field names and model parameters.
- It generates a description that explains exactly what the chart shows in plain English.
- Descriptions use your human-readable labels (e.g., “Google Search Ads”) so everyone understands the context immediately.
Benefits
- Clarity: Stakeholders can understand complex outputs without needing a background in statistics.
- Professionalism: Reports shared with clients include clear, self-explanatory annotations that build trust.
Suggested Model Refinements
Following the evaluation, the system provides refined setting recommendations to improve your next run.
How It Works
- The AI analyzes how your channels respond to spend and identifies where the model can be tightened.
- Based on these patterns, it suggests optimized bounds for your model parameters.
- These suggestions are delivered as a one-click action on your Results page.
One-Click Iteration
- Navigate to your completed run results.
- Select “Run with Suggested Refinements” to open a pre-populated configuration.
- The system automatically applies the AI-suggested bounds while keeping your original mappings.
- Review the settings and start the new run to see your improved results.
This creates a fast, empowering cycle: Run → Evaluate → Refine → Re-Run. You move toward an optimal model with professional precision and minimal manual effort.
Iteration Workflow
The platform is built to support your journey from raw data to confident strategy:
| Step | Action | Outcome |
| 1 | Run initial model | Establish your baseline and receive AI feedback. |
| 2 | Review AI suggestions | Discover clear opportunities for model refinement. |
| 3 | One-click re-run | Generate an improved model with higher precision. |
| 4 | Finalize your plan | Secure a converged, production-ready model for your business. |
Every run is saved with its full configuration, allowing you to compare iterations and maintain total control over your attribution story.