NoiseGrasp brings MMM into the modern era with AI-powered automation, fast deployment, and privacy-safe data handling. Unlike traditional models that take months and perfect data to build, our approach is faster, more flexible, and built to work with your actual marketing reality.
How NoiseGrasp Builds Smarter Marketing Models
For Agencies
Strategic Edge
Strategic Edge
For Advertisers
With NoiseGrasp, you get clear answers about what’s driving performance. Our platform helps marketing teams prove ROI, eliminate wasted spend, and forecast future impact based on real-world behavior. You’ll make faster decisions, defend your budget, and scale what works.
AI That Learns From Your Marketing Reality
Our models learn from your actual inputs — spend, conversions, channels, seasonality — and produce decision-ready insights without weeks of manual calibration. That means faster setup, smarter results, and more actionable recommendations from day one.
AI That Learns From Your Marketing Reality
Model development and experimentation are powered by Jupyter Notebooks and PyTorch, giving our team the flexibility to prototype and productionize cutting-edge attribution and MMM algorithms quickly. The result? Fast model refreshes, real-time scenario testing, and performance that scales — without requiring a full-time data science team on your side.
AI That Learns From Your Marketing Reality
NoiseGrasp’s modeling engine is built on advanced econometric foundations, but what makes it different is how it’s engineered for real-world marketing. At its core, the platform uses a Bayesian algorithm structure to model uncertainty and quantify confidence in predictions, giving you not just results, but trust in those results.
We apply a Transport Gaussian Process for smooth, data-efficient learning across campaigns and timeframes, and we leverage Scale-Free Parameterization to ensure model adaptability across brands, geographies, and channel mixes. Every model is shaped by our proprietary algorithm, specifically tuned for marketing mix modeling and media incrementality.
Built For A Cookieless, Data-Challenged World
NoiseGrasp was designed with privacy in mind — no tracking, no pixels, no hacks. Our models don’t rely on cookies or user-level data, so you stay compliant with today’s privacy standards (and tomorrow’s too).
Even more importantly, we work where other tools fail. Whether your data is noisy, incomplete, or lives across multiple spreadsheets, NoiseGrasp can still model true incrementality and performance. We meet you where you are and help you move forward.
Common Questions
What if our data is messy, in Excel spreadsheets, or split across multiple agencies?
That is the daily reality for 90% of our users, so don’t worry. We don’t need you to have a perfect Data Lake. To keep things simple, we use a standardized time-series “Data Template” in Excel. You just pour your information in there, and the model does the rest.
How do you measure true incrementality versus what digital platforms already report?
If you add up what digital platforms report separately, you will get an unreal and duplicated sales volume. NoiseGrasp’s MMM applies a top-down approach: it doesn’t track individual users, but models an “average customer.” This is how we evaluate how that total reacts to a mix of controllable variables (your media) and uncontrollable ones, revealing your true incrementality.
If we start today, how soon will I be able to make decisions using the platform?
Our standard timeframe is 3 to 4 weeks from the moment we have the complete “Data Template.” The first week is for data ingestion, the second and third for Bayesian calibration, and by the fourth week, you will be sitting with our team analyzing your first optimized scenario in our App.
What if we only have recent data or monthly granularity?
It is a valid concern, but by using Bayesian methodology, we don’t need the machine to learn blindly from scratch. We inject prior knowledge or industry benchmarks into the algorithm to compensate for that lack of historical data. This allows us to start strong even with monthly data or just one year’s worth of information.
Does my team need to know statistics or coding to use NoiseGrasp?
No, the platform is designed for any marketer. The mathematical complexity happens in the backend. Plus, we don’t just hand you a login and wish you good luck: you get periodic sessions with our Customer Success team to translate the model’s output into real media buying instructions.
Get In Touch
Speak With Our Team
Not sure where to start? Let’s talk.
Our team will walk you through how NoiseGrasp can solve your specific marketing challenges.
+1 (310) 302 - 7198
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Reach out to our team for any questions, product details, or support—we’ll respond promptly.