Lifesight vs Google Meridian
Compare Lifesightβs guided, end-to-end marketing measurement platform with Google Meridianβs open-source Bayesian MMM framework and choose the approach that fits your team, data, and measurement goals.

















































Go beyond open-source MMM with a complete, activation-ready unified marketing measurement platform.
Meridian provides the code, documentation, and modeling framework for teams to build and operate their own MMM. Lifesight provides a unified marketing measurement platform that brings together data integration, mixed media modeling, validation, causal attribution, and real-time optimization, allowing brands spend less time building measurement infrastructure and more time acting on insights.
Lifesight combines MMM with incrementality testing and causal attribution to help teams understand both overall marketing contribution and incremental impact.
Lifesight is designed to measure more than paid media. Its MMM approach can incorporate paid, owned, and earned media alongside pricing, promotions, distribution, competition, seasonality, brand factors, and other business drivers. This helps brands understand what is actually driving growth, not simply where media spend was placed.
Lifesight is built to connect measurement with planning and optimization. Brands can use measurement outputs for scenario planning, budget forecasting, and media optimization, helping teams move from βWhat happened?β to βWhat should we do next?β
Methodology
Lifesight connects each stage within a guided measurement workflow. Google Meridian provides an open-source modeling framework that teams configure, operate, and integrate into their own measurement stack.
Lifesight
01
Connect
Sync ad platforms, sales systems, CRM data, offline sources, and relevant business variables. Standardize marketing, media, and outcome data inside the platform.
02
Model
Map the causal structure of the business, account for carryover and saturation, and estimate media and non-media effects. Generate response curves, incremental returns, and forecast-ready outputs.
03
Calibrate
Use geo-lift and other experimental evidence to update model assumptions. Apply MMM- and experiment-derived incrementality factors to causal attribution so granular performance reporting reflects incremental impact rather than platform-reported credit.
04
Act
Marketing Intelligence Agents compare budget scenarios, forecast revenue and profit, and identify marginal returns, then push approved budget changes straight to the platforms in one click. New experiments and refreshed data strengthen the next measurement cycle, sharpening what the agents recommend next.
Google Meridian
01
Ingest
Assemble the target KPI, media exposures, media spend, control variables, geographic and time dimensions, and reach or frequency data where relevant.
02
Transform
Clean and aggregate the dataset, resolve missing values, define treatments and controls, configure adstock and saturation assumptions, and set channel-specific priors.
03
Infer
Run Google Meridianβs Bayesian model and MCMC sampling process to estimate posterior distributions, incremental outcomes, ROI, mROI and response curves.
04
Validate
Check convergence, model fit, baseline plausibility, prior-to-posterior behavior and overall model health. Generate reports and budget optimization scenarios, then implement the decisions through internal systems.
A side-by-side look at how Lifesight and Meridian differ in modeling, implementation, experimentation, and team requirements.
| Capability | Lifesight | Google Meridian |
|---|---|---|
| Measurement | ||
| Marketing mix modeling (MMM) | Included | Included |
| Incrementality testing | IncludedIntegrated incrementality measurement | PartialAccepts external experiment data as calibration input; doesnβt run tests |
| Causal attribution | Included | Not includedNot a core Meridian capability |
| Experiment calibration | Included | Included |
| Unified marketing measurement | Included | Included |
| Planning & activation | ||
| Forecasting | Included | Included |
| Budget optimization | Included | Included |
| Scenario planning | Included | Included |
| Measurement-to-action workflow | IncludedIntegrated | Requires additional systems |
| Implementation & support | ||
| Guided implementation | Included | Not included |
| Expert measurement support | Included | Not included |
| Integrated data connections | Included | Not includedRequires external data pipelines |
Who it is for
Choose based on the team you have and the operating model you want.
Lifesight
You need decisions, not another internal modeling project.
Google Meridian
Building and owning the modeling system is part of your strategy.
A few useful answers
Google Meridian is an open-source marketing mix modeling framework from Google designed to help teams build and analyze Bayesian MMM models.
Google Meridian is an open-source MMM framework that teams configure and operate themselves. Lifesight is a guided marketing measurement platform that combines MMM with incrementality testing, causal attribution, forecasting, and optimization.
Google Meridian is open-source software, but organizations may still incur costs for implementation, data engineering, infrastructure, compute, model development, maintenance, and technical resources.
Yes. Lifesight can serve as an alternative for organizations looking for a guided marketing measurement platform rather than building and maintaining their own MMM infrastructure.
It depends on the operating model. Google Meridian is suited to technical teams that want open-source model ownership and customization. Lifesight is suited to teams seeking a guided platform connecting measurement with experimentation, attribution, forecasting, and optimization.
No. Lifesight runs its own causal MMM methodology, integrated natively with incrementality testing and attribution. It is a separate platform, not a wrapper around Google Meridian or any third-party framework.
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