This page introduces the analysis module, which is key to measuring the
incremental impact of your campaigns. Learn how to prepare your data, understand
counterfactual modeling, leverage design-aware inference, and use your reporting
outputs for marketing mix model (MMM) calibration.

## Prepare your analysis

To begin the analysis, prepare for pretest and test period time
series data, such as new cost and conversion data. The analysis module
seamlessly leverages *provenance information* ---the specific design
configurations, analysis methodology, and geo assignment generated during the
earlier study design phase. Both the original design and the time series data
are required during the pretest and test periods to ensure that the analysis of
the incrementality effects and associated confidence intervals are calculated
accurately. For more information, see [Prepare your analysis data](https://developers.google.com/meridian/geox/prepare-your-analysis-data).

## Counterfactual modeling

To calculate the actual incrementality of your campaigns, Meridian GeoX
framework relies on counterfactual modeling, primarily time-based regression
(TBR) methodology. For more information, see [Counterfactual modeling](https://developers.google.com/meridian/geox/counterfactual-modeling).

## Robust inference

To determine whether the observed lift is statistically significant, Meridian
GeoX employs an advanced methodology called *design-aware inference* . This
approach solves the methodological challenges of other standard inference
frameworks, which often fail for GeoX. Our robust inference approach
ensures precise p-values without inflating the type-I error, while also
maximizing statistical power for your study. For more information, see
[Robust inference](https://developers.google.com/meridian/geox/robust-inference).

## Moving forward: Outputs and MMM calibration

The final output of the analysis phase provides you with actionable metrics,
including the point estimate of incremental conversions (lift) and percentage
lift, along with associated confidence intervals and p-values for these metrics.
You can also find metrics like the incremental conversion per dollar
(iCPD)---equivalent to incremental return on ad spend (iROAS) if revenue data is
used---accordingly. You can generate visualizations of these results for a
deep-dive analysis. These outputs can be adjusted if needed and exported as
custom, data-driven priors to calibrate your Meridian model for enhanced
long-term measurement. For more information, see
[Analysis outputs](https://developers.google.com/meridian/geox/analysis-outputs) and
[Calibrate Meridian priors with Meridian GeoX results](https://developers.google.com/meridian/docs/advanced-modeling/set-custom-priors-past-experiments).