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Why Every Test Should Improve the Model

The Incrementality Testing Suite is built around one principle: every experiment you run should make your model more accurate than it was before. Here's how it does that.

Platform reporting conflates captured demand with created demand, inflating the apparent performance of channels that intercept intent rather than generate it. The Incrementality Testing Suite isolates causal lift by running controlled geo experiments, interpreting results as ranges rather than single lift numbers, and feeding those findings directly back into your AMM as calibration inputs. The result is a test-calibrated MMM that gets more precise with every experiment you run, and a budget allocation you can defend with causal evidence, not modeled averages.

From Experiment to Budget Decision

Three capabilities that make every marketing incrementality test auditable, precise, and directly actionable inside your model.

Transparent Geo Selection

Transparent Geo Selection

Not every channel calls for the same test design, and geo selection should follow the same logic. LiftLab supports both Stratified Random Sampling and Synthetic Controls, deploying each where it performs best. The methodology is fully auditable, so Finance can interrogate the geo-selection process rather than accept the output on faith.

Enterprise-Grade Flexibility

Enterprise-Grade Flexibility

LiftLab supports Switchback tests for high-volatility environments, Strategy experiments for campaign-level shifts, and Go Dark with Pacing to map saturation curves with precision. Each design is matched to your measurement objective, not applied as a default template because it was easiest to build.

Detect Spend Contamination

Detect Spend Contamination

Ad platform spillover corrupts incrementality measurement. LiftLab proactively detects and corrects for effects like Performance Max automatically reallocating to Shopping in suppressed Geos’, so your causal measurement stays clean, and your budget decisions stay grounded in reality rather than contaminated platform data.

How Incrementality Testing Suite Works

The AMM Guides You

The AMM Guides You

The Agile MMM identifies channels with the widest confidence intervals and the least experimental validation, so every test targets the decision with the highest planning risk, not the channel that's easiest to measure.
Match Design to Decision

Match Design to Decision

Choose an auditable, empirical test design tailored to your objective: Switchback, Strategy, or Pacing. No guesswork. No one-size-fits-all templates.
Find Diminishing Returns

Find Diminishing Returns

Execute pacing experiments that deliberately vary spend to build robust response curves. Know exactly where returns flatten before you overspend, and feed those saturation points directly back into your AMM for the next planning cycle.
Refine the Model

Refine the Model

Causal results feed directly into the AMM through the Trust Engine, adjusting internal saturation parameters and tightening response curves. Each experiment permanently sharpens the model, so reallocation decisions compound in precision rather than reset with every planning cycle.
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The Output: Experiment
Dashboard & Insights

  • Experiment Dashboard

    Experiment Dashboard

  • Find Your Saturation Point

    Find Your Saturation Point

  • Transparent Geo Selection

    Transparent Geo Selection

  • The Trust Engine Loop

    The Trust Engine Loop

Featured Story

Unlocking Global Jewelry Growth with mROAS

Unlocking Global Jewelry Growth with mROAS

Pandora paired agile MMM with geo tests to shift just 2% of the budget, driving +9.5% revenue and +12.4% profit across key channels.​

"LiftLab's platform has been instrumental in helping us bridge the gap between long-term strategic goals and the need for frequent and short-term optimization."

Kasper Madsen,

Kasper Madsen,

Global Paid Media Analytics Manager, Pandora

See the Results for Yourself

Frequently Asked Questions

Most standalone tools run a test and return a lift number. LiftLab's Incrementality Testing Suite feeds every causal result directly back into your Agile MMM as a calibration signal, tightening response curves and sharpening saturation parameters. The test doesn't end at a lift percentage. It permanently improves every budget decision the model supports from that point forward.
Turn Your Next Incrementality Test Into a Model Calibration Signal

Go Deeper

Marginal ROI Optimization

Marginal ROI Optimization

Stop overfunding saturated channels. Find your exact point of diminishing returns to maximize your next best dollar. 

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Scenario Planning & Forecasting

Scenario Planning & Forecasting

Run constraint-aware budget scenarios to predict outcome ranges, set guardrails, and confidently align marketing with finance. 

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Why LiftLab

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(+1) 888-302-3861

marketing@liftlab.com

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