Geo-based Incrementality Testing

Stop Wasting 20% of Your Ad Spend on Conversions That Would Have Happened Anyway

Identify redundant spend and prove true incrementality with the world’s most automated geo-testing platform. Move beyond inflated platform ROAS to find the causal truth.

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The Leader in Unified Marketing Measurement

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Ad Spend Measured
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Companies Trust Us
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Average Sales Lift
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Unified Platform

Actionable Causal Insights in Just 21 Days

Traditional incremental geo-testing takes months of manual data science. Lifesight automates market pairing and analysis so you can optimize budgets in weeks, not quarters.

Day 1

Auto-Cluster Markets

Our algorithm automatically pairs similar geographic markets using synthetic control methodology – eliminating weeks of manual data science.

Automated

Day 3

Launch Test

Deploy your holdout geo-experiment with a single click. One region runs your campaign; the matched region serves as the control – capturing true incremental lift.

1-click Deploy

Day 21

Analyze & Reallocate Spend

Receive statistically significant results at 95%+ confidence. Immediately identify over-credited channels and reallocate budget to maximize incremental returns.

95% Confidence

3 – 6 Months

Traditional geo-testing with manual data science

21 Days

Lifesight automated geo-testing platform

One Version of the Truth Across Every Time Horizon

Geo-testing is the calibration engine that ensures your MMM and Causal Attribution models all speak the same language – causal reality, not platform – reported correlation.

Geo-Testing

The Source of Truth

Establish the causal ground truth. Geo-testing isolates incremental lift by creating perfect experimental and holdout markets. Results calibrate every other measurement model in your stack.

Causal MMM

Strategic Budget Planning

Long-term, channel-level budget optimization. Geo-testing results flow directly into Causal MMM to ensure your media mix model reflects real – world incrementality – not correlation artifacts.

Causal Attribution

Real-Time Campaign Optimization

Granular, always-on attribution for every touchpoint. Powered by the same causal coefficients established in geo-testing, giving you a single consistent version of truth across all time horizons.

Geo-testing results automatically calibrate your MMM and Causal Attribution coefficients – ensuring all three layers share a single causal foundation.

Proven results that speak for themselves

Sidenstickers

Seidensticker achieves 11.5% higher revenue with 11.7% lower ad spend

11%
Higher revenue

11.7
Lower ad spend

obvi logo

How Obvi Proved CTV Drove Walmart Sales

5%
Lift in retail sales

95%
Confidence in data accuracy

Everything You Need to Prove Incrementality.

Every feature is designed to reduce friction between running a test and
reallocating budget with confidence.

Automated Geo-Matching Algorithms

Synthetic control algorithms automatically identify and pair the most statistically similar geographic markets. No manual data science required – reducing setup from weeks to hours.

95%+ Statistical Confidence

Every test result ships with rigorous p-value and confidence interval reporting, ensuring you only act on results that are statistically meaningful – not noise.

1-Click MMM Calibration

Geo-test results are automatically injected as calibration priors into your Causal MMM. Keep your media mix model accurate as markets, channels, and behaviors evolve.

Omnichannel Halo Capture

Geo-testing measures total business impact across online and offline touchpoints – including how a Meta ad drives a search conversion or an in-store purchase.

Always-On Testing Framework

Measure the incremental lift of evergreen campaigns without long-term media blackouts. Continuously calibrate your model as consumer behavior and channel saturation evolve.

Causal Attribution

Real-time, granular campaign optimization powered by causal coefficients established through geo-testing. Every attribution report reflects the same causal truth as your MMM.

Seamless integrations to all your data

Seamless integrations to all your data

Frequently asked questions

Platform-reported ROAS often credits ads for sales that would have happened organically. Inflated ROAS gives you a false sense of security – you may be overspending on channels that are simply capturing intent that already existed. Incrementality shows you the actual growth you wouldn’t have had without the spend, letting you make budget decisions grounded in causal reality, not correlation.

We use advanced synthetic control algorithms to pair similar geographic markets. One market runs your campaign (treatment); the other serves as a holdout with no media exposure (control). By comparing the two, we isolate the exact lift created by your media – free from confounding variables like seasonality, organic demand, or competitive dynamics.

Most tests reach statistical significance in 21 to 30 days, depending on your baseline sales volume, campaign budget, and the magnitude of the effect you’re measuring. Higher baseline volume means faster significance. Our platform provides live power calculations during setup so you know exactly how long your test needs to run.

Yes. Our Always-On testing framework allows you to measure the baseline lift of core campaigns without long-term media blackouts. Instead of switching off campaigns entirely, we rotate holdout markets on a rolling basis – giving you continuous incrementality measurement without sacrificing revenue or efficiency.

Consumer behavior and channel saturation are dynamic. A channel that was highly incremental six months ago may now be primarily capturing organic demand. Competitor activity, seasonal shifts, and campaign frequency all affect the true lift your media delivers. We recommend periodic geo-tests – typically quarterly – to refresh your calibration factors as markets evolve.

Geo-testing captures the total business impact of your media investment – including cross-channel spillover effects. Because we measure actual business outcomes (revenue, conversions, in-store visits) at a geographic level, we capture how a Meta ad might drive a branded search query, or how an OOH campaign accelerates e-commerce purchases. This omnichannel lift measurement is something last-click and MTA models fundamentally cannot do.