Geo-Based Incrementality Testing

Prove The True Impact of Your Marketing

Leverage the easiest geotesting platform to design & deploy experiments for measuring true lift.

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Rigorous, Fast & Automated Measurement

Ditch the manual and time consuming way of running incrementality tests. Get started with few clicks, no marketing scientists required.

Manual Geo Experiments

  • Analyst struggle to find accurate matching regions

  • Several months to crunch data to get final test results

  • Under-powered; sample bias

Lifesight’s Geo-based Incrementality Testing

  • Design & deploy tests in minutes

  • Dashboard with results, live in as little as just 3 weeks

  • Up to 95 % confidence; feeds MMM & attribution seamlessly

Get True Incrementality Insights In Just a Few Weeks

Conventional geo-testing is expensive, time-consuming & takes data science expertise. Lifesight makes it easy to design, deploy complex tests and get accurate, true lift insights in as little as few weeks.

Accurate Geo-Matching Algorithms

Say goodbye to poor region matching and sample bias. Our algorithms auto-cluster test and control regions with minimal variance using advanced synthetic control algorithms.

Accurate Geo-Matching Algorithms
Always on Testing Made Easy For Everyone - Lifesight

Always-on Testing Made Easy For Everyone

Easily design and deploy geo-tests without code, and ensure you are always in test and learn mode. No data scientist required.

Smart Experiments That Saves Your Budget

Measure true incremental lift with less budget and time compared to classic tests. Our proprietary geo-lift algorithm delivers 95%+ confidence results faster and cheaper.

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Validate Calibrate your MMM Automatically - Lifesight

Validate & Calibrate your MMM Automatically

Validate your MMM insights & improve the accuracy of your model by calibrating it with your geo-test learnings automatically with 1-click.

When to run geo-based incrementality test?

Measure existing channels

Measure the incremental lift of a channel or campaign to ensure real results.

Measure channel saturation

Identify when increased spend leads to diminishing returns through experiments.

Measure new channels

Minimize ad spend waste by testing new platforms in select markets before scaling.

Geo-based incrementality testing

Geo-based Incrementality Testing in Lifesight’s UMM Framework

Geo-based incrementality tests continuously calibrates real-time attribution with incrementality and MMM insights, ensuring every budget decision is grounded in truth, not assumptions.

  • 1-click MMM calibration

  • Always-on attribution adjustments

  • Automated hypotheses recommendations

  • Enables accurate forecasting

Designing, Deploying & Adopting a Geo-based Experiment

Guided test design process

Generate hypothesis, choose experiment type, select markets & ensure feasibility.

Automated/manual deployment

Execute the design with accuracy over recommended duration of weeks and constantly monitor.

Analyze & adopt tests results

Leverage successful test results to calibrate MMM & attribution insights to power spend decisions.

Frequently asked questions

When you need channel-level truth that’s independent of user tracking—validating a new channel, auditing a big spender (retargeting/brand search), or sizing halo (RMN ↔ DTC, CTV ↔ Search).

Matched markets, stepped-wedge/“rolling thunder”, central-control, and synthetic control. We pick based on power, timeline, and operational risk.

We compute power & MDE from your baseline volume and expected lift. Typical windows: 4–6 weeks with 8–30 matched regions.

Risk is managed via staggered exposure, minimum presence rules, and auto-stop thresholds. We stop early if outcomes breach guardrails.

Prefer sales/revenue (for iROAS), plus new customers, CAC/NCAC, and—when specified—leading indicators (traffic, branded search).

A validated lift calibrates MMM curves and updates iAttribution multipliers. You’ll see the change in the Planner and Optimization queue.

Yes-multi-cell designs (“rolling thunder”) let you read continuously with less disruption and faster learn→apply cycles.