AI-powered Incrementality Test

Incrementality Test Introduction

A GeoLift experiment (often referred to as Incrementality Test) is, in general, the most accurate way to measure the true impact of marketing without relying on individual tracking, which can bias results due to privacy restrictions.

It splits the target market into similar test and control regions, launches ads only in the test regions while keeping the control regions as the holdout, and then compares the business outcomes between the two to estimate the incremental impact of the marketing activity.

Marketing Measurement Overview summarizes its benefits and limitations and compares this approach with other common methods.

The Maxma Advantage

While incrementality testing is the gold standard for measuring marketing impact, it has traditionally been limited to big brands and tech companies due to its high cost and complexity. Even modern vendors charge around $10,000 per experiment, making it impractical for most businesses to run tests at scale.

Maxma is changing that with our AI-powered Incrementality Test, designed to make rigorous experimentation accessible, scalable, and cost-effective.

Imagine an AI expert embedded with deep knowledge of attribution, statistical methods, and marketing domain knowledges, understand all the pitfalls and best practices of incrementality testing, to guide you through the entire process - from experiment design to analysis. Human experts with such expertise are hard to find and expensive. But our AI expert is always available to help you run rigorous tests with confidence.

Scale Without Sacrifice

• Reduce costs—run experiments for a fraction of traditional costs
• Instant guidance—AI expert available 24/7
• Human expert support—human expertise is optional, not a bottleneck

Flexible and Customizable

• Tailor experiments to fit your business needs and constraints
• Iterate quickly—refine your test design without additional costs or delays

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Use Cases

Different Testing Scenarios

Maxma Incrementality Testing supports a variety of testing scenarios:

• Current Budget: Measure incrementality at the existing spend level.
• Heavy-Up: Test the impact of increasing ad spend to prevent diminishing returns and saturation.
• Dial-Down: Reduce spend safely with potential missed opportunities measured.
• New Launch: Before scaling a new advertising initiative, test for detectable incremental impact at the lowest possible spend level to minimize risk.

Multiple Metrics

Maxma Incrementality Testing supports measuring multiple metrics within a single experiment. Beyond a primary conversion metric (e.g. orders, signups, app installs, etc.), you can measure additional metrics for a broader view of marketing impact. Examples include:

• Conversion Funnel Stages – Track multiple points in the funnel, such as web visits, signups, and purchases.
• Conversion Segments – Compare new vs. returning customers, or Shopify vs. Amazon orders.

Note: The experiment is optimized to detect lift for the primary metric, so additional metrics may have lower statistical power (i.e. ability to get statistically significant results). But the platform will tell you what's the minimum lift you can detect for the addtional metrics so you can adjust the design or promote the metric as the primary metric.

Lingering Effect

Incrementality Testing can capture short-term lingering effects of advertising. While it cannot fully measure long-term brand awareness effects that may take months to materialize, it can capture delayed impact in the weeks following the advertising.

The results of the experiment will show the incremental conversions continue to grow after the experiment concludes. { add a visual here}

Offline Advertising

Incrementality Test is not limited to digital advertising—it can also be applied to offline marketing channels, such as out-of-home, TV, radio, and print. The requirement is you can target only some of the regions with the offline advertising.

How It Works

1. Experiment Design

To set up a new experiment, the AI expert will guide you step-by-step through the following key decisions:

• Experiment Goals: Cleary define the objective of your experiment
• KPI Selection: Choose the right metrics to measure success
• Power Analysis: Determine required budget, test duration, and optimial test & control region selection to achieve the desired statistical power

2. Launch Experiment

Once the experiment is designed, marketers can implement it in the corresponding ad platform using the pre-defined experiment specification from the above step.

3. Results Analysis

When the experiment concludes, marketers returns to the Maxma platform to analyze the results and gain insights.

Getting Started

Sign up for a free trial coming soon. For now, please contact us here to get access to the platform.