Built For Commerce Media

With direct integrations across retailers, media platforms, and digital shelf data, Incremental automates the collection, cleansing, and mapping of data across the media and commerce ecosystem.

The end result is a 360-degree view of a manufacturer's media and commerce data—the foundation for measurement. Incremental uses an ensemble model that combines econometric approaches with designed and synthetic experiments to untangle what is actually causing growth in your business, and a continuous learning feedback loop that improves the model’s predictions each day.

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why we built it

What Incremental Does Best

Explore the “why” behind our methodology.

Causal Inference

Incremental’s methodology is built on multiple causal inference techniques to establish a clear connection between investment and outcome.

Continuous Learning

Once-per-year measurement leads to lags in reporting and outdated assumptions. To be actionable, measurement platforms move at the speed of your decision-making. Our model learns as you make changes in your business, progressively developing a deeper understanding of how each change impacts sales.

Speed & Granularity

With reporting down to the campaign- and line item-level and automated daily retraining, the Incremental platform provides insights at the speed and granularity you need to stay ahead.

how it works

Integrations & Data Collection

With just a few clicks, Incremental integrates directly with your retail and media ecosystem. You can also upload your own data.

Comprehensive Data Collection from all your media platforms

HOW IT WORKS

Data Cleansing & Normalization

At the core of Incremental is a map of your business, graphing and connecting all of your commerce and media data. It allows the platform to understand which products are the target of each campaign, both onsite and offsite, where products are on promotion across marketplaces, and where those products sit on the digital shelf. This holistic understanding of commerce and media is essential to developing measurement that is purpose-built for commerce media.

how it works

Untangling Incrementality

An ensemble causal inference model.

Incremental uses machine learning and an ensemble model that combines econometric techniques with designed and synthetic experiments to understand how each factor drives sales.

The end result is an ability to decompose your sales by retailer and channel (ecommerce vs. brick and mortar) into the factor that drove those sales—media, merchandising efforts, or organic factors.

With granular campaign- and line item-level reporting for media, you have the flexibility to drill down or aggregate data easily to meet your needs.

how it works

Continuous Learning

Always-on model learning

As the conditions of commerce change around your business, both intentional and unintentional, measurement can become out of sync with the recent reality. Incremental’s model learns daily to ensure it stays up to date.

The model continually makes short-term predictions about the future and compares those to actuals over the coming days and weeks. This creates a feedback loop that injects recency bias into the model.

how it works

Data Sharing

Incremental integrates directly with omnichannel media buying platforms to enable incrementality signals and recommendations to flow seamlessly into campaign management workflows. This integration enables the automated optimization towards incrementality at scale.

Incremental offers direct integration via APIs and feeds to flow the normalized, cleansed, and enriched data into your internal data lakes, so you can easily embed it in the platforms and workflows that already exist across your organization. Or you can just ask us to send you a daily email.