attribution

The State of Retail Media Networks & Consumer Behavior

  • Shopper 2025

On May 21, the industry’s top minds gathered in Chicago for a look at the future of retail, media, and consumer behavior and dove into the rapidly evolving role of Retail Media Networks (RMNs). Attendees gained actionable insights on the opportunities and challenges that RMNs present. Leading experts led discussions on optimizing RMN investments, navigating sales attribution complexities, adopting an "omni-normal" approach to connect with shoppers across all touchpoints, harnessing AI for brands and consumers, and more.

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Overcoming Last-Click Addiction: Strategies for Holistic Marketing Success

  • INSIGHTS STUDIOS

Is last-click performance reporting deeply embedded in your organization—and  holding your brand back. On April 10, panelists from OptiMine and NP Digital broke down the risks of last-click measurement and discussed another way forward. Attendees learned about a proven framework to transition from outdated attribution models and how to align the right tools with the right questions for better insights.

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The State of Privacy-First Marketing & Redefining Performance

  • Insights Studio Series

How we use data today looks different given evolving regulations, platform changes, consumers expectations of data transparency, and more. Our Insights Studio on January 30 explored the latest developments in data privacy and how they are impacting marketing strategies. Panelists unveiled strategies to establish consumer trust and effectively market, while aligning with privacy regulations.

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An Introduction to Robyn’s Open-Source Approach to Media Mix Modeling

  • MSI

As privacy-centric changes reshape the digital advertising landscape, deterministic attribution and measurement of advertising-related user behavior are increasingly constrained. In response, there has been a resurgence in the use of traditional probabilistic measurement techniques, such as media and marketing mix modeling (m/MMM), particularly among digital-first advertisers. To address the gap for small and midsize businesses, marketing data scientists at Meta have developed the open-source computational package Robyn, designed to facilitate the adoption of m/MMM for digital advertising measurement.

Robyn is a widely adopted and actively maintained open-source tool that continually evolves. This article explores the computational components and design choices that underpin Robyn, emphasizing how it “packages up” m/MMM to promote organizational acceptance and mitigate common biases. The solutions described are not definitive but outline the pathways that the Robyn community has embarked on.

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