modeling

People’s Performance Goals Shape Their Use of Predictive Algorithms

This study presents a framework for understanding people’s use of predictive algorithms, emphasizing their role as tools designed to support human decision-making. It argues that users’ performance expectations are a primary driver of their decisions to adopt these algorithms. By reviewing and reinterpreting the literature through the lens of laypeople’s performance expectations, the study aims to clarify why some algorithms are accepted and others are rejected. It concludes by suggesting avenues for designing algorithms that better meet users’ expectations, enhancing their usability and acceptance.

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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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Marketing Analytics Accelerator: 2024

The Marketing Analytics Accelerator – the only event focused exclusively on attribution, marketing mix models and the science of marketing performance measurement – returned for its ninth year on November 13. The industry’s boldest and brightest minds joined us in NYC to share their latest innovations and case studies that will improve your business outcomes.

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