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Analytics & Data Science

AI for Everyday Use

On November 20, the ARF held a workshop exploring prompts, personas and how to use AI responsibly. This dynamic event, designed for advertising and marketing professionals looking to explore the evolving landscape of AI-powered research, provided insights into prompt crafting. Participants also gained a deeper understanding of the promises and pitfalls of using personas in AI-powered advertising and marketing research.

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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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OTT 2024: Today's Dynamic Media Landscape -- What's Next?

Attendees joined us on October 23 for our annual OTT conference, offering the latest research on shifts in the TV and video landscape, viewer behavior, and cross-platform measurement. Industry experts discussed trends in viewing habits, advertising innovations, and predictions for 2025. Attendees also had the opportunity to participate in discussions and network with industry peers over breakfast, lunch, and the cocktail reception.

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AI for Data Analysis in Marketing and Advertising

Attendees joined ARF in NYC for two workshops – a morning session tailored for professionals without a background in coding, and an afternoon session for data scientists, analysts, engineers, and other data science professionals – that highlighted how to utilize LLMs to analyze example datasets. Additionally, attendees had the chance to participate in real-time AI tool demonstrations.

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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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The Importance of Incrementality in Retail Media Measurement

  • INSIGHTS STUDIOS

Despite massive growth driven by significant investments, retail media performance measurement still falls short in many areas. On October 15, OptiMine and Best Buy dove deep into the use of incrementality measurement for retail media, how it works and why it is so unique in the RMN space. Attendees explored why (and how) some of the world’s largest brands have embraced it for improved success.

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Improve Marketing Mix Model (MMM) Accuracy by Identifying these Effects

  • MSI

This study explores the identification of nonlinear and time-varying effects in marketing mix models (MMM). It highlights the challenges of conflation in model selection and proposes a framework for simulating and estimating these effects using Gaussian processes. The study emphasizes the importance of accurately identifying the underlying response to optimize marketing spending.

The research provides insights into the complexities of marketing effectiveness and offers practical solutions for improving model accuracy. By addressing the issue of conflation, the study aims to enhance the decision-making process in marketing strategies.

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