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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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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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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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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On October 30th, the ARF’s Organizational Council presented the results of the 2024 Organizational Benchmark Survey. This 3rd wave of the Benchmark Survey followed the 1st and the 2nd waves, which took place in 2019 and 2021, respectively. Council Chair Susan Pizzaro’s presentation touched on trends in research department structures, budgets and resources; changes in valued skills and tools used; and satisfaction with the value brought by insights and analytics teams. Afterward, Becky Bach of Pernod Ricard USA and Jim Spaeth of Sequent Partners joined Susan in a discussion moderated by ARF’s Chief Research Officer Paul Donato.
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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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Attendees joined us on September 10 for an Insights Studio on the latest in Marketing Mix Modeling (MMM). Panelists shared proven strategies for implementing and optimizing MMM and revealed valuable insights into best practices and real-world case studies to help build, power, and calibrate MMMs.
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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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