Research & Data Quality

• Research & Data Quality
• Article

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.

• Research & Data Quality
• Article

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.

• Research & Data Quality
• Article

ARF Attention Measurement Validation Initiative: Phase 2 Report (2nd Edition)

• ARF ORIGINAL RESEARCH

Explore the latest findings from the ARF Attention Measurement Validation Initiative. The phase two report is a comprehensive examination of various attention measurement methods used in creative testing. It concludes with reflections on the challenges of attention measurement, as well as some suggestions for advertisers on how to choose and evaluate attention measurement providers.

• Research & Data Quality
• Article

Measuring Marketing Impact Today: Practical Strategies and Tools

On August 21, experts from Meta and the Kellogg School of Management at Northwestern University shared practical steps to achieve better measurement in an era of evolving data availability. Attendees walked away with new practical approaches for understanding marketing impact – whether they have access to robust experimentation.

• Research & Data Quality
• Article

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.

• Research & Data Quality
• Article

MMM Best Practices and Success Stories

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.

• Research & Data Quality
• Article

AI Use in Advertising Research: Insights from the AI Handbook

Dive into the future of advertising research with this abridged version of the ARF's AI handbook. This Knowledge at Hand report and its accompanying one-page CMO brief describe best practices for utilizing AI tools for different aspects of advertising research. This short report is great for those already using AI and those thinking of interweaving it into their research function.

• Research & Data Quality
• Article

Overcoming the Limitations of Online A/B Testing

• MSI

This study explores how divergent delivery in A-B testing affects the accuracy of online advertising experiments. It highlights the role of algorithmic targeting and user heterogeneity in confounding test results, offering guidance for marketers to improve their experimental designs.