The advertising industry continues to undergo rapid and structural change driven by AI, automation, evolving media environments, privacy regulation, and mounting concerns about data quality and trust. To help members navigate these shifts, the ARF conducts independent, original research that addresses foundational questions about advertising effectiveness, measurement and research integrity.
8th Annual Privacy Survey
The ARF’s eighth annual Privacy Survey continues its longitudinal examination of U.S. consumer attitudes toward data sharing, personalization, and trust in advertising and marketing. Building on insights from prior waves, the 2025–2026 study places increased emphasis on consumer expectations around artificial intelligence, including the use of AI in creative development, targeting and decision-making, as well as expectations for transparency and responsible data practices.
The study tracks shifts in trust across advertisers, platforms and institutions, providing members with a rare longitudinal benchmark for understanding how privacy sentiment evolves over time and alongside technological and regulatory change.
Format and Schedule: The report will be released in January of 2026 on the ARF website and through PowerSearch. Database and tracking data is made available to members for reanalysis.
AI in Advertising & Marketing Workflows: Advertiser and Agency Perspectives
This study examines how advertisers and agencies are integrating artificial intelligence and generative AI into advertising and marketing workflows, with a focus on measurement, attribution and decision support. Based on a survey of industry professionals, the research documents levels of AI awareness, adoption, validation practices and organizational readiness.
The analysis moves beyond usage rates to assess how AI outputs are evaluated, where trust and uncertainty remain, and how organizations balance automation with human oversight in campaign development and measurement.
Format and Schedule: Survey report to be released in early 2026.
Psychology of Generative AI Research Series
This ongoing experimental research series investigates how large language models replicate, distort and diverge from human cognitive and emotional patterns. Each study isolates a specific psychological mechanism—such as bias, loss aversion, persona framing or moral reasoning—to clarify the boundaries between human judgment and machine-generated reasoning.
The series establishes an empirical foundation for evaluating generative AI as a research instrument, diagnostic tool and cognitive collaborator, helping members understand when AI can support insight generation—and when it cannot substitute for human consumers.
Format and Schedule: Monthly research briefs with an annual synthesis report at the end of 2026.
Read the Psych of GenAI Series
Synthetic Data in Advertising & Marketing Research
This initiative evaluates the use of synthetic data in advertising and marketing research through controlled empirical comparison. Using identical questionnaires, the ARF will compare results from AI-generated synthetic respondents with traditional, online consumer samples to assess where synthetic data performs comparably, where it diverges and what that means for research quality and decision-making.
The goal is not to validate synthetic data as a replacement for human samples, but to provide evidence-based guidance on appropriate use cases, limitations and risks.
Format and Schedule: Empirical comparison report and practical guidance to be released following completion of fieldwork.
Attention Measurement Validation Initiative – Phase 3
The third phase of the ARF’s Attention Measurement Validation Initiative evaluates how attention metrics perform across media platforms and how they relate to brand outcomes. Using real-world advertising campaigns, the study compares attention signals from multiple independent vendors across environments and examines their convergence, divergence and interpretive limits.
Phase 3 reinforces attention as a diagnostic indicator of exposure quality while clarifying why attention alone cannot serve as a standalone predictor of advertising effectiveness.
Format and Schedule: Phase 3 report in early–mid 2026, followed by a final initiative synthesis.
Read: The ARF Attention Measurement Validation Initiative: Phase 1 Report (Updated)
Read: ARF Attention Measurement Validation Initiative: Phase 2 Report (2nd Edition)
Retail Media Networks: Measurement Validity and Transparency
This multi-phase research initiative examines retail media networks with a focus on measurement credibility, metric consistency and incremental lift claims. Through RFIs and in-depth interviews with leading retail media networks, the ARF assesses similarities, differences and shared pain points across RMN measurement practices.
The work aligns with broader industry efforts to improve transparency and support emerging measurement standards.
Format and Schedule: Final report to be released in early 2026.
Premium vs. User-Generated Content Environments
This initiative moves beyond the traditional premium-versus-UGC binary by developing and testing a multi-dimensional framework for defining advertising environments. The research combines framework development with experimental testing to evaluate how contextual factors—such as content quality, screen context, brand safety and creator–audience relationships—shape cognitive and advertising outcomes.
The findings will help advertisers and planners make more informed, evidence-based decisions across increasingly hybrid media ecosystems.
Format and Schedule: Comprehensive experimental report expected in mid-2026.
Brand Suitability in Trusted News Environments
This project examines advertising effectiveness and brand suitability in news environments, reframing the issue from risk avoidance to opportunity creation. Using cross-publisher test-and-control designs, the study evaluates engagement, attention, recall and sales outcomes in news versus non-news contexts.
The research aims to deliver a practical playbook for advertising in trusted journalism environments without compromising brand objectives.
Format and Schedule: The News Advertising Playbook will be released mid 2026.
The Future of Media Planning
What will the impact of AI and other technologies be? In this current media landscape, what are the best practices for using different media channels, especially CTV, streaming, online video and programmatic? What role does each channel play? Which channels work best for new brands? For different campaign objectives?
Format and Schedule: This study will evaluate the impact of AI on media planning. The report is available now on our website or through PowerSearch.
Respondent Verification and Fraud Detection Initiative
This initiative addresses growing concerns about survey fraud, low-quality respondents and AI-assisted response behavior. Rather than promoting a single solution, the ARF is evaluating detection approaches, quality signals and prevention strategies across the research lifecycle.
The work is designed to clarify trade-offs between cost, speed and quality and to support best-practice guidance for survey-based research in an evolving fraud landscape.
Format and Schedule: Initial synthesis and research design proposals in 2026, with subsequent empirical work pending scope finalization.
The David Ogilvy Datasets
What is the relationship between brand and sales advertising? To find out, the ARF is sharing datasets to enable research on the subject. The annual project includes over 120 Ogilvy applicants.
The ARF has harmonized this effort with a similar project conducted by IPA in the UK. Each entry in the file contains the brand and product category, age, share, consideration, pricing position, growth, sales cycle, campaign objective, primary target, media plan, competitive strategy, outcomes, research used and brand equity.
Format & Schedule: The datasets are available as a CSV file. Contact the ARF Knowledge Center at knowledgecenter@thearf.org to receive the datasets and for a codebook. Each spring, the prior year’s applications will be added to the datasets.