Do big life changes make people more open to seeing the same ad again and again? In this episode, Ben Borenstein and Luke Nowlan join me to share insights from their Journal of Advertising Research article, “Life Transitions Influence Response to Ad Repetition: When Times of Change Increase Preference for Repeat Advertising Experiences,” coauthored with Tyler Milfeld.

Ben, Luke, and I talk through how moments like moving, changing jobs, or becoming a parent shift the way people respond to repeated ads. Across four experiments, they find that consumers in a life transition actually sustain enjoyment of repeated ads and form more positive brand attitudes — rather than tuning out. We also discuss why predictability feels comforting in times of change, how advertisers can spot these moments using behavioral signals, and what this means for ad frequency and targeting strategies.

Read the full paper here:
https://doi.org/10.1080/00218499.2025.2464306

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Can the way ads are scheduled change whether people watch or skip? In this episode, Dr. Mi Hyun Lee (Northwestern University) and Dr. Jaewon Royce Choi (Louisiana State University) join me to talk about their Journal of Advertising Research article, Acceptance Propensity of Pre-Roll Skippable Ads: An Analysis of Large-Scale Clickstream Data Using Dynamic Linear Models, coauthored with Su Jung Kim.

We dig into their concept of ad acceptance propensity — the underlying tendency to accept rather than skip an ad — and how it shifts depending on how ads are placed. Drawing on a dataset of 10,000 users and 36,000 ad exposures from a major video platform, they show that predictable, frequent exposures lower acceptance while irregular, spaced exposures boost it. We also talk about how their dynamic linear modeling approach lets researchers go beyond observed behavior to estimate hidden states, why this matters for both scholars and practitioners, and how advertisers can rethink reach and frequency.

Read the full paper here:
https://www.tandfonline.com/doi/full/10.1080/00218499.2025.2464294

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https://www.buzzsprout.com/2250188

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Can the depth of field in a video ad change how consumers process the message? In this episode, Dr. Lam An (University of Winnipeg) joins me to discuss his Journal of Advertising Research article, “The Effectiveness of Background Blurriness in Video Advertisements: How Video Background Blurriness and Construal Level Shape Consumer Perception.”

Lam explains how blurry versus clear backgrounds interact with message type. Blurry backgrounds make concrete, detail-heavy, near-term messages easier to process, while clear backgrounds align better with abstract, big-picture, future-oriented themes. Together we talk through his series of lab experiments and a field test on Meta that show how these simple production choices can significantly impact ad effectiveness. Lam also shares what this means for advertisers in practice—whether you’re promoting a limited-time deal, building long-term brand equity, or trying to stand out in a crowded feed.

Read the full paper here:
https://www.tandfonline.com/doi/full/10.1080/00218499.2025.2464281

Listen to the podcast here:
https://www.buzzsprout.com/2250188

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When a movie rolls out in stages, how do you decide where the ad dollars go first week in theaters, later weeks, discs and TVOD, then streaming? In this episode, Prof. Sönke Albers walks me through his Journal of Advertising Research article, “Optimal Rules for Advertising Budget Allocation Across Movie Versions Marketed in Sequential Distribution Stages.”

Sönke explains a simple, Excel-friendly rule that accounts for both stage size and long-term ad elasticity, plus the carryover and spillover that early ads create for later stages. The takeaway is clear: when there are meaningful carryover effects, front-loading spend early typically pays twice, but you still need to weight each stage by its expected profit and responsiveness. He also shows how the cascading structure scales to any number of release stages and why optimizing real profit beats rules that only look at elasticities.

We talk practicals for studios and any brand with staggered launches books, games, product lines and why getting decent elasticity estimates can materially improve outcomes.

Read the full paper here:
https://www.tandfonline.com/doi/full/10.1080/00218499.2025.2464282

Listen to the podcast here:
https://www.buzzsprout.com/2250188

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How is generative AI changing the creative process inside agencies? In this episode, Carla Ferraro, Sean Sands, and Vlad Demsar join me to unpack insights from their Journal of Advertising Research article, “Harmony or Discord? The Intersection of Generative AI and Human Creativity in Advertising,” coauthored with Andrew Kohn.

We talk about what senior agency leaders are actually doing with GenAI right now, where it reliably speeds up ideation, testing, and production, and where human guidance is still essential. The team shares why originality, ethics, and over-reliance on historical data remain real concerns, plus practical guardrails around brand fit, copyright, and data privacy. We also get into training and transparency, how teams can treat AI as a creative partner rather than a replacement, and smart next steps for research on consumer reactions and team workflows.

Read the full paper here:
https://www.tandfonline.com/doi/full/10.1080/00218499.2025.2464305

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Does calling out AI in your creative spark conversation or scare people off? In this episode, Sara Hanson, Jeffrey Carlson, and Heather Pressler unpack their Journal of Advertising Research article, “The Differential Impact of AI Salience on Advertising Engagement and Attitude: Scary Good AI Advertising.”

We dig into AI salience, meaning how obvious it is that AI made the ad through disclosures or clearly AI-looking imagery. Across four studies, they find a split effect. AI-salient ads boost engagement like more likes and longer comments, but they also trigger fear and reactance that lower ad attitudes and can dampen conversion intent. The team talks about how to handle disclosures, where AI fits along the funnel, and why finding the right balance is key.

Read the full paper here:
https://www.tandfonline.com/doi/full/10.1080/00218499.2025.2464307

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What really changes inside an ad agency when GenAI shows up? In this episode, Weila Cui joins us to unpack her Journal of Advertising Research article, “Exploring the Integration of Generative AI in Advertising Agencies: A Co-Creative Process Model for Human–AI Collaboration,” coauthored with Martin J. Liu and Ruizhi Yuan. Interviewed by David Ji, Weila walks us through a practical four-stage roadmap—readiness, co-creativity (co-inspiration → co-generation → co-calibration), validation (agency + client loops), and execution—that shows GenAI isn’t just speeding things up; it’s reshaping how ideas emerge, get refined, and make it to market.  

We dig into what “good” looks like in real workflows: building team mindset and skills, structuring feedback loops, balancing rapid AI ideation with human judgment, and tightening cross-functional handoffs so AI-assisted concepts ship cleanly across channels. We also get candid about the bumps—creative resistance, unpredictable outputs, cultural and brand-fit issues, and evolving legal/ethical questions—and how agencies are documenting prompts, fine-tuning models, and codifying best practices to learn project by project.

Read the full paper here:
https://www.tandfonline.com/doi/full/10.1080/00218499.2024.2445362

Listen to the podcast here:
https://www.buzzsprout.com/2250188

And watch this and more content on our YouTube page:
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Where’s the line between “helpful” and “a bit creepy”? In this episode, Dr. Pengfei Xie joins me to unpack findings from his Journal of Advertising Research article, “The Inverted U-Shaped Effect of Personalization on Consumer Attitudes in AI-Generated Ads: Striking the Right Balance Between Utility and Threat,” coauthored with Hongjie Sun and Yan Sun.  

We break down their core result: consumer attitudes peak at a moderate level of personalization—then drop off when ads get overly tailored. Pengfei explains the psychology behind it (a utility-vs-threat trade-off they call PUTD) and why privacy concerns make that curve even steeper. We also talk through their trio of experiments across categories (travel, sports drinks, smart speakers) and what it means for marketers in practice: segment for privacy sensitivity, be transparent about data use, and shoot for the “just-right” middle.

Read the full paper here:
https://www.tandfonline.com/doi/full/10.1080/00218499.2025.2462405?src=exp-la

Listen to the podcast here:
https://www.buzzsprout.com/2250188

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Can the fit between an ad and the program around it change how long people watch? In this episode, Dr. Wen Xie joins me to share insights from his Journal of Advertising Research article, “An Empirical Examination of the Ad Program Congruence Effect on Ad Viewing Behaviors: Evidence from TVision Data,” coauthored with Ming Chen and Chunxiao Xue.

Wen and I talk through what happens when ad themes line up with program themes, drawing on millions of second-by-second attention records from TVision. He explains why congruence lifts attention in some categories like entertainment and finance, but not in others like politics or food. We also dive into when in the program congruence makes the most difference, and why the beginning and end of a show are sweet spots. Wen also shares how they measured “fit” between ads and programs and what this means for media planning going forward.

Read the full paper here:
https://www.tandfonline.com/doi/full/10.1080/00218499.2025.2464286?src=exp-la

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Can AI imagery hurt luxury advertising? In this episode, Rita Ngoc To, Parichehr “Perry” Kianian, Yi-Chia Wu, and Zhe Zhang unpack their Journal of Advertising Research article, “When AI Doesn’t Sell Prada: Why Using AI-Generated Advertisements Backfires for Luxury Brands.” The team walks through three studies that span a real email field test and two lab experiments. The throughline is clear. When a luxury ad discloses AI-generated imagery, people infer low effort, see the ad as less authentic, and respond less favorably. Mainstream brands do not suffer the same hit. The group also shows a practical fix. Use AI to create highly creative visuals. Strong creativity lifts perceived effort and authenticity, which softens the negative impact of disclosure.  

Read the full paper here:
https://www.tandfonline.com/doi/full/10.1080/00218499.2025.2454120

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