『AI Marketing Research: Agency Survival, Churn AI & Disclosure』のカバーアート

AI Marketing Research: Agency Survival, Churn AI & Disclosure

AI Marketing Research: Agency Survival, Churn AI & Disclosure

無料で聴く

ポッドキャストの詳細を見る
When AI can write your ads, predict who's about to leave, and draft your strategy decks — what are humans still for, and when does it matter that you say so? This week's research batch lands on a single uncomfortable truth: the closer AI gets to judgment calls, the more it needs a human watching over its shoulder. In this Research Radar Brief, Dr. Eva Wolf reviews 3 recent AI marketing research papers covering the future of advertising agencies, deep learning models for customer churn prediction, and the growing gap between how AI is actually used in professional work and what anyone discloses about it. What you'll learn: - Why AI automating ad campaigns on Meta and Google may be eroding the most billable parts of your agency — and what to offer instead - How a deep learning model achieved 96% accuracy predicting customer churn on e-commerce data — and why that number needs careful context before you act on it - Why customer satisfaction scores appear to be a stronger loyalty predictor than purchase history, and what that means for your CRM setup - How AI disclosure norms are broken even in academic research — and what that gap reveals about transparency risks building up inside marketing teams - What a genuinely useful AI disclosure statement looks like versus a generic line that tells nobody anything Papers covered: 1. A Discussion on the Future of Advertising Agencies in the Impact of Artificial Intelligence - Source type: Peer-reviewed journal article (Intermedia International e-journal) - Access: Full text reviewed - DOI: 10.56133/intermedia.1740804 - Radar verdict: Test this week 2. Generative AI for Personalized Marketing and Customer Experience in E-Commerce - Source type: Peer-reviewed journal article (International Journal of Emerging Research in Engineering and Technology) - Access: Full text reviewed - DOI: 10.63282/3050-922x.ijeret-v7i1p103 - Radar verdict: Use cautiously 3. Expectations and Practices around AI Disclosure in CS Research - Source type: Preprint (arXiv) — not yet peer-reviewed - Access: Full text reviewed - URL: https://arxiv.org/abs/2608.23271v1 - Radar verdict: Test this week Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-agency-survival-churn-prediction-disclosure-2026-08-25 Disclaimer: This is a first-pass research briefing produced by an AI-generated research avatar trained on Dr. Eva Wolf's methodology. It is not a substitute for reading the original papers. Preprints have not undergone peer review and findings may change. Source quality and study limitations are noted for each paper. Nothing here constitutes financial, legal, or professional advice. -- This is a first-pass research briefing, not a final academic review. Read the original papers before making major marketing or business decisions. AI & Marketing Research Radar is produced by BigPlans Media. Subscribe wherever you listen to podcasts.

Thanks for listening to AI & Marketing Research Radar by Big Plans Media.

I’m Dr. Eva Wolf, and I help marketers, educators, consultants, and business owners turn AI marketing research into practical strategy, smarter workflows, and real business opportunities.

More episodes: https://bigplans.media/ai-marketing-research-radar/
Consulting: https://bigplans.media/ai-marketing-consulting/

Big Plans Media — Where Big Ideas Meet Smart Marketing.
adbl_web_anon_alc_button_suppression_t1
まだレビューはありません