Last week I shared some surprising new research: AI shopping agents are actively penalizing sponsored products, reducing the likelihood of them being selected by 8–14%. That sounds like a big red flag for retail media, right? But in today’s episode, I make the case that this 'ad penalty' is temporary, and far from the end of sponsored products.

We dig into why today’s AI models have inherited our own human ad skepticism, why that bias won’t last, and how the retail media ecosystem could adapt. From real-time basket bidding between retailers, to collaborative incentives from brands, to new revenue models around product content and reviews, I explore the paths forward that could actually make agentic commerce even more valuable for retailers, brands, and consumers alike.

This episode is sponsored by Connected Commerce at Acosta Group

Timeline

[00:15] – The surprising stat: AI agents penalize sponsored products by up to 14%
[01:00] – Why AI’s distrust of ads has been inherited from humans
[02:30] – Why ad avoidance won’t last (agents that miss good deals will frustrate users)
[02:58] – Scot Wingo’s vision for real-time retail bidding, and how brands could amplify offers
[05:00] – How AI could create a 'clean' monetization model without eroding consumer trust
[07:00] – Beyond ads: revenue opportunities in product content optimization and reviews
[09:50] – The big takeaway: don’t ditch sponsored products yet

Links & Resources

• New research from Yale & Columbia, What Happens When AI Does Your Shopping?
• Retail Media Breakfast Club article, What Is Your AI Agent Buying? [New Research]
• Retail Media Breakfast Club article, Why Agentic Shopping Poses an Existential Threat to Retail Media (Part 1)
• Retail Media Breakfast Club article, AI-Native Brands Will Be The New Amazon FBA Goldrush
• Subscribe to Scot Wingo's Retailgentic on YouTube
• Subscribe to Retail Media Breakfast Club's daily newsletter
• Follow Kiri on LinkedIn

Here’s a question that might sting a little: when your company launches a new product, are you finding out about it at the same time as everyone else? Or maybe you’re just getting a last-minute “Hey, can you build a forecast?” before it hits the market?

In this episode, I dive into the role e-commerce and retail media teams should play in shaping product development, and why it matters more than ever. You’ll hear from leaders across CPG, nutrition, toys, and retail media who share how they’re using marketplace insights, social listening, and sales data to influence packaging, pricing, and product decisions. Some are still fighting for a seat at the table, while others are showing just how powerful data-driven collaboration can be.

If you’ve ever wondered whether your customer insights could change what gets developed next, this conversation will spark ideas and give you some arguments to bring to your next leadership meeting.

This episode is sponsored by Connected Commerce at Acosta Group

Timeline

[00:58] - Alicia Ponzani on being brought in too late to influence product innovation

[02:09] - Brie Keating explains why e-commerce leaders hold the keys to future product design

[02:54] - Jamie Roller shares how Dr. Squatch integrates marketplace insights directly into product vetting

[04:23] - Neha Malik on using social listening to guide smarter product and packaging decisions

[05:18] - Kelsey Knight describes how Slumberkins combines creative vision with forecasting and data

[06:26] - Chris Lowrey highlights how search insights led to a packaging redesign that boosted sales

Links & Resources

• Follow Alicia Ponzani, Ecommerce Manager at Premier Nutrition, on LinkedIn
• Follow Brie Keating, Director of Ecommerce at Wilton, on LinkedIn
• Follow Jamie Roller, Director of Marketplaces at Dr. Squatch, on LinkedIn
• Follow Kelsey Knight, Chief Commercial Officer at Slumberkins, on LinkedIn
• Follow Neha Gupta Mallik, Head of Connected Commerce at Mizkan America, on LinkedIn
• Follow Chris Lowrey, Brand Director at Our Home, on LinkedIn
• Subscribe to Retail Media Breakfast Club's daily newsletter
• Follow Kiri on LinkedIn

Imagine sending three different people to buy you a pair of slippers and each person comes back with wildly different products. Now replace those people with AI agents like Claude, GPT, and Gemini. What slippers would they choose?

In this episode, I dive into groundbreaking new research from Columbia and Yale that reveals how AI agents shop when left to their own devices. The findings are eye-opening for brands, retailers, and anyone curious about the future of AI-driven commerce. From the surprising role of reviews, how AIs treat sponsored products, to the risks of market concentration, this study shines a light on what’s coming next for online shopping.

This episode is sponsored by Connected Commerce at Acosta Group

Timeline

[00:01:04] - The unique sandbox study design that reveals how AI models actually shop
[00:02:10] - Why product reviews are more valuable than ever in an AI-first shopping world
[00:03:28] - The surprising discovery regarding sponsored products
[00:04:45] - Market concentration risk: why AI tends to favor established brands
[00:06:40] - Mixed results on human-created product pages vs. AI-generated content
[00:08:30] - The limits of current research and what’s next with TikTok Shop, AI-to-AI shopping, and voice commerce
[00:10:15] - Why the real winners will be those focused on authentic product quality and customer satisfaction

Links & Resources

• New research from Columbia Business School, What Happens When AI Does Your Shopping?
• Retail Media Breakfast Club article, AI-Native Brands Will Be The New Amazon FBA Goldrush
• Subscribe to Retail Media Breakfast Club's daily newsletter
• Follow Kiri on LinkedIn

In today’s episode, I dive into a surprising paradox in the retail media world. While nearly 9 out of 10 brands say a retailer’s tech stack influences how they allocate ad spend, most retailers are still treating their technology decisions like state secrets. From awkward RFP scenarios to brand-side frustrations, we explore why this secrecy exists and how it could be slowing the entire industry down.

I also unpack the results of a recent LinkedIn poll showing just how much brands and agencies care about transparency, share the four main reasons retailers keep things under wraps, and highlight one retailer that’s breaking the mold with refreshing openness. If you’ve ever wondered why retail media networks feel like a black box, and what needs to change, this episode is for you.

This episode is sponsored by Connected Commerce at Acosta Group

Timeline

[0:45] - A surprising RFP story that shows how secretive retailers can be.

[2:30] - Poll results: why 88% of brands say tech transparency matters.

[4:15] - The four main reasons retailers hide their tech stack.

[7:25] - How tech opacity stifles programmatic buying and scalability.

[8:30] - A closer look at Home Depot’s transparent approach with Orange Apron Media.

[10:04] - The hidden costs of secrecy: stagnation, budget migration, and trust deficits.

[11:40] - Why transparency is now a competitive necessity in retail media.

Links & Resources

• Forbes article by Kiri Masters - Why Retail Media Networks Hide Their Tech Stacks From The Very Brands They Want To Attract
• Retail ad-tech stack LinkedIn poll results
• Forbes article by Kiri Masters - Why Real-Time Bidding Is Retail Media's Next Frontier
• Forbes article by Kiri Masters - Home Depot's Retail Media Chief Puts Suppliers At The Center
• Subscribe to Retail Media Breakfast Club's daily newsletter
• Follow Kiri on LinkedIn

I asked Amazon’s Rufus a simple question—and its answer was uncomfortably (and impressively) specific. In this episode, I unpack why that moment matters: Rufus appears to be building persistent memories about who we are as shoppers, shifting from a mere search tool into something that feels like a relationship.  

I break down how this differs from legacy “people who bought X also bought Y” personalization, why this could upend my prior stance on retailer chatbots, and what it means for both consumer brands and competing retailers. Think long‑term context, cross‑category intelligence, and what happens when your brand’s post‑purchase experience now influences future discoverability.    

Timeline Summary

• [0:00] — The surprisingly accurate Rufus moment that sparked this episode.  
• [0:32] — Why “memory” is more than a feature update—it’s a relationship shift.  
• [1:01] — Four ways memory beats traditional personalization: triggers, follow‑ups, methods, and context duration.  
• [2:38] — Rethinking retailer chatbots vs. integrating with personal AI agents (ChatGPT, Gemini, Claude).  
• [3:24] — Why most “me‑too” retail bots still fail—and the smarter bridge‑building play.  
• [4:48] — Brand impact: switching costs rise; quality and “kept” rates become defensible moats.  
• [5:50] — Retailer playbook: alliances, category depth, and in‑store data advantages.  

🔗 Links

Subscribe to Retail Media Breakfast Club's daily newsletter

Follow Kiri on LinkedIn

In retail media, the biggest wins often come from bold, high-stakes decisions. In this episode, I sit down with a panel of industry leaders who share the risks they took that could have gone either way. From betting on unproven product colors, to pulling the plug on ads during peak hours, these stories will inspire you to rethink what it means to take a chance in retail media.

If you’ve ever wondered whether that big, scary idea is worth pursuing, this episode just might give you the courage to take the leap!

This episode is sponsored by Connected Commerce at Acosta Group

Timeline

[1:11] - Josh Clarkson on a strategy that garnered 750M impressions via the world’s largest box of chocolates.
[2:10] - Todd Weagant's gamble on a bold, exclusive headphone color that became an Amazon bestseller.
[3:57] - Neha Gupta Malik’s high-stakes “go dark” search strategy with Walmart and the lessons it revealed.
[5:18] - Why Connected TV (CTV) was a risky but rewarding investment for Mizkan America.
[6:40] - Chris Lowrey's leap from one hero keyword to a diversified retail media strategy.

Links & Resources

• Largest box of chocolates by Russell Stover - Guinness World Records
• Follow Josh Clarkson, Global Lead of Retail Media at Mars, on LinkedIn 
• Follow Todd Weagant, Head of Sales at Masimo, on LinkedIn
• Follow Neha Gupta Mallik, Head of Connected Commerce at Mizkan America, on LinkedIn
• Follow Chris Lowrey, Brand Director at Our Home, on LinkedIn
• Subscribe to Retail Media Breakfast Club's daily newsletter
• Follow Kiri on LinkedIn

The retail media landscape is booming. But it’s also messy, fragmented, and heavily dominated by just a few players. In this episode, I unpack the challenges that brands face when navigating hundreds of retail media networks and explore whether alliances and federations might hold the key to leveling the playing field.

From eerie parallels with the early days of digital advertising to emerging federations like Rippl, I take a closer look at why cooperation may be the only path forward for smaller players who want to compete with giants like Amazon and Walmart. This is the first episode in a four-part series where I’ll peel back the layers of what it really takes to build sustainable, effective retail media alliances.

This episode is sponsored by Connected Commerce at Acosta Group

Timeline

[00:00] – How Google’s ad dominance offers a cautionary tale for today’s retail media chaos
[00:57] – Amazon’s commanding market share and the growth gap facing other RMNs
[02:00] – The “doom loop” of retail media networks: revenue vs. investment catch-22
[03:00] – Why brands are frustrated: lack of standardization and the walled garden problem
[04:36] – The case for federations: how alliances could reshape retail media
[05:05] – Rippl: a national consortium offering advertisers scale across regional grocers
[07:03] – Preview of the 4-part series exploring the mechanics, history, and future of RMN alliances

Links & Resources

• Learn more about Yield: How Google Bought, Built, and Bullied its Way to Advertising Dominance by Ari Paparo
• Follow Ari Paparo on LinkedIn
• Article by Grocery Dive about Rippl
• Subscribe to Retail Media Breakfast Club's daily newsletter
• Follow Kiri on LinkedIn

The world of advertising is changing faster than many expected and AI is leading the charge. In this episode, I dive into the rise of advertising inside large language models (LLMs) and explore whether eMarketer’s $25 billion projection for AI-driven search ads in the next five years is really as far-fetched as some think.

From Microsoft’s early experiments with sponsored links in Bing Chat, to Amazon’s push into AI-driven recommendations, to Perplexity’s twist on sponsored prompts, the landscape is already evolving in ways that could redefine how brands reach consumers. I also look at the global picture, including China’s AI commerce integration, and dig into why retail media as we know it could face an existential threat as consumers shift more of their research and buying decisions into AI-powered conversations.

We’ll also explore what smart retailers and brands must do to adapt: treating AI agents as VIP customers, rethinking loyalty programs, and preparing for a world where AI dynamically generates ads in real time based on context. This isn’t a distant future, it’s happening right now.

This episode is sponsored by Connected Commerce at Acosta Group

Timeline

[00:00] - The $25 billion projection for AI search advertising and why it raised eyebrows.

[01:00] - How Microsoft, Amazon, and Perplexity are already monetizing conversational AI.

[03:00] - A look at China’s approach: super apps and commerce-first AI.

[04:00] - Why retail media may lose ground as shoppers shift to LLM-driven research.

[06:17] - Emerging ad formats: showroom ads and dynamic ad generation.

[07:30] - Why conversational ads are proving more effective than traditional search ads.

[08:00] - The playbook for retailers: making it easy for both humans and AI agents to shop.

Links & Resources

• eMarketer article with $25 billion AI ad projections
• My article on this topic on the Retail Media Breakfast Club blog
• Subscribe to Retail Media Breakfast Club's daily newsletter
• Follow Kiri on LinkedIn

Did you know that while 70% of shoppers have experimented with AI tools to help them shop, fewer than 15% have actually used a retailer’s AI shopping assistant? In this episode, I unpack fresh shopper research from Acosta Group that reveals which retail AI tools are getting traction (and which are still invisible to most consumers).

We’ll dive into surprising adoption numbers for tools like Amazon’s Rufus, Walmart’s Sparky, and category-specific assistants like Kroger’s Chefbot and Ulta’s GLAMlab. I share what this data tells us about placement, awareness, and how retailers can make AI assistants an integrated part of the shopping experience rather than a hidden gimmick. Plus, I explore what all of this means for brands trying to win in the evolving AI-enabled shopping landscape.

This episode is sponsored by Connected Commerce at Acosta Group

Timeline

[00:00] - The surprising gap between general AI use and retailer AI assistant adoption
[01:00] - Usage stats for Amazon Rufus, Walmart Sparky, Kroger Chefbot, and Ulta GLAMlab
[02:45] - Why launch timing isn’t the key to AI assistant success
[03:30] - The “front door always wins” rule: why placement beats features
[05:00] - How reach and frequency shape awareness and adoption
[06:15] - Why category retailers should double down on specialization
[07:45] - Three takeaways retailers need to accept about AI assistant success
[08:45] - What brands must prepare for in the fragmented retail AI landscape

Links & Resources

• Acosta Group's Shopper Insights
• Supermarket News article on Kroger Chefbot
• My article Walmart Reveals AI Roadmap That Points To A World Without Search Bars
• My article Why Agentic Shopping Poses an Existential Threat to Retail Media (Part 1)
• Subscribe to Retail Media Breakfast Club's daily newsletter
• Follow Kiri on LinkedIn

Remember the Amazon FBA boom? When all you needed was an Alibaba find, a seller account and a dream? Between 2012 and 2020, thousands of entrepreneurs built entire businesses inside Amazon’s walls. And for a while, it was a gold rush. But like all gold rushes, the music eventually stopped. Costs went up, competition flooded in, and only a select few brands broke free.

Today, we’re standing at the edge of a similar moment — this time, powered by AI marketplaces. Imagine AI agents that don’t just recommend products, but handle the entire transaction right inside the conversation. The opportunity is huge… but the window will be even shorter. 

In this episode, I unpack the striking parallels between Amazon’s FBA era and the coming wave of AI-powered commerce, explore what AI-native brands might look like, and explain why the gold rush could be over in months, not years.

This episode is sponsored by Connected Commerce at Acosta Group

Timeline

[00:00] – Looking back at the Amazon FBA boom and how it created a new business model for entrepreneurial suburbanites.
[02:13] – The simplicity and early profitability of FBA for first movers.
[04:02] – The predictable shift from organic discovery to pay-to-play on Amazon.
[05:23] – How AI marketplaces could compress the same cycle into months.
[07:14] – The rise of AI-native brands and how small teams could scale to $100M+.
[09:15] – The risk of losing control over customer relationships in an AI-driven shopping world.
[10:12] – Why the AI marketplace gold rush will close much faster than Amazon’s.

Links & Resources

• Marketplace Pulse article Amazon Takes a 50% Cut of Sellers' Revenue
• Retail Media Breakfast Club article Mary Meeker Is So Back: My Notes From Her 340-Page AI Futurecast
• Karl Haller episode of Retailgentic podcast The AI-Native Brand Revolution: A Conversation with IBM’s Karl Haller
• Follow Karl Haller on LinkedIn
• Subscribe to Retail Media Breakfast Club's daily newsletter
• Follow Kiri on LinkedIn