Today I’m digging into the latest insights from Pentaleap’s biannual Sponsored Products Benchmark Report—and it’s challenging some long-held assumptions about online advertising. Shoppers say they don’t love ads, but the data tells a different story. I’m sharing what Amazon, Walmart, and Home Depot are doing right when it comes to high-volume sponsored product listings—and what mid-tier retailers can learn as they scale their retail media networks.

We explore the delicate balance between ad inventory expansion and shopper satisfaction, and I highlight how smart retailers are mastering ad relevance to avoid click fatigue. I also break down why increasing sponsored product coverage doesn’t have to mean compromising user experience—and how it can actually unlock significant revenue potential if done right. Whether you’re building your retail media strategy or refining an existing one, this episode is packed with practical takeaways.

🕒 Episode Timeline

[0:36] - The surprising truth: heavy ad coverage doesn’t always hurt engagement

[1:22] - Market leaders vs. mid-tier retailers: who’s winning at retail media

[2:26] - Kroger’s leap in ad coverage and why it matters

[3:18] - Why under-monetized search inventory is still a missed opportunity

[4:24] - How Amazon keeps CTR high even with more ads

[5:25] - Grid strategies: how Walmart, Staples, and CVS handle ad placement

[6:39] - The risk of irrelevant ads—and how they can hurt both sales and trust

[7:35] - A simple framework to decide how many ads are too many

[8:00] - Key takeaways for maximizing retail media without annoying your shoppers

🔗 Links
Pentaleap's 1H25 Sponsored Product Benchmark report
Read the original post for this episode in my Forbes column
Subscribe to Retail Media Breakfast Club's daily newsletter

Follow Kiri on LinkedIn

In today’s episode, I unpack why so many shoppers are brushing off AI chatbots and recommendation engines—even as they quietly benefit from other AI-powered features during their online shopping journeys. Drawing insights from a fresh Akeneo survey of U.S. consumers, I highlight the trust gap that exists when it comes to visible AI tech like chatbots versus the more invisible enhancements like AI-generated review summaries.

We’ll explore how consumer behavior contradicts what they say in surveys, why retailers might be misplacing their AI bets, and what types of AI integration actually do enhance the customer experience. This one’s a reality check for anyone building out retail AI strategies—and a bit of a defense for the oft-maligned chatbot (well… kinda).

Chapters

[00:00] – Reflecting on yesterday’s AI chatbot critique

[00:46] – New survey reveals big gap: 75% encounter AI, but only 44% engage

[01:33] – Why consumers claim they don’t trust AI shopping tools

[02:18] – The problem with self-reported surveys in understanding tech behavior

[02:40] – Amazon’s quiet success with AI-generated review highlights

[03:52] – Consumers unknowingly love certain AI features—but hate the label

[04:32] – The paradox: people trust ChatGPT, but not your retail chatbot

[05:19] – Where retailers should (and shouldn’t) use AI in customer experiences

[05:36] – Invitation to join the upcoming “Retail Media Halo Effect” webinar

Register for the Future Commerce webinar, "The Retail Media Halo Effect," on Wednesday (May 21, 2PM ET)
Subscribe to Retail Media Breakfast Club's daily newsletter

Follow Kiri on LinkedIn

Last week the Wall Street Journal reported that Walmart is building its own shopping agents for tasks like reordering groceries and handling requests like "plan a unicorn-themed party for my daughter." I walk through the key details: how Walmart is developing agent-to-agent protocols, preparing for interoperability with third-party agents, and recognizing that agent shopping is fundamentally different from human shopping.

How This Connects to Other AI Developments

I compare Walmart's open ecosystem approach to Amazon's walled garden strategy. While Amazon blocks other AI agents to develop their own suite (Alexa+, Buy For Me, Rufus), Walmart is preparing to work with both their own agents and third-party ones. I explain two key open standards - Google's Agent to Agent protocol and Anthropic's Model Context Protocol - that could enable this interoperability.

Industry Reactions

I share perspectives from industry experts, including Eric Heller's point about the importance of complete product detail pages and Bryan Gott's question about whether consumers actually want AI help. I discuss why cohort data matters more than individual reactions and explain the difference between underwhelming retailer chatbots and effective AI collaboration tools.

My Analysis and Outstanding Questions

I explore several key questions: What happens to Sponsored Product Ads when agents do the shopping? What's the opportunity cost for retailers building proprietary assistants versus preparing for third-party integration? How will site performance become competitive as agent traffic creates new load patterns?

I conclude that the winners won't be retailers with the flashiest AI features, but those who make it seamless for both humans and bots to do business with them.

Chapters:
00:00:00 - Breaking News: Walmart's AI Shopping Agent
00:00:17 - Introduction to Retail Media Breakfast Club
00:00:38 - Walmart's AI Shopping Agent: Key Takeaways
00:03:01 - Comparing Walmart and Amazon's AI Strategies
00:04:45 - Technical Insights: Open Standards and Protocols
00:05:58 - Industry Perspectives on AI Shopping Agents
00:08:06 - Final Thoughts and Conclusion

Subscribe to Retail Media Breakfast Club's daily newsletter

Follow Kiri on LinkedIn