In today’s episode, I dive into one of my favorite topics—those unexpected career-defining moments that shape everything. I’m talking about the “sliding doors” decisions that, in hindsight, changed the trajectory of some of the most impressive retail media leaders I know. You’ll hear real, raw stories from brand-side professionals who took chances, followed curiosities, or simply annoyed the right person at the right time—and it paid off.

From mentorship programs that reshaped mindsets to the grind of early Amazon days, and serendipitous job ads in local papers, this episode is packed with career pivot moments that will inspire you to lean into your own opportunities—even the ones that don’t look glamorous at first. Whether you’re new to eCommerce or a seasoned pro, these stories are a reminder that the path to success in retail media is rarely a straight line.

⏱️ Timeline Summary

[1:28] - Julie Liu shares how mentorship with Sarah Hofstetter led her to rethink her career through a new lens of soft skill development.

[3:30] - Josh Clarkson reveals how being persistently curious helped him land a role on the Amazon team—kickstarting his eCommerce journey.

[4:59] - Todd Wegen recalls a bold leap from a dull project management role into a startup that pioneered eCom tools—and eventually Amazon.

[7:00] - Jace Ree tells the story of how a chance conversation led him from shopper marketing into an Amazon Fresh role that changed everything.

[9:33] - Reflections on the evolution of eCommerce and how early adopters paved the way for today’s specialized talent pool.

🔗 Links & Resources
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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
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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)
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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

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The latest Sponsored Product Ads benchmark report from Pentaleap dropped today!
This benchmark compares the performance of major retail media networks across search terms, categories, and bidding models. In this episode I share four major takeaways for brands and advertisers: the importance of testing on mature platforms like Amazon and Walmart, the resilience of long tail queries, the differences between product-first and keyword-first bidding models, and category-specific opportunities. The episode provides actionable insights for brands looking to optimize their advertising strategies on retail media networks.

00:00 Introduction to the Pentaleap Sponsored Products Benchmark Report

00:36 Understanding the Methodology

01:46 Key Takeaways for Brands and Advertisers

01:56 Testing and Scaling on Major Platforms

03:31 Long Tail Resilience and Bidding Models

07:45 Category-Specific Opportunities

09:02 Conclusion and Next Steps

Read this episode as a blog post
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In this episode, I draw a parallel between the diverse approaches to making bolognese sauce and the varied nature of retail media networks.

Just as every cook has their unique bolognese recipe, every retail media network has its own way of managing advertising, measurement, and reporting.

This variety stems from differences in business models, technology, and market positions. I discuss the challenges brands face due to this fragmented landscape, including demands for standardization in metrics and transparency.

I conclude by contemplating whether embracing this variety might actually benefit the industry, much like savoring different takes on a classic dish.

00:00 Introduction: The Perfect Bolognese and Retail Media

01:10 Upcoming Webinar Announcement

02:05 Diverse Retail Media Networks

03:46 Challenges in Standardization

06:18 Retailers' Perspective on Standardization

09:46 Historical Context and Lessons

11:52 Conclusion: Embracing Variety in Retail Media

Read the full blog post here
Register for the Futurecommerce X Keen webinar, May 21st
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In this episode, I share Fidji Simo's remarkable journey as the CEO of Instacart and her upcoming transition to lead OpenAI's consumer products division.

Simo’s tenure at Instacart turned it into a profitable retail technology giant from a pandemic-boosted delivery service. Her key achievements include launching Carrot Ads and Carrot Insights, enhancing Instacart’s advertising business to generate nearly $1 billion in annual revenue.

I explore how Simo's expertise in retail media and AI could shape her role at OpenAI, potentially developing new revenue-generating consumer tools and integrating advanced AI into shopping experiences.

00:00 Fidji Simo's Transition to OpenAI

00:58 Introduction to Retail Media Breakfast Club

01:18 Fidji Simo's Impact at Instacart

03:30 Carrot Ads and Retail Media Network

07:11 AI Innovation in Grocery

07:59 Future Prospects at OpenAI

09:25 Conclusion and Final Thoughts

Retail Media Breakfast Club: Prime Day 2025 Participation Trends

In today's episode, I dive into the results of my recent LinkedIn poll about how brands plan to participate in Prime Day 2025. The numbers tell an interesting story: over half (51.79%) of respondents are either scaling back or skipping Prime Day entirely this year - a significant shift from previous years.

Poll Results:

• Going Bigger: 12.50%
• About the same: 35.7%
• Scaling back: 37.5%
• Skipping it: 14.29%

Why Brands Are Pulling Back:

• New tariff costs (and uncertainty) have made discounting financially difficult, especially for 3P sellers
• Advertising costs continue rising, with Sponsored Products CPCs up 12% during Prime Day 2024
• Amazon's fee structure remains at historically high levels
• Prime Day 2025 will be the first four-day U.S. event, plus eight weeks of "early deals" - stretching budgets thin

Three Cases FOR Prime Day Participation:

1. The Hidden Review Advantage

Jason Landro from Nectar points out that multiplying units sold during Prime Day can dramatically boost your review rate, providing a rankings boost that lasts long after Prime Day ends.

2. The Halo Effect

Data from Envision Horizons showed that even brands not directly participating in Prime Day saw a 60% sales increase compared to average days, with a 45% increase in Return on Ad Spend despite higher competition.

3. Prime Day as a Strategic Product Marketing Laboratory

Katherine McKee suggests using Prime Day strategically for medium-demand products to answer critical questions:

• Is awareness the main obstacle?
• Is pricing off?
• Is the product page set up poorly?
• Does the product have market fit?

Amazon's Perspective

Amazon claims they're seeing a "strong response from selling partners to Prime Day 2025."

Bottom Line

Prime Day 2025 requires more strategic thinking than ever. For some, particularly those with China-dependent supply chains, participation may be impossible. For others, focusing on data collection and review generation rather than pure sales volume might still deliver long-term value.

The era of automatic, all-in Prime Day participation is ending. Brands are becoming more selective and measured in their approach to Amazon's events.

Mentioned in this episode:

• Jason Landro (Nectar)
• Katherine McKee
• Envision Horizons
• Read the BLOG version of this podcast here