Retailgentic | Consumer Behavior & Retail Trend

In this episode, Scot sits down with Debra to unpack what might be the most important shift in digital advertising since social media.This isn’t theoretical. It’s happening right now, and brands that don’t understand it risk getting left out of the new chain of commerce.Highlights Why ChatGPT’s ad rollout is just the beginning, not an experimentThe tension between trust vs. monetization in AI interfacesHow retailers are both excited and terrified of AI shopping agentsThe emergence of “AI Media” as a new category (like social + retail media before it)Why current ad formats are “boring”… and what comes nextHow companies should actually prepare (hint: it’s not just media buying)The shift from advertising to agent influence, and what that means for the futureWe’re still early, but not that early. The rules of digital advertising are being rewritten in real time, and for the first time in decades, the winners aren’t obvious. The question isn’t whether AI will reshape commerce. It’s whether your products, and your data, are ready to compete when agents decide what gets bought.Timestamps: 02:19 – Meet Debra Aho Williamson  05:00 – From social media to AI: spotting the next shift  09:00 – What “AI Ad Economy” actually means  11:00 – Are we at a social media–level inflection point?  13:00 – ChatGPT ads: early signals and what matters  16:00 – Why current AI ads look like search ads  18:00 – Trust vs. monetization: the line platforms can’t cross  23:00 – Why retailers are leading AI ad adoption  25:00 – Google’s AI ad strategy vs. ChatGPT  29:00 – Perplexity, Copilot, and the fragmented landscape  33:00 – Where Meta fits (and why it’s surprising)  35:00 – New ad formats: sponsored prompts + conversational ads  38:00 – Reddit, TikTok, and emerging players  40:00 – How brands should prepare for AI media  43:00 – Why structured product data is critical  45:00 – The future: ads for agents, not humans👉 Connect with Debra: https://www.linkedin.com/in/debrawilliamson/👉 Learn more about Sonata Insights: https://www.sonatainsights.com/🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

Andrew Lipsman, independent media and commerce analyst, questions rapid agentic takeover. Sarah Marzano, eMarketer principal analyst, brings data-driven caution. Ekta Chopra, CDO at e.l.f. Beauty, pushes practical brand prep for AI discovery. Ben Miller, ShopTalk content VP, guides a lively debate. They spar over definitions, consumer adoption timelines, product data and brand visibility in an AI-driven retail future.

Ashish Gupta, VP/GM of Merchant Shopping at Google and Engineering Fellow, leads work on agentic commerce and UCP. He dives into why UCP was created, its open ecosystem design, and how it aims to go beyond checkout. The conversation covers discovery, conversational product data, merchant readiness, and how infrastructure choices will shape AI-driven shopping.

In this episode, we take a deep dive into what buyer-side agentic commerce could actually look like. The conversation explores the origins of the company, why Darryl and Ross focused on reducing friction for buyers, and how that unexpectedly opened up solutions for sellers, payment providers, and enterprise procurement teams as well.The episode also features a live demo of Vendee Labs’ platform, showing conversational discovery, real-time product retrieval, multi-vendor carting, and a multi-item ACP checkout flow. HighlightsWhy Vendee Labs is approaching agentic commerce from the buyer’s perspectiveThe founding story behind the company and the friction that inspired itHow ChatGPT and Claude changed the direction of the productA live demo of conversational commerce across real merchantsWhat a multi-vendor, multi-item ACP checkout could mean for online shoppingWhy autonomous commerce needs legal and governance frameworks, not just AIThe vision for a Universal Protocol Bridge across ACP, UCP, and future standardsHow strong permissions and audit trails could reduce chargebacks and disputesWhy poor product data creates broken outcomes in agentic shoppingWhere Vendee Labs sees opportunity across consumer, B2B, procurement, and white-label use casesVendee Labs is betting that the future of commerce won’t just be agent-powered—it will be buyer-centered, trust-driven, and built to work across whatever protocols come next.Timestamps: 00:06:09 — Ross shares his background in global technology planning and delivery 00:07:23 — Darryl shares his background in retail IT, telecom, AI, and governance 00:08:53 — Darryl reflects on AI before and after the ChatGPT moment 00:10:03 — Discussion on LLMs, explainability, and true intelligence 00:11:26 — The founding story behind Vendee Labs 00:13:13 — How the product evolved into its current form 00:16:06 — The Vendee Labs pitch: changing how the world buys 00:17:06 — Why solving buyer friction also solves seller-side pain points 00:20:18 — Live demo begins 00:21:10 — Running shoes search and conversational discovery demo 00:25:42 — Multi-vendor cart and checkout walkthrough 00:31:06 — Why richer product data is critical for agentic commerce 00:35:46 — Consumer, B2B, procurement, and white-label distribution paths 00:38:46 — Team size, bootstrapping, and current company stage 00:40:39 — Ross outlines roadmap, buyer taxonomy, and MVP plans 00:42:15 — Scot and Darryl discuss adoption speed in agentic commerce 00:44:18 — Darryl’s theory on trust events and adoption 00:45:34 — Governance-by-design versus fixing broken outputs later 00:47:46 — Where to learn more and try the demo👉 Connect with Darryl: https://www.linkedin.com/in/darrylcarlton/👉 Connect with Ross: https://www.linkedin.com/in/rossgardiner/👉 Check out the demo: https://vendeelabs.com/🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

In this episode of the top Agentic Commerce Podcast we explore the powerful shopping powers of the OpenClaw open-source agent. Can the Claw shop on Amazon, shop locally and use the VisionClaw system with META Ray-Ban’s to buy a very hard to search for dog treat? Tune in to find out!Highlights:What OpenClaw is (and why “persistent” changes everything)The real difference between OpenClaw vs. ChatGPT/Claude as toolsHow OpenClaw runs (Mac Mini vs. cloud VPS like DigitalOcean)Why “no guardrails” is both the innovation and the riskRisk mitigation: limiting blast radius with single-use virtual cardsWhy browser-driven commerce is riskier than server-to-server protocols (ACP/UCP)The “skills” layer: how OpenClaw becomes extensible like Lego bricksWhy SERP-style APIs beat slow webpage crawling for shopping tasksLive demos: product search, local inventory, and frictionless checkoutUsing Slack as the agent interface (channels for shopping, health, etc.)The sci-fi moment: Meta Ray-Ban glasses + VisionClaw + Gemini for visual shoppingOpenClaw isn’t the final answer for agentic commerce, security and architecture matter, but it is an incredible preview of where the UX is heading. If you want a glimpse of the “always-on shopping agent” future (and how people are hacking it together right now), this one’s for you. Happy agentic commerce.🦞Timestamps:01:38 — OpenClaw takeover begins: why Scot called Ryan as a lifeline05:26 — What OpenClaw is: persistent agent, open source, “unhinged,” and why that matters08:21 — The “gigantic loop”: always-on agent behavior (old-school “cron jobs,” new-school autonomy)09:26 — The killer feature: OpenClaw keeps working after you close your laptop12:33 — Read-only Gmail as an assistant: catching missed emails + reducing cognitive load14:35 — The trap: spending time building automation to “save time” (catch-22)15:33 — Why OpenClaw-style commerce is riskier than ACP/UCP: browser manipulation18:02 — Gateway Dashboard tour: where OpenClaw is configured (channels, skills, cron jobs)20:30 — Skill spotlight: Rye for agentic Amazon-friendly purchasing22:39 — Skill spotlight: SERP API for faster product search + ratings without crawling24:30 — Skill spotlight: Buy Anything for context-filled checkout (address, identity, card)28:19 — Demo: “Find me the 5 best-rated 65-inch TVs” (online + local)35:20 — Live purchase demo: finding USB-C cables, choosing Anker, and the agent checks out37:05 — “Most frictionless checkout”: no login, agent already knows everything37:31 — What this means for Alexa: why “available 24/7” changes habits39:07 — Meta Glasses demo setup: first-person vision commerce 40:24 — Vision commerce in action: identifies product + searches best price automatically41:34 — Multi-store results: Amazon + Chewy + Walmart links dropped into Slack👉 Connect with Ryan: https://www.linkedin.com/in/ryaneade/🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

Retail media has been a profit engine for retailers, especially onsite sponsored product ads with massive margins. But what happens when shopping shifts from browsing and searching to AI agents that “decide the SKU” before a shopper ever hits a retailer site? In this episode, Scot and Kiri map the collision course between retail media networks and agentic commerce, walk through emerging ad formats from Google, Amazon (Rufus), and LLMs, and dig into the hardest problem of all: monetizing AI attention without breaking trust.What’s Covered:Why agentic shopping compresses the journey, and shrinks onsite ad inventoryThe “two threats” to onsite retail mediaHow offsite retail media depends on audience signals that may dry up as browsing declinesWhy in-store media may be the most resilient channel Google’s “Direct Offers,” the rise of an agentic storefront, and what it unlocksThe emerging idea of “Agentic PLAs” and retailers bidding at the SKU level (Buy Box vibes)Kiri’s wishlist: multimodal ads (video/try-ons), offsite audience extension, and contextual targeting over “creepy” behavioral retargetingAgentic commerce won’t kill advertising, but it will force it to evolve fast. The winners will be the platforms that can monetize attention without sacrificing trust, and the brands/retailers that learn to show up in these new surfaces early.Timestamps00:05:04 — Meet Kiri Masters + Retail Media Breakfast Club00:08:01 — The three buckets: onsite, offsite, in-store retail media00:10:01 — Why onsite is the money machine (and most vulnerable)00:11:11 — Offsite retail media + closed-loop attribution00:14:23 — In-store media: small today, resilient tomorrow00:16:11 — Are retailers already seeing traffic shifts? Category matters00:19:27 — ChatGPT ads: early signals and why it’s still rudimentary00:21:22 — Scott’s framework: ad formats + Instant Checkout incentives00:23:06 — Google’s “Direct Offers” and the agentic storefront idea00:25:10 — Collaborative bidding: retailer + brand split the spend00:28:11 — Google testing new units: “Agentic PLA” / paid retailer placement00:33:14 — Trust vs monetization: don’t break the golden goose00:34:04 — Amazon Rufus: sponsored prompts as a new surface00:39:08 — Instacart’s ad playbook + trade dollars as inspiration00:40:38 — Why it’s not a race to the bottom: service layers + loyalty00:43:24 — The big hope: context-based targeting over creepy retargetingk00:46:52 — If Kiri ran ChatGPT ads: offsite + multimodal + new formats00:48:04 — Virtual try-ons + “throw away the sponsored product textbook”00:50:00 — Closing + follow Retailgentic👉 Connect with Kiri: https://www.linkedin.com/in/kiri-masters/👉 Learn more about Retail Media Breakfast Club: https://www.retailmediabreakfastclub.com🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai 📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

True Fit is evolving from a static “what size should I buy?” widget into a conversational agent that can handle the nuanced questions shoppers actually ask: comfort, flattering fit, fabric behavior, and edge cases like petite proportions. We also dig into how vertical agents (like True Fit) can accelerate horizontal super-agents via Model Context Protocol (MCP), and why the future of agentic shopping will be built on clean, structured, prioritized proprietary data, not scraped internet sentiment.HighlightsTrue Fit’s specialized size + fit agent (and why it matters now)Why 70% of fashion agent questions are about size/fitThe “Fit Passport”: from form-filling to natural conversation profilingWhat generic agents miss: real-time sales + returns behavior, not just PDPs/reviewsVertical vs. horizontal agents, and how True Fit uses MCP as an accelerantThe unglamorous moat: data cleaning, normalization, canonicalizationTrue Fit scale: 80M active users, hundreds of millions of profiles, ~100K brands, ~500 retailersIf agentic commerce is collapsing the funnel, fit is one of the biggest friction points left, and True Fit is making it a first-class agent powered by the kind of data most models will never see.Timestamps01:44 — Breaking news episode + guest intro (Jessica Murphy, True Fit)03:12 — True Fit announces a specialized size + fit agent04:20 — From static widget to agentic shopping assistant05:47 — Why fit-related returns are so brutal in apparel07:02 — What the agent experience looks like08:05 — “Fit Passport” and conversational profiling09:07 — Where checkout happens (and what’s coming later)10:17 — Why generic agents break: stale info + limited context11:35 — The moat: structuring + cleaning sizing data12:30 — Vertical vs. horizontal agents13:29 — MCP as an accelerant for super-agents15:18 — Top-of-funnel value: narrowing choices to “most likely kept”16:10 — Who might use TrueFit’s MCP (LLMs + agent builders)16:37 — Availability: March partners, April target GA18:01 — Founder story: why Jessica started True Fit19:41 — Fundraising reality + “it’s a data problem”21:16 — True Fit scale + global complexity of sizing👉 Connect with Jessica: https://www.linkedin.com/in/jessica-murphy-68a8b8/👉 Learn more about True Fit: https://www.truefit.com/🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai 📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

There’s a fundamental difference between adding AI to today’s ecommerce workflows and re-architecting commerce for an agent-driven world.In this episode, we start with Deloitte’s Agentic Commerce paper and quickly fan out into what’s changed since its release. If you’re trying to separate signal from noise in the rush toward AI-powered shopping, this conversation grounds Agentic Commerce in real systems, real economics, and real decisions retailers need to make now.Highlights Why Agentic Commerce is a paradigm shift, not a bundle of AI featuresThe evolution from SEO → GEO → ACO, and why GEO is just a waypointThe two biggest misconceptions Deloitte is hearing from retailers and brandsWhy structured product + data catalogs are the no-regret investmentThe real question execs keep asking: Where do we start? (and what’s measurable)The “Acommerce ecosystem”: orchestrators + specialized “nano agents”Trust, security, returns, customer service, and why this can’t be a side projectForecasts for how big agentic commerce gets, and why the point is: it moves the needleAgentic commerce is becoming a new channel with new unit economics, and the brands and retailers that get their product truth, governance, and trust foundations right now will be the ones that win when agents become the default interface.Timestamps:01:54 — Meet Deloitte02:10 — The paper: Agentic Commerce: Redefining Retail Economics03:55 — ACO + the SEO/GEO conversation04:11 — VJ’s background: SAP → Deloitte, retail AI intersection05:50 — Brian’s background: supply chain → strategy → consulting07:49 — “Traditional AI” vs GenAI in retail09:38 — Why Deloitte wrote the paper (and why GEO isn’t the endpoint)11:49 — Deloitte’s definition: why it’s a journey, not a switch13:33 — NRF vibe check + what’s changed since December14:27 — Common misconceptions (and what leaders miss end-to-end)16:14 — The questions execs are asking: where to start + ROI18:03 — Why this could be a golden age of storytelling + loyalty21:06 — The no-regret starting point: catalogs + structured data21:34 — Org design + governance + democratizing AI usage23:15 — CFO-ready thinking: measuring value by channel26:12 — Zero-click pressure + “what are you doing about it?”28:31 — Balanced portfolio: fast wins vs complex upside30:32 — The core distinction, again: AI add-ons vs agentic redesign31:18 — Do we still need websites? (channels vs replacement)33:17 — Deloitte’s role: advise, build, operate37:29 — “Acommerce” + ecosystems of nano agents41:31 — Protocols + UCP + what changes next42:50 — Meta, OpenAI, Google: where this is headed46:58 — 2030 forecasts: conservative vs aggressive cases50:02 — Where to follow Saurabh's podcast: The Retail Tales👉 Connect with Saurabh: https://www.linkedin.com/in/svijayvergia/👉 Connect with Brian: https://www.linkedin.com/in/briancmccarthy/👉 Learn more about Deloitte: https://www.deloitte.com/us/en.htmlCheck out the materials we discuss: 🔗 Agentic Commerce: Redefining Retail Economic🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai 📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

Ian Simpson, SVP of Innovation and Strategy at Sensor Tower, leads data-driven retail media research. He breaks down Holiday ’25 Rufus funnel data and a reported ~3.5× conversion lift. They discuss where Rufus shows up in shopping flows, ten distinct conversational shopping profiles, intent and attribution caveats, and why brands should focus on product truth, reviews, and storytelling as AI-driven shopping grows.

Ken Moore, Mastercard Chief Innovation Officer and head of Foundry, builds production-grade products for secure agentic commerce. He breaks down Agent Pay, Know Your Agent, Order Intent, Insight Tokens, passkeys/biometrics, and the Agentic Toolkit. The conversation focuses on trust, tokenization, consent, standards, and how to move from experiments to global scale.