Retailgentic | Consumer Behavior & Retail Trend

This week’s episode is a little different. We’ve has been noticing vibe-code platforms quietly showing up all over digital retail… at trade shows, in conversations with retailers and brands, and on the platforms’ own commerce pages. So we went to the source. This is a platform deep dive with Vercel, the enterprise company behind v0 and Next.js, on what a “vibe coding” company is actually doing in our world of commerce, and it turns out the answer is: a lot more than you’d think.Highlights 𝗧𝗵𝗲 𝟭𝟬𝟬-𝗺𝗶𝗹𝗹𝗶𝘀𝗲𝗰𝗼𝗻𝗱 𝗺𝗮𝘁𝗵: A Deloitte Digital + Google study cites clients found 100ms of load-time reduction drives a 7–8% lift in e-commerce conversion. “If the thing is faster, you’re gonna convert more. It’s just math.”𝗛𝗲𝗹𝗹𝘆 𝗛𝗮𝗻𝘀𝗲𝗻’𝘀 𝗻𝘂𝗺𝗯𝗲𝗿𝘀: The Kontoor Brands-owned retailer cut load times from 2.5 to 1.5 seconds on Vercel, grew conversion 20% year over year, doubled its A/B test velocity, and blew away its Black Friday/Cyber Monday plan.𝗧𝗵𝗲 𝗰𝗼𝗰𝗸𝘁𝗮𝗶𝗹-𝗽𝗮𝗿𝘁𝘆 𝗽𝗶𝘁𝗰𝗵: Vercel in three phrases… a developer tools company, an infrastructure provider, and an open-source software factory.𝗬𝗼𝘂’𝘃𝗲 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝘂𝘀𝗲𝗱 𝗩𝗲𝗿𝗰𝗲𝗹: walmart.com and target.com run on Next.js, and Under Armour, Crocs, Buck Mason, PetSmart, McAlister’s, DeWalt, Clorox, and even Meta.ai are Vercel-delivered applications.𝗡𝗼𝘁 𝗮 𝗦𝗵𝗼𝗽𝗶𝗳𝘆 𝗸𝗶𝗹𝗹𝗲𝗿: Vercel doesn’t do product catalogs, inventory, or order management. It’s the storefront layer on top of your commerce platform. “We help you own your storefront and own your destiny.”𝘃𝟬 𝗺𝗲𝗲𝘁𝘀 𝗦𝗵𝗼𝗽𝗶𝗳𝘆: v0 is now deeply integrated with Shopify, so you can customize your storefront in plain English 𝗧𝗶𝗺𝗲𝗹𝗶𝗻𝗲𝘀 𝗵𝗮𝗹𝘃𝗲𝗱: Custom storefront projects that were planned for a year are landing in six months, six-month plans in three.𝗧𝗵𝗲 𝗮𝗴𝗲𝗻𝘁 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿: Next.js 16 was built to be readable and manipulated by Cursor, Claude, and Codex, “now we have this new customer, this agent customer, who wants to interact with your code base.”𝗧𝗵𝗲 𝗹𝗶𝗴𝗵𝘁-𝗯𝘂𝗹𝗯 𝗺𝗼𝗺𝗲𝗻𝘁: Jaime’s conversion story: feeding 50-page client 10-Ks into ChatGPT in early 2023 and realizing everything about go-to-market, and the factories that make software, was about to change.This one really lifted the veil on what the vibe-code platforms are actually doing in retail, and I think we’re just seeing the tip of the iceberg. Enjoy the conversation.Timestamps: 05:29 Welcome Jaime Sorgente06:08 Jaime's path to Vercel: ChatGPT and 10-Ks12:29 Utilities vs. builders15:00 What is Vercel? The cocktail-party pitch17:10 Why retail as a vertical21:20 The Helly Hansen story24:05 Vercel's other verticals: digital natives and marketing26:45 Enabler, not competitor: where Vercel fits vs. Shopify & Salesforce29:35 Beyond the storefront: clienteling and staff apps30:45 Agents everywhere: Crocs, Amazon image annotation36:05 v0 + Shopify: customize your storefront in English37:45 Next.js 16: built for the agent customer39:20 Custom storefront timelines, halved40:35 Does owning your storefront de-risk replatforming?42:20 The 100-millisecond study44:30 The compounding effect: 4X feature velocity46:45 Next.js explained: the stage manager analogy52:20 Framework-defined infrastructure54:30 Vercel vs. Lovable, Replit, and Base4458:15 Where to learn more + wrap-up👉 Connect with Jaime: https://www.linkedin.com/in/jsorgente/👉 Learn more about Vercel: https://vercel.com/for/retail🧠 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

This week’s episode is a deep dive into personalization, a huge category in e-commerce that’s getting rebuilt from the ground up for the AI era. FERMÀT is an AI-native personalization platform that sits on top of your e-commerce platform and customizes the site experience based on a visitor’s behavior, not their identity. That distinction sounds subtle, but it turns out to be the whole ballgame and it connects directly to agentic commerce because agents show up with intent, not an identity. We also pick up Rishabh’s founder journey and some very candid company-building advice along the way.Highlights 𝗧𝗵𝗲 𝟮𝟬% 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗹𝗶𝗳𝘁: FERMÀT's data shows personalizing on behavior alone, even for fully incognito visitors, converts roughly 20% better than personalizing on identity and past purchases.𝗠𝗮𝗻𝘆 𝘁𝗼 𝗼𝗻𝗲, 𝗻𝗼𝘁 𝗼𝗻𝗲 𝘁𝗼 𝗼𝗻𝗲: the marketer's dream of one-to-one was "a lack of imagination", the same person is a different shopper on Instagram, Google, and ChatGPT. 𝗗𝗲𝘁𝗲𝗰𝘁, 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱, 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲: instead of humans watching a sample of session recordings and shipping site changes months later, agents trained on commerce watch every session, recommend changes, and generate the new experience.𝗧𝗵𝗲 𝗕𝗹𝗼𝗼𝗺𝗿𝗲𝗮𝗰𝗵 𝗽𝗿𝗼𝘃𝗼𝗰𝗮𝘁𝗶𝗼𝗻: identity-based personalization was state-of-the-art 10 years ago. Rishabh's take on the incumbents: if nothing changes, "their 3 to 400 million of revenue will become 2 to 300."𝗠𝗶𝗻𝗲 𝘁𝗵𝗲 𝗮𝗱, 𝗻𝗼𝘁 𝘁𝗵𝗲 𝗜𝗗: even when an Instagram visitor is anonymous, the ad they clicked carries demographics, performance history, and frequency data… context most brands never use.𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗲𝘀𝘁𝗮𝘁𝗲 𝗮𝗴𝗲𝗻𝘁 𝘁𝗲𝘀𝘁: an agent is only as good as the feedback, context, and iteration speed you give it and every "actually, I also care about the collar" update is behavior data.𝗦𝗮𝘆 𝘄𝗵𝗮𝘁'𝘀 𝘁𝗿𝘂𝗲: Platforms are using AI to verify your pages and truth gets rewarded, not dinged.𝗦𝘂𝗽𝗽𝗼𝗿𝘁 𝗮𝗴𝗲𝗻𝘁 ≠ 𝘀𝗵𝗼𝗽𝗽𝗲𝗿 𝗮𝗴𝗲𝗻𝘁: support agents should stick to facts and policies; shopper agents should infer.Rishabh is one of the clearest thinkers I’ve talked to on where personalization goes in an agent-first world, and his founder advice at the end is worth the listen on its own. Enjoy the conversation.Timestamps: 02:44 Welcome Rishabh 03:37 Rishabh's backstory: physics, Wall Street, PhD06:33 Building three businesses at LiveRamp07:56 Founding story: Apple ATT and iOS 14.510:33 Detect, recommend, generate12:27 Where FERMÀT sits in the stack13:57 Many-to-one personalization15:22 The Bloomreach question19:00 Does current behavior beat past behavior?21:18 The data: a 20% conversion lift22:34 The agentic commerce connection23:44 The real estate agent analogy25:41 Reading intent from incognito traffic26:28 Into the weeds: mining a Meta ad for context30:37 Side quest: the SEO cloaking myth33:47 Writing for agents, bots, and humans34:49 On-site shopper agents39:40 Company building: know your why42:38 Where to find Rishabh + the 1 to 100 podcast👉 Connect with Rishabh: https://www.linkedin.com/in/rishabhmjain/👉 Learn more about FERMÀT: https://www.fermatcommerce.com/👉 1 to 100 podcast: https://open.spotify.com/show/6WAB5oOzco9oWrQmYmuFZ6🧠 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

This week’s episode is a data deep dive… two of them, actually. Salesforce just dropped a back-to-back data release: the latest edition of its State of Commerce report and its Holiday 2026 predictions. Caila Schwartz, Salesforce’s newly minted Head of Agentic Commerce Shopper Insights, walks us through both. Think of it as a rearview mirror on the first half of 2026 and headlights into the holiday season, with agentic commerce showing up in nearly every number.Highlights:𝗧𝗵𝗲 𝟮𝟬𝟬% 𝗷𝘂𝗺𝗽: 15% of shoppers now start their buying journey with an LLM or agent, up from 5% last spring.𝗛𝗮𝗹𝗳 𝗼𝗳 𝘀𝗵𝗼𝗽𝗽𝗲𝗿𝘀: About 50% have used a general-purpose LLM, social media agent, or branded agent somewhere in their buying journey in the past 12 months, a 67% increase over last year.𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗸𝗶𝗻𝗴: Agentic search traffic converts at roughly 2.5–3.5%, about 2–3x overall conversion and far above social’s sub-1%.𝗧𝗵𝗲 𝘁𝗿𝘂𝘀𝘁 𝗻𝘂𝗺𝗯𝗲𝗿𝘀: 74% of shoppers trust agent recommendations, and over 80% feel more confident in purchases made after interacting with a brand-owned agent like Rufus or Sparky.𝗧𝗵𝗲 𝗿𝗲𝗳𝗲𝗿𝗿𝗮𝗹 𝗯𝗹𝗶𝗻𝗱 𝘀𝗽𝗼𝘁: Discovery is happening inside conversations that never send a click back to the brand site.𝗧𝗵𝗲 𝗖𝗮𝗶𝗹𝗮 𝗙𝗶𝘃𝗲: Salesforce’s Holiday 2026 predictions: non-human traffic, branded agents everywhere, social commerce acceleration, the store’s new hybrid role, and the free-shipping squeeze.𝟮𝟬% 𝗻𝗼𝗻-𝗵𝘂𝗺𝗮𝗻 𝘁𝗿𝗮𝗳𝗳𝗶𝗰: This holiday, Salesforce predicts about one in five e-commerce visits will come from crawlers and agents, not people.𝗕𝗿𝗮𝗻𝗱𝗲𝗱 𝗮𝗴𝗲𝗻𝘁 𝗿𝗮𝗰𝗲: About a third of B2C orgs have agents deployed today, over half plan to deploy within six months, and by Cyber Week one in three e-commerce sites will have a branded agent on site.𝗦𝗼𝗰𝗶𝗮𝗹 𝗴𝗿𝗼𝘄𝘀 𝟵𝗫: Social commerce is predicted to grow nine times faster than traditional e-commerce this year, and it’s high-income shoppers, even more than Gen Z, saying they’ll buy in-app this holiday.𝗛𝘆𝗯𝗿𝗶𝗱 𝗵𝗼𝗹𝗶𝗱𝗮𝘆: 37% of holiday dollars will be “hybrid sales” that rely on both digital and physical to close the deal, 80% of shoppers use their phone while standing in your store.𝗗𝗮𝘁𝗮 𝗶𝘀 𝘁𝗵𝗲 𝗯𝗲𝗱𝗿𝗼𝗰𝗸: Four in five commerce pros say their tech stack grew over the last two years, making data unification the #1 barrier to good agents.Caila brings the receipts, real numbers on a shift most of us are still trying to eyeball. We’ll get her back in the fall when the actual holiday forecast drops. Enjoy the conversation.Timestamps: 06:30 Interview begins, Caila's new title07:20 Caila's role and 12 years at Salesforce08:30 Two reports: State of Commerce + Holiday predictions09:30 State of Commerce methodology12:50 What's new in this edition14:45 The agentic discovery shift: 50%, 200%, 15%17:25 Who's losing share in discovery19:00 Faster than mobile or social ever moved22:20 The measurability problem25:20 Conversion: 2–3x better than average27:10 Why shoppers lean on agents, by income29:30 Trust: 74% and the 80% confidence stat32:00 The branded-agent race34:30 The #1 barrier: data unification40:20 Caila Five #1: 20% non-human traffic42:30 #2: One in three sites get a branded agent43:15 #3: Social commerce grows 9x44:25 #4: The store's new role 37% hybrid sales46:20 #5: Free shipping and the K-shaped economy47:30 Decoupled transactions deep dive53:10 Top recos: unify data, turn on ACP👉 Connect with Caila: https://www.linkedin.com/in/caila-schwartz/👉 Learn more about Salesforce: https://www.salesforce.com/👉 Check out the State of Ecommerce: https://www.salesforce.com/commerce/resources/state-of-commerce/👉 Look at the Holiday 2026 Predictions: https://www.salesforce.com/blog/holiday-retail-predictions-2026/🧠 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

This one is a build deep dive. Daniel has spent eight years on the same problem, and the answer has changed shape three times along the way: a consumer app in 2018, a shoppable recipe platform in 2023, and now a conversational shopping assistant running inside grocers’ own sites. We go deep on the plumbing here: product catalogs, ontologies, eval systems, model selection, retail media, and what an agent does when a shopper types “taco night.” If you like knowing how these things actually work under the hood, this is your episode.Never miss the latest Retailgentic news→Highlights:𝗧𝗵𝗲 𝗻𝘂𝗺𝗯𝗲𝗿𝘀: Live in over 700 stores, reaching over 10 million shoppers, with the number of locations set to double before the end of the year. The consumer app has over a million users. 𝟰𝟭 𝗱𝗮𝘆𝘀 𝗰𝗼𝗻𝘁𝗿𝗮𝗰𝘁 𝘁𝗼 𝗹𝗶𝘃𝗲: A one-line JavaScript install that reuses the retailer’s existing catalog, add-to-cart, analytics, and retail media. National scale in six weeks.𝗦𝗲𝗮𝗿𝗰𝗵 𝗮𝗻𝗱 𝘀𝗲𝗹𝗲𝗰𝘁 → 𝗿𝗲𝘃𝗶𝗲𝘄 𝗮𝗻𝗱 𝗮𝗰𝗰𝗲𝗽𝘁: Daniel’s framing for the whole shift. The old era: you search one thing, you select it. The new one: the agent assembles a solution and you approve it. 𝗧𝗵𝗲 𝗲𝘃𝗮𝗹 𝘀𝘆𝘀𝘁𝗲𝗺: Thousands of test scenarios with grading criteria aligned to each retailer’s merchandising principles, run tens or hundreds of times to get a distribution of responses. 𝗧𝗵𝗲 𝗳𝗶𝘀𝗵 𝗿𝘂𝗹𝗲: Retailers write procedures the agent pulls when a scenario matches. One of Daniel’s favorites: if you’re cooking fish today or tomorrow, it recommends fresh. If it’s later in the week, frozen.𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗮 𝗻𝗲𝘄 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗲: Onboarding is essentially an interview with the business. What are your values? How do you respond? What are your merchandising principles? That becomes the agent’s identity and personality. 𝟭,𝟬𝟬𝟬 𝗙𝗼𝘂𝗿𝘁𝗵 𝗼𝗳 𝗝𝘂𝗹𝘆 𝗯𝘂𝗻𝗱𝗹𝗲𝘀: Instead of one holiday carousel every shopper sees, merchant teams define ~20 axes — price, dietary needs, brand preference — and an agentic process generates permutations personalized against transaction history.𝗔𝗜 𝗖𝗵𝗲𝗳𝘀 𝗼𝗻 𝗧𝗶𝗸𝗧𝗼𝗸: Long before ChatGPT, Cooklist ran a TikTok series generating recipes with GPT-2 and early GPT-3. The models got good at basic recipes so fast that the fun moved to challenging them to be creative.Daniel is one of those founders who has clearly built the thing himself, and it shows in the answers. We learned about a thousand things from this one. Enjoy the conversation.Timestamps:02:57 Welcome Daniel Vitiello, CEO & co-founder of Cooklist03:10 Grocery, CPG, and retailer-hosted agents: the pod's favorite topics04:46 The $1 check and the handwritten letter for loyalty data05:46 Why 2017 was the moment06:12 Inside the Cooklist app: home inventory and the AI chef07:35 AI as the thread: Kurzweil, GPT-2, and the AI Chefs TikTok series09:37 B2C to B2B, and the synergies of running both12:05 The cat food problem13:34 The core identity system: hummus, three ways15:58 Search and select vs. review and accept16:23 The spark for B2B: Target, Techstars, and saying no18:45 Recipe commerce and meal-pairing merchandising20:19 Funding: RevTech, Mercury Fund, and profitability21:56 Freemium, pro, and advertising in the app22:48 700 stores, 10 million shoppers24:28 The flagship deployment: live in 41 days25:56 Ontology, context engineering, and interviewing the retailer27:03 Non-determinism and the eval system29:06 Entry points: sparkles, suggested prompts, and PDP workflows31:01 How the catalog and inventory get in33:41 Procedures: the weekly flyer and the fish rule35:55 Cost, speed, and the token-efficient stream37:38 Model agnostic: scoring Opus against Sonnet38:15 Instacart, Storefront Pro, and winning head-to-head39:47 Retail media and Criteo40:22 Agentic search and the "taco night" problem42:02 Agentic merchandising: 1,000 Fourth of July bundles42:55 Proactive carts, and the 50% who finish in the store43:43 Smart fridges and forecasting demand44:44 Where to find Daniel👉 Connect with Daniel: https://www.linkedin.com/in/dkvitiello/👉 Learn more about Cooklist: https://cooklist.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

This week Retailgentic goes full Tron… in reverse. Instead of getting sucked into the digital world, Scot steps out of it and into into the analog one, bringing the AI angle with us. Ben Rodier is the first AI guest on the show who isn’t from e-commerce. He’s building physical AI for the sales floor: an AI sales coach for the people who sell to you face-to-face in furniture stores, apparel shops, bank branches, and beyond. It’s part founder-journey story (three companies, two exits, twenty years in retail) and part product deep dive into how you actually coach a human salesperson with AI without being creepy about it.Highlights 𝗧𝗵𝗲 𝗥𝘂𝗹𝗲 𝗼𝗳 𝟯𝟬: There’s an inflection point (around 30 AI coaching sessions) where practice turns measurable. Reps who cross it sell roughly $2,000 more per week, about $100,000 more per year, than those who don’t.𝗧𝗵𝗲 𝗰𝗿𝗼𝗰𝗼𝗱𝗶𝗹𝗲 𝗰𝗵𝗮𝗿𝘁: Plot the reps who practiced 30+ times against those who practiced 10, and the two lines pull apart into a “crocodile-shaped separation”… the clearest picture of coaching ROI Ben’s ever had.𝗧𝗿𝘂𝘀𝘁-𝗳𝗶𝗿𝘀𝘁 𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲: Data (find the goal) → AI role play (practice it) → privacy-compliant listening (coach the real conversation). Each step earns the right to the next.𝗥𝗼𝗹𝗲 𝗽𝗹𝗮𝘆 𝗶𝗻 𝘃𝗼𝗶𝗰𝗲 𝗺𝗼𝗱𝗲: The coach is a ChatGPT-style voice agent trained on your company’s own playbook. It throws curveballs, like someone walking into the room mid-pitch. “No one likes to do role play with their manager. It’s super awkward.”𝗔 𝗽𝗿𝗼𝗳𝗶𝘁 𝗰𝗲𝗻𝘁𝗲𝗿, 𝗻𝗼𝘁 𝗮 𝗰𝗼𝘀𝘁 𝗰𝗲𝗻𝘁𝗲𝗿: Unlike most training software, if you practice you sell more so the tool pays for itself. 𝗕𝗼𝗿𝗻 𝗼𝗻 𝘁𝗵𝗲 𝗳𝗹𝗼𝗼𝗿: Ben invented retail-media ads on Walmart’s website in 2009 before the term existed. Google execs opened a meeting with: “Who are you, and how did you figure out how to get these properties as advertising publishers?”𝗧𝗵𝗲 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 𝘃𝗲𝗿𝗱𝗶𝗰𝘁: McDonald’s tried a humanless AI drive-through and it “failed miserably”. They pivoted right back to a human. Ben’s bet: five years out, most buying and selling is still face-to-face.It’s not often we leave the digital surface behind on this show, but Ben’s take on physical AI, and what happens when the sales floor and the digital world finally connect, is one of the more grounded, human conversations we’ve had. Enjoy the conversation.00:46 Welcome to Retailgentic02:01 Scot's intro: a fun diversion into physical AI03:47 Meet Ben Rodier, FrontlineIQ04:33 From a TJ Maxx floor to third-time founder06:07 Sales guy, not a technical founder06:53 Corporate to startup: the TV advertising leap07:37 Inventing retail media on Walmart's site in 200910:31 Salesfloor: the original idea13:42 Bootstrapping, PE at the pandemic peak, the Tulip merger17:19 The genesis of FrontlineIQ: Up Labs & Ashley20:10 What "physical AI" actually means21:24 Launching Jan 1, 2025 & hiring AI-native talent24:41 30 customers in under 18 months27:36 The oversubscribed seed round28:46 How it works, part 1: data & trust30:58 Part 2: AI role play in voice mode32:43 Part 3: privacy-compliant listening36:00 The Rule of 30 & the "up" system37:33 Coach the coach, God view & the control center39:48 ROI: the crocodile chart & turnover45:14 The future: cameras, glasses & Plaud pins49:23 Robots on the floor? The McDonald's test51:44 Merchandising insight from what reps hear52:36 Where to learn more & outro👉 Connect with Ben: https://www.linkedin.com/in/benrodier/👉 Learn more about FrontlineIQ: https://www.frontlineiq.ai/🧠 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

This week Scot goes on a markets deep dive with one of Wall Street's leading internet analysts. It’s a tour through the mega-cap playbook (Meta, Amazon, Google, eBay, Shopify) and how professional investors are actually pricing the agentic-commerce shift. Colin covers over $12 trillion of market cap across five names alone, so this is the view from the models, the channel checks, and the trading desk.This is a wide-ranging, numbers-forward conversation about where the money moves as agents become the buyers and which companies Wall Street thinks come out ahead. Highlights:𝗧𝗵𝗲 𝗦𝗣𝗘𝗘𝗗 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: Baird’s formula for internet winners: Scale, Product, Engineering, Efficiency, and Data. Nail all five, and the competitive advantage compounds.“𝗟𝗲𝘁 𝘁𝗵𝗲 𝗮𝗴𝗲𝗻𝘁 𝗱𝗼 𝘁𝗵𝗲 𝘄𝗮𝗹𝗸𝗶𝗻𝗴”: Colin explains why skeptics are dramatically underestimating the size of the opportunity.𝗠𝗲𝘁𝗮 𝗶𝘀 𝘁𝗵𝗶𝘀 𝘆𝗲𝗮𝗿’𝘀 𝘁𝗼𝗽 𝗽𝗶𝗰𝗸: Colin’s highest-conviction AI bet is Meta driven by WhatsApp business agents, Meta AI, and unmatched consumer reach. (Last year’s pick: Google.)𝗠𝗼𝗱𝗲𝗹𝘀 𝘄𝗶𝗹𝗹 𝗯𝗲𝗰𝗼𝗺𝗲 𝗰𝗼𝗺𝗺𝗼𝗱𝗶𝘁𝘆: The real value won’t live in foundation models, it accrues to the platforms, applications, and distribution layers built on top.𝗔𝗺𝗮𝘇𝗼𝗻’𝘀 𝗼𝗻𝗲-𝘄𝗮𝘆 𝗱𝗼𝗼𝗿: By opening its catalog to AI agents, Amazon may have crossed a line it can’t reverse and that could strengthen its ecosystem even further.“𝗖𝗹𝗼𝘀𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗲𝘆𝗲𝘀 𝘁𝗼 𝘁𝗵𝗲 𝗯𝗶𝗹𝗹𝗯𝗼𝗮𝗿𝗱𝘀”: If AI agents skip search results and category pages, they also skip the ads, putting pressure on retail media’s biggest revenue stream.𝗪𝗵𝗼 𝗼𝘄𝗻𝘀 𝘁𝗵𝗲 𝗮𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰𝗮𝘁𝗲𝗱 𝗰𝗼𝗻𝘀𝘂𝗺𝗲𝗿 𝘄𝗶𝗻𝘀: The long-term winners will control identity, payments, checkout, and fulfillment, not just discovery.𝗪𝗵𝘆 𝗪𝗮𝗹𝗹 𝗦𝘁𝗿𝗲𝗲𝘁 𝗶𝘀 𝗻𝗲𝗿𝘃𝗼𝘂𝘀 𝗮𝗯𝗼𝘂𝘁 𝗦𝗵𝗼𝗽𝗶𝗳𝘆: AI could bypass storefronts and even Shop Pay. That uncertainty alone is enough for investors to discount the stock.“𝗪𝗲’𝗹𝗹 𝘀𝗲𝗲 𝗶𝘁 𝘁𝗵𝗶𝘀 𝗵𝗼𝗹𝗶𝗱𝗮𝘆”: Colin expects agentic commerce adoption to meaningfully accelerate after Q4, even a one- or two-point lift on today’s numbers would be significant.Colin is one of the sharpest lenses out there on how the market is actually pricing all of this. Enjoy the conversation!Timestamps:3:28 Meet Colin Sebastian5:04 20 years of history & the Wall Street event7:00 From bartender to Baird7:56 Baird's coverage universe & "TMT"9:29 The GTA VI mega-launch call11:12 Buy side vs. sell side, explained13:52 The SPEED framework & top picks16:16 What is agentic commerce?20:05 Sizing it: trillions & consumer surveys22:42 Meta's social-graph advantage25:05 Amazon's walled garden & the one-way door29:40 Google, UCP & why models get commoditized32:36 eBay's used-goods moat39:44 Retail media networks at risk?44:33 OpenAI, ads & the closed-loop logic48:36 Payments: PayPal, stablecoins & who wins51:57 Protocols: UCP vs. ACP52:23 Why Wall Street is nervous about Shopify👉 Connect with Colin: https://www.linkedin.com/in/cosebastian/👉 Learn more about Baird: https://www.rwbaird.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

This epsiode is a platform-and-stats deep dive: Scot gets Mani to pin down what agentic commerce actually is (with a four-stage framework that’s the cleanest map we’ve heard), then pulls out a run of genuinely wild numbers on what Shopify is seeing across millions of merchants, before going deep on the catalog, the protocol soup, and everything that shipped in the Spring ‘26 Edition.Highlights:Crawl, walk, run, fly: The framework of the episode. Crawl is AI-driven discovery (the biggest, most impactful stage today); fly is fully discretionary, budget-based buying. Mani’s verdict on where the industry actually is: “somewhere between walk and run today.”8X traffic, 13X orders: Shopify’s Q1 numbers… AI-driven traffic to merchants up 8X year over year, and orders through those channels up 13X.AI buyers just hit harder: New buyers who discover a merchant through AI order at roughly twice the rate of organic search, are about 50% more likely to convert, and spend about 14% more per order because they show up deeper in the consideration funnel.70% of AI orders are long tail: About 70–71% of AI-attributed orders last year fell outside the top 100 product categories. Models “don’t need to learn how to reach for the small merchant, they just need to learn the intent of the buyer.”2X on fresh data: The Shopify catalog, over a billion products across millions of merchants, converts about 2X better than stale or scraped data, thanks to real-time pricing and availability straight from the merchant.A “7 out of 10 at everything”: On how AI is reshaping product, design, and engineering roles.The non-merchant-of-record era: Don’t become the marketplace reselling goods, just be the interface to the merchant. The merchant keeps the customer relationship and runs their own checkout.UCP was a “labor of love”: Shopify was at the genesis of the Universal Commerce Protocol.Sidekick, Pulse & Autopilot: Sidekick usage is up about 4X year over year; Pulse turns Shopify’s data into proactive recommendations right on your admin homepage; and the guiding principle stays “always put the control in the merchant’s hand.”B2B may reach “fly” first: By 2030, Mani splits the world into DTC and wholesale/B2B and bets B2B, where both sides transact professionally and obsess over efficiency, may hit full automation before consumers do.Mani’s four stages are the cleanest map of agentic commerce we’ve heard, and the numbers behind them are frankly staggering. And as he reminds us, we’re still in the early innings. Enjoy the conversation! Timestamps:03:55 Welcome; watching Shopify's rise from ChannelAdvisor04:38 Mani's path to VP of Product at Shopify06:37 The Wish / ContextLogic founding story08:18 Vibe coding and "AI makes everyone a 7 out of 10"11:10 What Mani owns across the commerce loop12:42 Non-merchant-of-record channels (ChatGPT, Gemini)13:45 Defining agentic commerce14:44 The crawl / walk / run / fly framework17:50 The stats: 8X traffic, 13X orders, +50% conversion, +14% AOV20:03 Out-of-the-box UCP compatibility and agentic storefronts23:10 The Shopify catalog superpower (2x conversion)26:40 WebMCP and the protocol stack (AP2, x402, Web Bot Auth)29:15 UCP: Shopify's labor of love32:24 Top things merchants should do to win35:28 The escalation "escape hatch"37:24 Word of mouth and the long tail, 70% of AI orders42:41 Spring '26 Edition: Shop app, Ship & Pick Up, Pulse, Autopilot48:10 Where it all goes by 2030: B2B vs DTC52:29 Wrap-up👉 Connect with Mani Fazeli: https://www.linkedin.com/in/mcfazeli/👉 Learn more about Shopify: https://www.shopify.com/👉 And check out the Shopify newsroom blog here🧠 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

Kartik Hosanagar wears a lot of hats: Wharton professor, serial entrepreneur, angel investor, and now co-founder of an applied AI lab building simulation tools for AI search. Scot and Kartik land in almost exactly the same place on where agentic commerce is heading, but they get there from opposite directions: Scot on gut and operator instinct, Kartik on research. The result is a wide-ranging conversation about treating AI as a customer, the levels of agentic commerce, and what brands should actually be doing this week, this quarter, and this year.Highlights:AI is a new customer category: Once shopping goes agentic, Kartik argues you have to ask of AI what you ask of any customer: how do we inform it, persuade it, and what biases does it have? The driverless-car model: Agentic commerce has levels 0–5, just like autonomous vehicles. Level 5 is “buy the shoe and make sure it arrives in a week” hands-off; Instacart-style automation and AI-enabled discovery are lower levels and we’re already in the era.The funnel got outsourced: Top-of-funnel work customers used to do themselves like discovering brands and building a consideration set is now done by AI, so shoppers arrive far later in the funnel. Discovery is “fundamentally transformed.”4 words → 60 words: From his CommerceNext keynote, average search went from about four words on Google to about 60 words on the first ChatGPT turn, then multi-turn. Nobody types “men’s running shoes” anymore; shoes show up on conversation turn seven.UCP, ACP and the protocol wars: Kartik explains Google’s UCP (product feeds today, transactions later), why OpenAI backed off ACP instant checkout, and reads Amazon joining UCP as “testing the waters,” not a strategy reversalCounterfactual simulations: Bodhium builds “digital twins” of ChatGPT and Gemini and spins up virtual worlds where your site looks different, testing a thousand hypotheses in minutes to find what makes AI answers more accurate and favorable. Market research, but for AI.The today / this quarter / this year roadmap: Now: audit conversations, visibility, and which bots read your site. This quarter: build simulators and a UCP/MCP workstream. This year: scale it with agentic workflows. Two front doors: Kartik doesn’t think websites disappear, but “a website is not the right front door for an agent.” Expect a human web door and an MCP door for agents, plus omnichannel behavior where each feeds the other.Kartik calls himself an "agentic commerce maximalist," and after this conversation you'll see why... the research and the gut instinct point the same direction. Enjoy the conversation.Timestamps:03:04 Welcome: the "renaissance man" background problem03:49 Kartik's cocktail-party version: academic + entrepreneur, Yodle04:36 The Yodle / Milo mobile-social-local era (and Fidji at OpenAI)06:05 Wharton AI Center and what Kartik researches07:37 The thesis: AI search is more than another channel10:08 Defining agentic commerce: the driverless-car levels12:34 UCP, Gemini, and why Amazon joined15:55 Amazon vs. Walmart strategies (Rufus vs. Sparky)16:29 Bodhium Labs: what it is17:00 The AEO/GEO problem: guesswork and the Reddit trap18:56 Research-led counterfactual simulations21:02 The long tail: multi-turn conversations replace keywords22:49 CommerceNext keynote: 4 words to 60 words24:57 The "AI is just another channel" misconception26:48 Shopper trust: high for discovery, not for checkout28:15 You can't fully control what AI thinks about you30:51 The roadmap: today, this quarter, this year34:41 Rufus, Sparky, UCP, and MCP endpoints36:37 Does agentic commerce grow the pie or shift it?38:32 Do we still need websites? Two front doors40:39 Where to find Kartik: LinkedIn and Substack👉 Connect with Kartik: https://www.linkedin.com/in/kartik-hosanagar-22272115/👉 Learn more about A Human’s Guide to Machine Intelligence: https://www.amazon.com/dp/0525560882?lv=shuf&channelId=500&plpRedirect=mhFallback👉 Visit his substack: https://hosanagar.substack.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

This is a report deep dive, and Deloitte gave Retailgentic the exclusive first look at brand-new research: hundreds of senior merchant leaders and a thousand-plus recent online shoppers, both sides of the counter, with trend data from two years back layered in. The result is a map of where brands and consumers see the same picture and where they see completely different ones. And the data is fresh, fielded this spring, analyzed over the last month, unveiled here.They describe exactly what those leaders do differently, and why it pays off. You want the edge? This is it. Highlights The basics are the new battleground: Accurate search, real inventory visibility, clear delivery dates, easy returns are no longer differentiators, just expected. And a majority of consumers say brands haven’t improved on them in two years.The perception gap: Only 16–18% of consumers rate brands “excellent,” while brands rate themselves in the low-to-mid 30s, a false-confidence gap that’s driving under-investment where it matters.57 definitions of personalization: the “golden term” has “probably 57 different definitions”, but ~70% of consumers say personalized experiences genuinely matter. Get it wrong and you hurt trust more than you help.14–15 loyalty programs: 99% of surveyed brands offer one and 80% of customers belong to more than one, the average U.S. consumer is a member of 14–15 but active in only four or five. “You are fighting for head space.”The cashback gap: Over half of consumers say cashback is the loyalty benefit they’d value most but only 14% of brands offer it. Customers want financial value and simplicity; brands keep adding tiers and complexity.The leaders’ payoff: Consumers spend 34% more with the brands that nail the basics + personalization + sticky loyalty, 57% will try a new product from them, and 55% will recommend them to family and friends.Efficiency over experience: The two top-reported benefits merchants cite from AI aren’t customer-facing at all, they’re better decision-making and greater efficiency. Brands are getting their own house in order first.Machine-readable product data: Product content is still “teeny tiny” and over-optimized for the keyword era, even as LLMs collapse the old 20-tabs-and-a-spreadsheet decision into one answer. If the data isn’t there, the agent won’t infer it, it just gives what’s available.Connecting the dots: Data, loyalty, and AI in isolation aren’t enough; the winners execute across all three and make deliberate choices about the purpose of the store vs. the site vs. the app vs. the LLM.Fresh data, both sides of the counter, and a clear-eyed read on the gap between what brands think they’re delivering and what shoppers actually feel. Bobby and AP brought the goods. Enjoy the conversation! 👇Timestamps:01:57 An exclusive first look06:12 Meet Bobby Stephens & Apurva Pangam07:19 AP's background: 20 years in commerce08:01 Bobby's background — buyer to footwear founder09:29 Where they fit in Deloitte's retail team10:18 Inside the report: methodology12:32 The consumer side — the basics14:47 The perception gap & false confidence15:50 Personalization: 57 definitions17:30 On-site agents: Rufus, Sparky & TSA20:02 Playbooks, CDPs & the customer P&L21:21 AI for operational efficiency25:40 Making product data machine-readable26:38 Answer engines & the decision collapse29:34 Loyalty: everyone plays, few win33:52 Who's winning: profiling the leaders38:44 Connecting the dots40:18 Closing & where to find the report👉 Check out the report: https://www.deloittedigital.com/us/en/insights/research/b2c-commerce-experiences.html👉 Connect with Bobby Stephens: https://www.linkedin.com/in/bobby-stephens-digital/👉 Connect with Apurva Pangam: https://www.linkedin.com/in/apangam/👉 Learn more about Deloitte: https://www.deloitte.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

This one's a research deep dive. Forrester just published "The State of Agentic Commerce" for Q2 2026, a client-only report built on a fresh consumer survey, and its headline read like a splash of cold water: the hype is running past reality. We invited principal analyst Chuck Gahun on Retailgentic to defend that framing, walk through Forrester's (strict) definition of agentic commerce, and separate what consumers are actually doing from what the market keeps promising. Highlights Shopping vs. buying: Forrester defines agentic commerce as “shopping or buying experiences that include AI agents acting autonomously on behalf of consumers, buyers, or sellers”, and until buying is involved, they call it conversational commerce, not agentic commerce.The 38 / 17 gap: Among consumers familiar with answer engines, 38% use them for product discovery but only 17% complete purchases, a trust gap Chuck says is the single thing holding agentic commerce back.Who’s liable?: When something goes wrong on an answer-engine purchase, 44% of consumers said they’d hold the answer engine itself liable, a sign of how many guardrails, policies, and return paths still have to be built.The Amazon corollary: “On Amazon, I’d let my kids, my friends, my family have my credit card and go shopping.” That same trust does not yet transfer to ChatGPT or Gemini, closing that gap is the whole game.The merchant verdict: “We’re not telling anybody to wait. We’re telling them to go in strategically while the commerce trust angle is catching up.”Machine advantage: Forrester’s four-quadrant merchant framework (agentic fit, machine advantage, operations, and organizational adaptability) pushes brands to build content strategy for machines, not just humans.The SKU mountain: The hardest conversation in the field, “you need to upgrade 100,000 SKUs,” and the merchant answers that one SKU takes six months, so “this is gonna take infinite years.” Protocols like OpenAI’s ACP and Google’s UCP keep changing underneath them, on an exponential curve.Old B2B PDFs are gold mines: Those spec-heavy, JavaScript-free product pages everyone mocked turn out to be exactly what agents want, and Chuck says B2B (business & industrial) is actually taking off faster, with a report prediction that 20% of B2B moves to human-authorized, agent-executed transactions by year-end.Death of the retail website?: A companion Forrester paper argues the website isn’t dead, it’s becoming a repository of data for agents. By 2030, Chuck expects “dual optimization”: machines bring the shopper, and the site’s only job is to convert them.Less traffic, 3X conversion: Organic traffic is down, but answer engines filter the traffic so well that conversions are up.A sharp, honest look at where agentic commerce actually is right now: the trust gap, the merchant playbook, and a few 2030 predictions worth arguing about. Enjoy the conversationTimestamps:03:47 Meet Chuck Gahun, Forrester principal analyst05:03 Chuck's background: two decades, Sapient, the services side07:57 How Forrester's commerce team is structured10:52 Defining agentic commerce: shopping vs. buying12:37 Conversational commerce vs. the strict definition13:49 Semi-autonomous vs. autonomous (the dog-treats test)14:38 Inside the answer-engine consumer survey15:47 The numbers: 38% discover, 17% buy, 62% research16:22 Beyond retail: healthcare, travel, government19:48 Figure 1: owned vs. not-owned, four levels21:47 The trust gap and who's liable (44%)24:37 Marketplaces, merchant of record, and returns27:52 What Forrester tells merchants: don't wait29:57 Product fit, profitability, and the ACP/UCP specs31:58 Figure 3: the four-quadrant framework & machine advantage35:53 The SKU problem and exponential change management38:35 The B2B surge prediction41:25 2030 predictions & death of the retail website46:32 Less traffic, higher conversion: the 3X surprise47:18 Where to find Chuck, events, and outro👉 Connect with Chuck: https://www.linkedin.com/in/chuckgahun/👉 Learn more about Forrester: https://www.forrester.com/👉 Get the report: https://www.forrester.com/report/the-state-of-agentic-commerce-q2-2026/RES195671🧠 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, we sit down with Jennifer Peters, Director of DTC, MarTech & Digital Compliance at OLLY, on building an AEO foundation the right way: FAQs and catalog attributes, measuring agentic visibility, and staying human-centered in a regulated CPG world.We start with a Shopify “side quest”, how a self-taught developer ended up in AI god mode with Claude and MCP, before getting into what OLLY actually is and why a brand that does most of its revenue in-store suddenly cares so much about its website.Jennifer has been quietly building one of the most grounded, real-world Agentic Commerce playbooks we've heard on the show. She shares the basics done tightly and gives a clear-eyed take on what's worth investing in while the ground shifts week to week.It’s a grounded, refreshingly un-hyped conversation about building for the agentic era without losing your head, or your customers. Hit play.Highlights: The cold-resource, high-impact win: Jennifer on catalog feed enhancement.The FAQ slam dunk: OLLY added FAQs to its PDPs using content already on the page, just repackaged into bite-sized chunks. LLMs love the format, and so do humans.AEO is just good SEO: Clean up your schemas, clean up your data structure, and do the things that are good for your brand anyway.Attributes Google never asked for: A partner ingests OLLY’s public catalog and pushes back AI-ready attributes, none of them customer-facing.The website is now the point of entry: A site that was “7 or 8% of the business” is now the brand authority source agents go to first, for OLLY’s own site, Walmart’s Sparky, and Amazon’s Rufus.Trust but verify: OLLY triangulates recommendations across Profound, Contentsquare, and Envive. If all three flag the same thing, it’s probably worth acting on.Don’t “do AI to do AI”: “We’re not changing the goals because we have AI. We’re keeping the goals and just doing a better job getting to them.” Same OKRs, just faster.Fix the un-AI basics first: Connect your DAM, your creative stack, and your marketing stack before you try to sprinkle AI magic on top. Scot adds that AI can be the excuse to finally get it prioritized.The AI bubble in the bubble: From San Francisco, Jennifer on the coming counterculture: “No AI in our creative” as a selling point, growing data center backlash, and Ronny Chieng’s Harvard commencement speech.Jennifer is exactly the kind of hands-on practitioner this show exists to find: strategic, tactical, and refreshingly honest about what’s real and what’s noise. We’ll have to get her back in a year to see what other magical (and weird) things she’s figured out. Enjoy the conversation.Timestamps:00:00 Cold open — lowest resource, highest impact00:21 Welcome to Retailgentic01:36 Scot's intro: a real practitioner doing the work04:13 Welcome, Jennifer Peters05:20 Jennifer's background: agency, Cokesbury, OLLY06:51 Becoming a self-taught Shopify developer07:56 Side quest: Claude, MCP, and AI "god mode"11:34 What is OLLY? The square-bottle homeland12:18 Inside the DTC + MarTech role13:15 Why the website is now the point of entry16:21 Jennifer's agentic commerce journey begins17:48 Start with the basics: AEO is just good SEO18:21 FAQs on PDPs — the easy slam dunk19:48 Catalog feed enhancement & digital attributes21:52 Profound and the AEO vendor landscape23:57 Panel data: "super sus"24:42 Trust but verify across tools25:45 The Reddit problem27:14 Bazaarvoice and review syndication28:44 Don't skip the un-AI basics30:20 Measuring impact without getting fooled31:31 Same OKRs, AI just gets there faster35:40 Does it leak into Walmart & Target?37:48 Sharing content across channels40:06 What's next: AI backlash and counterculture42:37 Where to find Jennifer & outro👉 Connect with Jennifer: https://www.linkedin.com/in/jennifer-peters-3bbb6220/👉 Learn more about Olly: https://www.olly.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

Scot Wingo sits down with Andrew Bell, ReFiBuy's new VP of Research and host of the new RetailPlaybook channel, for a deep dive on Alexa for Shopping, Amazon's patent playbook, and what agentic commerce optimization looks like across Amazon, Walmart, and Target.This is a launch episode. We're announcing two things at once: Andrew Bell joining ReFiBuy as VP of Research, and the debut of RetailPlaybook. Going forward Andrew hosts Retail Playbook himself, but for episode one Scot jumped in to introduce the channel and interview Andrew in person. It's airing here on Retailgentic as a crossover. Highlights: • 𝗚𝗼𝗼𝗱 𝗔𝗖𝗢 𝗶𝘀 𝗽𝗹𝗮𝘆𝗯𝗼𝗼𝗸-𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰: "Good ACO on Amazon means optimizing for Alexa for Shopping, while also keeping the basic mechanics of SEO" — two distinct layers in symbiotic union, and a different playbook for every marketplace.• 𝟭𝟬𝟬 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝘂𝘀𝗲𝗿𝘀: Amazon just announced its shopping agent (the artist formerly known as Rufus, now Alexa for Shopping) is reaching roughly 100 million people.• 𝟲𝟬% 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗹𝗶𝗳𝘁: Andrew is seeing conversion rates climb ~60% on product pages in particular.• 𝗔𝗺𝗮𝘇𝗼𝗻'𝘀 𝗲𝗰𝗼𝗻𝗼𝗺𝗶𝗰 𝗲𝗻𝗴𝗶𝗻𝗲: ~$400B in counted revenue, with true GMV likely north of $600B once you account for third-party sales.• 𝗕𝘂𝗶𝗹𝘁 𝗼𝗻 𝗖𝗹𝗮𝘂𝗱𝗲 𝗮𝗻𝗱 𝗡𝗼𝘃𝗮: Alexa for Shopping runs on Claude, Amazon's own Nova, and custom models — and the question that matters is "is your product being reasoned through?"• 𝗧𝗵𝗲 𝗽𝗹𝗮𝘆𝗯𝗼𝗼𝗸 𝗺𝗲𝗻𝘁𝗮𝗹 𝗺𝗼𝗱𝗲𝗹: Andrew frames each marketplace like a different era of basketball, Jordan's two-pointer game vs. today's spread, zone-defense, three-point era. Different era, different playbook.• 𝗙𝗿𝗼𝗺 𝗔𝗻𝗰𝗶𝗲𝗻𝘁 𝗚𝗿𝗲𝗲𝗸 𝘁𝗼 𝗔𝗦𝗜𝗡𝘀: Andrew studied Ancient Greek and preaching, then self-taught business by reading every book on the Barnes & Noble shelf over six months.• 𝗣𝗮𝘁𝗲𝗻𝘁 𝗧𝘂𝗲𝘀𝗱𝗮𝘆: Andrew reads Amazon's granted patents every Tuesday (and non-granted ones Thursday), scoring each on a levels 1–5 framework because "patents are Amazon's playbook of the future."• 𝗗𝘂𝗲𝗹𝗶𝗻𝗴 𝗨𝗖𝗣 𝘁𝗵𝗲𝗼𝗿𝗶𝗲𝘀: Andrew thinks Amazon joined the universal commerce protocol to publish its data outward; Scot thinks they'll pull UCP inward. They agree to see who's right.A new channel, a new voice, and a host who reads Amazon patents for fun. If you sell on Amazon, Walmart, or Target, as a brand or a third-party seller, this is the playbook you'll want open. Enjoy the conversation.Timestamps: 01:02 Scot introduces the new podcast02:39 In studio — Retailgentic x Retail Playbook, first time meeting IRL03:06 Andrew joins ReFiBuy as VP of Research + channel launch04:13 The vision for Retail Playbook (and how it differs from Retailgentic)05:54 "ACO everywhere" — answer engines vs. retailer-hosted agents06:09 Amazon's scale: $400B+ and 100M Rufus users06:55 60% conversion lift; vertical + horizontal agents; built on Claude and Nova08:34 Why playbooks work — the Jordan-vs-LeBron era model11:48 "Christopher Nolan style" — rewinding to Andrew's story12:02 Andrew's background: Ancient Greek, Bible school, self-taught12:23 Touch of Class: $100K/mo to $4M, 1,500 pages by hand13:00 GPT store, tens of thousands of sellers, 1,000 ad campaigns15:08 NFPA: unauthorized resellers and 3x buy box16:25 "Amazon Science Made Simple" — patents as source of truth18:08 Patent Tuesday and the levels 1–5 framework19:07 Use-case language and predicting the Alexa–Rufus fusion20:51 How Alexa for Shopping ranks: 100 → 30 → the best 5–822:39 Full autonomy: price-trigger auto-buy23:18 Sparky goes live on the web — and where Walmart lags25:35 The Death Star flywheel and Amazon's selection obsession27:34 Shop Direct and the dueling UCP theories28:53 ChatGPT's 20% commerce intent and the horizontal flank30:49 Back to Retail Playbook: the first Substack and query-planning optimization32:13 Where to follow Andrew + outro👉 Connect with Andrew Bell: https://www.linkedin.com/in/andrew-bell-540403275/👉 Learn more about RetailPlaybook: www.retailplaybook.ai🧠 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

Roger Dunn has watched retail media grow up from the agency side (Mediacom, GroupM, WPP), the tech side (he launched Criteo's retail media business in Australia), and the brand side (a global retail media role at Diageo, home of Johnnie Walker, Guinness, and Baileys). Now he's Chief Commercial Officer (CCO) at Thrad, a Silicon Valley startup building the ad infrastructure for LLMs, "ChatGPT ads, but for everyone else."In this episode, Roger and Scot get into where advertising actually lives inside answer engines, what's working today, and how brands should think about showing up when shopping stops looking like a search box.Highlights: What Thrad is building: both the supply side (helping retailers and chatbots monetize conversational surfaces) and a self-serve buy side where brands can run ads across existing AI inventory globally, not just in the four countries where ChatGPT ads have launched.The new ad formats: sponsored messages, sponsored prompts, polling ads, and product carousels, plus the steady stream of formats Google unveiled at Google Marketing Live.AI-native campaigns: how Thrad turns a URL, a brief, or a prompt into keyword, prompt, and dynamically generated persona targeting, and why creative (human faces beat a bare logo) is where the human edge still lives.What ChatGPT ads look like right now: CPCs roughly in the $1–$5 range, and why the early “hot mess vs. holy grail” takes are both missing the point.Roger’s definition of agentic commerce: not a robot doing the final click, but AI shaping every stage of the journey: discovery, comparison, price, review synthesis.The state of the field: Gemini’s full-court press, Perplexity’s Comet browser, Meta routing UCP checkout into Instagram, the Shopify question Wall Street keeps asking, and where Anthropic/Claude might (or might not) play.Down Under as a test lab: Woolworths’ Olive, Bunnings’ Buddy, a duopoly retail market, and why Australia keeps getting the pilots.The advice brands actually need: start small (think $10–20K in a market) but start; get out of “keyword jail”; and the analogy that lands it: keywords are ice cubes, prompts are snowflakes. A few uniform ice cubes everyone fights over, versus infinite unique prompts where a challenger brand can finally own its wedge.This is a genuinely useful tour of the side of agentic commerce most of us squint at, ads, from someone who has built the playbook three times over. Enjoy the conversation.Timestamps:02:00 Scot's intro — who is Roger Dunn?05:17 Conversation begins — live from Sydney06:47 Roger's backstory — UK to Australia, the agency years08:00 Criteo, Epsilon, and a global retail media role at Diageo09:05 What Thrad is — ads inside LLMs09:38 Why retail media is "the nirvana of marketing"11:13 SSP, DSP, self-serve — and ChatGPT ads in just 4 countries17:58 The new ad formats: sponsored prompts, polling ads, product carousels19:53 AI-native campaigns — URLs, briefs, and dynamic personas22:30 Real ChatGPT ad numbers — CPCs and why human faces win24:30 Roger's definition of agentic commerce27:05 OpenAI's $100B ad target27:55 Answer engines, product cards, and checkout in Australia29:13 The state of the arena — ChatGPT, Gemini, Meta, Perplexity, Apple30:57 The UCP checkout in Instagram and the Shopify squeeze32:50 Inside the Australian market — duopolies, Temu, and Shein35:52 Will Anthropic/Claude ever do commerce?38:55 Retailer-hosted agents — Alexa, Woolworths' Olive, Bunnings' Buddy42:17 The top questions brands are asking Roger48:44 Escaping "keyword jail"50:40 Ice cubes vs. snowflakes52:00 How challenger brands find their wedge54:30 Where to find Roger👉 Connect with Roger Dunn: https://www.linkedin.com/in/rogerdunn/👉 Learn more about Thrad: https://www.linkedin.com/company/thrads/🧠 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

This is an exclusive first look at ShopAgentic, and we cover a lot of ground with both co-founders. First we go over the big company news, then rewind through two decades of e-commerce history that brought Alex and Kai to this moment, and why they think the ground is shifting under the entire industry.From there it’s a wide-ranging conversation about what changes when agents, not humans, become the buyers: how a commerce platform built for this era might actually work, how merchants would use it, and where payments, protocols, and front ends are all heading. It’s part founder story, part state-of-the-union on agentic commerce, and part early peek at what they’re building. Hit play. 👇Highlights:The €1.9M pre-seed: Led by Mayventures and Greenfield Capital, with around nine entrepreneur and business-angel tickets, a “US-feeling” round raised in Europe.Who buys, not just how: Kai’s framing for the whole thesis, agentic commerce is the first shift that changes the buyer itself, not just the channel.Built for humans, not agents: Why the founders believe legacy platforms, even the ones they helped build, aren’t architected for what’s coming.The ACP moment: The OpenAI release that made the duo sit down and say “this is gonna change potentially everything.”The weekend prototype: Asked for screenshots for the pitch deck, Kai vibe-coded a working demo instead, and it’s part of why investors leaned in.A squad of agents, not a platform: The product reimagined from the outcome backward, sold into innovation budgets rather than million-dollar replatforming.Ephemeral UIs: “The fast fashion of front ends” interfaces generated on the flyThe protocol soup: Why UCP is “the one to go for” right now, and how ShopAgentic wants to absorb that complexity so merchants don’t have to.A wake-up call for brands: “You’re not even part of that conversation. That’s why you’re not seeing the traffic.”Debut at K5 Berlin (June 22–24): Their first time on the trade-show circuit, including a business-user AI hackathon.Two founders who've lived through every era of e-commerce software, now betting the next one gets rebuilt for agents. Whether you run a brand wondering where your traffic went or you're just curious what a platform "born agentic" looks like, this one's a glimpse into the future. Enjoy the conversation.Timestamps: 04:21 The big news: a €1.9M pre-seed06:07 How the round came together (the inbound snowball)07:54 Alex's background: age 14, Magento, CouchCommerce10:09 Meeting Stephan Schambach and building NewStore11:35 The German e-commerce family tree13:27 Kai's background: Metro, robotics, commercetools16:19 From SaaS to open source to composable17:30 Why agentic needs a new platform — the ACP moment20:28 The founding story (and a little Guinness)22:07 The weekend prototype that sold investors25:43 How agentic commerce is actually different26:04 The "squad of agents" vision27:59 Dashboard, chatbox, and voice for merchants30:30 Vibe coding, Lovable, Visa, and ephemeral UIs32:30 Stablecoins and cross-border payments34:48 x402, MPP, micropayments, and the local-agent explosion37:07 Debut at K5 Berlin (and a hackathon)38:17 The agent OS and guardrails39:09 Navigating the protocol soup: UCP, ACP, AP242:00 Who should be an early merchant44:14 Launching agentic-first44:48 LinkedIn, shopagentic.com, and wrap-up👉 Connect with Alex: https://www.linkedin.com/in/alexanderringsdorff/👉 Connect with Kai: https://www.linkedin.com/in/kaithomaskrause/👉 Learn more about ShopAgentic: https://www.shopagentic.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

This week we have a rare double header. Scheduling conflicts meant no three-way interview, so we sat down with two Salesforce leaders back to back, both there to unpack the company’s big June release, headlined by the launch of its newest platform, Storefront Next.First up is Nitin, who walks through the full sweep of the June release and makes the case for why, taken together, it's Salesforce's biggest commerce release in five years. Then Lennart takes us deeper into the agentic guts, one of our favorite parts.The two interviews rhyme in one important way: both leaders insist that agentic commerce on your owned-and-operated channels matters just as much as showing up in ChatGPT and Gemini. As Nitin puts it, skipping your own shopper agent is like the old days of saying "I participate on Google Shopping, but I don't have search on my website." Highlights Biggest release in five years: Nitin frames the June release as Salesforce Commerce’s biggest swing since he arrived.“It’s 2026, let’s combine the two together”: The forced choice between enterprise-grade and easy-to-launch is a false distinction that can be engineered away.The acquisition cheat code: Rather than spend five years building modern AI search in-house, Salesforce bought Cimulate. It now powers every shopper agent prompt, and it’s available even to non-Commerce Cloud customers.“This code should be written by Claude prompting and not by you”: Storefront Next ships you to the 90% point out of the box; the last 10% is vibe-coded. Migration utilities plus Claude Code shrink what used to be a capital-T front-end project.Live in under 30 minutes: Lennart’s demo path: name the storefront, connect a code repo, click go, and you’re previewing a high-performance site in under half an hour.You need your own Rufus AND to play off-site: Both guests hammer the distinction between agentic commerce on owned-and-operated channels and syndicated commerce via UCP on Gemini, OpenAI, and beyond. One without the other is like being on Google Shopping with no search box on your own site.Focus is magic: Nitin consolidated 20 initiatives down to 4–5, runs two-week iteration cycles instead of two-year PRDs, and credits that discipline (plus AI-native development) for the release’s scope.Advisor and confidant: Lennart’s favorite anecdote… a jewelry brand found customers were more comfortable asking an agent “how big should the ring be, how much should it cost?” than asking a friend.Checkout wisdom from Nitin: Stop offering eight payment options. “Just put Apple Pay on your PDP” four options max, on a good day.The era of choosing between enterprise and easy looks like it's ending and the agents are coming either way. Enjoy the conversation.Timestamps:01:43 Scot's intro: a rare Salesforce double header04:17 Part 1: Nitin Mangtani, EVP & GM of Salesforce Commerce05:40 The Cimulate acquisition story06:50 Inside the June release: search, Storefront Next, merchandising, POS, OMS10:00 Four kinds of customers, one platform11:50 Migration, Claude Code, and the 90/10 rule14:10 Shopper agents: owned & operated vs. syndicated17:05 How Cimulate is baked in search and agentic collapse into one19:05 "Enterprise or easy" is a false choice20:15 Focus, two-week iterations, and acquisitions as a cheat code23:10 ChatGPT leaving checkout and the state of agentic commerce26:10 Part 2: Lennart Stevens, VP of Product, Agentforce Commerce27:15 Lennart's background: two decades on the partner side29:15 Where Storefront Next fits in the Salesforce lineup32:45 The unlock: a storefront live in under 30 minutes35:20 React, Tailwind, shadcn + MCP server and 40+ skills38:05 Design partners and the adoption curve40:55 AI readiness: e-commerce leaders' #1 concern43:50 The shopper agent as advisor and confidant44:45 Agentic merchandising and the Figma unlock👉 Connect with Nitin Mangtani: https://www.linkedin.com/in/nitinmangtani/👉 Connect with Nitin Mangtani: https://www.linkedin.com/in/lennart-stevens/👉 Learn more about Storefront Next: https://www.salesforce.com/blog/storefront-next/🧠 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

May 20th at Google Marketing Live, right before my high-level strategic chat with Nick Fox, SVP of Knowledge and Information at Google (you can read/listen to that one here), I got to sit down with Ashish Gupta, VP & GM of Merchant Shopping at Google.If the Nick Fox conversation was the 30,000-ft strategic view of where Google is taking AI Mode, AIO, and the answer engine, this one with Ashish is the exact opposite. It’s the on-the-ground tactical roadmap for merchants. Ashish is literally one of the people building the thing, and he’s telling you what to do about it before holiday.This interview was recorded right after his fireside chat with Augustina Sartori at Google HQ. On that panel, he laid out the 4 things merchants should do right now: Product feedsData strengthAI campaigns, Agentic infrastructure (i.e., UCP). We get into all four. In this interview we discuss:The 6 new conversational attributes — just launched, live now in the supplemental feed (FAQs, related items, popularity rank, document links, additional variants, item group). Why they exist, how to use them, and the “best sales associate in your store” analogy for how AI surfaces are now expected to behaveUCP’s expansion into new verticals — food delivery and travel. Why now, and why the “U” in Universal Commerce Protocol is doing real workLoyalty in UCP via Google account linking — your Ulta $10 reward shows up at checkout. Critical for merchants who don’t allow guest checkoutData strength — bringing first-party loyalty data into Gemini / AI Mode surfaces so loyal customers see more of the brands they loveAI Max & P-Max and the new ad formats showing up across AI surfaces (and YouTube)AI Performance Insights coming to Merchant Center — the new Share of Voice metric, why the funnel doesn’t behave like a normal funnel (it can actually widen deeper in), and how Google is moving from a “click/keyword” company to an “answer engine” companyThe keyword vs. long-tail question — in an answer engine world, is there even such a thing as a “popular search term” anymore? (Ashish’s answer is interesting)What’s neat about doing these back-to-back is you get both layers in one day. Nick’s interview is about framing: how Google thinks about AI Mode vs. traditional Search, the Innovator’s Dilemma, the ~5 prior attempts at “transactions on Google” and why this one is different, and trust at the intersection of answer engines and AI ads. Ashish’s interview is the merchant-facing manifestation of all of that: here’s exactly what’s shipping, here’s what to put in your feed, here’s how we’ll measure you.Read both together and you get a pretty complete picture of what Google is doing with agentic commerce in 2026.Timestamps: 01:41 — Episode intro: Ashish Gupta returns, context on GML, the merchant vs. consumer org structure at Google04:39 — Interview begins (on-site at Building 100 Bayview)05:18 — Breaking news: the 6 new conversational attributes are live06:32 — The "best sales associate" analogy for AI surfaces08:09 — Popularity rank: how merchants can signal without giving away proprietary data09:37 — Related items, additional variants, and item group attributes11:01 — UCP expansion into new verticals (food delivery, travel) — why now12:32 — The 4 things merchants should do: feeds, data strength, AI campaigns, agentic infrastructure13:02 — Data strength explained: first-party loyalty data in AI surfaces14:08 — Loyalty in UCP via Google account linking (the Ulta $10 example)16:01 — AI campaigns: AI Max, P-Max, and showing up across AI surfaces17:46 — New ad formats and YouTube shopping18:04 — UCP on YouTube and what's next (Gmail?)19:19 — AI Performance Insights & the Share of Voice metric20:17 — Discover / Explore / Purchase: Google crosses from search engine to answer engine21:34 — Why the AI funnel doesn't behave like a traditional funnel23:20 — Long-tail vs. keyword: do "popular search terms" still exist in an answer-engine world?25:05 — What Ashish is most excited about26:06 — Outro👉 Connect with Ashish: https://www.linkedin.com/in/ashishgupta98/🧠 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

May 20th at Google Marketing Live, I was very fortunate to be able to sit down for ~20 minutes with Nick Fox, SVP of Knowledge and Information at Google. Earlier in the day he had a fireside chat with Ben Smith, Editor-in-Chief Semafor. Later that afternoon after I had time to reflect on this conversation, I had a ~20min interview with Nick.It’s not often you get to sit down with one of the top execs at a ~$5T company so I worked a lot of topics into a short time. As always, I try and approach this with you, the audience in mind. What would YOU ask? I had just completed a super tactical Agentic Commerce / UCP/Universal Checkout chat with Ashish, so for this one flipped into high-level strategic mode. In this interview we discuss:How does Nick ‘frame’ AIO/AI Mode/GeminiWill AI Mode/AIO and traditional search transition from traditional to AI Mode or will they merge, or ‘other’ down the road?Google’s had ~5 previous attempts from the Froogle era to today for ‘transactions on Google’ - why is this the moment they are getting super serious about it?Navigating the Innovator’s DilemmaFinally, managing trust at the intersection of ‘Answer engines’ and ‘AI Ads’Timestamps: 01:45 — Scot introduces Nick Fox, Google SVP of Knowledge & Information02:31 — “Search in the AI Era” and Google’s AI strategy03:21 — What this interview covers: AI Mode, Gemini, ads, and commerce04:00 — Why Google believes transactions will work this time 04:33 — The innovator’s dilemma and defending Search 05:16 — Ads, trust, and AI-generated answers 05:52 — Interview begins live from Google Marketing Live 06:23 — How Gemini is “supercharging” Google’s advertising products 06:50 — Ads inside AI Mode and agentic commerce tools 07:11 — Universal Commerce Protocol + Universal Cart 07:26 — Nick Fox on 23 years at Google and the AI era 08:07 — Why Google sees tech shifts as growth accelerators, not disruptions 08:53 — Search vs AI Overviews vs AI Mode vs Gemini explained 09:12 — Google’s “two main products”: Search and Gemini 10:16 — Reinventing the Search box for the AI era 11:01 — Will AI Mode eventually become the default? 12:10 — Google’s philosophy: combining AI + the web 13:00 — Why Google believes users still want the web 13:03 — Gemini “Spark” and agentic capabilities 13:43 — AI agents running 24/7 in the background 14:14 — Using Spark to manage complex tasks like event planning 14:50 — The future of Gemini in the agentic era 14:59 — Google as an economic engine and ad marketplace 15:42 — The innovator’s dilemma and Search resilience 16:04 — “Lean into the technology shifts” philosophy 16:52 — Why Google didn’t see AI as a business-model threat 17:17 — Google’s ad model as a marketplace between users and marketers 18:18 — Why Google Shopping is different this time 19:02 — Why AI enables better shopping confidence and discovery 19:43 — AI helping users get further down the purchase journey 20:24 — Trust, ads, and AI-generated answers 21:04 — Google’s principles for ads in AI experiences 21:31 — “Ads are clearly labeled, separate, and relevant” 21:58 — Closing thoughts and wrap-up👉 Connect with Nick: https://www.linkedin.com/in/nickthefox/👉 Learn more about Google Marketing Live: https://www.googlemarketinglive.com/digital🧠 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

Today at Google I/O, in her part of the larger keynote, VP/GM of Ads and Commerce, Vidhya Srinivasan announced a raft of Agentic Commerce items with the anchor new feature being Universal Cart. After Vidhya’s keynote comments, I was left with these questions that I know merchants will have too:Googlers talk about Universal Cart being available on surfaces like Gmail and YouTube - what’s that actually look like IRL? What are the use cases that merchants can think about and start experimenting with?Universal Cart is coming this Summer - that’s typically June/July/August - that’s a long window in AI-time, early/mid/late Summer?I haven’t heard Google, at least the Agentic Commerce team, talk about AG2 in a while, and suddenly it popped back up in the context of the new consumer agent called Gemini Spark. What’s that all about that.Loyalty (via identity linking) was part of the UCP features announced back on March 19th (details here) but kind of missing here? Even though if you read Vidhya’s blog post very carefully it says that Universal Cart uses “loyalty information”, but it’s not like the Copilot UCP-based loyalty linkage we saw with Target back on April 22 (here if you missed it).That’s a lot of questions - I only had 30mins with Suresh, so had to pick and choose, but we covered some good ground. The good news is I have two more interviews scheduled for Wed 20th at Google Marketing Live and will work them all in.Subscribe, engage and stay tuned for more great Google I/O content coming at you all week! 👉 Connect with Suresh Ganapathy: https://www.linkedin.com/in/sureshsganapathy/👉 Learn more about Google I/O: https://io.google/2026/🧠 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, Scot sits with Elizabeth Lachhar to unpack Rezolve AI’s end-to-end agentic commerce platform, including its closed retail-trained LLM, Brainpower, and modules across search, discovery, conversational commerce, checkout, and loyalty.A lot of the agentic commerce conversation focuses on offsite experiences like ChatGPT, Perplexity, Gemini, and other AI shopping agents. But there’s another major shift happening onsite, where retailers are rethinking search, merchandising, conversational commerce, checkout, loyalty, and personalization for an AI-native world.Elizabeth brings a deep enterprise background from Microsoft, Google, Oracle, and more, and now works with retailers, brands, food service, hospitality, and B2B companies navigating this transition.Highlights Why onsite agentic commerce matters just as much as offsite AI shopping agentsHow Rezolve AI approaches search, merchandising, conversational commerce, checkout, loyalty, and geolocationWhy closed, retail-trained LLMs may matter for hallucination, security, and enterprise trustHow conversational commerce can help retailers move beyond flat, 2D ecommerce experiencesWhy B2B discovery is a major agentic commerce use caseHow loyalty, memory, and past purchases can create better personalizationWhat retailers are asking about right now: security, compliance, fraud, ROI, and partner strategyWhy Elizabeth believes agentic commerce is already here, not years awayWhat Generation Alpha could mean for the future of shopping experiences by 2030Agentic commerce is also about rebuilding the onsite experience so retailers can understand, personalize, transact, and convert in a world where consumers expect commerce to be faster, smarter, and more conversational.Timestamps 00:00 — Introduction to Retailgentic 01:34 — Meet Elizabeth Lacchar of Resolve AI 04:18 — Elizabeth’s background at Microsoft, Google, Oracle, and more 07:14 — Why she joined Resolve AI 09:54 — What Resolve AI does 10:32 — The end-to-end agentic commerce platform 11:29 — Quick service, geolocation, and hospitality use cases 13:25 — Search, discovery, merchandising, and visualization 15:08 — B2B catalogs and complex SKU discovery 17:12 — Why agentic commerce is different from legacy site search 18:11 — Resolve’s closed LLM, Brainpower 20:26 — Checkout, wallets, crypto, and international payments 26:02 — Loyalty, data, and the full customer lifecycle 29:50 — Brain Suite, Brain Commerce, Brain Checkout, and Brain Assist 31:09 — Resolve AI’s customer mix 34:22 — Elizabeth’s role as EVP of the Americas 35:55 — Vibe check: where retailers are in adoption 38:31 — Is agentic commerce a race to the bottom? 40:28 — Fraud, bots, security, and guardrails 42:35 — Selling agentic commerce across enterprise teams 46:26 — Predictions for holiday and 2030 49:41 — Where to learn more about Resolve AI👉 Connect with Elizabeth Lachhar: https://www.linkedin.com/in/elizabeth-lachhar/👉 Learn more about Rezolve Ai: https://www.linkedin.com/company/airezolve/🧠 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, we sit down with Michele Fisher (Global Director, Business Strategy for Retail & CPG) and Atanu Ghosh (Director of Agentic Commerce & AI Innovation), who sit at the intersection of Azure AI, Copilot, and real-world retail and brand Agentic Commerce implementations.This conversation dives into how Microsoft is thinking about agentic commerce as a full operating model shift, not just a feature or channel.From Copilot shopping to data infrastructure to ads inside LLMs, the discussion connects the dots between:Highlights Conversational discovery is fundamentally different from search: The way people talk about brands inside AI systems looks nothing like traditional keyword behavior, and most companies have zero visibility into it.Agentic commerce is not one thing, it’s an operating model shift: Microsoft defines it broadly: agents participating in discovery, decision-making, and transactions, not just checkout.Copilot + catalog + data = the new commerce stackAds are changing from persuasion to evaluation: Agents don’t care about creative. They evaluate structured data, trust signals, and relevance.Loyalty becomes infrastructure, not a programThe “frontier firm” is the North Star: A future where humans and agents work together across workflows, not just AI acting as an assistant.Protocols like UCP matter more than people realize: Open standards enable discoverability across surfaces and prevent fragmentation in agent-driven ecosystems.The funnel is collapsingIf your brand is still thinking about traffic as the starting point, you’re already behind.In an agentic world, discovery happens before you ever see the user, and increasingly, without them.Timestamps00:00 – Why brands have zero visibility into conversational discovery01:50 – Scot’s “Big 6” podcast goal and Microsoft joins the list04:00 – Michelle & Atanu backgrounds + roles at Microsoft10:00 – What agentic commerce actually means (and why definitions vary)14:00 – Microsoft’s agentic commerce stack: Copilot, agents, data layer18:00 – The “Frontier Firm” and human + agent workflows20:00 – UCP, protocols, and why openness matters23:00 – Loyalty, identity, and friction in agent checkout28:00 – Ads in agentic commerce: from persuasion to evaluation33:00 – First-party data vs. conversational behavior data39:00 – Why most retailers aren’t ready (and what they need first)45:00 – The real blocker: operating models, not technology46:30 – Where to learn more + how leaders are consuming information now👉 Connect with Michele: https://www.linkedin.com/in/michelekfisher/👉 Connect with Atanu: https://www.linkedin.com/in/buildingai/👉 Learn more about Microsoft in AI: https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/the-future-of-ai-harnessing-ai-for-e-commerce---personalized-shopping-agents/4386980🧠 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 Retailgentic, Stephan breaks down how agentic commerce is evolving globally, with a particular focus on Europe’s rapid adoption.We explore why AI-driven shopping is accelerating faster than previous technology shifts, how brands are already losing visibility without realizing it, and what practical steps companies can take today to stay competitive.From product data strategy to protocol wars to the future of loyalty, this conversation offers a clear view of where commerce is heading next.Highlights Discovery is the new battleground: If your product is not readable, trustworthy, and rich in context for AI agents, it will not be recommended.Agentic commerce starts before checkout: The most important shift is happening in discovery, comparison, and decision-making, not the final transaction.Europe is moving differently, not slower: Adoption among younger consumers in markets like Germany is already very high, with many using AI in shopping workflows.Product data is now infrastructure: Years of optimizing for search engines are being replaced by the need to structure data for AI systems.Loyalty and identity are becoming core systems: Future commerce will depend heavily on how well brands manage identity, value, and customer relationships across AI ecosystems.Protocols are evolving fast: Systems like UCP and MCP are shaping how agents interact with product data, pricing, and checkout layers.Small experiments already create visibility gains: Even limited API exposure or structured data improvements can increase inclusion in AI-driven recommendations.Agentic commerce is accelerating existing problems: Many of today’s challenges, like poor data quality and disconnected systems, have existed for years but are now becoming urgent.Agentic commerce is already reshaping how products are discovered today, and the brands that adapt fastest will define the next era of retail.Timestamps00:00 – Opening and overview of agentic commerce 02:00 – Who Stefan Ritter is and his background 05:00 – Why agentic commerce adoption is happening faster than mobile 09:00 – What agentic commerce actually means 11:00 – Human vs autonomous decision-making 13:00 – Why context is replacing keywords 16:00 – State of agentic commerce in Europe 20:00 – Data quality and infrastructure challenges 23:00 – AI platforms and protocol landscape 26:00 – Loyalty, identity, and authentication of agents 28:00 – The three opportunity spaces for brands 32:00 – How AI changes product storytelling 36:00 – Events, ecosystem, and European perspective 37:00 – Deloitte research and discovery battleground 39:00 – Retail media and monetization challenges 42:00 – Practical roadmap for brands 46:00 – The future of agentic commerce 49:00 – Closing thoughts and where to follow Stefan👉 Connect with Stephan: https://www.linkedin.com/in/stephanritter/👉 Learn more about Deloitte: https://www.linkedin.com/company/deloitte/🧠 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

This episode goes beyond surface-level AI hype and into how retail organizations are actually responding.Krystina shares what she’s hearing from operators, board members, and data leaders and why the biggest risk right now is moving in the wrong direction.At the same time, we explore how agentic commerce is reshaping traffic, discovery, and brand relationships and what that means for the future of ecommerce.Highlights AI is forcing a full end-to-end transformation of retailMany companies are prioritizing the wrong AI initiatives, focusing on hype instead of P&L impactA growing concern: “dark” or untracked AI-driven traffic is already impacting performanceData strategy is becoming a core battleground: What do you give AI platforms? What do you get back? Do CRMs need to evolve entirely?The real unlock for AI shopping is complex, multi-step purchases (travel, events, planning)The industry is early, but pressure from boards and declining traffic is accelerating adoptionThe future of retail will be defined by who applies it to the right problems.⏱️ Timestamps00:00 — The future of retail data + AI uncertainty 00:47 — Retailgentic intro 03:10 — Kristina Gustafson’s background (CNBC → Shoptalk → RetailClub) 08:02 — Why RetailClub exists: AI needs a verticalized event 10:00 — From “retreat” to “festival” 12:00 — Intimacy vs scale in events 17:00 — What “festival format” actually means 20:00 — RetailClub themes: full AI transformation of retail 26:00 — How Kristina tracks AI trends (75%+ of her time) 28:00 — AI prioritization problem inside companies 29:00 — Data, CRMs, and “dark agentic traffic” 30:00 — Traffic decline + board pressure 36:30 — Agentic commerce: what actually works 38:00 — Why brands won’t fully disappear 40:00 — RetailClub details + closing👉 Connect with Krystina: https://www.linkedin.com/in/krystina-gustafson-908a5a14/👉 Learn more about RetailClub: https://retailclub.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, we go deep into what agentic commerce actually looks like in a real-world vertical, and why grocery may be one of the most important battlegrounds.We walk through the shift from “tools that help you shop” to systems that shop for you, and how that fundamentally changes everything from discovery to monetization.We also unpack the tension between grocers and platforms like Instacart, the rise of retail media networks, and why owning your data, and your customer relationship, may matter more than ever in an AI-driven world.Highlights Regional grocers are losing both data and margin to platforms like InstacartAgentic commerce shifts grocery from manual planning → “do it for me” automationDelectable combines food intelligence + shopper intelligence + real-time inventoryAI closes the gap between inspiration (TikTok/recipes) → instant cart creationVertical AI beats horizontal models with better accuracy, speed, and cost efficiencyGrocery e-commerce hasn’t saved time, until nowRetail media networks are massive, but broken by middlemen and inefficiencyAgentic advertising creates unlimited, contextual ad inventoryThe future of grocery is about owning discovery, not renting itIf you want to understand where agentic commerce gets real, beyond theory and into infrastructure, this is one to pay attention to.⏱️ Timestamps00:00 — Who owns grocery discovery today 02:05 — Intro to Delectable AI 04:00 — Joe’s background in enterprise commerce 10:00 — Why grocery (and why now) 12:50 — The Agentic Experience Platform explained 14:30 — Why grocery e-commerce hasn’t saved time 15:50 — “Do it for me” shopping vs tools 17:00 — Retail media inefficiencies and opportunity 19:00 — The shopper journey (TikTok → cart) 22:00 — Fundraising + early traction 26:00 — Vertical vs horizontal AI debate 30:00 — Instacart, data ownership, and margins 32:00 — Why vertical AI wins (accuracy, speed, cost) 34:30 — What’s next for Delectable👉 Connect with Joseph Lee: https://www.linkedin.com/in/josephchiahsunlee/👉 Learn more about Delectable AI: https://www.linkedin.com/company/delectable-ai/🧠 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

Everyone is focused on how AI helps people discover products. But what happens after that? In this episode of Retailgentic, we go deep on the missing layer of agentic commerce: checkout, payments, and fulfillment. Because it turns out, the hardest part isn’t finding the product. It’s buying it.Rye is building what they describe as the “Stripe for commerce.” It connects AI agents, apps, and platforms to merchants handling:Checkout and order placementPayment orchestrationFulfillment across retailers like Amazon and ShopifyIn short: if an AI agent decides what to buy, Rye helps it actually buy it.Highlights Checkout is the real bottleneck: Discovery is improving fast, but actually placing an order across fragmented systems is still incredibly hard.Rye enables real AI purchasing: They connect agents to merchants, allowing products to be bought directly from platforms like Amazon.Amazon is a critical unlock: Most bots are blocked, but Rye’s API-based approach allows real transactions to go through.Protocols won’t solve everything: Even if UCP/ACP take off, long-tail merchants and major players won’t fully standardize.B2B is the sleeper opportunity: Complex procurement decisions are a perfect fit for agent-driven commerce.AI reduces returns: More context leads to better decisions, driving return rates extremely low.We’re still early, but close: One breakout use case could flip massive volume into agentic commerce quickly.Agentic commerce isn’t just about what gets recommended—it’s about what actually gets bought.Timestamps: 02:00 — Meet Arjun Bhargava and Rye 04:00 — Founding story and early vision 08:00 — Contextual commerce → agentic commerce 11:00 — What Rye does (simple explanation) 14:00 — How AI agents place orders 18:00 — The rye.com story 22:00 — Amazon integration and why it matters 26:00 — Payments, tokenization, and infrastructure 30:00 — UCP vs ACP debate 35:00 — Why protocols won’t cover everything 40:00 — Where agentic commerce is heading 42:00 — B2B opportunity and procurement 46:00 — Real-world AI agent example 47:30 — Closing👉 Connect with Arjun: https://www.linkedin.com/in/arjunbhargava/👉 Learn more about Rye: rye.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, 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

Today we’re dropping a surprise podcast that is different than anything we’ve done before and a first of it’s kind! Scot Wingo was invited by Ben Miller, VP of Content and Strategy to participate in the first ever shoptalk debate format talk. The topic - Agentic Commerce Will AI agents transform retail? On the pro agentic side we had Ekta Chopin, CDO at ELF Beauty and myself.  If you’re not familiar with Ekta, she’s a thought leading CDO and has a great substack for other CDOs.On the ‘anti agentic side’ we had Sarah Marzano, Principal Analyst, Retail Ecommerce and Retail Media at Emarketer and Andrew Lipsman - independent analyst and consultant for media, ads and commerce.Before the show, Scot asked and received permission from Shoptalk and all the participants to turn the raw audio into a podcast. In the AI era, speed matters so we are getting this in your hands only 2 days after it happened. This debate took place at 12pm PDT on Tuesday March 24th at Shoptalk’s AI Stage.Timestamps00:01 – Why this episode is different from anything Retailgentic has done before 01:28 – The Shoptalk debate topic: Will AI Agents Transform Retail? 02:04 – Meet the debaters: Ekta Chopra, Andrew Lipsman, and Sarah Marzano 07:48 – The first big battle: how should agentic commerce be defined? 10:25 – Scot’s argument: consumers are already changing behavior faster than many retailers realize 13:16 – Sarah’s pushback: brands need clarity before making big bets 15:18 – Consumer adoption: how much automation will shoppers really accept? 17:16 – Why product data and offer-card visibility matter now 19:05 – Andrew’s argument: shopping still requires human decision-making 23:05 – Ekta on brand visibility, content readiness, and why this matters for beauty 24:49 – 2030 predictions: will 10% of e-commerce be bot-to-bot? 27:03 – Does agentic commerce threaten retail media? 29:11 – Sarah’s case for why AI referrals may actually help retailers 32:22 – Ekta on why rich product data matters more than media for e.l.f. 33:06 – Scot’s case that traffic decline is already starting in some categories 37:16 – What brands and retailers should do over the next 6–18 months 40:25 – Why Sarah says brands should test, but not overreact 42:11 – Scot’s closing case for why this shift is fundamentally different 43:22 – Andrew’s closing warning against fear-based decision-making🧠 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

This episode explores the shift from traditional search and ecommerce flows into a new agentic commerce environment where shoppers are using AI surfaces to discover, compare, and increasingly delegate parts of the buying journey.Ashish explains what Google was seeing internally that led to the development of UCP, why the protocol was designed to be open and ecosystem-wide, and why the ambition goes far beyond checkout. He also shares how Google is thinking about discovery, conversational product data, merchant readiness, and the long-term role of AI across the shopping journey.For retailers, brands, marketplaces, and commerce tech teams, this conversation is a helpful window into what Google believes is changing now, and what foundations businesses should be investing in before the market fully shifts.Highlights How Google’s large-scale ad and data systems shaped his approach to commerceWhy UCP emerged now, and the two major trends that inspired itWhy Google believes agentic commerce needs an open, ecosystem-wide standardWhy the future of UCP extends far beyond checkoutHow discovery is starting to take shape within the protocolWhy richer, more conversational product data matters in AI shopping experiencesWhat retailers need to do now to improve visibility on AI surfacesHow Google is thinking about the relationship between agentic commerce and advertisingWhy agentic commerce is still early, but already moving from concept to realityAgentic commerce is still early, but this conversation makes one thing clear: the infrastructure decisions being made now will shape who gets discovered, considered, and chosen in the next era of shopping.Timestamps2:32 — Welcome and introduction to Ashish Gupta5:01 — Building Google’s data infrastructure and declarative querying at scale9:43 — AI at Google before the current wave11:32 — What it means to be an Engineering Fellow at Google14:00 — Balancing technical leadership and operational leadership16:10 — Why Ashish moved into merchant shopping17:41 — The origin story behind UCP24:58 — Why Google chose an open protocol approach27:50 — Responding to skepticism around Google’s commerce efforts32:30 — Discovery, catalog search, and where UCP expands next35:39 — Multi-item and multi-merchant cart support37:43 — New protocol capabilities and partner onboarding38:42 — Why product data quality matters more in AI shopping43:22 — How shoppers are using AI surfaces in more complex ways47:47 — Agentic commerce and advertising50:10 — Where agentic commerce may go from here51:46 — Closing thoughts and where to follow Ashish👉 Connect with Ashish: https://www.linkedin.com/in/ashishgupta98/ 👉 Check out UCP announcement: https://www.retailgentic.com/p/flash-googlenrf-announces-universal🧠 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, 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

In this episode, Scot digs into a question he keeps getting from readers and listeners: What’s actually going on inside Amazon’s Rufus, and what should brands do about it?Ian brings fresh analysis from Sensor Tower’s panel-based methodology (privacy-compliant, double opt-in), walking through Holiday ’25 shopping sessions to show where Rufus shows up in the funnel, how usage spikes during peak moments, and why it appears to correlate with dramatically higher conversion. Along the way, they zoom out to the bigger shift: as more people learn to “talk to AI” (thanks to ChatGPT-style habits), conversational shopping becomes increasingly normal, and increasingly hard to “optimize” using old keyword-era tactics.Highlights:“The consumer is trained.” A year of daily conversational AI use has taught people how to prompt, so when they see Amazon Rufus, they already know how to use it.Rufus sessions show a major conversion lift. In Ian’s read of the report: ~3.5× lift vs. non-Rufus sessions, with Rufus-touch sessions far more likely to end in purchase.Rufus had outsized influence during Holiday ’25. A large share of purchases included Rufus interaction, even if not every session did.Their team mapped ten distinct Rufus-assisted shopping paths, including the standout “Research Conversationalist” profile.Correlation vs causation is real. Ian flags measurement caveats: not every “non-Rufus session” is a shopping mission; intent bias exists; so the takeaway is directional, but meaningful.Brands should shift from “keyword jail” to “product truth.” Better attributes, clearer specs, stronger review signals, and real storytelling matter more in conversational shopping.AEO anxiety + the brand-level rebound. Ian argues the future isn’t just “optimize for prompts”, it may reward brands with stronger reputation and social proof signals (think forums and communities).AI can talk consumers out of premium. They’ve seen examples where AI steers price-sensitive users away from expensive brands, an early warning system for brand teams.Retail media won’t vanish, but it will mutate. In a lower-click world, retailers will experiment heavily to preserve value, without turning the experience into ad soup.If you’ve been treating Rufus like a curiosity, this data makes it hard to ignore: conversational commerce isn’t “coming”, it’s already shaping how high-intent shoppers decide.Timestamps:00:00 – The Consumer Is Now Trained02:09 – Why This Episode Focuses on Rufus05:49 – Ian Simpson’s Background06:47 – Founding a Bottled Tea Startup09:14 – Pathmatics → Sensor Tower Acquisition10:11 – How Retail Media Intelligence Was Born13:50 – How Sensor Tower Delivers Its Data15:36 – Why Sensor Tower Started Tracking Agentic Commerce21:08 – How the Rufus Analysis Was Done22:48 – The 3.5× Conversion Lift Explained24:18 – Amazon’s $10B Rufus Claim vs. Independent Data28:16 – Correlation vs. Causation in Rufus Usage31:23 – Rufus as a Research Companion32:20 – The Cup Holder Story (Problem-Based Shopping)39:55 – Why Rufus Usage Sticks After the Holidays40:19 – The 10 Rufus Shopping Profiles41:35 – The “Research Conversationalist” Funnel45:00 – Why “AEO” Makes Ian Nervous46:47 – Brand Matters Again in Agentic Commerce48:47 – When AI Talks Consumers Out of Premium Products58:21 – Retail Media’s Future in a Low-Click World01:01:31 – Avoiding the Minority Report Ad Nightmare01:06:21 – Instacart: The Wild West of Retail Media01:07:15 – Where to Follow Ian👉 Connect with Ian: https://www.linkedin.com/in/iansimpson/👉 Learn more about Sensor Tower: https://sensortower.comCheck out the materials we discuss: 🔗 Sensor Tower Black Friday AI Trend Update  🔗 How Amazon’s Rufus Shaped Holiday Shopping🧠 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 Retailgentic, Scot and Ken map out how Mastercard saw agentic commerce coming early, and what they built in 2025 to prepare the ecosystem, especially around trust, identity, consent, and tokenization.We dig into: How Mastercard Foundry takes ideas from experiments → production-grade products → global scale“Know Your Agent”: registering legitimate agents (agentic equivalent of KYC/KYB) to reduce malicious bot risk“Order Intent”: adding richer context so that with consent, agents/merchants can fulfill the right order (not just process a payment)Why consumer consent is non-negotiable (passkeys/biometrics + tokenized credentials)Mastercard Insight Tokens: a secure and governed way for agents to access and apply permissioned insights from Mastercard, which will enable consumers to receive, with their consent, more personalized and useful experiencesAgentic Toolkit and why Mastercard leaned into services to support customers move from strategy → execution fastMastercard’s Agent Pay Acceptance Framework: helps merchants totransact with trusted agents with a minimal liftStandards: why Mastercard will support ACP + AP2 and expects interoperability (or convergence) over timeAgentic commerce won’t be won by whoever moves fastest, it’ll be won by whoever earns trust at scale.Key timestamps05:14 — Ken’s background: technologist, global banking work, startups, Accenture, Citi → Mastercard Foundry07:44 — How Foundry works: experiment, build, then “graduate” products into core teams10:32 — The pace-of-change thesis: why organizations must be built to adapt continuously13:07 — How Mastercard saw agentic commerce early (signal-spotting in 2024)14:23 — The 3 converging forces: AI reasoning, compute, and foundations (tokens/passkeys/consent)19:01 — AgentPay launch + what it includes (Know Your Agent, Order Intent)21:05 — Consumer consent, passkeys/biometrics, and tokenizing payment credentials22:25 — First agentic transaction (partner example)23:19 — Agentic Toolkit + Insight Tokens + consulting expansion26:00 — Merchant Acceptance Framework + scaling agentic readiness for the “long tail” of merchants27:13 — Tokenization explained simply (cocktail-party version)29:37 — Passkeys explained (biometric identity replacing passwords)33:37 — Returns problem + how agentic workflows could reduce “buy 3, return 2”40:19 — Standards wars: ACP vs AP2 + why Mastercard stays agnostic44:03 — Crystal ball: adoption, trust, and why B2B may go autonomous faster47:43 — The travel agent analogy: why some flows stay assisted by choice👉 Connect with Ken: https://www.linkedin.com/in/ken-moore-cio/👉 Learn more about Mastercard: https://www.mastercard.com/us/en.html🔗 Agentic Toolkit: https://www.mastercard.com/us/en/news-and-trends/press/2025/september/mastercard-unveils-new-tools-and-collaborations-to-power-smarter,-safer-agentic-commerce.html🔗Agentic Commerce Rules, Mastercard Joins Google: https://www.mastercard.com/us/en/news-and-trends/stories/2026/agentic-commerce-rules-of-the-road.html🔗Agent Suite: https://www.mastercard.com/us/en/news-and-trends/press/2026/january/mastercard-launches-agent-suite-to-ready-enterprises-for-a-new-e.html🧠 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 🎧 Listen wherever you get your podcasts: Spotify, Apple, etc: https://retailgentic.transistor.fm

Consumer behavior is already shifting, people are asking LLMs what to buy, building shopping lists in chat, and moving through commerce in new ways. In this episode of Retailgenic, Scot sits down with Maia to unpack what “agentic commerce” actually means, why Stripe is moving fast, and what merchants can do now to get ready for checkout inside AI experiences. They discuss:Why agentic commerce is a spectrum: fully autonomous agents vs. AI-assisted buying inside chat interfacesStripe’s four AI focus areas (and why agentic commerce is only one bucket)The big initiatives driving Stripe’s agentic pushWhat Copilot Checkout looks like in practice: Stripe-powered checkout embedded natively in chatHow Stripe is approaching merchant control and merchant-of-record requirementsHow product discoverability works today (feeds + syndicator integrations) vs. the longer-term self-serve visionWhat merchants are asking for most: fraud, trust, identity, and governance in an agent-led worldThe “why now” moment: traffic shifts, zero-click pressure, and board-level attention accelerating experimentsAgentic commerce is no longer theoretical, it’s becoming a real channel. The winners will be the merchants who make their catalogs discoverable, keep control of checkout, and build trust and fraud defenses for an AI-led future.Notable Timestamps02:06 – Scot introduces Maia, AI CRO at Stripe04:07 – Maia’s background: e-commerce founder → LivingSocial → Stripe06:54 – Stripe’s 4 AI buckets (infrastructure, AI across payments, dev tools, agentic commerce)09:22 – The “agentic commerce is a mirage” debate + definition confusion10:43 – Maia’s spectrum definition: autonomous vs. chat-native buying14:40 – Copilot Checkout: what it is, how Stripe fits, and where to sign up (waitlist)18:15 – Agentic Commerce Suite: discoverability, checkout/fraud, choosing agents in dashboard20:04 – How products become discoverable: direct feed vs. syndicators + onboarding reality today21:15 – Shared Payment Tokens (SPTs): secure handoff + merchant-of-record control24:05 – Merchant sentiment shift: from skepticism → exec sponsors + resources dedicated29:37 – Fraud + trust layer: Radar expansion, Link wallet, and SPT fraud signals31:58 – 2030 sizing: Stripe won’t pick a %, but “this is happening”33:07 – Where to follow Maia/Stripe + NRF context👉 Connect with Maia: https://www.linkedin.com/in/maiaj/👉 Connect with Scot: https://www.linkedin.com/in/thescotwingo/👉 Learn more about Stripe: https://stripe.com/payments/ai🧠 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

This week on the retailgentic podcast, we have an experiment for you. NRF concluded Tuesday Jan 13th and Scot's good friend and podcast partner over at the Jason and Scot show, Jason Goldberg (Chief Digital Commerce Officer at Publicis) was invited to ‘tie the bow’ on the conference in the last keynote: Commerce Disrupted: Rise of the AI Native Consumer.This episode is the audio from that presentation on 1/13/26. Jason covers:Agentic commerce, defined clearly: not “AI efficiencies,” but new consumer behaviors (and the full “iceberg” of influence, not just robot-takes-card transactions).Is it hype or historic? Jason frames the debate (skeptics vs believers) and uses live audience polling to set the stakes.A disruption of discovery: the decline of “saw in store,” then “search,” then “social”, and now the robot becomes the front door.The cautionary tale (Tudor Ice): why incumbents often miss the next business model, even when they dominated the last one.Retail growth is concentrated: a few giants capture a huge share of growth, while challengers (Shein/Temu/TikTok Shop) rewrite the playbook.AI shopping ramps fast: from research → to product tiles → to direct purchase inside AI experiences, plus retailer catalogs moving upstream.0-click commerce: the next leap isn’t fewer clicks, it’s no clicks (automation, replenishment, “never let me run out”).Onsite vs offsite agents: retailers’ on-site assistants (ex: Amazon) vs consumers using neutral offsite agents that choose the retailer for them.Winning the robots: why optimization shifts toward what models care about (criteria, sources, “GEO/AEO/ACO”), and why this changes constantly.Change management wins: Doug McMillon’s “How did you use AI to prepare?” as a culture lever—and why org adoption matters as much as tech.If AI changes the way people discover, it changes everything downstream. Brands, retailers, and platforms all have to learn to win the robot’s shelf.Notable timestamps 00:00 — The real disruption: new consumer behavior, not efficiency gains01:43 — Scott sets up the “special episode” + NRF context03:17 — The experiment: “put you in the audience” (keynote replay)06:29 — The big questions: how big is agentic commerce + who wins?08:07 — Skeptics vs believers: “hallucination” vs “overhyped” vs transformational11:05 — Defining agentic commerce + the “influence vs transaction” iceberg15:07 — Tudor Ice story: disruption, incumbents, and missing the next model19:14 — $5.3T retail + who captured the growth (concentration)22:16 — “Disruption of discovery”: saw-in-store → search → social25:04 — Viral demand shock example (whipped coffee)26:53 — Sunscreen example + TikTok → then “ask the robot”29:08 — “How fast this changed” (recent launches + ecosystem momentum)30:19 — From “order” to “never let me run out” (automation framing)31:11 — Clicks: 22 → 4 → “one-click” → 0-click32:40 — Proof points: agent assistants and rising adoption33:49 — Offsite agents: buying without choosing a retailer first34:03 — In-store: pointing ChatGPT at the shelf (real-world agent use)36:29 — Scale math: small % of prompts can still be massive volume38:34 — Robots optimize differently + why brands need new processes/tools39:36 — GEO/AEO vs the bigger strategic layer (Agentic Commerce Optimization)40:33 — Doug McMillon’s culture lever: “How did you use AI to prepare?”42:12 — Final message: change management to avoid being the “ice harvesters”👉 Connect with Jason: https://www.linkedin.com/in/jasongoldberg/👉 Connect with Scot: https://www.linkedin.com/in/thescotwingo/👉 See the slides: https://open.substack.com/pub/scotwingorefibuy/p/jason-goldbergs-full-nrf-keynote🧠 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

Today we have a special FLASH episode - no fancy intros, just the news as it's breaking at NRF.

Consumer behavior doesn’t change overnight, even when the technology is obvious. In this episode of Retailgentic, Scot sits down with Hamish Gunasekara to unpack why agentic commerce is inevitable, why it’s moving slower than the hype suggests, and why product data infrastructure, not checkout, is the real unlock.We cover:Why “fully autonomous shopping” is the wrong definition of agentic commerceWhy consumer habits change slower than technologyWhy global mega-catalogs don’t work (and never really have)How vertical AI shopping experiences can thrive alongside ChatGPTThe hidden trust and governance problem no one is talking aboutWhy product catalogs are the hardest unsolved problem in commerceIf you’re a retailer, brand, agent builder, or investor trying to understand what actually matters in the agentic commerce stack, this episode is foundational.Timestamps:02:39 Meet Hamish & the origin of Catalog04:55 From Afterpay to Cash App Commerce11:30 The Naya experiment & lessons learned14:24 How AI is changing discovery16:08 Why catalog data is broken18:30 Fundraising & early traction20:48 Who Catalog is built for23:20 Why global catalogs don’t work28:30 The agentic commerce stack33:40 Defining agentic commerce (correctly)37:30 Why vertical agents will win43:45 Trust, governance, and adoption44:51 Where to learn more👉 Connect with Hamish: https://www.linkedin.com/in/hamish-gunasekara/👉 Learn more about Catalog: https://getcatalog.ai/🧠 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 🎧 Listen wherever you get your podcasts: Spotify, Apple, etc: https://retailgentic.transistor.fm

Matt Nichols is back, and a lot has changed since his first appearance on Retailgentic. Scot and Matt revisit the predictions he made six months ago, look at what came true far faster than expected, and dig into the infrastructure challenges that still stand between us and frictionless agentic transactions. From SKU mapping and API-first checkout to the economics of feeds and the future of retailer traffic, this episode is a full-stack view of where Agentic Commerce stands at the end of 2025, and what’s coming in 2026.If you want more of Matt’s backstory and Commerce Ventures’ thesis, listen to Episode 4! It pairs perfectly with this deep dive. In this episode, they cover: Why VC predictions used to take 5–10 years to play out… and now take 5–10 weeksWhat Commerce Ventures is hearing from both startups and their LP base (top retailers + PSPs)Why ACP isn’t “the solution”—and what infrastructure still needs to be builtThe “API vs. fake-it-til-you-make-it” debate in agentic transactionsHow retailers should think about feeds, reviews, and blocking scrapersWhy “AI magic on your own site” is step one for most brandsPredictions for 2026: traffic shifts, wallet battles, Apple’s eventual entry, and moreWhere Matt thinks the industry is overly optimistic, and where the real upside isIf this year taught us anything, it’s that the next six months will change more than the last six years. Stay tuned.Timestamps05:00 — Welcome back, Matt Nichols05:10 — Six months later, the world looks different05:35 — Commerce Ventures in 60 seconds06:30 — What changed in 2025?08:00 — Standards vs. infrastructure10:00 — Retailers’ three priorities right now12:40 — Static feeds → AI-centric feeds15:00 — Reviews, Q&A, and proprietary data17:30 — SKU-level identifiers20:00 — API-first checkout vs. agentic scraping22:30 — Fraud, agent authentication & whitelisting24:00 — Payments are further ahead than commerce infrastructure27:00 — What retailers are actually worried about30:00 — Google’s role in accelerating the shift32:00 — Vertical agents vs. horizontal giants34:00 — Predictions for 2026 & beyond38:00 — Final reflections👉 Connect with Matt: https://www.linkedin.com/in/matthewnichols/👉 Learn more about Commerce Ventures: https://commerce.vc/🧠 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 🎧 Listen wherever you get your podcasts: Spotify, Apple, etc: https://retailgentic.transistor.fm

In this episode of Retailgentic, Scot sits down with Luca to unpack a research paper that blends academic rigor with real-world implications:“LLMs Reproduce Human Purchase Intent via Semantic Similarity licitation of Likert Ratings.”The paper, co-authored with Colgate-Palmolive researchers, explores whether AI can accurately simulate human reactions to product concepts, enough to replace or accelerate traditional consumer panels, which are slow, expensive, and hard to scale.This one goes deep, but in ways that any retail or AI leader should care about. Scot and Luca discuss:Colgate’s Challenge: How to test product concepts faster and at scale.Synthetic Consumers: AI models that react to products like human panels.Accuracy Breakthrough: Reaching ~73–74% agreement with real consumers.Fixing LLM Failure Modes: Why naive prompts don’t work, and what does.Bayesian Reasoning: Adding uncertainty so AI stops being confidently wrong.Smarter A/B Testing: Using AI to pre-screen ideas before running live experiments.Digital Clones: Future consumers earning money by sharing preference data safely.Simulated Populations: Matching real audiences for testing and predictions.AI isn’t just helping brands write copy or generate images, it’s beginning to think like their customers. If synthetic consumers continue to evolve at this pace, product development, A/B testing, and personalization may look completely different in just a few years.Timestamps: 03:00 — Luca’s background: Rocket Internet, HelloFresh, Lazada, Stitch Fix08:00 — How PyMC Labs was founded & why Bayesian modeling matters16:00 — Bayesian thinking explained in simple terms19:00 — High-stakes decisions & why probabilistic reasoning matters24:00 — Colgate’s challenge: testing product concepts at scale26:00 — How synthetic consumer panels work30:00 — Accuracy results: humans vs. AI (~73–74%)32:00 — Why naive LLM prompting fails (“mode collapse”)35:00 — How reasoning → scoring solves accuracy issues38:00 — Example: synthetic consumers evaluating PyMC’s own website redesign44:00 — How AI can pre-screen ideas for smarter A/B testing48:00 — Where AI cannot replace causal testing49:00 — Digital clones & monetizable consumer preferences52:00 — Future benchmarks, new LLMs & evaluation methods👉 Connect with Luca: https://www.linkedin.com/in/lfiaschi/👉 Learn more about PyMC Labs: https://www.pymc-labs.com👉 Check out the paper: https://arxiv.org/pdf/2510.08338🧠 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 🎧 Listen wherever you get your podcasts: Spotify, Apple, etc: https://retailgentic.transistor.fm#Retailgentic #AgenticCommerce #SyntheticConsumers #AIShopping #ProductTesting #CPGInnovation #GenerativeAI #BayesianModeling #Ecommerce #FutureOfRetail #DataScience #LLMs #AIResearch

In this episode of Retailgentic, host Scot sits down with Mike Edmonds, PayPal’s VP of Agentic Commerce & Commercial Growth, to unpack the massive pivot PayPal has made into the Agentic Commerce era, and what it means for retailers, brands, platforms, and developers.Mike goes deep on:PayPal’s Agentic Bet: Why PayPal is going all-in on Agentic CommerceMerchant Anxiety, Explained: The real reason so many merchants are anxious about LLMsInstant Checkout 2.0: Where PayPal sees Instant Checkout heading nextWallets as Identity: Why wallet identity will matter more than ever2030 Predictions: Mike’s bold predictions for shopping agents in 2030Two-Track Future: A world split between autonomous commerce and luxury human-led experiencesProtocol Chaos Simplified: How PayPal plans to tame and unify an explosion of competing protocolsMerchant of Record Relief: The surprising emotional fear merchants have about disintermediationAs AI agents reshape discovery, checkout, and trust, PayPal is building the rails for the future of digital commerce.Key Timestamps:02:15 — Mike introduces his background.04:45 — How Mike’s career path led directly into PayPal’s Agentic Commerce leadership role.06:20 — What “VP of Agentic Commerce & Commercial Growth” really means at PayPal.07:48 — The biggest lessons Mike learned leading AI strategy at Microsoft.10:35 — What merchants are actually thinking about Agentic Commerce (the real pulse).12:18 — Mike explains the off-surface vs on-surface Agentic Commerce model.13:10 — Why merchants feel overwhelmed by LLMs, APIs, and protocol sprawl.14:47 — PayPal’s role as the one-to-many connector across LLMs and platforms.16:06 — What technical pieces merchants need in place to integrate Agentic checkout.17:45 — How on-surface conversational agents can finally boost conversion rates.19:30 — Why conversational checkout is the missing piece in Agentic shopping.20:55 — What the Perplexity partnership enables for checkout, payments, and reach.23:30 — How PayPal is powering ChatGPT Instant Checkout and expanding ACP.26:12 — Why Agentic protocols are diverging, and how PayPal navigates the chaos.28:30 — The emotional fear merchants have of LLMs.30:05 — Mike’s 2030 prediction31:40 — Why some categories will automate, while luxury experiences stay human.33:10 — Multimodal will reshape shopping through voice, gestures, and identity.35:00 — The top concerns merchants raise in every PayPal Agentic conversation.37:05 — Where to find Mike and what PayPal has coming next.Announcements & press releases related to the conversations:Perplexity: https://newsroom.paypal-corp.com/2025-05-14-Perplexity-Selects-PayPal-to-Power-Agentic-CommerceGoogle (commerce agent for merchants: https://cloud.google.com/blog/topics/financial-services/introducing-an-agentic-commerce-solution-for-merchants-from-paypal-and-google-cloudOpenAI: https://newsroom.paypal-corp.com/2025-10-28-OpenAI-and-PayPal-Team-Up-to-Power-Instant-Checkout-and-Agentic-Commerce-in-ChatGPTAP2: https://developer.paypal.com/community/blog/PayPal-Agent-Payments-Protocol/ and https://cloud.google.com/blog/products/ai-machine-learning/announcing-agents-to-payments-ap2-protocolPayPal’s Agentic Commerce Services: https://newsroom.paypal-corp.com/2025-10-28-PayPal-Launches-Agentic-Commerce-Services-to-Power-AI-Driven-Shopping👉 Connect with Mike: https://www.linkedin.com/in/michaeledmonds/👉 Learn more about PayPal: https://www.paypal.com/us/home🧠 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 Retailgentic Podcast, Scot talks with Stu Solomon, CEO of HUMAN Security, the company analyzing 20+ trillion digital interactions every week to detect bots, fraud, and now agentic AI behavior. Stu breaks down:Why bots now exceed human trafficThe 1300% growth in agentic activityHow HUMAN identifies good vs. bad botsThe rise of agentic logins, navigation, and even checkoutsWhy spoofing of ChatGPT and Perplexity traffic is explodingWhat retailers need to know about letting AI agents crawl their sitesThe coming world of agent-to-agent commerceIf you’re preparing for the future of retail, ad tech, AI commerce, or online security, this is essential listening.Timestamps02:20 — What HUMAN actually measures (bot vs human vs agentic)03:40 — Stu’s background (military → Amazon → banking → VC → CEO)06:40 — The logistics + retail connection09:00 — How HUMAN works: media + enterprise security11:00 — The digital journey from ad → login → checkout12:11 — HUMAN at 20 trillion interactions/week16:55 — Why HUMAN started publishing agentic data17:50 — 1300% growth in agentic activity18:30 — Machine traffic surpasses human traffic19:40 — The diversification of generative AI traffic20:30 — Agentic login + website navigation behavior24:00 — How HUMAN distinguishes bot vs agent vs human33:00 — The bad side: spoofed ChatGPT & Perplexity traffic38:30 — Retailers blocking bots without realizing it47:00 — The inevitability of agentic adoption48:40 — The future: agent-to-agent transactions49:30 — The end of 2FA hell?👉 Connect with Stu: https://www.linkedin.com/in/stu-solomon-733a217/👉 Learn more about HUMAN: https://www.humansecurity.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 Retailgentic, Scot sits down with one of the most influential product leaders in commerce technology: Nitin Mangtani, SVP & GM of Salesforce Commerce Cloud. Their relationship goes back almost two decades, intersecting at Google, during the rise of online shopping, and now again at the dawn of agentic commerce. Nitin shares his journey from supply chain analytics at i2 Technologies, to building Google’s earliest commerce products, to founding and scaling PredictSpring, and finally leading Salesforce’s reinvention of unified and agentic commerce. This conversation is packed with history, strategy, and forward-looking insights into where AI shopping agents are taking the industry.Timestamps:03:20 – Early career: i2 Technologies & supply chain beginnings10:00 – Joining Google in 200613:30 – Launching Google Commerce Search & Site Search16:40 – Froogle/Google Shopping goes from “fun project” to billion-dollar business18:00 – Comparison engines, feed specs & early retail taxonomy challenges20:15 – Canonicalization and why product data was Google’s first “AI problem”22:40 – Leaving Google to start PredictSpring24:20 – PredictSpring’s original vision: mobile commerce & no-code apps26:05 – Pivoting PredictSpring: TAM realities & shifting to Point of Sale29:00 – Competing with Shopify POS, Square & the white space in enterprise POS31:30 – Startup lessons: pivots, risk, funding & an 11.5-year journey34:45 – Salesforce approaches PredictSpring: acquisition story38:00 – Meeting Marc Benioff & Salesforce’s leadership culture41:00 – Becoming SVP/GM: unifying Commerce Cloud, POS, OMS & Payments44:10 – Agentforce & the Agentic Commerce Protocol (ACP) with OpenAI & Stripe47:10 – Discovery vs checkout: why syndicated checkout is harder49:30 – Messaging commerce: WhatsApp, SMS & conversational transactions51:30 – Full automation: replenishment, grocery & true agentic behavior52:45 – Why commerce is strategically important to SalesforceAgentic commerce isn’t just a channel change, it’s a full-stack rewrite of how discovery, decision-making, and checkout work. Nitin makes clear that the next wave won’t be about small UX improvements, but about systems that think, act, and transact on behalf of consumers and retailers alike. With leaders like Nitin driving Salesforce’s transformation, the future of unified and agentic commerce is arriving faster than expected.👉 Connect with Nitin: https://www.linkedin.com/in/nitinmangtani/👉 Learn more about Salesforce: https://www.salesforce.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 Retailgentic, host Scot Wingo sits down with Johnathan McGowan, co-founder & CEO of PayOS, to discuss how AI agents will handle payments safely and compliantly.From Visa and Mastercard partnerships to the first live Agentic token transaction, Johnathan explains how “day-one-ready” infrastructure will power the future of Agentic Commerce.Timestamps:01:56 — Meet Johnathan McGowan, co-founder of PayOS04:00 — From Visa to PayOS: the founding story06:40 — What Agentic Payments really mean08:10 — Partnering with Visa & Mastercard10:25 — “Day-one-ready” vs new payment rails12:50 — What PayOS actually does15:30 — Agent builders and early use cases18:40 — Understanding “intent” in payments21:50 — Future-proofing across protocols (AP2, ACP, etc.)24:55 — How the first live Agentic transaction worked29:50 — Why PCI compliance & trust matter36:00 — The global scale of Agentic CommerceAs AI agents start making real-world transactions, companies like PayOS are making sure those payments are not just possible, but trusted, secure, and global from day one.👉 Connect with John: https://www.linkedin.com/in/johnathanm/👉 Learn more about the PayOS: https://www.linkedin.com/company/payos/🧠 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

OpenAI’s Chief Economist Ronnie Chatterji joins Scot Wingo on the Retailgentic Podcast to unpack OpenAI's recent National Bureau of Economic Research working paper "How People Use ChatGPT".From asking vs. doing to AI-powered shopping behavior, this deep dive reveals how generative AI is transforming the economy and how soon “agentic” commerce will redefine online retail.This episode is more than a window into OpenAI, it’s a look at the data shaping how humans and agents will interact, shop, and make decisions in the years ahead. If you care about where AI is really headed, this one’s not just worth your time, it’s required listening.Timestamps:02:00 – Meet Ronnie Chatterji, OpenAI’s Chief Economist06:00 – How the ChatGPT usage study began10:30 – What surprised the team most15:00 – Asking vs. Doing: the evolution of agentic behavior19:00 – The viral “colored columns” chart and what it shows22:00 – AI and the future of writing, learning, and work26:00 – How Ronnie bought jeans with ChatGPT28:00 – The 2.1% insight: early AI commerce signals33:00 – Voice + vision = the next leap for agentic shopping38:00 – The global view of AI adoption42:00 – What’s next in OpenAI’s research45:00 – Closing thoughts & how to follow Ronnie👉 Connect with Ronnie: https://www.linkedin.com/in/aaron-ronnie-chatterji/👉 Learn more about the paper we discuss: https://openai.com/index/how-people-are-using-chatgpt/🧠 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 Retailgentic, Salesforce’s Director of Strategy and Consumer Insights Caila Schwartz joins Scot Wingo to break down Salesforce’s 2024 Holiday Forecast, and how AI agents like ChatGPT, Perplexity, and Gemini are transforming the path to purchase.They cover:How 21% of global holiday spend will be influenced by AIWhy discovery (not discounts) is this year’s themeWhy Baby Boomers are finally using ChatGPT for shoppingHow Gen Z is bringing the mall back with AI in handThe return of “Discount Chicken” and the Tuesday-after-Cyber-Monday surpriseTimestamps:00:00 – Welcome + Caila intro01:00 – What Salesforce’s Consumer Insights team does04:30 – Agentforce and AI momentum post-Dreamforce07:00 – Holiday forecast: “Discovery” as the 2024 theme08:00 – How Agentic tools are changing product search09:45 – $263B in AI-influenced sales12:00 – Gen Z, Baby Boomers, and agentic adoption15:00 – Q3 data: growth, traffic, and product detail engagement19:30 – LLM referrals vs social media conversions22:00 – ChatGPT Checkout and embedded commerce25:00 – AI in physical stores — 57% of shoppers use agents in-store28:00 – Holiday sales forecast and discount trends33:00 – The rise of “Discount Chicken”38:00 – Loyalty consolidation and the price-sensitive consumer42:00 – Gen Z’s love of in-store experiences47:00 – The future of unified data and physical + digital retail50:00 – Closing thoughts👉 Connect with Manil: https://www.linkedin.com/in/caila-schwartz/👉 Learn more about Salesforce: https://www.salesforce.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 Retailgentic, Scot Wingo talks with Manil Uppal, Founder & CEO of CartAI, about building the “execution layer” of agentic commerce, where AI agents don’t just recommend products, they buy them. From his early startups acquired by H-E-B and UPS to his vision for CartAI, Manil shares how his team is solving the hardest problem in agentic shopping: completing checkout seamlessly across any retailer.Key Timestamps00:02:00 – Manil’s background: from delivery startups to AI infrastructure00:09:00 – The “aha” moment: from “Where to Buy” to “Go Buy It”00:15:00 – The 3 layers of Agentic Commerce: Catalog, Payments, Checkout00:20:00 – How CartAI executes merchant-native checkouts across platforms00:26:00 – Why retailers need a whitelist for good agents00:33:00 – Handling out-of-stocks, variants, and dynamic pricing00:40:00 – Thoughts on ChatGPT’s new ACP standard00:43:00 – Lessons from early food delivery startups for agentic commerce00:46:00 – The future: vertical AI apps, expert agents, and commerce everywhereAgentic commerce is evolving fast and CartAI is building the rails to make it work.👉 Connect with Manil: https://www.linkedin.com/in/maniluppal/👉 Learn more about CartAI: https://www.cartai.ai👉 Explore their substack: https://substack.com/@cartai🧠 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 special Retailgentic episode, guest host Kiri Masters turns the tables on our regular host, Scot Wingo (CEO, ReFiBuy). They unpack the next big retail revolution, Agentic Commerce, and what it means for shoppers, retailers, and brands as AI shopping agents like ChatGPT and Perplexity redefine discovery, loyalty, and checkout.Scot shares the lessons behind ChannelAdvisor, Spiffy, and now ReFiBuy, plus why messy product catalogs, ad overload, and loyalty programs will determine who wins in the AI marketplace era.⏱️ Key Timestamps00:00 – Intro: Kiri turns the tables02:15 – Scot’s early career & first startup07:50 – Building ChannelAdvisor14:30 – Lessons from going public20:05 – Spiffy and the services economy26:40 – Discovering AI → the spark for ReFiBuy33:00 – What is Agentic Commerce?38:20 – ChatGPT & Perplexity in the marketplace race45:00 – The product catalog problem explained51:00 – How ReFiBuy solves it with AI55:20 – Retailers’ edge: loyalty, data, customer experience59:00 – The next phase: marketplaces 2.01:02:00 – Close: The future of AI shopping👉 Connect with Scot: https://www.linkedin.com/in/thescotwingo/👉 Learn more about ReFiBuy: refibuy.ai🧠 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://youtu.be/4xI9qXNU_R0

In this episode of the Retailgentic Podcast, Scot Wingo sits down with Jason Nyus, General Manager of North America at Shopware, a leading open-source e-commerce platform. Jason brings over 25 years of experience (20+ at Digital River) to unpack where e-commerce is heading, why Shopware is betting big on agentic commerce, and how the Agentic Commerce Alliance could shape the industry’s future.Timestamps:02:00 – Jason’s 25-year journey in e-commerce, from Digital River to Shopware06:00 – The early days of app stores: Nokia, Blackberry, Microsoft09:45 – Why Digital River pivoted and what commoditization taught him13:00 – Why Shopware sees opportunity in mid-market and complex use cases20:30 – Shopware’s scale: $23B processing volume, top 6 global commerce platform26:00 – Introducing the Agentic Commerce Alliance: vision, openness, and independence36:00 – Use cases for agentic commerce: competitive pricing, loyalty, and customer service42:00 – Risks and opportunities for Shopify, Google, and Amazon in the agentic era46:00 – Jason’s predictions: a billion-dollar brand without a website, 25% of e-commerce becoming agentic by 2030Jason makes it clear: the future of commerce won’t be decided by one platform. Shopware’s vision of an open, agent-friendly ecosystem is a bold alternative to a closed, platform-controlled future. The Agentic Commerce Alliance could become one of the most important initiatives shaping AI-driven retail.👉 Connect with Jason: https://www.linkedin.com/in/jasonnyhus/👉 Learn more about Shopware’s vision: shopware.com👉 Explore the Agentic Commerce Alliance: agentic-commerce.org🧠 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://youtu.be/4xI9qXNU_R0

On this special Retailgentic episode, we sit down with Jordi Montes, CEO & co-founder of SimpleCheckout.ai, who officially launched today. Jordi shares his journey from Bitcoin’s Lightning Network to building a unified checkout and payment framework for AI agents. We dive into why agentic payments matter, what SimpleCheckout solves, and how it could reshape the future of online retail.Timestamps:00:01:55 – Jordi’s background: from TravelPerk to Lightning Network00:05:30 – The “sci-fi moment” that inspired SimpleCheckout00:12:00 – Why payments must evolve beyond the browser00:18:00 – Mapping agentic commerce to the travel industry model00:23:00 – Competing visions: SimpleCheckout vs. PayOS vs. Nacuda00:31:00 – The role of personalization in agentic commerce00:39:45 – Why SimpleCheckout is payment- and merchant-agnostic00:43:30 – Looking ahead: the future of agent-to-agent paymentsSimpleCheckout’s launch marks a turning point in how AI agents will transact. As agentic commerce takes hold, Jordi’s vision of a universal, flexible checkout protocol could define the rails of the next decade.Checkout their substack announcement: https://simplecheckout.substack.com/p/agentic-commerce-made-simple🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai📺 Watch episodes on YouTube: youtube.com/@retailgentic🎧 Listen wherever you get your podcasts: Spotify, Apple, etc.