Retailgentic: Agentic Commerce meets Retail and Brands

Scot Wingo
  • 5.0 (5)
  • TECHNOLOGY

Retailgentic is the podcast where Agentic Commerce meets retail innovation. We help retailers and brands prepare for the future of agent-driven shopping with actionable news, expert insights, deep analysis, and forward-looking predictions.

  1. Sensor Tower SVP Ian Simpson breaks down Holiday ’25 funnel data, conversion lift, and what brands should do next.

    5D AGO

    Sensor Tower SVP Ian Simpson breaks down Holiday ’25 funnel data, conversion lift, and what brands should do next.

    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 Trained 02:09 – Why This Episode Focuses on Rufus 05:49 – Ian Simpson’s Background 06:47 – Founding a Bottled Tea Startup 09:14 – Pathmatics → Sensor Tower Acquisition 10:11 – How Retail Media Intelligence Was Born 13:50 – How Sensor Tower Delivers Its Data 15:36 – Why Sensor Tower Started Tracking Agentic Commerce 21:08 – How the Rufus Analysis Was Done 22:48 – The 3.5× Conversion Lift Explained 24:18 – Amazon’s $10B Rufus Claim vs. Independent Data 28:16 – Correlation vs. Causation in Rufus Usage 31:23 – Rufus as a Research Companion 32:20 – The Cup Holder Story (Problem-Based Shopping) 39:55 – Why Rufus Usage Sticks After the Holidays 40:19 – The 10 Rufus Shopping Profiles 41:35 – The “Research Conversationalist” Funnel 45:00 – Why “AEO” Makes Ian Nervous 46:47 – Brand Matters Again in Agentic Commerce 48:47 – When AI Talks Consumers Out of Premium Products 58:21 – Retail Media’s Future in a Low-Click World 01:01:31 – Avoiding the Minority Report Ad Nightmare 01:06:21 – Instacart: The Wild West of Retail Media 01:07:15 – Where to Follow Ian 👉 Connect with Ian: https://www.linkedin.com/in/iansimpson/👉 Learn more about Sensor Tower: https://sensortower.com Check 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

    1h 8m
  2. Ken Moore, Mastercard Chief Innovation Officer, on the Blueprint for Agentic Commerce: Trust, Tokens & “Know Your Agent”

    JAN 29

    Ken Moore, Mastercard Chief Innovation Officer, on the Blueprint for Agentic Commerce: Trust, Tokens & “Know Your Agent”

    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 timestamps 05:14 — 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

    49 min
  3. Maia Josebachvili on Stripe’s Agentic Commerce Playbook

    JAN 22

    Maia Josebachvili on Stripe’s Agentic Commerce Playbook

    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

    35 min
  4. Jason Goldberg's Full NRF Keynote on Agentic Commerce: "Commerce Disrupted: Rise of the AI Native consumer"

    JAN 15

    Jason Goldberg's Full NRF Keynote on Agentic Commerce: "Commerce Disrupted: Rise of the AI Native consumer"

    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

    43 min
  5. FLASH: Google Goes ALL-IN on Agentic Commerce at NRF: UCP, Gemini Checkout, Shopify and more

    JAN 11

    FLASH: Google Goes ALL-IN on Agentic Commerce at NRF: UCP, Gemini Checkout, Shopify and more

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

    33 min
  6. Hamish Gunasekara, CEO of Catalog, on Why Agentic Commerce Starts With Product Data

    JAN 8

    Hamish Gunasekara, CEO of Catalog, on Why Agentic Commerce Starts With Product Data

    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

    46 min
  7. Matt Nichols Returns: What 2025 Got Right (and Wrong) About Agentic Commerce

    12/18/2025

    Matt Nichols Returns: What 2025 Got Right (and Wrong) About Agentic Commerce

    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

    52 min
  8. A Conversation with Luca Fiaschi of PyMC Labs: Synthetic Consumers & the Future of Product Testing

    12/11/2025

    A Conversation with Luca Fiaschi of PyMC Labs: Synthetic Consumers & the Future of Product Testing

    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

    54 min
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Retailgentic is the podcast where Agentic Commerce meets retail innovation. We help retailers and brands prepare for the future of agent-driven shopping with actionable news, expert insights, deep analysis, and forward-looking predictions.

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