Retailgentic | Consumer Behavior & Retail Trend

Retailgentic explores consumer behavior and retail trends to help brands and retailers innovate. Join Scot Wingo for expert insights, actionable news, and ecommerce innovation strategies to navigate the future of retail and agentic commerce.

Retailgentic | Consumer Behavior & Retail Trend is a technology podcast hosted by Unknown Host, with 65 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Unknown Host hosts Retailgentic | Consumer Behavior & Retail Trend, a technology show with 65 episodes published.

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  Episode #62

  Shopify's Agentic Commerce Playbook: VP of Product Mani Fazeli on 8X Agentic Traffic Growth and the Long-Tail Boom

  Jul 30, 202653 min

  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 ChannelAdvisor 04:38 Mani's path to VP of Product at Shopify 06:37 The Wish / ContextLogic founding story 08:18 Vibe coding and "AI makes everyone a 7 out of 10" 11:10 What Mani owns across the commerce loop 12:42 Non-merchant-of-record channels (ChatGPT, Gemini) 13:45 Defining agentic commerce 14:44 The crawl / walk / run / fly framework 17:50 The stats: 8X traffic, 13X orders, +50% conversion, +14% AOV 20:03 Out-of-the-box UCP compatibility and agentic storefronts 23:10 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 love 32:24 Top things merchants should do to win 35:28 The escalation "escape hatch" 37:24 Word of mouth and the long tail, 70% of AI orders 42:41 Spring '26 Edition: Shop app, Ship & Pick Up, Pulse, Autopilot 48:10 Where it all goes by 2030: B2B vs DTC 52:29 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

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  Episode #61

  AI Is a New Customer Category: Wharton Professor & Bodhium Labs Co-Founder Kartik Hosanagar

  Jul 23, 202643 min

  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 reversal Counterfactual 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 problem 03:49 Kartik's cocktail-party version: academic + entrepreneur, Yodle 04:36 The Yodle / Milo mobile-social-local era (and Fidji at OpenAI) 06:05 Wharton AI Center and what Kartik researches 07:37 The thesis: AI search is more than another channel 10:08 Defining agentic commerce: the driverless-car levels 12:34 UCP, Gemini, and why Amazon joined 15:55 Amazon vs. Walmart strategies (Rufus vs. Sparky) 16:29 Bodhium Labs: what it is 17:00 The AEO/GEO problem: guesswork and the Reddit trap 18:56 Research-led counterfactual simulations 21:02 The long tail: multi-turn conversations replace keywords 22:49 CommerceNext keynote: 4 words to 60 words 24:57 The "AI is just another channel" misconception 26:48 Shopper trust: high for discovery, not for checkout 28:15 You can't fully control what AI thinks about you 30:51 The roadmap: today, this quarter, this year 34:41 Rufus, Sparky, UCP, and MCP endpoints 36:37 Does agentic commerce grow the pie or shift it? 38:32 Do we still need websites? Two front doors 40:39 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

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  Episode #60

  ‼️EXCLUSIVE 👀 FIRST LOOK 👀: Deloitte Digital’s "Bridging the commerce divide" with Bobby Stephens & Apurva Pangam

  Jul 16, 202642 min

  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 look 06:12 Meet Bobby Stephens & Apurva Pangam 07:19 AP's background: 20 years in commerce 08:01 Bobby's background — buyer to footwear founder 09:29 Where they fit in Deloitte's retail team 10:18 Inside the report: methodology 12:32 The consumer side — the basics 14:47 The perception gap & false confidence 15:50 Personalization: 57 definitions 17:30 On-site agents: Rufus, Sparky & TSA 20:02 Playbooks, CDPs & the customer P&L 21:21 AI for operational efficiency 25:40 Making product data machine-readable 26:38 Answer engines & the decision collapse 29:34 Loyalty: everyone plays, few win 33:52 Who's winning: profiling the leaders 38:44 Connecting the dots 40:18 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

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  Episode #59

  Fewer Visitors, 3X the Conversion: Forrester VP and Principal Analyst Chuck Gahun Discusses 'The State of Agentic Commerce (Q2)'

  Jul 9, 202649 min

  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 conversation Timestamps: 03:47 Meet Chuck Gahun, Forrester principal analyst 05:03 Chuck's background: two decades, Sapient, the services side 07:57 How Forrester's commerce team is structured 10:52 Defining agentic commerce: shopping vs. buying 12:37 Conversational commerce vs. the strict definition 13:49 Semi-autonomous vs. autonomous (the dog-treats test) 14:38 Inside the answer-engine consumer survey 15:47 The numbers: 38% discover, 17% buy, 62% research 16:22 Beyond retail: healthcare, travel, government 19:48 Figure 1: owned vs. not-owned, four levels 21:47 The trust gap and who's liable (44%) 24:37 Marketplaces, merchant of record, and returns 27:52 What Forrester tells merchants: don't wait 29:57 Product fit, profitability, and the ACP/UCP specs 31:58 Figure 3: the four-quadrant framework & machine advantage 35:53 The SKU problem and exponential change management 38:35 The B2B surge prediction 41:25 2030 predictions & death of the retail website 46:32 Less traffic, higher conversion: the 3X surprise 47:18 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

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  Episode #58

  OLLY Agentic Commerce Optimization: MarTech & Digital Compliance Director Jennifer Peters On Building an AI Foundation the Right Way

  Jun 30, 202643 min

  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 impact 00:21 Welcome to Retailgentic 01:36 Scot's intro: a real practitioner doing the work 04:13 Welcome, Jennifer Peters 05:20 Jennifer's background: agency, Cokesbury, OLLY 06:51 Becoming a self-taught Shopify developer 07:56 Side quest: Claude, MCP, and AI "god mode" 11:34 What is OLLY? The square-bottle homeland 12:18 Inside the DTC + MarTech role 13:15 Why the website is now the point of entry 16:21 Jennifer's agentic commerce journey begins 17:48 Start with the basics: AEO is just good SEO 18:21 FAQs on PDPs — the easy slam dunk 19:48 Catalog feed enhancement & digital attributes 21:52 Profound and the AEO vendor landscape 23:57 Panel data: "super sus" 24:42 Trust but verify across tools 25:45 The Reddit problem 27:14 Bazaarvoice and review syndication 28:44 Don't skip the un-AI basics 30:20 Measuring impact without getting fooled 31:31 Same OKRs, AI just gets there faster 35:40 Does it leak into Walmart & Target? 37:48 Sharing content across channels 40:06 What's next: AI backlash and counterculture 42:37 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

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