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Retailgentic | Consumer Behavior & Retail Trend

Scot Wingo | Retail Trends Analyst

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.

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  • 34 episodes
  • weekly
  • Avg 42 min
  • English

Episodes 34

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  • #77
    Thursday · 48 min

    AI Meets Fashion: Co-Founder & Chief Brands Officer Lisa Yamner on Daydream’s Big Bet

    When you think about vertical shopping agents, the AI agents built to solve shopping in one category, one name keeps coming up: Daydream. We’d wanted to get the Daydream team on Retailgentic for a while, and this week we finally did. This one is part founder story and part deep dive into what a fashion-native agent learns when shoppers stop typing keywords and start describing their lives. Highlights: 𝗧𝗵𝗲 $𝟱𝟬𝗠 𝗿𝗮𝗶𝘀𝗲: Daydream has raised $50 million. The Pinterest exit kept earlier investors on board and brought in new ones who had wanted into The Yes before it was acquired. 𝗢𝗻𝗹𝘆 𝟯% 𝗼𝗳 𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝘀 𝗻𝗮𝗺𝗲 𝗮 𝗯𝗿𝗮𝗻𝗱: In Lisa’s Google days, brand search drove everything. On Daydream, people search by occasion, lifestyle and body type. 𝗤𝘂𝗲𝗿𝗶𝗲𝘀 𝗴𝗲𝘁 𝗱𝗲𝗲𝗽𝗲𝗿: New users start with Google-style searches like “red dress.” The more often they return, the longer and richer their queries get. One real example: “Going to a Tulum vacation for five days. Help me dress like a Jacquemus ad.” 𝗦𝘁𝘆𝗹𝗶𝘀𝘁 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗽𝗼𝗰𝗸𝗲𝘁: “You never ask your personal assistant to actually pick it out for you.” Lisa says that gap is where Daydream fits. 𝗟𝗶𝘃𝗲 𝗶𝗻 𝘁𝘄𝗼 𝗱𝗮𝘆𝘀: Daydream works from brands’ existing Google or affiliate feeds, takes its commission through affiliate networks, and gets most partners live within about two days. The catalog covers 350+ partners, 10,000 brands and 3 million products. 𝗧𝗵𝗲 𝗳𝗮𝘀𝗵𝗶𝗼𝗻 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗴𝗿𝗮𝗽𝗵: Daydream doesn’t take a feed as finished. It enriches each one using text, images and input from real stylists, so it can tell that a skirt is both A-line and pleated, and that a white dress is the wrong answer for a wedding guest. “𝗠𝘆 𝗳𝗲𝗲𝗱 𝗶𝘀 𝗴𝗮𝗿𝗯𝗮𝗴𝗲”: It’s what Lisa hears most often from brands. Daydream’s goal is to level the field so a brand with a 25-person feed team doesn’t automatically beat a one-person Shopify shop. 𝗧𝗮𝘀𝘁𝗲 𝘃𝘀. 𝘀𝗽𝗲𝗰: Lisa splits shopping into two kinds. In spec-based buying (“the Samsung Frame TV in 65 inches, just buy me the best price”), agents will act fast. In taste-based categories like fashion and home decor, people “want agency in” the process. Lisa has spent her whole career bringing fashion along into what’s next, and Daydream may be the clearest picture yet of what a category-native agent can do. Timestamps: 03:55 Welcome Lisa Yamner, Co-Founder of Daydream 04:45 Lisa's background: 12 years at Google 05:35 Condé Nast, The Yes and the Pinterest acquisition 07:40 The original 2023 Daydream pitch 10:05 Raising $50M 10:45 What Daydream learned about consumer behavior 12:40 The stylist in your pocket 13:55 Getting fashion brands on board 16:25 The SoHo pop-up, brand activations and AI Decoded 19:30 How merchants get started 21:10 Powered by Daydream 21:50 Building B2B and consumer at the same time 23:00 Conversion and the "shop with AI" problem 26:00 What brands learn from natural-language search 28:50 Profiles, context and personalization 30:40 Product data gaps and the fashion knowledge graph 34:55 What's next: a proactive AI stylist 39:25 Will consumers let agents buy? Taste vs. spec 45:05 Protocols and payments 46:55 Agentic commerce in 2030 47:50 Wrap-up 👉 Connect with Lisa: https://www.linkedin.com/in/lisayamnergreen/ 👉 Learn more about Daydream: https://daydream.ing/ 🧠 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

  • #78
    Thursday · 45 min

    How Brands are Leveraging AI in the Design Phase: Raspberry AI Founder & CEO Cheryl Liu

    About every six months on Retailgentic, we step away from the front end of agentic commerce to look at how AI is changing a different part of the retail stack. This week it’s product creation. Raspberry AI helps fashion brands and other retailers visualize, test and sell products before a physical sample exists. It’s part founder story and part look at what happens downstream when making products gets that fast. Highlights : 𝟭𝟱% 𝗵𝗶𝗴𝗵𝗲𝗿 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻: Raspberry measured 15% higher conversion on AI-generated e-commerce PDP imagery than on traditional photo shoots, at 80% to 90% lower cost. Cheryl thinks video and personalized content could push that to 25% within a year. 𝟭,𝟰𝟬𝟬 𝗶𝗻, 𝟰𝟱 𝗼𝘂𝘁: Wholesale brands walk into a Nordstrom or Bloomingdale’s buy meeting with 1,400 products and get 45 adopted. “1,400 products did not need to be created at all.” 𝟮.𝟯𝘅 𝘁𝗵𝗲 𝗗𝗶𝗰𝗸’𝘀 𝗼𝗿𝗱𝗲𝗿: One of the world’s largest sportswear companies changed products and styling live in front of the CEO of Dick’s Sporting Goods and came away with 2.3x the order. Across wholesale customers, orders are up 1.5x to 2.5x. 𝟭𝟮–𝟭𝟴 𝗺𝗼𝗻𝘁𝗵𝘀 𝘃𝘀. 𝟯–𝟭𝟰 𝗱𝗮𝘆𝘀: Most fashion brands take 12 to 18 months to get from a designer’s idea to a product you can buy. The fastest players get that down to three to 14 days. 𝗜𝗺𝗮𝗴𝗲 𝗲𝗻𝗴𝗶𝗻𝗲 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 (𝗜𝗘𝗢): After SEO and GEO, Cheryl’s next frontier is measuring which angles, models and lighting convert for each brand. For some men’s brands that’s flat lays. For women’s brands it’s on-body. 𝟰𝟲𝟬 𝗯𝗿𝗮𝗻𝗱𝘀 𝗶𝗻 𝟮.𝟱 𝘆𝗲𝗮𝗿𝘀: Raspberry has been selling for about two and a half years and works with 460 brands. 70% of clients use it in three or more departments, most often design, e-commerce and marketing. 𝗙𝗼𝘂𝗿 𝘄𝗲𝗲𝗸𝘀 𝗲𝗮𝗿𝗹𝘆: One of the world’s biggest retailers had never turned in private-label design specs on time in 20 years. With Raspberry, they turned them in four weeks early. 𝗕𝘂𝗶𝗹𝘁 𝗳𝗼𝗿 𝗰𝘂𝘁-𝗮𝗻𝗱-𝘀𝗲𝘄: Raspberry trains its own models for fabric, drape and physical feasibility, and generates the tech packs factories need. “At the end of the day, someone has to cut and sew that.” Cheryl calls it starting at the end: show the finished product before doing the work. We loved this one, and we’ll have her back once she’s built more of the future she described. Enjoy the conversation. Timestamps: 00:48 Welcome to Retailgentic 02:04 Scot's intro: AI in product creation 03:27 Welcome Cheryl Liu of Raspberry AI 03:55 Cheryl's background: KKR, AWS, DoorDash 06:50 The origin story at DoorDash 08:05 Seven fingers and a glimpse of the future 09:50 12–18 months vs. 3–14 days 11:05 Amazon's press release meets Shein 13:35 From Shopify 2.0 to product creation 16:05 Fundraising and the $23M a16z Series A 20:25 Landing the first customers 22:35 Product-market fit and the 1,400-to-45 problem 25:10 Case study: 2.3x the Dick's Sporting Goods order 27:40 Moving downstream to e-comm, marketing and stores 30:35 The ROI: speed, wholesale lift, 15% better conversion 33:05 Can consumers design their own products? 37:05 Training their own models and generating tech packs 40:25 Where Raspberry is headed: new categories 43:25 IEO: image engine optimization 44:20 How will AI agents see product images? 44:50 Wrap-up 👉 Connect with Cheryl: https://www.linkedin.com/in/cheryl-jiaping-liu/ 👉 Learn more about Raspberry AI: https://www.raspberry.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

  • #76
    October 29 · 44 min

    Shoppers Take the Agent’s Top Pick: Growth Memo Author Kevin Indig on How People Really Shop in ChatGPT and AI Mode

    This week is a research-heavy episode with a conversation of one of the sharpest observers of how real people search and shop now that AI sits between them and the products they want. Kevin’s user-behavior research helped inspire our own product card study at ReFiBuy, so we’ve wanted to have him on for a while. Highlights 𝗧𝗵𝗲 𝘀𝗵𝗼𝗿𝘁𝗹𝗶𝘀𝘁 𝗲𝗳𝗳𝗲𝗰𝘁: Over 88% of participants in Kevin’s user-behavior studies didn’t question the frame from AI. “When AI says, ‘These are the best X,’ people barely question it.” 𝗧𝗼𝗽 𝗼𝗳 𝘁𝗵𝗲 𝗹𝗶𝘀𝘁 𝘄𝗶𝗻𝘀: Almost 75% of people picked the item at the top of the shortlist. The top-heaviness of classic Google search carries straight over into AI mode. 𝗢𝗻𝗹𝘆 𝟯% 𝘃𝗲𝗿𝗶𝗳𝘆: In a ChatGPT study, only 3% of people checked the shortlist anywhere else on the open web: not publishers, not affiliates, not YouTube. 𝗧𝗿𝘂𝘀𝘁 𝗶𝘀 𝘁𝗵𝗲 𝘀𝗵𝗼𝗿𝘁𝗰𝘂𝘁: The one thing that breaks the pattern is a brand the shopper recognizes and trusts. Show up as Nike in position five and people who trust Nike will pick you over the #1 item. 𝗧𝗵𝗲 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗯𝗲𝗵𝗶𝗻𝗱 𝗶𝘁: Five user-behavior studies over roughly 24 months, with 100+ participants and 400+ tasks. Every click, hover, and scroll was recorded, and participants talked through what they were thinking. 𝟵𝟲% 𝗰𝗮𝗿𝗼𝘂𝘀𝗲𝗹𝘀: Kevin analyzed 4,000+ shopping queries on regular Google (not AI mode). Over 96% showed at least one product carousel, and when one appears, click-through on classic blue links drops by at least 50%. 𝗔𝗱𝘀 𝗶𝗻 𝗱𝗶𝘀𝗴𝘂𝗶𝘀𝗲: Google shows more ads, bigger ads, and ads that are harder to tell apart from organic results. “I’ve been in this space for over 15 years. I more and more accidentally click on ads.” 𝗤𝘂𝗲𝗿𝘆 𝗳𝗮𝗻-𝗼𝘂𝘁𝘀: AI engines run live searches on anywhere from two to hundreds of keywords before they answer. Ranking better on those fan-out queries has repeatedly increased citation rates and AI visibility. 𝗠𝗲𝗿𝗰𝗵𝗮𝗻𝘁 𝗖𝗲𝗻𝘁𝗲𝗿 𝗼𝘃𝗲𝗿 𝗦𝗲𝗮𝗿𝗰𝗵 𝗖𝗼𝗻𝘀𝗼𝗹𝗲: Google’s Merchant Center now says more about how products show up in AI than Search Console does, which is why Kevin calls commerce the beachhead for AI optimization. 𝗧𝗵𝗲 𝗼𝘃𝗲𝗿/𝘂𝗻𝗱𝗲𝗿: For AI-assisted product research, Kevin takes the over on 10–20% of shoppers. For fully agentic checkout, he expects under 1% over the next 12 months. Kevin is one of the best at separating what the data says from what the hype says. Subscribe to Growth Memo after you subscribe to Retailgentic, and enjoy the conversation. Timestamps: 05:00 Welcome Kevin 05:25 From SEO to growth: Meta, Reddit, Ramp & Shopify 06:40 The growth ninja: why companies call Kevin in 07:45 Three turnaround patterns: strategy, AI erosion, broken channels 09:20 Can AEO/GEO make up for lost SEO traffic? 11:10 The 4,000-query study: 96% show product carousels 12:10 Ads are taking over Google 14:55 Is Google pushing people into AI mode? 17:00 Will AI mode become the default? 20:05 Universal cart, UCP & richer context for ads 21:05 User-behavior findings: shortlist, slot #1, trust & 3% verify 23:30 Surveys vs. observed behavior vs. panel data 26:30 How do you get slot one? AEO vs. GEO 27:55 Query fan-outs & classic SEO tactics that still work 29:35 ACP, UCP & the product feed 30:40 Merchant Center data & closed loops 32:55 "More butter out of the dish": agents sniff out false claims 34:05 Websites matter less & direct checkout is inevitable 35:10 Back-endification: buyer data, retention & direct traffic 38:15 OpenClaw, Muse & the new consumer AI agents 40:00 Agents as a threat to marketplaces: Amazon vs. Shopify 41:20 20% agentic by 2030? Kevin's over/under 43:45 Wrap-up & where to find Growth Memo 👉 Connect with Kevin: https://www.linkedin.com/in/kevinindig/ 👉 Learn more about Growth Memo: https://www.growth-memo.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

  • #74
    October 22 · 43 min

    The Missing Link Is Shopper Context: eComID CEO Oscar Rundqvist; Plus eComID’s Big Funding Announcement 📣

    This week is a product deep dive with a fresh funding story attached. eComID just closed Europe’s largest fashion tech seed round, and the company is building something agentic commerce needs: shopper context that belongs to the shopper and goes wherever they shop. The ID was born inside H&M, it already runs on about 70 brand sites, and it’s now headed for the US. Highlights 𝗧𝗵𝗲 $𝟭𝟳.𝟰𝗠 𝘀𝗲𝗲𝗱 𝗿𝗼𝘂𝗻𝗱: Europe's largest fashion tech seed round. Oscar says it's the second-biggest in the world, led by London's Systemiq Capital, and Nordic sports retailer Stadium (one of eComID's biggest customers) joined as a strategic investor. Scot rang the gong 🔔 𝗕𝗼𝗿𝗻 𝗶𝗻𝘀𝗶𝗱𝗲 𝗛&𝗠: Oscar pitched eComID internally in a Dragon's Den–style process and H&M's startup arm invested from day one. 𝗔 𝘃𝗲𝗿𝘆 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝘀𝘁𝗿𝗮𝗻𝗴𝗲𝗿: Models are very capable, catalogs are open to agents and payments are getting solved. But without shopper context, AI "still starts from zero." It doesn't know your size, your taste or what you sent back. 𝗧𝗵𝗲 𝘀𝗵𝗼𝗽𝗽𝗶𝗻𝗴 𝗽𝗮𝘀𝘀𝗽𝗼𝗿𝘁: One source of truth for your size, taste and preferences, tied to your email. It goes with you across eComID brands like H&M, Björn Borg, Peak Performance and Haglöfs. "We want to democratize personalization." 𝟵𝟭% 𝗯𝘂𝘆 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝘀𝗶𝘇𝗲𝘀: 91% of shoppers buy different sizes from different brands. Oscar says that shows how broken sizing is. 𝗧𝗵𝗲 𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻: About 70 merchants, about 20 million shoppers reached each month, and 15% of users already in the US. Shoppers who use eComID have about 30% lower return rates and about 10% higher conversion. +𝟮𝟲% 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗽𝗲𝗿 𝘃𝗶𝘀𝗶𝘁𝗼𝗿: In a head-to-head test, eComID's AI search beat traditional on-site search by 26% on revenue per visitor. 𝗞𝗶𝗹𝗹 𝗮𝘃𝗲𝗿𝗮𝗴𝗲 𝗼𝗿𝗱𝗲𝗿 𝘃𝗮𝗹𝘂𝗲: "Average order value is a completely useless metric." What matters is average kept order value, because each handled return costs brands $21–46. 𝗧𝗿𝘂𝘀𝘁 𝗶𝘀 𝘁𝗵𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁: If an agent spends $1,000 for you, you need to know whose agent it is, what you authorized, what context it used and what happens if something goes wrong. Oscar argues Europe's GDPR-first approach suits agentic commerce. 𝗦𝗵𝗼𝘄 𝘀𝗵𝗼𝗽𝗽𝗲𝗿𝘀 𝘁𝗵𝗲𝗶𝗿 𝗿𝗲𝘁𝘂𝗿𝗻 𝗿𝗮𝘁𝗲: 92% of shoppers want to see their own return rate, and 75% say seeing it makes them want to return less. The live demo on Houdini Sportswear shows the search, sizing and nudge modules working together. Timestamps: 00:35 Welcome to Retailgentic 01:50 Announcement: Kiri Masters launches Adgentic 05:00 Welcome Oscar Rundqvist, CEO & founder of eComID 05:25 Big news: $17.4M, Europe's largest fashion tech seed round 06:15 Oscar's background at H&M 07:35 Lessons from H&M: why personalization never worked 08:55 Pitching eComID inside H&M's startup studio 09:40 Why we need eComID: AI without context starts from zero 10:55 The shopping passport: portable shopper context 13:20 Building the consumer side through brand modules 14:45 How the ID works across brands 16:30 Shopper control and a visible shopping algorithm 18:05 Beyond sizing: capturing taste and intent 20:35 The merchant suite: search, sizing, personalization, agents 23:00 Modular by design 23:50 Traction: 70 merchants, 20M shoppers, -30% returns 24:50 Why average order value is a useless metric 25:35 Use of proceeds and coming to the US 26:30 The fundraising journey and cap table 28:50 Fashion, shoes and future categories 30:15 Why AI can crack sizing when others couldn't 32:50 Product-led growth: no marketing, no sales 33:35 Agentic commerce adoption in Europe 37:15 AI platforms vs. brand sites and product context 38:55 Live demo: eComID on Houdini Sportswear 42:30 Wrap-up and how to reach Oscar 👉 Connect with Oscar: https://www.linkedin.com/in/oscarrundqvist/ 👉 Learn more about eComID: https://www.ecomid.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

  • #75
    October 20 · 17 min

    SPECIAL EPISODE: Ensh*ttification is coming to personal AI agents, from AdGentic

    Retailgentic listeners: this week we're sharing an episode of AdGentic, our sister show in the ReFiBuy Media Network. Retailgentic covers how AI agents are changing shopping. AdGentic covers what happens to advertising when your agent does the shopping. If you like this one, subscribe to AdGentic for more. Personal AI agents feel magical right now, and part of the magic is what's missing: ads. Kiri Masters walks through how Google, Facebook, WhatsApp and Amazon all started clean and ended up ad-funded, why AI is following the same script, and why that might not be the worst outcome. The real question isn't whether ads come to your agent. It's how bad they'll be. In this episode: → The broken no-ads promises of Google, Facebook and WhatsApp → Ensh*ttification, and why ads are still the least-worst way to pay for consumer tech → Subscriptions vs fees vs ads, and why fees quietly turn into ads → What Meta's Muse, OpenAI's Dots and Instinct have said about making money → The ad formats starting to appear in AI, and the ones agents might borrow Chapters 00:25 Welcome to AdGentic 00:50 The magic of an ad-free agent 01:55 Every platform starts like this: Google 02:30 Facebook and the scarf 03:05 WhatsApp's "No Ads!" note 03:25 Amazon: the store became the content 04:00 Ensh*ttification 04:40 Why I'm an advertising maximalist 05:05 Three ways to pay for an app 06:20 How Muse, Dots and Instinct plan to make money 07:05 The problem with subscriptions 07:30 Why fees turn into ads 08:25 How bad will it be? 09:15 AI ad formats so far 09:55 Formats agents could borrow 10:25 Off-site: ads without ads 11:20 Kiri's wish list for Ad Santa 11:50 The dark scenario 12:30 Ads are the least worst Subscribe to AdGentic Substack: https://www.adgentic.ai/ LinkedIn: https://www.linkedin.com/company/adgentic-podcast Podcast: https://adgentic.transistor.fm/ 🧠 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

  • #73
    October 15 · 29 min

    The Shelf Is a Zero-Sum Game: Wilde Brands Senior Director Justin Bomberowitz on Growing Challenger CPGs in the Agentic Commerce Era

    This episode was recorded live at the RetailClub AI Festival in Huntington Beach (Sept 22–24), where Jason Goldberg and I set up shop to record with retail and e-commerce leaders between sessions. You’ll hear a few nods to the festival in the conversation, and if there’s a little extra crunch in the audio, blame the snacks. We start with a quick tour of every CPG brand Justin has worked for, and the very scientific method he uses to pick the next one. From there it turns into a crash course in how challenger brands actually grow: the brutal economics of the physical shelf, why big brand houses are reshuffling their portfolios, and what it really takes to get into Costco and stay there. There’s also a snack reveal and a crunch our audio engineer will never forget. Hit play. Highlights 𝗧𝗵𝗲 𝘀𝗵𝗲𝗹𝗳 𝗶𝘀 𝘇𝗲𝗿𝗼-𝘀𝘂𝗺: “We haven’t added any square footage into a shelf.” When an emerging brand earns its way in from the innovation aisle, something else has to come out. “𝗜 𝘄𝗮𝘀 𝘄𝗿𝗼𝗻𝗴”: A year ago Justin would have said TikTok Shop would never be a main part of his job. Then came “a tsunami of interest,” and today Wilde runs live selling on TikTok Shop and Whatnot. 𝗧𝗵𝗲 𝗖𝗼𝘀𝘁𝗰𝗼 𝘁𝗵𝗿𝗲𝘀𝗵𝗼𝗹𝗱: Landing a Costco rotation is the moment brands post the hype video. If you miss the sales threshold, you don’t get a repeat, and the regional buyers talk to each other. 𝗦𝗽𝗲𝗲𝗱 𝘀𝗲𝗹𝗹𝘀: “Conversions go up the faster you get delivery.” Justin says ship-from-store is the fastest-growing part of Walmart digital, and if your product isn’t in that store, the conversion you paid Walmart Connect for disappears. 𝗘𝘃𝗲𝗿𝘆 𝘀𝗮𝗹𝗲, 𝗲𝘃𝗲𝗿𝘆 𝗭𝗜𝗣 𝗰𝗼𝗱𝗲: With two years of Amazon sales mapped by ZIP code, Justin can see that barbecue over-indexes in the Southeast and sea salt and vinegar in the Northeast. With AI, building creative for those regions is now quick. 𝗢𝗻𝗲 𝗰𝗲𝗻𝘁𝗿𝗮𝗹 𝗻𝗲𝗿𝘃𝗼𝘂𝘀 𝘀𝘆𝘀𝘁𝗲𝗺: Instead of building agents on top of separate data silos, Wilde built a data lake. Target store data, Roundel media, Shipt, Instacart, and DoorDash data all sit in one place, so a sales lead can ask a small language model what to do next. 𝗧𝗵𝗲 𝗽𝗿𝗼𝗺𝗼-𝘄𝗮𝘁𝗰𝗵𝗶𝗻𝗴 𝗮𝗴𝗲𝗻𝘁: When a retailer’s promotion drops a price on Instacart, one of Justin’s agents spots it through the API and flags it. He then decides whether to push ads to new-to-brand shoppers or pause them for 30 days and let the promo do the work. 𝗨𝘀𝗲 𝘁𝗵𝗲𝗺 𝗮𝗹𝗹: Justin builds mostly in Claude but stays LLM-agnostic, trying Grok, Muse, Kimi, and NVIDIA’s open models. “Don’t let your frame just get put into one.” 𝗗𝗼𝘇𝗲𝗻𝘀 𝗼𝗳 𝗮𝗴𝗲𝗻𝘁𝘀: “I have dozens of agents that I’m working with. That is the new norm.” I learned more about how CPG actually works in 30 minutes with Justin than I have in years of nodding along when Jason explains it. Grab a bag of something crunchy and enjoy the conversation. Timestamps: 01:47 Disclosure: Justin is on the ReFiBuy advisory board 02:00 Every CPG brand Justin has worked at, and the spouse test 03:00 How challenger brands grow: from D2C to Walmart, Target, and Costco 03:55 Acquired or spun off: why CPG portfolios are reshuffling 04:10 Turns and the zero-sum shelf 05:10 PopCorners and the protein pivot 06:10 Social commerce is here: TikTok Shop and Whatnot live selling 06:50 Snack reveal: "I was wrong" about TikTok Shop 08:40 Plot twist: chips made of chicken breast (plus the crunch) 10:00 Making it in Costco: pallets, thresholds, and regionality 11:10 The Justin playbook: it starts with Amazon data 12:55 DoorDash comes to Costco, and why Instacart vs. DoorDash isn't zero-sum 14:00 Jason's take: another nail in the coffin for Costco? 15:05 Ship-from-store, speed, and conversion 17:15 Who gives brands better data: Amazon, Walmart, or Target? 18:15 Every sale by ZIP code: flavor geo-targeting with AI 19:15 How AI changed everything: one data lake for Target, Roundel, Shipt, and more 21:35 Walmart's 4.7-petabyte data lake and Code Puppy 23:00 The AI cheerleader and climbing the agent ladder 24:05 Instacart media and the promo-watching agent 26:00 Claude, Grok, Muse, Kimi: use them all 27:45 What's next for CPG: dozens of agents 28:45 Wrap-up 👉 Connect with Justin: https://www.linkedin.com/in/justin-bomberowitz-%F0%9F%90%94-07030414/ 👉 Learn more about Wilde: https://wildebrands.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

  • #72
    October 8 · 26 min

    “Bad Data Equals Bad AI”: Ekta Chopra, e.l.f. Beauty’s Chief Technology & AI Officer - Live from Retailclub

    We pick up where we left off a year ago and get into what has changed since. Ekta walks us through how e.l.f. is structuring its AI work, what kind of person they’re hiring to do it, and how a public company makes the case for investing before the ROI is fully provable. The live audience jumps in with some sharp questions along the way. We close by looking ahead to what Ekta thinks brands need to get ready for in the next 12 months. Hit play. Highlights: 𝗟𝗲𝘁 𝗶𝘁 𝗿𝗶𝗽 𝗼𝗿 𝗹𝗼𝗰𝗸 𝗶𝘁 𝗱𝗼𝘄𝗻: Ekta says companies tend to pick one of two AI philosophies, giving it to everyone or locking it down. e.l.f. has tried to do both so it doesn't kill innovation. 𝗧𝗵𝗿𝗲𝗲 𝗽𝗼𝗱𝘀: e.l.f. runs three AI pods covering agentic commerce/growth, intelligent operations, and the human-agent workforce. Each pod owns data, change management, integrations, and training. The agentic growth roles are now being hired as dedicated full-time positions across e.l.f.'s brands. 𝗡𝗼 𝗼𝗻𝗲 𝗵𝗮𝘀 𝗺𝗲𝗮𝘀𝘂𝗿𝗲𝗺𝗲𝗻𝘁 𝗳𝗶𝗴𝘂𝗿𝗲𝗱 𝗼𝘂𝘁: "Anybody that tells you they have figured it out haven't figured it out." Ekta measures readiness instead, and focuses on the products where e.l.f. has the right to win. 𝗥𝗲𝗮𝗹 𝗽𝗿𝗼𝗺𝗽𝘁𝘀, 𝗳𝗶𝗻𝗮𝗹𝗹𝘆: Jason points out that most visibility tools rely on synthetic prompts. Google's new Agentic Insights tab in Merchant Center is the first look at what real people actually type, at least on Google surfaces. 𝗕𝗮𝗱 𝗱𝗮𝘁𝗮 = 𝗯𝗮𝗱 𝗔𝗜: Ekta's case for fixing the foundation first. If you don't solve the plumbing, you can't scale. 𝗘𝘅𝘁𝗲𝗿𝗻𝗮𝗹 𝘃𝗼𝗶𝗰𝗲𝘀 𝗹𝗶𝗴𝗵𝘁 𝘁𝗵𝗲 𝗳𝗶𝗿𝗲: About 14 months ago e.l.f. brought in an outside search expert, and that put "fire in the belly." 𝗦𝘂𝗽𝗽𝗹𝘆 𝗰𝗵𝗮𝗶𝗻 𝗶𝘀 𝘁𝗵𝗲 𝘀𝗹𝗲𝗲𝗽𝗲𝗿: e.l.f. has invested in Lyric for forecasting and demand planning. Its planners "are actually now engineers," and AP, AR, payroll and inventory teams are building their own AI workflows. 𝗔𝗴𝗲𝗻𝘁 𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝘀𝗵𝗶𝗽 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Ekta's prediction is that Meta wins the agent shopping race. She says brands need to put agent identity in place now, so they know which agent is arriving and which customer it represents. It's the next CDP/CRM-style plumbing project. Huge thanks to Ekta for running over from the main stage, and to our live audience at RetailClub for the great questions. Enjoy the conversation. Timestamps: 01:17 Live from Retail Club: meet Ekta Chopra & co-host Jason Goldberg 02:04 One-year reunion and a new title 02:38 e.l.f. Beauty: a house of brands, 30 straight growth quarters 03:19 Eyes, lips, face… and the Jeopardy! moment 03:43 Ekta's role as Chief Technology & AI Officer 04:02 From the main stage: let it rip or lock it down 05:04 e.l.f.'s three AI pods 06:14 Making agentic growth a full-time job 07:00 Who do you hire for agentic commerce? 08:33 Jason's "you've reached your quota" hiring hack 08:48 Selling AI investment to a public company board 10:06 Measuring readiness when no one has measurement figured out 11:31 "My board member couldn't find our product" 13:06 Synthetic prompts vs. real prompts: Google's Agentic Insights 14:00 Audience Q: build vs. buy 14:52 Where to start: external voices and fire in the belly 16:23 Foundation first: bad data equals bad AI 17:47 Back office, supply chain, and Lyric 19:52 Personal shopping assistants and agents 20:59 Serving a house of brands and working with retail partners 22:55 Audience Q: is governance keeping pace? 24:50 Next 12 months: Meta, agent identity & agent relationship management 26:20 Wrap-up 👉 Connect with Ekta: https://www.linkedin.com/in/ektachopra/ 👉 Learn more about e.l.f. Beauty: https://www.linkedin.com/company/e-l-f-beauty/ 🧠 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

  • #71
    October 6 · 45 min

    ChatGPT Agentic Commerce User Behavior Study Deep Dive with AI Search and SEO Researcher, Erik Van Buskirk

    This week is a research deep dive. ReFiBuy commissioned a behavioral study of how real people shop inside ChatGPT and Google's AI Mode, and Scot sat down with the researcher who ran it to walk through what was found. The full study is published today This is the conversation behind the numbers. Highlights: 𝟴𝟰% 𝗼𝗳 𝗰𝗵𝗼𝗶𝗰𝗲𝘀 𝘀𝘁𝗮𝗿𝘁 𝗼𝗻 𝗮 𝗰𝗮𝗿𝗱: About 84% of product choices in the study came from a product card. That's 83.7%, and Scot rounds it up "if you allow." 𝗣𝗼𝘀𝗶𝘁𝗶𝗼𝗻 𝘁𝗵𝗿𝗲𝗲 𝗯𝗲𝗮𝘁𝘀 𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 𝘁𝘄𝗼: The first card wins by a wide margin, with roughly 43% of picks. But card three outperformed card two in both ChatGPT and AI Mode. Eric's take is that "it's not really a ranking." Scot's guess is curiosity, because card three is only partly visible in the carousel. 𝗣𝗶𝗰𝘁𝘂𝗿𝗲𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝗽𝗮𝗿𝗮𝗴𝗿𝗮𝗽𝗵𝘀: About 75% of shoppers skipped the AI's written answer and went straight to the product cards. They'd come back to the text later, but only as a second step. 𝟵𝟴% 𝗼𝗳 𝗾𝘂𝗲𝗿𝗶𝗲𝘀 𝘁𝗿𝗶𝗴𝗴𝗲𝗿𝗲𝗱 𝗰𝗮𝗿𝗱𝘀: Purchase-intent prompts like "I want to buy X today" brought up product cards almost every time. 𝗧𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗼𝗳𝗳𝗲𝗿 𝘄𝗶𝗻𝘀: When shoppers had to click out to a retailer, they leaned even harder toward the first offer than toward the first product card. The likeliest path is first card, first offer. 𝗔𝗱𝘀 𝘁𝗵𝗮𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗹𝗶𝗸𝗲: About 6 in 10 free-plan users saw ads or sponsored content on a task. 71% rated them at least as useful as Google search ads, and about 35% said an ad influenced what they considered buying. 𝗧𝗵𝗲 𝗿𝗲𝘃𝗶𝗲𝘄𝘀 𝗽𝗮𝗿𝗮𝗱𝗼𝘅: Reviews were the main reason for a pick only 2% of the time. Afterward, about 75% said reviews mattered. Scot's explanation is that nobody reads them, but everyone takes the 4.8 over the 3.2. 𝗧𝗿𝘂𝘀𝘁, 𝘂𝗻𝘁𝗶𝗹 𝗶𝘁 𝗯𝗿𝗲𝗮𝗸𝘀: Eric says the biggest surprise after two years of these studies is "the extent to which people trust, even when they say they don't." A mismatched price or a wrong spec breaks that trust quickly. 𝗧𝗵𝗲 𝗸𝗲𝘆𝘄𝗼𝗿𝗱 𝗷𝗮𝗶𝗹 𝗲𝗿𝗮: Scot compares 20 years of chasing "men's running shoe" on Google with a world where shoppers let the AI choose for them. 𝟰𝟬 𝗽𝗲𝗼𝗽𝗹𝗲, 𝗺𝗼𝗻𝘁𝗵𝘀 𝗼𝗳 𝘄𝗼𝗿𝗸: The study had 40 remote participants doing 30-minute think-aloud sessions on screen recordings. The team logged small behaviors down to seconds spent and scroll percentages. Scot came out of the Amazon era believing the buy box was everything, and this study tells him ChatGPT has one too. Enjoy the conversation. Timestamps: 01:57 Meet Eric Van Buskirk, Clickstream Solutions 02:15 Why ReFiBuy commissioned this study 02:48 Eric's background: SEMrush, Backlinko, Kevin Indig 04:05 Stated preference vs. observed behavior 06:05 How a behavioral study works 08:30 Why 40 people is enough 10:20 Who took part, and who got cut 11:55 The Amazon buy box and agentic commerce optimization 14:25 Finding #1: Pictures beat paragraphs 16:40 Card position: #1 wins, #3 beats #2 18:55 84% of choices come from a product card 20:35 Google SEO vs. AI: the "keyword jail" era 23:40 When do shoppers click out? 25:30 75% skip the text and go straight to the cards 27:25 Offer cards: the first offer dominates 30:20 Ads in ChatGPT: what shoppers really think 35:50 Trust and the reviews paradox 40:25 When bad data breaks trust 41:35 Where to get the study and work with Eric 44:55 Wrap-up 👉 Connect with Eric: https://www.linkedin.com/in/vanbuskirk/ 👉 Learn more about Clickstream Solutions: https://clickstream.cc/ 🧠 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

  • #70
    October 1 · 26 min

    Stripe Global Agentic Commerce Solutions Lead Danny Smith: The Rise of Personal Agents Powered by Link Wallet, WebMCP and More!

    Danny Smith is the Global Agentic Commerce Solutions Lead at Stripe, where he runs technical go-to-market (think pre-sales architect, not engineering) for Stripe’s agentic commerce products. One of his first projects was adding the payments layer to Amazon’s Rufus shopping assistant, and three years ago he got on stage at Stripe Sessions to talk about agentic commerce. We recorded this one live from day two of RetailClub in Huntington Beach. It was a little overcast, which after a day of baking in the sun, we didn’t mind at all. Jason Goldberg joined me as co-host, and we grabbed Danny between meetings. It was his first time at the show. Danny’s a first-timer, both on the pod and at RetailClub. This week’s episode is a product deep dive: Stripe has been shipping agentic commerce products at a pace that makes three months ago feel like ancient history. Danny walks us through what’s live, what launched last Monday, and what’s coming soon, including how the checkout Scot kept seeing inside Meta’s new Muse app actually works. Jason brings the payments-industry history. It goes back to when card-not-present transactions were illegal and runs up to Stripe’s jump from developer darling to incumbent. We also get into the thing that’s still breaking agentic commerce today, and it isn’t the agents. Along the way there’s a hallucinating agent, a leather jacket, and a Cheeky Pint swag request. Hit play. Highlights 𝗟𝗶𝗻𝗸 𝗪𝗮𝗹𝗹𝗲𝘁 𝗳𝗼𝗿 𝗔𝗴𝗲𝗻𝘁𝘀: A skill you teach any agent (Claude, GrokBot, your homebrew Hermes agent) so it can pay “in a guarded and secure manner.” Details at link.com/agents. “𝗬𝗼𝘂𝗿 𝗔𝗣𝗜 𝗰𝗵𝗮𝗻𝗴𝗲𝗱 𝗺𝘆 𝗹𝗶𝗳𝗲”: Developers really do stop Danny at conferences to ask for a photo. Stripe’s founders’ mantra: “Let’s win all startups, and then let’s go win them again.” 𝗢𝗽𝗲𝗻 𝗵𝗲𝗮𝗿𝘁 𝘀𝘂𝗿𝗴𝗲𝗿𝘆: Changing payments at an enterprise is “like open heart surgery.” Jason adds that it’s open heart surgery while you’re running a marathon. 𝗪𝗼𝗿𝗹𝗱’𝘀 𝗳𝗶𝗿𝘀𝘁 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝘁𝗼𝗸𝗲𝗻: Stripe’s shared payment tokens launched with OpenAI, and Etsy was the first merchant. Link wraps them as a single-use virtual card capped at the amount you budgeted, so the merchant doesn’t have to be on Stripe. 𝗦𝘁𝗿𝗶𝗽𝗲 𝗖𝗵𝗲𝗰𝗸𝗼𝘂𝘁 𝗳𝗼𝗿 𝗔𝗴𝗲𝗻𝘁𝘀: Launched last Monday and built on WebMCP, it makes human checkouts machine-readable at the same time. Stripe merchants on hosted checkout or invoices get it with no extra work. 𝗧𝗵𝗲 𝗪𝗲𝗯𝗠𝗖𝗣 𝗻𝘂𝗺𝗯𝗲𝗿𝘀: 42% fewer tokens burned, 38% fewer tool calls, and 39% faster checkout. “Three seconds is annoying to a human, 800 milliseconds is beyond annoying to an agent.” 𝗗𝗼𝘂𝗯𝗹𝗲𝗱 𝘄𝗲𝗯 𝘁𝗿𝗮𝗳𝗳𝗶𝗰: Through the Agentic Commerce Suite (ACS), some merchants have doubled their web traffic in three or four months just by getting their catalogs in front of agents. Instant checkout on Gemini is expected around late October. 𝗗𝗼𝗼𝗿𝗺𝗮𝗻 𝘃𝘀. 𝗯𝗼𝘂𝗻𝗰𝗲𝗿: Most merchants are bouncers that block all bot traffic, and bots were already 53% of internet traffic in 2024. Stripe is working on protocols to tell good bots from bad ones. Stripe is building both sides of the agentic transaction, and Danny is the one out there getting retailers across the line. Enjoy the conversation. Timeline 00:27 Welcome to Retailgentic 01:44 Live from Retail Club, day two 02:05 Meet Danny Smith, Stripe 02:38 From cloud architect to Stripe 03:48 Adding payments to Amazon's Rufus 04:55 Stripe launches agentic commerce 06:08 Jason on payments history & developer-first Stripe 07:40 "Your API changed my life" 08:40 Enterprise payments = open heart surgery 09:05 Meta Muse and the Link checkout 10:25 What is Link Wallet for Agents? 11:00 The weekend Meta scramble 12:20 GrokBot, Instinct & the pipeline 13:55 How Link works at non-Stripe merchants 14:35 The model airplane story 15:40 The world's first agentic token 16:05 Stripe Checkout for Agents & WebMCP 17:10 Two sides of the same coin 17:55 Agentic Commerce Suite & doubled traffic 20:55 WebMCP numbers: 42% fewer tokens 22:10 The leather jacket that got blocked 23:50 Doorman vs. bouncer 25:10 Danny's first Retail Club 26:30 Wrap 👉 Connect with Danny: https://www.linkedin.com/in/danny-r-smith/ 👉 Learn more about Stripe: https://stripe.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

  • #69
    September 17 · 53 min

    Elastic Path CEO Bryan House: The $3M Ecommerce Platform “Re-platform” is Dead, What’s Next?

    This week’s episode is a platform deep dive with one of the longest-tenured companies in e-commerce. Elastic Path has been building commerce software for 26 years and Bryan is now steering the company straight into the agentic era. It’s part founder-journey (craft brewing to CEO is not a typical path), part product deep dive, and part industry-shift conversation about what AI does to the economics of running a commerce platform. Highlights: 𝗙𝗿𝗼𝗺 𝗯𝗿𝗲𝘄𝗲𝗿 𝘁𝗼 𝗖𝗘𝗢: Bryan spent eight years as a professional brewer, with an actual brewing degree, at a brewpub across from Fenway Park. "Everything I learned in my career that really moved the needle for me, I learned as a brewer." 𝟮𝟲 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗲: Elastic Path's claim to fame was building the store for the Vancouver 2010 Winter Olympics, the birth of its self-managed commerce product. 𝗧𝗵𝗲 $𝟱𝟬𝟬𝗞 𝘂𝗽𝗴𝗿𝗮𝗱𝗲, 𝗸𝗶𝗹𝗹𝗲𝗱: Elastic Path built an AI updater so one developer can upgrade a self-managed platform in about two weeks, replacing what used to be a half-million-dollar annual project. 𝟭𝟬,𝟬𝟬𝟬 𝘃𝗮𝗿𝗶𝗮𝘁𝗶𝗼𝗻𝘀: where typical platforms cap out at 250 variations per item, Elastic Path supports 10,000, plus bundles of up to 1,500 items. 𝗦𝗶𝘅 𝘄𝗲𝗲𝗸𝘀 𝗮𝗻𝗱 𝟭𝟬𝟬 𝗴𝗿𝗮𝗻𝗱: Bryan's prediction… AI takes re-platforming from a 6-month-to-2-year, $500K–$3M digital transformation down to a setup fee. "That's the place we're gonna see the biggest impact of AI in commerce." 𝗧𝗵𝗲 𝟴𝟬-𝗽𝗮𝗴𝗲 𝗣𝗗𝗙: in a world of AI discovery, every product needs the equivalent of an 80-page PDF of data to train the LLM on when to recommend it. (Scot's line, which Bryan says he "steals with credit" as often as he can.) 𝗣𝗿𝗼𝗼𝗳 𝗶𝗻 𝗻𝘂𝗺𝗯𝗲𝗿𝘀: a UK custom greeting-card seller saw conversion jump 40% almost immediately after adopting Elastic Path's checkout 𝗡𝗼𝗯𝗼𝗱𝘆 𝘄𝗮𝗻𝘁𝘀 𝗰𝗵𝗮𝘁𝗯𝗼𝘁𝘀: customers are asking about UCP and ACP, discovery, and the long tail, not chatbots. 𝗪𝗵𝗲𝗿𝗲 𝘁𝗵𝗲 𝗿𝗼𝗮𝗱𝘀 𝗮𝗿𝗲 𝘄𝗲𝗹𝗹-𝗽𝗮𝘃𝗲𝗱: Bryan's framework for where AI lands first… well-understood patterns like checkout, front ends, and reorders, not judgment-heavy edge cases. Bryan is a product guy after our own heart, and this one gets satisfyingly deep, from CPQ to protocols to the future of re-platforming. Enjoy the conversation. Timestamps: 03:20 Welcome Bryan + podcasting since 2009 04:05 Internet Retailer booth memories 04:55 From craft brewing to software 07:35 The Acquia and Drupal years 08:20 Moltin, Neural Magic, joining Elastic Path 11:05 Elastic Path history: the Olympics store 13:20 Two products: SaaS + self-managed 13:45 The AI updater: killing the $500K upgrade 14:50 80 people, profitable, constraints breed innovation 17:00 Customer base and the B2B focus 19:15 CPQ, PXM, and 10,000 variations 22:45 Serena & Lily case study 24:10 The MACH Alliance backstory (spicy) 29:55 Vibe coding the front end + Shopify as fintech 33:20 AI re-platforming: six weeks and $100K 39:00 The ReFiBuy partnership + the 80-page PDF 40:55 AI roadmap: workflows, promotions, analytics 43:20 B2B agentic commerce and EDI 47:10 UCP, ACP, and the long tail 49:05 Predictions: where the roads are well-paved 51:20 What's next for Elastic Path 👉 Connect with Bryan: https://www.linkedin.com/in/bhouse/ 👉 Learn more about Elastic Path: https://www.elasticpath.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

  • #68
    September 10 · 59 min

    Exploring the Intersection of Vibe Coding and Agentic Commerce with Vercel’s Head of Retail Jaime Sorgente

    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 Sorgente 06:08 Jaime's path to Vercel: ChatGPT and 10-Ks 12:29 Utilities vs. builders 15:00 What is Vercel? The cocktail-party pitch 17:10 Why retail as a vertical 21:20 The Helly Hansen story 24:05 Vercel's other verticals: digital natives and marketing 26:45 Enabler, not competitor: where Vercel fits vs. Shopify & Salesforce 29:35 Beyond the storefront: clienteling and staff apps 30:45 Agents everywhere: Crocs, Amazon image annotation 36:05 v0 + Shopify: customize your storefront in English 37:45 Next.js 16: built for the agent customer 39:20 Custom storefront timelines, halved 40:35 Does owning your storefront de-risk replatforming? 42:20 The 100-millisecond study 44:30 The compounding effect: 4X feature velocity 46:45 Next.js explained: the stage manager analogy 52:20 Framework-defined infrastructure 54:30 Vercel vs. Lovable, Replit, and Base44 58:15 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

  • #67
    September 3 · 44 min

    Behavior Beats Identity: FERMÀT Co-Founder & CEO Rishabh Jain

    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, PhD 06:33 Building three businesses at LiveRamp 07:56 Founding story: Apple ATT and iOS 14.5 10:33 Detect, recommend, generate 12:27 Where FERMÀT sits in the stack 13:57 Many-to-one personalization 15:22 The Bloomreach question 19:00 Does current behavior beat past behavior? 21:18 The data: a 20% conversion lift 22:34 The agentic commerce connection 23:44 The real estate agent analogy 25:41 Reading intent from incognito traffic 26:28 Into the weeds: mining a Meta ad for context 30:37 Side quest: the SEO cloaking myth 33:47 Writing for agents, bots, and humans 34:49 On-site shopper agents 39:40 Company building: know your why 42:38 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

  • #66
    August 27 · 54 min

    Caila Schwartz, Head of Agentic Commerce Salesforce is Back! Holiday 2026, State of Ecommerce, Plus... “The Caila Five”

    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 title 07:20 Caila's role and 12 years at Salesforce 08:30 Two reports: State of Commerce + Holiday predictions 09:30 State of Commerce methodology 12:50 What's new in this edition 14:45 The agentic discovery shift: 50%, 200%, 15% 17:25 Who's losing share in discovery 19:00 Faster than mobile or social ever moved 22:20 The measurability problem 25:20 Conversion: 2–3x better than average 27:10 Why shoppers lean on agents, by income 29:30 Trust: 74% and the 80% confidence stat 32:00 The branded-agent race 34:30 The #1 barrier: data unification 40:20 Caila Five #1: 20% non-human traffic 42:30 #2: One in three sites get a branded agent 43:15 #3: Social commerce grows 9x 44:25 #4: The store's new role 37% hybrid sales 46:20 #5: Free shipping and the K-shaped economy 47:30 Decoupled transactions deep dive 53:10 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

  • #65
    August 20 · 45 min

    700 Stores, 10 Million Shoppers, $3M Raised: Cooklist CEO & Co-Founder Daniel Vitiello

    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 Cooklist 03:10 Grocery, CPG, and retailer-hosted agents: the pod's favorite topics 04:46 The $1 check and the handwritten letter for loyalty data 05:46 Why 2017 was the moment 06:12 Inside the Cooklist app: home inventory and the AI chef 07:35 AI as the thread: Kurzweil, GPT-2, and the AI Chefs TikTok series 09:37 B2C to B2B, and the synergies of running both 12:05 The cat food problem 13:34 The core identity system: hummus, three ways 15:58 Search and select vs. review and accept 16:23 The spark for B2B: Target, Techstars, and saying no 18:45 Recipe commerce and meal-pairing merchandising 20:19 Funding: RevTech, Mercury Fund, and profitability 21:56 Freemium, pro, and advertising in the app 22:48 700 stores, 10 million shoppers 24:28 The flagship deployment: live in 41 days 25:56 Ontology, context engineering, and interviewing the retailer 27:03 Non-determinism and the eval system 29:06 Entry points: sparkles, suggested prompts, and PDP workflows 31:01 How the catalog and inventory get in 33:41 Procedures: the weekly flyer and the fish rule 35:55 Cost, speed, and the token-efficient stream 37:38 Model agnostic: scoring Opus against Sonnet 38:15 Instacart, Storefront Pro, and winning head-to-head 39:47 Retail media and Criteo 40:22 Agentic search and the "taco night" problem 42:02 Agentic merchandising: 1,000 Fourth of July bundles 42:55 Proactive carts, and the 50% who finish in the store 43:43 Smart fridges and forecasting demand 44:44 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

  • #64
    August 13 · 53 min

    Physical AI Hits the Sales Floor: FrontlineIQ CEO & Co-Founder Ben Rodier

    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 Retailgentic 02:01 Scot's intro: a fun diversion into physical AI 03:47 Meet Ben Rodier, FrontlineIQ 04:33 From a TJ Maxx floor to third-time founder 06:07 Sales guy, not a technical founder 06:53 Corporate to startup: the TV advertising leap 07:37 Inventing retail media on Walmart's site in 2009 10:31 Salesfloor: the original idea 13:42 Bootstrapping, PE at the pandemic peak, the Tulip merger 17:19 The genesis of FrontlineIQ: Up Labs & Ashley 20:10 What "physical AI" actually means 21:24 Launching Jan 1, 2025 & hiring AI-native talent 24:41 30 customers in under 18 months 27:36 The oversubscribed seed round 28:46 How it works, part 1: data & trust 30:58 Part 2: AI role play in voice mode 32:43 Part 3: privacy-compliant listening 36:00 The Rule of 30 & the "up" system 37:33 Coach the coach, God view & the control center 39:48 ROI: the crocodile chart & turnover 45:14 The future: cameras, glasses & Plaud pins 49:23 Robots on the floor? The McDonald's test 51:44 Merchandising insight from what reps hear 52:36 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

  • #63
    August 6 · 54 min

    Baird Managing Director of Internet Research Colin Sebastian: What Wall St. Thinks About Agentic Commerce

    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 Sebastian 5:04 20 years of history & the Wall Street event 7:00 From bartender to Baird 7:56 Baird's coverage universe & "TMT" 9:29 The GTA VI mega-launch call 11:12 Buy side vs. sell side, explained 13:52 The SPEED framework & top picks 16:16 What is agentic commerce? 20:05 Sizing it: trillions & consumer surveys 22:42 Meta's social-graph advantage 25:05 Amazon's walled garden & the one-way door 29:40 Google, UCP & why models get commoditized 32:36 eBay's used-goods moat 39:44 Retail media networks at risk? 44:33 OpenAI, ads & the closed-loop logic 48:36 Payments: PayPal, stablecoins & who wins 51:57 Protocols: UCP vs. ACP 52:23 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

  • #62
    July 30 · 53 min

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

    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

  • #61
    July 23 · 42 min

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

    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

  • #60
    July 16 · 41 min

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

    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

  • #59
    July 9 · 49 min

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

    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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