Retailgentic | Consumer Behavior & Retail Trend

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

Retailgentic | Consumer Behavior & Retail Trend

Show Notes

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: retail

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Oct 22, 2026

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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

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