Every company that sells online wants frictionless commerce. But what does that actually look like in practice? Most businesses have already figured out the #1 rule of cutting out friction in their physical supply chain: all of its parts need to talk to each other, and somebody needs to own it. ㅤ Far fewer have figured that out for their digital supply chains. And somewhere in that pile of disconnected projects, data and commerce stopped talking. The most expensive relationship in your business needs work. This is their standing appointment. This is Data vs. Commerce. ㅤ Each week, hosts Matt Johnson and Floyd Blaikie sit down with the people who own the data, run the platforms, and pay the price when those two stop playing nice. ㅤ If you're responsible for any part of how products get from a database to a doorstep, this is your show. New episodes drop weekly. Subscribe on Apple, Spotify, or wherever you listen.
Data vs. Commerce
Claim This Podcastby Pivotree
Podcast Overview
Every company that sells online wants frictionless commerce. But what does that actually look like in practice? Most businesses have already figured out the #1 rule of cutting out friction in their physical supply chain: all of its parts need to talk to each other, and somebody needs to own it. ㅤ Far fewer have figured that out for their digital supply chains. And somewhere in that pile of disconnected projects, data and commerce stopped talking. The most expensive relationship in your business needs work. This is their standing appointment. This is Data vs. Commerce. ㅤ Each week, hosts Matt Johnson and Floyd Blaikie sit down with the people who own the data, run the platforms, and pay the price when those two stop playing nice. ㅤ If you're responsible for any part of how products get from a database to a doorstep, this is your show. New episodes drop weekly. Subscribe on Apple, Spotify, or wherever you listen.
Language
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Publishing Since
5/20/2026
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Recent Episodes
July 1, 2026
Using AI in field sales without gutting the sales team | Lauren McCullough, Co-Founder & CEO, Tromml | Ep. 6
<p>Field sales is the part of commerce that data never quite reaches. The rep has the relationship, the context, and forty years of counter knowledge, and most of it dies in a notebook nobody reads. This episode is about closing that gap. <a href="https://www.linkedin.com/in/matt-d-johnson/" rel="noopener noreferrer" target="_blank">Matt Johnson</a> calls in from the AI for Distributors event in Chicago while <a href="https://www.linkedin.com/in/floyd-blaikie/" rel="noopener noreferrer" target="_blank">Floyd Blaikie</a> hosts two guests from <a href="https://www.pivotree.com" rel="noopener noreferrer" target="_blank">Pivotree</a>'s automotive world: <a href="https://www.linkedin.com/in/laurenrmccullough/" rel="noopener noreferrer" target="_blank">Lauren McCullough</a>, co-founder and CEO of Tromml, and Pivotree's <a href="https://www.linkedin.com/in/datacrewchief/" rel="noopener noreferrer" target="_blank">Sam Russo</a>. Lauren takes the side most software founders won't: the human relationship is the asset, and AI exists to make it sharper, not replace it. The friction that comes out of it is where you point AI in a high-trust business, and where you keep it out.</p><p>ㅤ</p><p><strong>👤 Guest Bio</strong></p><p><a href="https://www.linkedin.com/in/laurenrmccullough/" rel="noopener noreferrer" target="_blank">Lauren McCullough</a> is co-founder and CEO of Tromml, a vertically focused software company for the automotive aftermarket and industrial distribution. Tromml started on the analytics side, giving distributors visibility into what products were actually making money, and now builds field-sales tooling that captures rep conversations and turns them into next best actions. Lauren argues for keeping relationship-driven selling human while using data and AI to support it.</p><p>ㅤ</p><p><strong>📌 What We Cover</strong></p><ul><li>Why reps in distribution aren't just selling parts, they're selling relationships and trust, and why that changes how AI fits</li><li>The difference between a system of record (put information in, pull a report out) and a system of action (surfaces the next best action and gets smarter over time)</li><li>A rep's actual Monday workflow: prioritized accounts, optimized routes, a human-digestible briefing before the visit, and voice-note capture after</li><li>The field signal that never reaches the boardroom, like a shipping delay or a launch that isn't landing, because nobody reports bad news up the chain</li><li>Hiring implications: when the data lives in the system, you hire for emotional intelligence instead of category memory</li><li>Where to point AI in a high-trust industry, and Lauren's blunt take on automating the customer relationship away</li></ul><br/><p>ㅤ</p><p><strong>🔗 Resources Mentioned</strong></p><ul><li>Tromml (Lauren's company; mobile conversation-capture app for field reps)</li><li><a href="https://www.pivotree.com" rel="noopener noreferrer" target="_blank">Pivotree</a></li><li>AI for Distributors event, Chicago (Matt's reference; the event's formal name is Applied AI for Distributors, run by Distribution Strategy Group)</li><li>Claude (AI note-taking tool referenced by Sam)</li><li>Salesforce (referenced as a CRM)</li><li>Genuine Parts Company (referenced by Sam; see flag below)</li></ul><br/>
June 24, 2026
Taking the order is easy. Keeping the promise is where it breaks | Keith Gorney, OMS Practice Director, Pivotree | Ep. 5
<p>The catalog looks right, the website takes the order, and then the promise falls apart somewhere between the click and the dock. That gap between what a screen shows and what actually ships is where this episode lives. <a href="https://www.linkedin.com/in/matt-d-johnson/" rel="noopener noreferrer" target="_blank">Matt Johnson</a> and <a href="https://www.linkedin.com/in/floyd-blaikie/" rel="noopener noreferrer" target="_blank">Floyd Blaikie</a> sit down with <a href="https://www.linkedin.com/in/keith-gorney/" rel="noopener noreferrer" target="_blank">Keith Gorney</a>, OMS Practice Director at <a href="https://www.pivotree.com" rel="noopener noreferrer" target="_blank">Pivotree</a>, who took the commerce side of the table.</p><p>ㅤ</p><p>His argument: taking an order is the easy part, and almost none of your hard problems live there. The friction starts on the execution side, when the promise date has to hold across phone, web, and field sales running on the same inventory. Keith makes the case for order management as the orchestration layer that sits on top of the ERP instead of working around it.</p><p>ㅤ</p><p><strong>👤 Guest Bio</strong></p><p><a href="https://www.linkedin.com/in/keith-gorney/" rel="noopener noreferrer" target="_blank">Keith Gorney</a> has spent 25 years in direct-to-consumer, B2B, and order fulfillment. He started at Best Buy overseeing their enterprise order management platform, carried that into consulting roles touching URBN brands including Urban Outfitters, Free People, and Anthropologie, and now leads order management work at <a href="https://www.pivotree.com" rel="noopener noreferrer" target="_blank">Pivotree</a>. On this episode, he took the commerce side, arguing that the order is where commerce becomes real.</p><p>ㅤ</p><p><strong>📌 What We Cover</strong></p><ul><li>Why taking an order is easy, and the execution side is where the friction really starts to manifest</li><li>The "real-time version of the truth" problem when phone, device, salespeople, and manual orders all race the same inventory</li><li>What happens to the customer service rep stuck inside a legacy ERP, jumping between systems, emails, and phone calls</li><li>Why canceling and recreating a six-figure order to change one line is effectively unacceptable</li><li>How an OMS reads an order as pieces and parts, with line statuses and quantities, instead of one all-or-nothing object</li><li>Selling a job three months out without freezing 1,000 units of inventory for a quarter</li><li>Why this is a component-by-component migration, not a big-bang rip-out, with implementations Keith has seen go live in three months</li></ul><br/><p>ㅤ</p><p><strong>🔗 Resources Mentioned</strong></p><ul><li><a href="https://www.pivotree.com" rel="noopener noreferrer" target="_blank">Pivotree</a></li><li>Best Buy, Urban Outfitters, Free People, Anthropologie (Keith's career background)</li><li>ERP, OMS, global inventory visibility, BOPUS / curbside, DoorDash (referenced in conversation)</li></ul><br/>
June 17, 2026
The robots.txt setting that hides your catalog from ChatGPT | Dan Ornstein, Retail Industry Leader, Pivotree | Ep. 4
<p>A customer asks ChatGPT how to fix his style, gets sent to three stores, and nobody on the retail side can explain why those three and not the other thirty. That gap is where this episode sits. <a href="https://www.linkedin.com/in/matt-d-johnson/" rel="noopener noreferrer" target="_blank">Matt Johnson</a> and <a href="https://www.linkedin.com/in/floyd-blaikie/" rel="noopener noreferrer" target="_blank">Floyd Blaikie</a> talk with <a href="https://www.linkedin.com/in/daniel-ornstein-22167b7/" rel="noopener noreferrer" target="_blank">Dan Ornstein</a>, Retail Industry Leader at <a href="https://www.pivotree.com" rel="noopener noreferrer" target="_blank">Pivotree</a>, about how large language models decide which retailers to recommend and what that means for the people who own product data.</p><p>ㅤ</p><p>Dan took the data side, and the friction surfaced fast. The marketers want brand, lifestyle photography, and emotional copy to carry the search. The machine starts with UPC codes, GTINs, inventory, and shipping policy before it cares about any of that. The conversation covers the robots.txt settings that quietly block AI crawlers, the attribution problem when a shopper leaves ChatGPT and goes straight to a store, and why content marketing still earns its place once the data foundation is solid.</p><p>ㅤ</p><p><strong>👤 Guest Bio</strong></p><p><a href="https://www.linkedin.com/in/daniel-ornstein-22167b7/" rel="noopener noreferrer" target="_blank">Dan Ornstein</a> is Pivotree's Retail Industry Leader, focused on helping retailers grow revenue through unified commerce, customer experience, product data, and practical AI. Before Pivotree he was a Partner at KPMG Canada and a Director at Publicis Sapient, working across e-commerce, omnichannel, and loyalty. On this episode he took the data side, arguing that product data completeness, not brand copy, is what gets a retailer surfaced by AI shopping agents in the first place.</p><p>ㅤ</p><p><strong>📌 What We Cover</strong></p><ul><li>Why retailers suddenly see traffic from ChatGPT, Perplexity, and Gemini without doing anything to earn it</li><li>The order an LLM works in: product data first, then price and availability, then third-party trust signals from sites like Vogue, GQ, or Reddit</li><li>The robots.txt problem, where fraud and denial-of-service settings block the AI crawlers before they ever reach your catalog</li><li>How subjective attributes like "soft" or "puffy and warm" have to become data the model can read, like down fill rate and temperature rating</li><li>The attribution gap when a shopper exits ChatGPT and goes straight to the store, and why LLM referrals still convert at a higher rate</li><li>Which categories suit agentic shopping now (grocery, hardware) versus where brand still drives the decision (fashion, home furnishings)</li><li>What an e-commerce or merchandising leader should check tomorrow to confirm they show up at all</li></ul><br/><p>ㅤ</p><p><strong>🔗 Resources Mentioned</strong></p><ul><li>ChatGPT, Perplexity, Gemini (AI assistants surfacing retailer recommendations)</li><li><a href="https://www.shopify.com" rel="noopener noreferrer" target="_blank">Shopify</a> (embedded LLM referral analytics)</li><li>Vogue, GQ, Reddit (third-party reference sites the models check)</li><li>Amazon (marketplace-seller comparison)</li><li>TikTok, YouTube, Instagram (social channels referenced)</li></ul><br/>
7 total episodes available
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