eCommerce Podcast

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If you’re looking for great tips and insights into how to run your online store, look no further than the Ecommerce Podcast: a show dedicated to helping you deliver eCommerce WOW. New episodes are released every Thursday, and each episode features interviews with some of the biggest names in the eCommerce world. Whether you’re just starting out in eCommerce or you’re a seasoned veteran, you’re sure to learn something new from each episode. So what are you waiting for? Subscribe to the Ecommerce Podcast today!

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October 29, 202647 min

Stop Using Generic AI In Your Ecommerce Business

ChatGPT once invented a 20% advertising budget for a founder who hadn't made a single sale yet. Marissa Rodriguez explains why that happens, and what she does differently. Marissa Rodriguez has spent twenty years building and scaling direct-to-consumer brands, first as a fractional CMO and COO, now as the founder of Through Experience, a mentorship platform for ecommerce founders. She talks to Matt Edmundson about the risk of handing serious decisions to generic, industry-agnostic AI tools, and why she thinks the real opportunity lies in training AI on the judgement of people who have actually done the job. She shares how her own email marketing training module grew from six videos to fifty once she tried to capture everything she actually knows, and the moment a founder's P&L came back with a 20% advertising budget that ChatGPT had invented from nothing. Along the way, they cover decision fatigue, shiny object syndrome, and where Marissa tells founders to focus first when they're starting out with AI in their business. 08:22 - Why Generic AI Puts First-Time Founders at Risk 15:40 - Training AI With Her Own Frameworks 29:33 - Decision Fatigue and Shiny Object Syndrome 40:06 - ChatGPT Invented a 20% Ad Budget Why Generic AI Puts First-Time Founders at Risk (08:22) Matt asks Marissa the question she gets most often, what's going wrong for people right now with AI. Her answer isn't about a specific tool or tactic. It's about who's giving the advice. Most ecommerce founders are first-time founders with no deep domain expertise to fall back on, and a generic AI tool doesn't know what it doesn't know. It won't ask the qualifying questions a human expert would, and it will hand over confident answers regardless. Marissa has watched this happen with financial models and P&Ls built in ChatGPT, where the tool makes assumptions about costs and budgets without ever checking whether they're right for that particular business. "Having a generic AI working with you, I think you're gonna end up in a bad place." Marissa Rodriguez Her point isn't that AI is the problem. It's that AI without operator judgement built into it is the problem, and that gap is exactly what she thinks founders need to close. Training AI With Her Own Frameworks (15:40) Marissa began mapping her own expertise into an AI the same way Matt describes doing with SAM, Aurion's internal AI layer built on their own playbooks. She assumed it would be straightforward. She already had a structured curriculum from years of building courses and digital products. It wasn't straightforward. One email marketing module alone, originally six videos and forty five minutes, grew into fifty videos once she tried to capture every exception, every variation by AOV (average order value) or customer path to purchase, every moment she'd normally break her own rule because the context called for it. "It went from six videos to fifty videos, because there was so much more than I anticipated that I actually had to sit down and give it the context for understanding." Marissa Rodriguez That's the gap most generic AI tools skip. The judgement isn't a setting you switch on, it's decades of decisions that nobody writes down until someone asks them to. Decision Fatigue and Shiny Object Syndrome (29:33) Founders are surrounded by noise, Marissa says, a constant stream of other people's wins and warnings on LinkedIn and Instagram, most of it stripped of the context that would tell you whether it actually applies to your business. Her advice is to narrow the focus deliberately rather than chase every new tactic. "There's only three actions a person can take on the internet that matter to an ecommerce business. Click, subscribe, and buy." Marissa Rodriguez Everything else, in her view, is in service of those three actions. Paid ads and content drive the click, email marketing earns the subscribe, and the operations behind the scenes, inventory, reporting, unit economics, make the buy possible. She'd rather be great at a handful of things that compound predictably than good at everything and consistent at nothing. ChatGPT Invented a 20% Ad Budget (40:06) A founder came to Marissa with a P&L that ChatGPT had built for them. It looked complete. It wasn't. The advertising line assumed 20% of revenue, with nothing behind the number, for a business that was pre-revenue and hadn't launched yet. "ChatGPT just made up the paid advertising line. ChatGPT just decided like 20% is what you need for paid advertising." Marissa Rodriguez Marissa's challenge back to the founder was simple, on what basis. A properly trained financial model, in her experience, knows which questions it can answer from publicly available information and which ones it has to ask the founder directly, the weight of a product before it estimates shipping, the likely return rate for that specific category. Generic AI skips the asking and goes straight to the guessing. About Marissa Rodriguez Marissa Rodriguez is the Founder & CEO of Through Experience, a mentorship platform for ecommerce founders. She has spent 20 years in DTC and ecommerce, including close to a decade as a fractional CMO and COO scaling brands across fashion, wellness, CPG and lifestyle. She now builds AI trained on her own operator frameworks for founders and small teams. Website: throughexperience.com LinkedIn: Marissa Rodriguez Instagram: Marissa_ThroughExperience Episode link: https://www.ecommerce-podcast.com/ai-for-small-business-why-generic-ai-fails-you

October 22, 202649 min

How to Actually Use AI in Your eCommerce Business

AI will not run your ecommerce store on autopilot. Cyril Golub joins Matt Edmundson to explain how to actually put it to work, as a supervised assistant you give a clear goal, not a magician you hand the keys to. It is a practical, often funny conversation about where AI genuinely helps online sellers and where it just burns tokens. Summary Cyril Golub has been building ecommerce software since 2003, so he watches the AI wave with the eye of someone who has seen a few hype cycles come and go. In this episode he and Matt dig into what AI changes for online sellers and what it quietly leaves exactly the same. Cyril's thesis is that "ecommerce" is turning into "AI commerce", where by early 2027 both buyers and sellers have their own agents, and "how do I start selling online?" becomes a single sentence typed to an agent. Along the way they get practical. Most AI startups are building for buyers, leaving the seller side wide open. Marketplaces own your customer data, and on Amazon a buyer is one click from a competitor. Matching the right model to the job matters more than reaching for the biggest one every time. And competitor monitoring at scale lets you act alongside rivals rather than react to them. Key points covered in this episode: Who's building AI for sellers, not just buyers (10:25) Who really owns your customer data (17:41) Which AI model you should actually use (26:55) Using AI to monitor your competitors at scale (31:43) Who's Building AI for Sellers, Not Just Buyers (10:25) Cyril points out something surprising about where the money is going. Roughly three quarters of AI-native ecommerce startups are building buy-side tools, helping shoppers find bargains and streamline their buying. The seller side, by contrast, is far less crowded, which he finds odd given how much easier it usually is to sell to businesses than to chase millions of individual consumers. That gap raises a harder question for any small founder building in the space. If a tool genuinely helps sellers increase their margin, who gets to build it? The giant sitting on terabytes of data, a mid-size player, or a small third party with neither the data nor the audience? "The main question that early-stage investors are asking to startup founders, what if, then put the name of the huge company. What if Amazon will develop it on their own, directly in-house, and then roll out to all of their hundreds of thousands of customers?" — Cyril Golub Matt's hope is that the answer turns out to be the small operator in the garage rather than another platform giant, which is exactly the kind of story this show roots for. Who Really Owns Your Customer Data (17:41) The storefront, Cyril argues, is a habit inherited from the offline world, the digital echo of goods on a shelf. But not every visitor wants to browse a shelf. Some arrive with a clear intention and want to reach checkout in two or three clicks. Others arrive to explore, unsure what they want yet. The problem is that most sellers know almost nothing about which is which, often only the channel or the ad that brought someone in, and rarely anything that ties through to the actual purchase. That blindness is the real cost of not owning your data, and on a marketplace it gets worse. "When we are talking about Amazon sales, your buyer is just one click away from buying from your competitor. That's a huge problem." — Cyril Golub His practical steer is to pull as much data as you can out of whatever platform you sell on, through the richest API access available, so you can connect your own agent and ask it for actionable insight rather than just advice. Which AI Model You Should Actually Use (26:55) This is where the conversation gets genuinely useful for anyone watching their AI bill. Cyril's view is that you should match the model to the job, the same way you would match a hire to a task. "It might be like if you are hiring a PhD to just calculate simple numbers in your Microsoft Excel sheet. You must choose the exact type of model that is quite enough, but not more, for your particular goal." — Cyril Golub He gives a concrete number. Connecting Claude to an Amazon store through the SP-API to process an inventory of around 2,000 SKUs costs roughly 4 million tokens, mostly input. That is far too simple a job to hand a frontier model. His answer is to think in layers: A deterministic layer that prepares the data quickly. If a task is fully deterministic, it is just software, no AI needed. A cheap supervisor model to decide which parts of the data actually matter for the goal at hand. A frontier model reserved only for the work that genuinely needs judgement. Matt notes he is seeing this layered thinking take hold more widely as people wake up to what AI actually costs. Cyril adds a warning about context too, in that the right answer moves over time. What was true a week ago, around a season, a sale or a competitor's campaign, can be wrong the next week. Using AI to Monitor Your Competitors at Scale (31:43) Cyril's most vivid example is competitor monitoring. Imagine your store suddenly does half the usual sales on running shoes. Nothing has changed in your store or your traffic, so as a human, or using older tools, you have no idea why. Now imagine an AI tool watching not two or five rivals but a hundred of them, with insider accounts inside each. It can spot a competitor's loyalty campaign quickly, map it to your own inventory, and launch a comparable campaign at the same time, sometimes before the rival's first email even reaches most of its audience. "It's a real game changer because you are not reacting. You are acting at the same time on the same issue, same field as your competitors are doing right now." — Cyril Golub Matt's follow-up is the honest one every founder should sit up for. If it has never been easier to monitor your competitors, it has also never been easier for them to monitor you. The Closing Advice for an Overwhelmed Founder Matt ends by asking what a roughly million-pound ecommerce brand, feeling swamped by it all, should do. Cyril's answer is the line the whole episode hangs on. "Think about AI like your assistant that must be supervised and must be clearly set with the goal and the expected outcome. Don't think that it is kind of a magician or wizard that will do everything without you and without your supervision." — Cyril Golub Today's Guest Cyril Golub is the founder of Jinnify (jinnify.ai) and has been building ecommerce software since 2003. He spent years in early-stage venture as an angel investor and brings a builder's eye to where AI genuinely helps online sellers. LinkedIn: Cyril Golub Jinnify: jinnify.ai Cyril likes to connect with like-minded people on LinkedIn. Reach out and say hello, especially about all things AI. Keep Listening Find the full archive of episodes, the free monthly eCommerce Cohort meetups, and everything else at ecommercepodcast.net . If you enjoyed this one, make sure you like and subscribe in your favourite podcast app or on YouTube so you never miss a show. Episode link: https://www.ecommerce-podcast.com/ai-in-ecommerce-what-actually-works

October 14, 202649 min

Are You Running Ads to Products People Can't Buy?

Ecommerce Merchandising, and How to Stop Advertising Sold-Out Stock Most stores are quietly leaking sales, and ad spend, to products customers literally cannot buy. In this episode Matt Edmundson talks merchandising with Leon Bart-Williams, co-founder and CEO of Akikumo, a merchandising-intelligence app for Shopify brands. Before Akikumo, Leon built the first shoppable-TV commerce experience at NBCUniversal and helped hundreds of brands scale on Amazon, so this is a proper operator conversation about the part of ecommerce almost nobody owns. Summary Merchandising is the most overlooked driver of conversion, and it is far more than shop-window mannequins. Leon defines it as putting the right product in the right place at the right time in front of the right audience, with the right inventory to satisfy demand. It is the process of turning inventory into sales. The conversation works through where stores go wrong. Out-of-stock products sitting in the prime slots of a collection. Ads pointing at sold-out or partially sold-out products. A failure to understand which variant is actually driving the sales of a given product. From there Leon and Matt move into curation over volume, why more choice tends to sell less, A/B testing collections rather than just the checkout, and inventory planning that starts with sales velocity at the variant level. Practical throughout, with real brands named and a ten-minute daily habit any store can start tonight. Merchandising Is the Job Nobody in Your Store Is Doing Merchandising usually gets wrapped in grandiose language. Leon's definition is plain. "Merchandising is really the process of taking your inventory and converting it to sales." — Leon Bart-Williams The point most brands miss is that merchandising applies to the ecommerce storefront, not just the physical store. The first positions in a collection do the same job as the front window of a shop. "Think of the first 10 slots of your website as the moment people walk through the door of a physical store and see a mannequin with nothing on." — Leon Bart-Williams Out-of-stock products in the first ten positions of bestsellers or new arrivals are the fastest, most common leak. The problem starts biting at around 400 to 500 SKUs, not tens of thousands, especially in apparel where size, colour and style variants multiply. It is almost always human error and broken team communication, not strategy. As Leon's co-founder Jared (previously a principal engineer at Figs and Chewy) puts it, most of ecommerce is just fixing human errors and self-inflicted wounds. Are You Running Ads to Products People Can't Buy? A costly and common mistake is ad spend hitting stock that is already gone. Leon describes checking a friend's brand, Johnny O, in Meta's Ad Library and spotting a top-selling product with three quarters of its variants sold out, sitting in the top ad slot. One email to their ads team fixed it. The subtler version is the partially sold-out product, and this is where the 80/20 rule matters at the variant level. "The dress in blue, size 2, is driving 80% of the sales of this specific product. You need to know that, and you need to at least be fully stocked in that product." — Leon Bart-Williams Roughly 20% of a product's variants drive roughly 80% of its sales. If that core variant is out, the listing can look in stock while the ad is effectively pointing at a sold-out product. When a product is gone but the creative still works, point the ad to the collection, or to the category, rather than a dead page. When in doubt, point to the collection. Why More Products Means Fewer Sales Leon and Matt agree that curation beats volume, and the science backs it up. Matt recounts the jam experiment, where a display of six jams sold well and a display of thirty-six exotic jams saw sales fall. More choice created paralysis, not more buying. "More does not mean more sales." — Leon Bart-Williams "People want fewer options. People want to be told what to do." — Leon Bart-Williams Keep collections tight. Around 50 SKUs or fewer per collection is manageable and tends to convert better. Curation is part art, part science. The science is how many products. The art is telling a story around a hero product, the dress plus the handbag plus the shoes, and writing content around it. Brands Leon rates for this include Cara Cara NYC, and his customer Brooke at Simply Moab and Desert Soul in Moab, Utah, who matches her ecommerce experience to her physical stores. Endless scroll with no curation is the opposite of this, and it kills conversion. Test Everything, and Plan Inventory at the Variant Level Testing should not stop at the checkout. Leon argues for A/B testing collections, layouts, price points and new products, each with a hypothesis and a finite goal. "You can't optimise your way to success all the time." — Leon Bart-Williams The counter-example is Vince at the Texas golf brand Bogey Brothers, who built sale pages by hand from memory, guessed the pricing, launched, and never tested how they performed. Inventory planning is merchandising too. Understanding sales velocity at the variant level before cutting a purchase order stops a brand restocking the wrong sizes and colours that then sit on shelves. Leon's customer Brooke spends 20 to 30 hours a week with pencil and paper walking her stores to work out what to reorder. Matt frames the stakes plainly. "Stock on the shelves is cash not doing anything." — Matt Edmundson Matt's own examples make the point across business models. His beauty business carried seven days of stock because the supplier held the risk, while his supplement business runs 18-month lead times, so the data has to be dialled in because a single mistake locks up cash for a year and a half. Leon's rule number one sits underneath all of it. "Don't piss off the customer." — Leon Bart-Williams Where to Start This Week Leon's advice for anyone starting out, limited by time, space and money, needs no tool at all. Go into your top collections tonight and make sure they are fully stocked. Keep collections tight and curated. Archive products that are not selling. Push out-of-stock items to the bottom of the page. Do it every single day. It takes intentionality and diligence, not software. Today's Guest Leon Bart-Williams is co-founder and CEO of Akikumo, a merchandising-intelligence app for Shopify brands that handles collection sorting, collections intelligence, variant-level analytics and inventory planning, giving small, lean teams the power of an entire merchandising team. Before Akikumo he worked in business development at Comcast and NBCUniversal, was recruited by Amazon in 2014 to help brands scale on the marketplace, and returned to NBCUniversal on the founding team that built its shoppable-TV and livestream-shopping commerce product. Akikumo offers a 30-day free trial. Website, akikumo.com Shopify App Store, apps.shopify.com/akikumo LinkedIn, in/leonbartwilliams Email, leon@akikumo.com About the eCommerce Podcast The eCommerce Podcast is hosted by Matt Edmundson, who has run his own online businesses since 2002 and still ships products all over the world. Each week Matt talks with ecommerce experts and founders from around the world, digging into the questions that help all of us run our online stores better. With more than 300 episodes in the archive, you can find every show, the show notes, the newsletter and the cohort groups at ecommercepodcast.net .

October 7, 202653 min

He Fed 500,000 Emails Into an AI Copy of Himself

Drew Morgans spent 15 years and around $50,000 building an AI trained on his own work, and it now helps run his Amazon agency. Summary Drew Morgans, founder of the Amazon and marketplace agency Marknology, returns to the eCommerce Podcast for a conversation that is all about AI in the real world rather than the hype. Drew explains how he fed 15 years of his own work into an AI system, roughly 500,000 emails, around 300 podcast episodes, blogs, SOPs, playbooks and won and lost proposals, to build something that thinks the way he does. The pair get into the practical build behind it, why context is the hard part, how he keeps his running costs sane by using cheap local models for ingest and expensive frontier models only for client-facing work, and why he chose a single "super agent" over a crowd of specialist bots. Matt and Drew also compare notes on being founders who came up through code, stepped away, and have now picked it back up. It is a generous, concrete look at where AI actually pays off for an ecommerce operator, and where it does not. Turning 15 Years of Work Into an AI That Thinks Like Him Drew describes the shift from using AI for one-off tasks to building a system trained on his own history. He ingested roughly 500,000 of his own emails, around 300 podcast episodes, blogs, SOPs, playbooks and old proposals, turning past work into present value. "I really needed a copy of me." - Drew Morgans "The real meat's in the emails." - Drew Morgans The starting point was helping himself first, then rolling the tools out to his bookkeeper, design team and wider team. Old work he had already paid for in time and energy became a source of ongoing value, including 500 real examples of how he handled objections over the years. A QuickBooks-approved app now auto-drafts invoices from incoming email, always human-gated, never sent automatically. Why Context Is the Real Problem Drew argues the genuine bottleneck is not the model, it is context. AI works sequentially, checking one source then the next, and never holds everything at once the way a close colleague would. His answer was to build the context in before the model ever runs. Drew IQ is a set of around 350 operator rules, a series of "if this, then this" checks that mirror what he already knows as an operator, plus tags that give each product context such as whether a SKU is a launch. WCS is a context engine that surfaces everything relevant to a brand in about half a second, locally, so the model arrives with the full picture already in front of it. Winston is his always-on system, built to be model-agnostic with fallbacks, so if one provider went down he could switch and keep running. He built it on OpenClaw, an open-source always-on agent framework, rather than tying himself to a single vendor. Cheap Model In, Expensive Model Out One of Drew's most useful principles is matching the model to the job. He runs cheap local models via Ollama for the overnight grind of ingesting emails, transcripts and Amazon data, and reserves the expensive frontier models for anything client-facing or "trying to be me". "Cheap model in, expensive model out." - Drew Morgans All the pre-work, the rules, the routing and the context surfacing, happens on his own machine, so it is effectively a free call. By the time the reasoning model is called, it is doing only the final, high-value layer, which keeps costs in check without dumbing down the output. Both Drew and Matt land on the same conclusion about tool-switching, that the opportunity cost of constantly jumping between systems is real, and there is more value in committing to one setup and getting genuinely good at it. One Super Agent Beats Twenty Specialists Drew tried the popular approach of building a crowd of named specialist agents, a CFO agent, a design agent and the rest, all chatting and arguing in Discord. It did not work as well as the alternative. "I cut down the jungle, my team manicures the lawn." - Drew Morgans Instead of managing twenty different personalities, he invested his time in one super agent that knows where all his information lives and can genuinely help. Drew's view on where things are heading is that mediocre roles are in trouble, trades will grow in value, and strong operators will be fine, with a parallel movement back towards authenticity and in-person work. On Amazon specifically, he sees AI helping him do the deep, non-scalable work an agency normally cannot afford at scale, cross-referencing ranking, margin, inventory, reviews, Reddit and search query gaps to work out why a listing is not converting. "It's helping scale the unscalable." - Drew Morgans Today's Guest Drew Morgans (Andrew Morgans) is the founder and CEO of Marknology, a full-service Amazon and marketplace agency based in Kansas City, working across Amazon, TikTok Shop, Walmart and Shopify. He also runs a warehouse and 3PL operation and a portfolio of brands. This is his second appearance on the show. Website: marknology.com LinkedIn: in/amorgans Instagram: @andrewmorgans About the eCommerce Podcast The eCommerce Podcast helps you deliver eCommerce WOW, with real talk about building, growing and running online stores. Hosted by Matt Edmundson, each episode brings on experts and founders who have built the stores and learned the hard way, so you do not have to. New episodes every week. Website: ecommerce-podcast.com Episode link: https://www.ecommerce-podcast.com/ai-for-ecommerce-personal-ai

September 30, 202657 min

How to Sell on TikTok Shop With AI

How do the best brands actually win on TikTok Shop, and where does AI genuinely earn its keep in the process? Summary Matt Edmundson talks with Sohun Sanka, founder of Clankers and former head of growth at the TikTok Shop outreach tools Euka and Reacher. Having audited more than 2,000 affiliate programmes and seen the backend of over 150 agencies and 1,000 brands, Sohun has a clear read on what separates the brands that win on TikTok Shop from the ones quietly burning through samples. The conversation moves from the biggest mistake most of us make with AI (never showing it what good looks like) to the practical mechanics of creator commerce. Sohun explains why top affiliates post 15 to 21 times a week, why lighting matters more than copy in the first two seconds of a video, and how the best brands treat their affiliates like a sales team rather than a mailing list. On the AI side, he walks through Claude Code plan mode, turning repeat tasks into skills, and the single connection almost nobody has switched on that would save agencies 15 or more hours a week. 03:14 Who Sohun is and what Clankers does 07:36 The biggest mistake we are all making with AI 08:33 Why you have to show AI what good looks like 15:06 First steps on TikTok Shop before you touch AI 17:42 Using AI to analyse video, lighting and hooks 25:03 Frontier models versus the agents that connect them 28:27 Claude Code plan mode and turning tasks into skills 32:38 The hundred dollar versus two thousand dollar task 44:12 Why consistency and volume win on TikTok Shop 48:25 Treating your affiliates like a sales team 50:43 The window fans affiliate making a million a year 55:38 Where to begin with TikTok Shop and AI Show AI What Good Looks Like 08:33 The first mistake Sohun sees is that almost nobody has their processes written down clearly, and their data is rarely clean enough for AI to learn the business. Feed a tool like Claude Code or Codex nothing, and it hands back what he calls AI slop. "You don't even have a folder on what good looks like, your brand colours and stuff. You're not feeding it anything." - Sohun Sanka His fix is to onboard AI the way you would onboard a person. A new employee gets 90 days, a meticulous onboarding guide, multiple calls a week and time to shadow. Most people give AI two sentences and then conclude it does not work. "Think about how much context a human gets when they're signing on for a new job, and then they give nothing to AI." - Sohun Sanka Working out what good looks like is uncomfortable precisely because it forces you to define processes most of us keep vague. As Matt put it, the reason we do not tell AI what good looks like is often that we are not sure ourselves. Win on TikTok Shop Before You Touch AI 15:06 Plenty of the early wins have nothing to do with being AI-forward. Sohun's first moves are the unglamorous ones. Pull the copy from your highest performing Meta ad angles and landing pages, then feed it into a creative testing brief for affiliates. Mine your last 30 days of Amazon reviews for one-liners customers actually use, and hand those to creators. Use social listening to find creators already talking about your product, then reach out personally rather than starting a slow sampling process. Benchmark against comparable brands. Tools like Kruva scrape and index every video and its KPIs daily, so you can pace yourself against five similar brands and use that as a working definition of good. The context most people miss is scale. There are roughly 4.5 million TikTok Shop sellers in the US, and only about 1.6% are making a couple of hundred dollars in the last 30 days. That gap is an education problem, and it is exactly where AI can help. Use AI to Read Your Video, Not Just Your Copy 17:42 TikTok affiliates are not polished UGC creators. They often miss the softer craft, like lighting and camera setup, and on a fast-scrolling feed a slightly off frame can cost you the view before a word is spoken. Sohun uses Gemini to break a video into frames and analyse the first two seconds, pulling out the lighting style so creators can be coached with real examples rather than vague advice. Cost is the catch, because generating a transcript and classifying every hook frame by frame gets expensive across a thousand videos. Tools like Kruva already pass through transcript, hook and lighting analysis, which lets him reduce the Gemini spend by three to five times by only analysing the final slice of each video with his own framework. The payoff is reuse. Inside GMV Max you can pull the two-second and six-second video view rates, find every creative clearing a 33% hook rate, analyse what those openings share, and splice those hooks back into your Meta ads or even Amazon sponsored display. Plan Mode, Skills and the Connection Nobody Switches On 28:27 Sohun's view is that prompt engineering is already on the way out. "You don't need to learn how to prompt anymore." - Sohun Sanka Claude Code plan mode interviews you instead. Ask for a report and it works through which brand, which KPIs, what output format, whether it should run as a cron job, and whether it lands in Slack for review or goes straight to a client. When you find yourself doing that 10 to 15 times a week, you turn it into a skill and run it on demand. The bigger miss sits underneath all of it. Most brands and agencies have never connected their TikTok Shop tool to Claude as a connector, even though these tools expose around 110 MCP tools. One connection turns the model into an expert on the platform, yet agencies are still spending 15 to 17 hours a week on manual reporting that could be automated. This ties back to how Sohun runs his own day. He puts a dollar value on his time and sorts tasks into hundred dollar, five hundred dollar and two thousand dollar an hour work, then pushes the cheap tasks to AI or to someone on Upwork. Treat Your TikTok Shop Affiliates Like a Sales Team 44:12 On TikTok Shop the follow-through is human. Where a performance marketer lets the ad mechanism do the work, here someone has to sit with creators, coach them, share the data and keep them posting. "The top affiliates are posting 15 to 21 times a week per brand." - Sohun Sanka Volume matters because the algorithm is getting very good at matching niche interests to the right moment, and there simply is not enough content in the US to feed it (China's feed runs at roughly 60% shoppable content by comparison). The brands getting this right build real communities. Javy Coffee grew TikTok Shop revenue from $300K to $1M a month with 15 community managers, each owning a book of affiliates and rewarded on the GMV growth they drove, making sure new affiliates post 30 times in their first 30 days. Then there is the story that anchors the whole episode. One of Sohun's friends is a top-100 affiliate who prints around $1M a year in commissions selling window fans. He runs a dedicated account posting the same fan under different lighting gradients, hundreds of videos, purely to A/B test lighting, then scrapes the top-100 videos each month into a Claude Code testing pipeline. "We A/B test copy. And I was like, nah, we need to A/B test lighting, because on TikTok Shop, the lighting matters so much." - Sohun Sanka Matt recognised the pattern from his own son, a nutritionist with a large Instagram following who tests everything down to the camera angle, and once found that a tea towel over his shoulder lifted engagement. It is the same instinct ecommerce operators already have for split-testing headlines, applied to video. Where to Begin with AI on TikTok Shop 55:38 Sohun's single starting move is to connect your Claude or ChatGPT connector to your TikTok Shop outreach tool. That tool holds every affiliate activation you are running, so one connection lets the model learn all of it. From there he asks it to lay the whole flow out on a FigJam board, note what should be switched on and off, and show where the leaks are. You will still need TikTok Shop domain knowledge to sense-check what it says, but it is a fast way to see what is actually going on. Sohun's question for Matt's audience: what is the thing that scares you most about getting started with AI? Matt will be answering it on social, so come and join the conversation. Today's Guest Sohun Sanka is the founder of Clankers and previously served as head of growth (employee number one) at the TikTok Shop outreach tools Euka and Reacher. With a background in influencer and affiliate marketing, he now helps brands and agencies build custom in-house software with Claude Code and become genuinely AI-enabled across their TikTok Shop and creator commerce operations. Website: clankersapp.com LinkedIn: linkedin.com/in/sohun-sanka About the eCommerce Podcast The eCommerce Podcast helps you deliver eCommerce WOW. Every Thursday, Matt Edmundson talks with experts and founders who have built the stores and learned the hard way, so you can grow, scale and eventually exit your own business. Website and newsletter: <a href="https://www.ecommerce-podcast.com/" rel="noopener noreferrer"...

September 23, 202650 min

How to Get AI to Recommend Your Brand Instead of Your Competitors

When someone asks ChatGPT for the best hiking boots, it names brands 97% of the time. Is yours one of them? That question sits at the heart of this episode, the second time the eCommerce Podcast has hosted two guests at once. Matt Edmundson talks with Dave McAnally and Alan Osetek, two search veterans with almost 30 years each in the game, about how AI search is reshaping ecommerce ahead of Q4. They dig into "funnel compression", why your own website may not be where AI gets its answers, and the surprising story of a YouTuber with roughly 6,000 subscribers who ended up answering more questions about Adidas than Adidas itself. There is a practical checklist too, from FAQ blocks and schema markup on product pages, to video and Reddit, to the niche third-party sites AI keeps citing. They also cover how to measure it all with GA4's new "AI Assistant" channel, the early days of OpenAI's ad program, and why AI overviews on ecommerce searches are jumping from around 9% to 25% this year. Here is where to jump in: [07:28] The biggest mistake ecommerce brands are making right now [10:11] Why your website isn't where AI finds its answers [17:54] The two-part checklist for product and category pages [25:45] The Adidas story and the 6,000-subscriber YouTuber [32:35] Measuring AI search and getting ready for Q4 [47:10] Owning the niche and defending your turf Why AI Is Compressing the Sales Funnel [07:28] Dave McAnally's core point is that AI collapses the old research-then-shortlist journey into a single prompt. Instead of browsing ten links, a shopper asks one question and gets a handful of brands back. If you are not on that shortlist, you are not in the conversation. "97% of the time, if you ask a question like that, ChatGPT is going to give you brands. So you're going from that real high level, just kind of exploring, learning about a product to a shortlist. And if you're not on that list..." — Dave McAnally Matt tested it live on Perplexity during the recording, asking for the best men's hiking boots for rainy days. It came back with two options, the Salomon X Ultra 5 GTX and the Lowa Renegade Evo GTX, along with a detailed reason for each. As Dave put it, that is a very different experience from a page of blue links, and it means brands are being recommended far earlier in the journey than they used to be. Why Your Website Isn't Where AI Gets Its Answers [10:11] Oddly, the answer often does not come from your own site at all. When Matt clicked through Perplexity's cited sources, they were third-party review and media sites, one packed with verdict scores, pros and cons, comparison tables, cut-open boot photos and even waveform charts. AI loves that kind of structured, corroborated data. "YouTube is the 2nd biggest source for Gemini. Right now for where it gets answers." — Dave McAnally Dave shared the standout example. This spring, when people asked about Adidas's return policy, the most-cited source was not any Adidas property. It was a YouTube channel run by a woman with around 6,000 subscribers, plus a Reddit thread. "None of their own properties were even part of that answer." — Dave McAnally Dave also flagged a shift in how the models behave. Compared with last summer, ChatGPT names fewer brands per answer, but cites roughly three times as many sources to get there. That means your product story needs to line up with what third parties are saying, and it means PR now includes building relationships with small bloggers and niche channels, not just the big review titles. A Simple Checklist for Product and Category Pages [17:54] Asked for the obvious things any brand can do straight away, Dave named two that move the needle. Add proper FAQ blocks to product and category pages that mirror Google's "People also ask" questions. AI is not just answering the question you asked, it is anticipating the next few, so give it those answers directly. Use schema markup , including FAQ schema. It helps AI agents understand what your content actually is, from price to product attributes. "They're not answering the one question you ask. They're anticipating the next 4 or 5 that you might ask." — Dave McAnally On schema specifically, Dave noted a useful quirk. Google has said it no longer reads FAQ schema, but ChatGPT still does, and OpenAI's crawlers are all over sites right now. His broader advice is to write product descriptions around real use cases and pain points rather than marketing fluff, because that is what the AI grabs onto. "Google did say they don't read it anymore, but ChatGPT still does." — Dave McAnally Alan Osetek added a strategic layer. Before spending anything, do an honest assessment of the opportunity. Work out what share of your ecommerce sales comes from AI search today, what it could be in 6 to 12 months, and what it costs you to do nothing. He drew the parallel with the early days of search and TikTok, when smaller players who went in early beat much bigger rivals. How to Measure It and Get Ready for Q4 [32:35] The scale of the shift is the reason this matters now. Last year, AI overviews appeared on roughly 9% of ecommerce queries. This year Dave expects that to hit about 25%. "This year, it's going to be about 25%. So 1 in 4 ecommerce searches are going to have that AI in there." — Dave McAnally To track it, Google added an "AI Assistant" channel to GA4 in May, covering the likes of Perplexity and OpenAI, with an AI-overview breakout still to come and already visible in Search Console. Filter your ecommerce reporting by that channel and you can build a trend line. Dave also noted that AI-referred visitors tend to convert at higher rates, because they arrive already informed rather than cold. [38:09] On paid, OpenAI has launched an advertising program that slots products into relevant prompts. Dave has tested it on a golf accessory brand and found conversions roughly in line with organic, with costs closer to Bing than Google. It is cheap to experiment with right now, though still limited and, at the time of recording, US-only. Alan pointed out the program had reportedly hit around $1 billion in revenue in roughly six months. [42:28] As for who wins, Dave's view is that reports of Google's decline are overstated. Google still holds around 90% of search, has strong momentum with Gemini and the Apple deal to power Siri, and years of crawler advantage. Clicks may be down about 20%, but the traffic that does come through is more qualified. "I do say I think rumours of Google's death are greatly exaggerated." — Dave McAnally Own the Niche, or Defend Your Turf [47:10] Both guests closed with clear, opposite advice depending on your size. For small and mid-sized brands, Alan's steer is to hunt for the niche questions where you can win. "Find those niche questions that people are asking on the AI engines where you can own or dominate those questions." — Alan Osetek For the bigger players, the message flips. "Defend your turf, make sure you're defending your turf." — Alan Osetek Dave's parting advice for everyone is to treat product marketing as mission critical, drive descriptions with real pain points rather than brand fluff, and not to ignore video. Unboxing videos and how-to content on YouTube, which trades with Reddit as the most-cited source, are shaping what AI recommends this holiday season. Today's Guests Dave McAnally is Head of Content Orchestration and SEO at Resolution Media, part of Omnicom Media Group, where he grew the SEO practice into a major share of the business over around a decade and works with Fortune 500 brands. He has spent almost 30 years in search and now also consults with ecommerce and Shopify brands. Connect with Dave on LinkedIn: linkedin.com/in/dave-mcanally Alan Osetek has spent almost 30 years across the global ad agency holding companies and ad tech, including as Global President of Resolution Media, which is where he and Dave first worked together. He now advises in the retail media and ecommerce space, including Brandlight, an AI-visibility platform that monitors and manages how brands are represented across ChatGPT, Gemini and Perplexity. Connect with Alan on LinkedIn: linkedin.com/in/alan-osetek About the eCommerce Podcast The eCommerce Podcast helps you deliver eCommerce WOW with real talk about building online stores. Every Thursday, Matt Edmundson sits down with experts and founders who have been in the trenches, built the stores and learned the hard way, so you do not have to. It is a show for Digital Davids, the small-to-mid-size founders running at the giants they face. Subscribe and find every episode at ecommerce-podcast.com Watch on YouTube at youtube.com/@ecommercepodcast If you enjoyed this...

September 16, 202653 min

She Deleted 19,000 Email Subscribers And Turned Deliverability Around

Email isn't dead. It's just being treated like a newsletter, and that's why so many of them get ignored. Laryssa Wirstiuk runs a boutique email and SMS agency and joins Matt Edmundson to explain what actually works in Klaviyo right now. Summary Laryssa Wirstiuk, founder of the Klaviyo-focused retention agency Joy Joya and host of the Marketing with Laryssa podcast, sits down with Matt to talk about the channel everyone underrates. Her core point is simple. Email is the owned list, the CRM, the lifecycle, the one place where people have actually opted in and want to hear from you. The two biggest mistakes brands make are not valuing it enough, and being so afraid of annoying people that they never send. The conversation moves through the fears founders bring to email and why the numbers rarely justify them. Unsubscribe rates are almost never as high as owners imagine, and disengaged contacts harm deliverability, so letting them go is a gift, not a loss. Laryssa shares a client whose inherited list of around 20,000 was cut to roughly 1,500 genuinely engaged people to escape the spam folder and recover revenue. She and Matt dig into segmentation thresholds, list cleanup, the transactional emails most brands ignore, why simple content beats elaborate design, how to handle dark mode, and which metrics still tell the truth in a world of Apple Mail Privacy Protection and Gmail's AI summaries. Email Is the One Channel People Actually Opted Into Laryssa's definition cuts through the jargon. Unlike social ads, SEO or paid traffic, where people are effectively being shouted at, email and SMS reach people who have expressed interest and asked to hear from you. That changes the job entirely. The relationship is already there. The work is keeping it going. And because you own that list outright, unlike a rented social audience, the data and the relationship are yours to keep. "Behind it all, it's just the owned list, the CRM, the lifecycle of it that I don't think is ever going to go away." - Laryssa Wirstiuk The word "email" is what makes it feel unsexy, she says, but the mechanics underneath are as valuable as ever. The two mindset barriers she meets most often are brands that only half believe in it, and brands that believe in it but are terrified of bothering people. Why the Unsubscribe Is Nothing to Fear (It Protects Your Deliverability) The fear of hitting send comes from a real place. It is easy to judge our customers by our own inbox habits and assume everyone will unsubscribe. Laryssa watches the actual numbers, and the reality is calmer than the anxiety. "Most of the people on that list, they want to be there. And you know what, if they don't want to be, that's a good thing because they're just holding you down." - Laryssa Wirstiuk Disengaged contacts who never open or click send a signal to inbox providers, Gmail chief among them, that your mail has no value. That is how good senders drift into spam folders, and it is slow to recover from. The distinction between spam and value is about intent. Spam is a concerted effort to exploit or harass. Value is styling tips, gift ideas, education, new arrivals, a full picture of what you offer. Frequency is managed with segmentation, not silence. Clean the List, Even When It Hurts List cleanup is the scary phrase most of us resist, and it is one of the most important things we can do. Email addresses go stale, people stop checking inboxes, and dead weight drags down deliverability for everyone still engaged. The mechanic is a sunset flow as a last-chance effort, then suppress or archive. "We cut it down, I want to say, to like 1,500 from 20,000. We basically started over and turned it around, got it out of spam, started getting revenue conversion rates back up." - Laryssa Wirstiuk On segmentation, her rough thresholds are practical. It starts to matter once a brand is sending two to three times a week and the list is somewhere north of 10,000 to 15,000. Below that, a weekly send to the whole list is usually fine, minding the disengaged. Segment by engagement windows, 90, 180 and 365 days, blending email engagement, site activity, purchase activity and how new someone is to the list. Simple Content, Sensible Design, Honest Metrics A recurring theme is that plainer wins. One idea, one desired action, and get the reader moving. Matt shares a rule from one of his own sites where no block of text ran longer than three lines, which lifted conversion, and the same discipline holds in email. Long-form only earns its place as a rare one-off, like a founder's annual update, and even then it has to stay customer-focused. Two often-overlooked wins came up. Transactional emails, the order confirmation and shipping notification, are among the most-read messages a brand sends, yet most ship raw Shopify defaults or leave the shipping note to the courier. Branding them is a real opportunity. And Matt's own brands found their highest-grossing revenue emails are the ones announcing a new podcast episode, though only because they sit inside a wider mix rather than replacing the offers. "There is sort of an art to that type of email too. You still have to make it customer-focused while sharing the information that you want to share about your brand." - Laryssa Wirstiuk On design, the emerging best practice is a hybrid of plain text and HTML, so something still renders and delivers if part of it breaks. Image-based emails give the most brand control but must be sized and compressed. Always A/B test the fancy version against the simple one, and always test for dark mode, mobile and different devices before sending. Gmail now runs its own AI to summarise emails, so give it real text or strong alt text to read. For metrics, open rate has become unreliable since Apple's Mail Privacy Protection auto-marks opens, so treat it as a trend signal only. Click rate is the honest measure of engagement, with two to three percent a healthy benchmark and anything under two worth fixing through CTA placement, contrast and layout. Revenue per recipient is a useful newer metric, and unsubscribe rate should sit under one percent. The Unhinged Study Laryssa signed up to the welcome offers of around 360 ecommerce brands across different verticals and logged exactly what happened after each opt-in. "44% of this random sample did not send anything, even though it was promised to me." - Laryssa Wirstiuk Roughly 12 percent went straight to spam. The lesson is to go back to basics. The welcome email or text is the single most important message in the whole programme, because it is the only moment a subscriber is genuinely waiting to hear from you. Nailing that first touchpoint matters more than chasing a fancier next level. She released the full findings as a free report. Today's Guest Laryssa Wirstiuk is the founder of Joy Joya , a boutique email and SMS marketing agency specialising in Klaviyo and retention for product-based ecommerce brands. A former creative-writing instructor, she niched her agency from the jewellery industry into email and SMS marketing. The name is a nod to that origin, since "joya" means jewel in Spanish. She also hosts the Marketing with Laryssa podcast. Website: joyjoya.com Free report (the "unhinged study"): joyjoya.com/frontdoor Podcast: Marketing with Laryssa , available on audio everywhere and on YouTube LinkedIn: linkedin.com/in/lawirstiuk Find every episode, the show notes, blog posts and more at ecommerce-podcast.com . Episode link: https://www.ecommerce-podcast.com/email-deliverability-for-ecommerce-brands-what-actually-works

September 9, 202652 min

Two Years, 100 Newsletters, and Not a Single Sale Yet

Two Years, 100 Newsletters, and Not a Single Sale Yet Gabriel Lindh has written 100 weekly newsletters and taken 20-odd pre-orders for a pair of swim shorts he still hasn't sold. Summary Gabriel Lindh is the co-founder of Nordic Dudes, a Swedish brand making anti-chafing swim shorts for "guys, or Vikings, with bigger legs". The idea was born on a painful 40-minute beach walk in Australia, sat dormant for a couple of years, then came back to life when Gabriel and his brother decided to build it together. What follows is a rare, honest look at the pre-launch grind. Before a name or a product existed, they asked around 60 to 70 people whether they would actually pay, and 20 to 30 pre-ordered up front. Two years later, after three or four manufacturers and endless sample iterations, they have just placed their first production run of 200 pairs, and they still haven't sold a thing to the public. The through-line is patience. Gabriel has published The Weekly Pillage newsletter every week for around 100 weeks, building an audience while the product was still in development. Matt and Gabriel dig into demand validation, the "theory of eights", and why the unboxing matters as much as the shorts. In this episode: [05:51] The origin story: a chafing beach walk in Australia [09:56] Why the build took four times longer than planned [14:09] Validating demand before spending a penny [21:53] Building an audience before the product exists [37:13] The unboxing as a point of difference Build the Audience Before the Product [21:53] Most founders wait until they have something to sell before they start talking. Gabriel did the opposite. The nordicdudes.com landing page collects newsletter sign-ups, and The Weekly Pillage has gone out every week for roughly 100 weeks, sharing the messy reality of building the business as it happens. The goal is trust. By the time the shorts launch, the audience already knows who Nordic Dudes are, so the product lands with people who are warmed up rather than starting cold. "We haven't missed an email in, I think, 100 weeks at this point, which is pretty crazy." Gabriel Lindh Gabriel is candid that social media has lagged behind, something Matt gently pushes him on: with a humour-led brand and samples in hand, Instagram is an open goal. The lesson is less about the channel and more about the principle. Start building the audience long before you have anything to sell them. Validate Demand Before You Spend a Penny [14:09] Before committing money to manufacturing, Gabriel and his brother built a list of 60 to 70 people they thought might want the product, drawn from friends, friends of friends, and his brother's ice-hockey team. They reached out one by one and asked a simple question: would you actually buy this? Most said no. But 20 to 30 said yes and paid up front through Swish, a Swedish payment app. There was no promised delivery date and the money was fully refundable, yet the cash in hand gave them the confidence to commit. "We should test something to just make sure that we're not spending all this money and time on something that nobody wants in the end." Gabriel Lindh They never set a formal minimum. Instead they worked to a rough sense that two orders would not be enough, but twenty or thirty would. Real money from real people, even a small amount, is a far stronger signal than a survey or a like. It Takes Longer and Costs More Than You Think [09:56] Gabriel and his brother expected the build to take four to six months. It has taken more than two years, with no real e-commerce background between them beyond a bit of dropshipping that earned around $400. Their first sample, ordered off a text message with no tech pack, was unusable. They eventually paid a Fiverr designer for a proper tech pack and worked through three or four manufacturers, iterating on every sample. "It's the most difficult thing I've ever done." Gabriel Lindh Matt's "theory of eights" gives the mindset a name: aim to consistently hit an 8 out of 10 rather than exhausting yourself chasing a 10 you will rarely reach. Launch at an 8, then improve with real customer feedback. Gabriel's own advice echoes it. "Take it one step at a time... what's the most important thing that I can do right now to get a little bit closer to where I want to go?" Gabriel Lindh The Unboxing Is Part of the Product [37:13] Nordic Dudes will ship in a reusable cotton bag printed with the logo, an idea that came from Gabriel's mum. A bag beats a box on several counts: it is cheaper, it takes less space, it won't get crushed in transit, and customers can reuse it for their swim shorts, towel and water at the beach. The fabric bag being a surprise is deliberate, a small moment of delight when the parcel is opened. Matt's own beauty company made the same bet. Swapping plain padded envelopes for a gift-style box, with tissue paper and popcorn as packaging material, cost less than 10 pence per parcel, yet it changed everything. Customers stopped using social media to complain and started posting about the popcorn instead. "The more you can create a remarkable opening experience, the more you're going to create a loyal customer base." Matt Edmundson There is also a case for packing your first orders yourself. Nordic Dudes will fulfil manually from Sweden to begin with, and Matt argues that founders who pick and pack early understand their product and their customer in a way a third-party warehouse never will. Today's Guest Today's guest: Gabriel Lindh Company: Nordic Dudes Website: nordicdudes.com (sign up for the newsletter, The Weekly Pillage) YouTube: Gabriel Lindh (personal brand documenting the build) Instagram: Nordic Dudes About the eCommerce Podcast The eCommerce Podcast is dedicated to helping you deliver eCommerce WOW, with real talk about building online stores. Every Thursday, host Matt Edmundson sits down with guests, experts and founders who have been in the trenches, built the stores, and learned the hard way, so you don't have to. For show notes, past episodes, the link to today's guest, and the free eCommerce cohort groups, head to ecommercepodcast.net . While you're there, sign up for the weekly newsletter and you'll get the notes and links from every episode straight to your inbox. If you're an eCommerce founder with a story to tell, click the "Be a Guest" link at ecommercepodcast.net and come and share it on the show.

September 4, 202652 min

Is It Time We Talked About Turning Off Your Ads? (And Yes, You Read That Right)

Your best-ever ROAS month can still lose you money. Brenden Delarua explains why the number on your ad dashboard rarely matches the number in your bank account, and what to measure instead. Summary Brenden Delarua spent 11 years in paid media, hitting and smashing ROAS targets across Meta, Google and Criteo, until a CFO asked him a simple question at a quarterly review. If the ad numbers are this good, why is revenue down? That question sent him into causal measurement, and he now runs Stella (Growth Intelligence), a marketing-measurement company that helps brands work out what is actually driving sales rather than what the platforms claim. In this conversation Brenden unpacks why platform-reported ROAS is a correlation metric that can overstate how well your ads are working, and how chasing it pushes marketers into retargeting and branded-search quick wins that flatter the dashboard without growing the business. He walks through the practical ladder any small brand can climb, from multi-touch attribution and post-purchase surveys up to full geo-holdouts and media mix models. Along the way there is a YouTube campaign that looked like a disaster, a lesson on why branded search is not always what it seems, and the one post-purchase survey question worth more than the rest. ROAS Is Not the Same Thing as Profit Brenden's whole approach traces back to one uncomfortable review meeting. As a media buyer he had beaten every ROAS goal he was set, then presented record-breaking results, and still got questioned by the CFO. "If you're showing us that ROAS is so high, why am I not seeing that in our actual bank account?" — Brenden Delarua, on the CFO question that started it all The problem is what ROAS actually measures. It is a correlation metric. Someone saw or clicked an ad and later converted, so the platform claims the sale. "ROAS is not correlated with profit, even though a lot of people think it is." — Brenden Delarua Because ROAS rewards clicks, it tends to deprioritise channels you cannot click, like connected TV or audio, and it tempts marketers to pile budget into retargeting or branded search for a quick win. The dashboard looks great. The business stops growing. Brenden's point is that what owners ultimately care about is profit, not a platform-reported number. The YouTube Campaign That Looked Like a Money Pit One story makes the gap between platform numbers and reality concrete. Brenden runs ads for a client spending heavily on YouTube, a channel infamous for a poor click-to-convert ratio. In-platform, the YouTube ROAS sat at around 0.2, so the account ROAS looked like it was suffering. The obvious call was to question why so much was going into a channel that appeared to be losing money. Then he pulled the post-purchase survey data from NoCommerce, and around 7% of buyers said they came from YouTube. Set against the spend, that share of revenue worked out at roughly a 3x return, and the channel was actually very profitable. The lesson is not that YouTube always works. It is that a single click-based number can hide the truth, and a second data point, in this case a qualitative survey, can change the whole decision. "Sometimes increasing incremental ROAS is the opposite of increasing platform ROAS." — Brenden Delarua What is Causal Measurement? Brenden is keen to stress that incrementality is not just a big-brand concern, and you do not need to turn off ads to benefit from the thinking. He lays out a practical ladder that scales with the business. Start with proper multi-touch attribution. For e-com tools he rates Triple Whale and Northbeam. It maps the customer journey by stitching anonymised touchpoints together until someone converts, then shows first touch, last touch or a fairer linear model. Add post-purchase surveys. Even a brand-new store can ask buyers where they came from and, more importantly, why they bought. Tools like NoCommerce can use conditional logic to ask which specific ad someone remembers. Add causal analysis when you are big enough. Once sales volume is there, usually for brands over roughly 10 million a year running on two or three platforms, holdout testing and media mix models come into play. "You don't have to do holdouts to understand that what's causing sales to happen might be different from what you're seeing in ad platforms." — Brenden Delarua For a brand doing a million a year, the same issues exist at a smaller scale. The trouble is that as you grow, working out what is really driving growth gets harder, not easier. What are iROAS and Holdouts? For brands ready to test properly, Brenden explains the terms plainly. A holdout study means turning ads off in certain geographical regions and watching your source-of-truth revenue, usually Shopify, against the regions that stayed live. The measure that comes out of it is iROAS. "iROAS stands for incremental return on ad spend, every dollar we put in that gives us back money that would not have happened without that investment." — Brenden Delarua A few practical points from the conversation: Test in a cycle, from channel level (all of Meta, all of Google) down to tactic level (branded versus non-branded) and then individual campaigns, then start again. Holdouts typically run 20 to 30 days, with top-of-funnel channels like CTV closer to 45. Branded search is often called non-incremental, but not always. If the brand name is effectively the product category, it can be highly incremental. Matt's own analogy landed it well, as if a company selling omega-3 were simply called Omega-3. Media mix models look back over around two years, factor in seasonality and other variables, and are forward-looking, so they can forecast how to allocate next quarter's budget. Brenden recommends using holdouts and media mix models together, with the holdout calibrating the model. There is a catch, and Brenden names it. A holdout is a snapshot in time, shaped by your bid strategy, the platform algorithms and how many competitors are in the market that month. His ads in February behave nothing like his ads in the run-up to Black Friday. "The moment you get that iROAS report back, the next day it starts to shift. We call it causal decay." — Brenden Delarua The Post-Purchase Question You Should Ask Asked for his best parting tip, Brenden returned to post-purchase surveys and one question in particular, credited to Jarrell Blades, VP of Growth at Tushy. "I love asking what almost stopped you from converting, because that gives you tons of insight into your messaging and targeting." — Brenden Delarua His advice is to begin with the end in mind, borrowing the idea from The 7 Habits of Highly Effective People, and design the survey around the answers that will actually help you convert more people. Surveys surface the things attribution never sees, like a friend's recommendation or word of mouth. They also reveal which ad someone remembers, which is not always the ad they clicked. When the most memorable ad differs from the clicked one, that tells you something powerful about which creative is really doing the work. Today's Guest Today's guest: Brenden Delarua Company: Stella (Growth Intelligence) Website: https://www.stellaheystella.com/ LinkedIn: Connect with Brenden on LinkedIn TikTok: @brendanbuilds (the lighter, more sarcastic side of his marketing content) Resources Mentioned Triple Whale and Northbeam — multi-touch attribution tools Brenden recommends for e-com NoCommerce — post-purchase survey tool, including conditional logic on higher plans Jarrell Blades , VP of Growth at Tushy — source of the "what almost stopped you from converting" survey question Neil Hoyne , former Google data specialist and author of Converted — a previous EP guest, referenced for the shopper whose single purchase involved 236 touchpoints The 7 Habits of Highly Effective People — for the "begin with the end in mind" principle applied to survey design Keep Listening Find the full archive, free tools and everything else at ecommerce-podcast.com . New episodes land every week. If you are getting value from the show, subscribe on your podcast player of choice and share this episode with a fellow founder who is still judging their ads by the dashboard alone. Episode link: https://www.ecommerce-podcast.com/is-it-time-we-talked-about-turning-off-your-ads-with-brenden-delarua

August 21, 202646 min

Why Pay an Agency 15k When Your Customers Will Tell You for Free

A brand Cem Atik helped scale from $15m to $50m paid an outside firm $15,000 to be told what it was doing wrong. It already had 100,000 customers who would have said the same thing for nothing. Cem co-founded Harucon Ventures in Düsseldorf, in western Germany, and spends his days pulling apart the numbers behind ecommerce brands in the UK and the DACH region (Germany, Switzerland and Austria). He has been in the space for 13 years. He scaled his own first business to $7m, then burned more than $250,000 on a second one he started alongside it and went bankrupt in five or six months. That failure shapes most of what he says here. The two things holding brands back, he argues, are a loose grip on unit economics and the ego that arrives somewhere between $2m and $5m in revenue. He makes the case that ecommerce only really starts past $10m, that retention rather than paid marketing is where the profit is made, and that a rising customer acquisition cost is only a problem if the repurchase rate is low. He also walks through what happens inside a growth audit, including a packaging change that took 25% out of one client's costs before any extra ad spend. In this episode 02:57 - Who Cem is and what Harucon Ventures does 08:33 - The two mistakes he sees in almost every brand 11:11 - Why pay 15k when you already have 100,000 customers 13:45 - The $250,000 second business that went bankrupt in five months 16:54 - Why a rising CAC is not automatically bad 20:45 - What actually happens inside a growth audit 24:18 - Cut the feelings and call your customers 34:32 - How Cem uses AI to read data he has no time to read 43:02 - The five numbers every ecommerce founder should know The Two Mistakes He Sees in Almost Every Brand (08:33) Asked for the single biggest mistake ecommerce businesses make, Cem named two. The first is having no control over unit economics. His opening question on a first call is what the brand's customer acquisition cost to lifetime value ratio is, and he asks it less for the number than to find out whether the founder knows it at all. The second is ego, and it tends to show up between $2m and $5m in annual revenue. "The first call that I have with people is usually like roasting them for 30 minutes." - Cem Atik He is not dismissive of that milestone. Getting a business to $2m or $5m is difficult and most people never do it. His argument is that the game changes afterwards. "Ecommerce is actually, if you're just asking me, starting after you're passing the $10 million, because then you just really start to feel pressure, competition, and you also just need to play the game differently, or otherwise you die within like a 3-month period." - Cem Atik He has paid for the lesson himself. His first business reached $7m in revenue, at which point he assumed everything he touched would turn to gold. He started a second business alongside it, spent over $250,000 and went bankrupt inside five or six months. Matt offered the same story back from his own history, copying the code behind Jersey Beauty Company to launch Jersey Gift Company, which died in about three weeks. "People only learn with pain. You just need to feel this pain at least once or twice until you understand." - Cem Atik Your Customers Already Know What Is Wrong (11:11) A brand Harucon had helped take from $15m to $50m told Cem it had hired an outside firm for $15,000 to identify what it was doing wrong. Harucon has invested in that business, so Cem asked the founder why. "Marcel, you have 100,000 customers to ask for what you are doing wrong. Why are you just hiring a company?" - Cem Atik The founder's answer was that it felt like the next step. "Who say you that this is the next step? You're just only increasing your OpEx cost for no reason." - Cem Atik The objection Cem expected was credentials, so he dealt with it directly. "These guys have like huge reference. And your customers has no reference. They buy, they bought your product. So what kind of reference you need more, right?" - Cem Atik The catch is that free feedback still has to be accepted. Cem's view is that a sparring partner is only useful to a founder who can take criticism, provided the criticism comes with a reason and a fix rather than just a verdict. Matt tied that back to Jim Collins in Good to Great , and the idea that a great leader confronts the brutal facts while holding on to a belief that the future can be different. Retention Is Where the Profit Sits (16:54) A client complains that their customer acquisition cost is rising. Cem's first question is the repurchase rate. At 40%, a rising CAC is not a problem. At 10% or 15%, it is. "A raising cost number doesn't mean that something is going bad or good. It more shows you where your business is moving on." - Cem Atik Category matters here. Beauty products tend to bring in new customers, supplements should bring the same customers back, and a supplements brand without a repurchase rate of 30% to 40% is leaving money on the table. His wider point is that paid marketing has a ceiling. "You cannot stay always profitable with your marketing if you just reached 100, 150, 200 million. That is not working. Marketing is not made for that." - Cem Atik Retention, conversion rate on the shop and signup forms are the levers that turn unprofitable traffic into profit. "Retention is the only channel that is generating your pure profitability." - Cem Atik Scaling Usually Starts Before the Ad Spend (20:45) Harucon runs two due diligence workstreams before it touches anything, marketing with Cem's team and finance with his partner Tobias Münnich and his team. The scan covers rates, supply chain and process, and the fixes it surfaces are rarely about buying more traffic. One food and beverage client was producing in Poland and Bulgaria, shipping the product to Germany, unpacking it, repacking it, then selling it. Finishing the packaging at the point of production took roughly 25% off the packaging cost. A separate change to fulfilment on the same brand saved another 12%. The findings get delivered in what Cem calls the second roast meeting, where the brand hears exactly what is wrong, why it is wrong and how it gets fixed. He is firm that the last part is what makes the first two worth anything. Naming the problem is cheap. Handing over the method is the bit brands can act on, and it leaves them free to run the fix themselves or bring Harucon in to do it. Cut the Feelings and Follow the Data (24:18) "Your ecommerce brand is your baby. You just grow it up from the beginning and there is a lot of emotion into it. Cut it. It's hard to say, but cut it." - Cem Atik A 15% to 20% return rate does not need a dashboard or a consultant. It needs phone calls to the customers who sent the product back. The same instinct applies inside the data. One of Harucon's partner brands asked why repurchase rate fell away after the third order. The numbers showed no gifts, no welcome series and no contact of any kind after the first purchase. "It takes us 5 minutes to fix something that you just thinking about like 2, 3 weeks." - Cem Atik For founders with nobody to ask, his suggestion is LinkedIn. Message ten people who work in the area. If eight of them say the same thing, fix that. He answers his own messages, prompted by his team when one has been sitting there a day or two. The last piece is pace. One of the larger private equity operators Cem knows describes himself as not especially smart, but says he understands how pace and execution work together. He runs five things at once, cuts whatever is not working inside a month and rotates. He burns money doing it, roughly 5% or 6% of it, and that buys him the other 90%. "If you are not able to sacrifice 5, 6 or even 10% to generate another 90% which are insanely profitable, you are leaving money on the table and you are just wasting your time." - Cem Atik The Five Numbers He Names (43:02) Asked to close with the metrics every ecommerce founder should be able to state, Cem gave five. Customer acquisition cost Average order value New customer share, meaning the percentage of customers coming in who are new Lifetime value Repurchase rate His closing advice was borrowed, heard on another podcast and repeated because he thinks it is true. Work so hard and so much that it makes it unreasonable not to succeed, and do not let pace and execution be the last thing you care about. Cem's Question for Matt Every guest leaves Matt with a question, and he answers it on social rather than on the show. "If you compare your biggest success with your biggest failure, which one teaches you more? Failure, for sure, right? But are you sure about that?" - Cem Atik Matt's answer goes up on LinkedIn and Instagram. Today's Guest Cem Atik (pronounced "Jem") is Co-Founder of Harucon Ventures GmbH, based in Düsseldorf, Germany. Harucon is a growth partner for ecommerce brands in the UK and the DACH region, which covers Germany, Switzerland and Austria. Cem runs it with his partner Tobias Münnich, who leads the finance side. The firm works on a performance-based model, caps itself at 15 brands at a time and takes equity positions...