eCommerce Podcast

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 MorgansThe 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 MorgansAll 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 MorgansInstead 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 MorgansToday'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

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 SankaHis 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 SankaWorking 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 SankaClaude 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 SankaVolume 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 SankaMatt 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:

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 McAnallyMatt 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 McAnallyDave 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 McAnallyDave 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 McAnallyOn 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 McAnallyAlan 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 McAnallyTo 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 McAnallyOwn 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 OsetekFor the bigger players, the message flips.
"Defend your turf, make sure you're defending your turf." — Alan OsetekDave'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
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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 WirstiukThe 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 WirstiukDisengaged 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 WirstiukOn 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 WirstiukOn 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 WirstiukRoughly 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

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 LindhGabriel 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 LindhThey 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 LindhMatt'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 LindhThe 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 EdmundsonThere 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.
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