Sean Kim

Meta shared their Creative Diversification Cheat Sheet (great for ecom brands) Oversimplified, but a solid baseline to audit your mix Use it to spot gaps fast, then layer real testing frameworks Great for 0→1 teams to get moving—learn the advanced stuff once you’re shipping consistently

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Google is the single best business ever created. They own the front door to the internet for most people (90% share in a GIANT market). And they monetize that front door by selling search ads... that have 85% gross margins. An enviable position if you can get it! This explains why they generate more profits than any other US company, including even Apple, Microsoft, or Berkshire Hathaway. But now, that insane business is under threat in the AI era. And the trillion-dollar question is... can they maintain their dominance monetizing human intent amidst this tectonic shift? (Ironic of course, because Google basically invented modern AI.) To attempt to answer that, you really need to understand how Google was built the first time around. And David and I spent this Acquired episode doing just that. Here are a few reasons that Google worked so incredibly well in its first decade: 🔗The best search algorithm: PageRank Larry Page and Sergey Brin had the brilliant insight that instead of ranking pages by keyword frequency (which was easily gamed), they ranked by how many OTHER authoritative sites linked to you. It was genius—your competitors couldn't fake having The New York Times link to your site. This insight alone separated Google from every other search engine in 1998 and created the foundation for everything that followed. 💰 The Perfect Economic Model: Auctions + Intent Google didn't invent the paid search business model—a company called GoTo (later Overture) did. But Google perfected it by adding ad quality to the auction formula. Your ad ranking became bid price × click-through rate, which meant better ads could win while paying less. This created the optimal algorithm for Google's revenue AND advertiser satisfaction AND user experience. Aligning incentives is a magical thing. 🏗️ Infrastructure as a Moat While competitors used expensive enterprise servers, Google built everything from commodity hardware and clever software. They designed distributed file systems, custom data centers, and revolutionary approaches to scaling. This wasn't just cost savings—it let them operate at a scale nobody else could match while maintaining industry-leading margins. Technical architecture became a fundamental competitive advantage. 🚚 Distribution at (Almost) Any Cost Once Google realized that search was winner-take-all (more bidders = more searches monetized & higher winning bids = more revenue per user), they spent aggressively on distribution in the form. Google Toolbar, bundled with everything from Adobe to Dell PCs. Portal deals giving away the vast majority of revenue. Even revenue sharing 100% initially to win traffic. They understood that controlling distribution in an auction-driven network effects business was worth almost any price. The craziest part? This all happened before Gmail, Maps, Android, Chrome, or YouTube. This is just search—and it's still the source of Google's cashflow 25 years later. https://lnkd.in/gXMEUuqh

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Traditional AB testing vs Modern 'Growth Experimentation' differs in the question being asked: 𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗔𝗕 𝘁𝗲𝘀𝘁𝗶𝗻𝗴: "Which version works best?" 𝗚𝗿𝗼𝘄𝘁𝗵 𝗘𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: "What would happen if we did this?" In this way, 'Growth Experimentation' sits above the tactical AB test or similar approaches (analytics, UX research, etc). It is at the '𝗕𝗲𝘁' level. As a bit of an illustration of the concept in application, in my interview last year with Marty Cagan, he contrasted Booking's 'optimization' culture with Amazon's 'experimentation' culture. Marty didn't see what booking was doing as 'experimentation', rather 'optimization'. So these thoughts recently made me think of the 𝘗𝘙𝘍𝘈𝘘 (Press Release + FAQ) model from Amazon. (now being used to some degree, with different names, in many large testing programs, including some that Speero helps consult on) In Amazon’s culture, big ideas start with a 𝘱𝘳𝘦𝘴𝘴 𝘳𝘦𝘭𝘦𝘢𝘴𝘦 𝘸𝘳𝘪𝘵𝘵𝘦𝘯 𝘧𝘳𝘰𝘮 𝘵𝘩𝘦 𝘧𝘶𝘵𝘶𝘳𝘦, a narrative that imagines the impact of a successful initiative, and an FAQ that anticipates hard questions. This 𝘗𝘙𝘍𝘈𝘘 (or whatever 'Bet' document) forces clarity of thought, customer obsession, and strategic alignment 𝘣𝘦𝘧𝘰𝘳𝘦 a single line of code is written or pixel moved. Used in the context of Growth Experimentation, the PRFAQ becomes the articulation of your 𝗕𝗲𝘁: • What’s the bold change we’re testing? • Why would this matter for the customer and the business? • What would success 𝘭𝘰𝘰𝘬 𝘭𝘪𝘬𝘦 if this worked?    It elevates testing from optimization to 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻. From marginal gains to transformative bets. From “Which button works best?” to “What if we reimagined the entire onboarding?” So the taxonomy here looks like: 1. Biz Problem/Opp pillar or objective (NOTE, this MUST come from biz 'leaders') 2. Bets ("how might we...." or "What would happen if we...?") 3. Experiments (AB tests, Surveys, Analytics, etc... data that is seen and 'done') This framing not only helps prioritize high-leverage experiments but also aligns/enrolls cross-functional teams around a shared narrative and ambition, essential in moving from isolated A/B tests to experimentation-led growth (#ELG ftw) My most recent thinking on how this taxonomy is tactically handled in what operationally represents a true 'experimentation operating system' for an org has 3 core components: 1. A Data-to-Action core 𝗿𝗶𝘁𝘂𝗮𝗹 (ideation + solutioning + accountability loop) 2. A 'XOS' knowledge repo 𝗮𝗿𝘁𝗶𝗳𝗮𝗰𝘁 (aka product ops, aka 'bottom-up intelligence system') 3. A 'bets' linkage 𝗮𝗿𝘁𝗶𝗳𝗮𝗰𝘁 (a la 𝘗𝘙𝘍𝘈𝘘 document...this can also be 𝘪𝘯 the XOS above) You have the best tool in the world, the best people, but you still have to figure out the 'HOW' of the workflows. How things get prioritized and built. This setup helps IMO

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I took a brand from $0 to $1M in 30 days. While most entrepreneurs are stuck endlessly tweaking their store theme, I've identified the 6 core principles that actually move the needle in eCommerce. And they're hiding in plain sight: 1️⃣ Product Selection is Everything I don't touch anything without high margins ($110 price, $35 COGS) that solves a genuine pain point. Forget dropshipping trinkets. I specifically target products that are lightweight (avoiding shipping nightmares), incorporate consumable parts (guaranteeing repeat customers), and deliver an immediate "wow" factor. This product-first approach created an immediate 3X ROAS advantage over competitors selling commodity items. 2️⃣ Funnel Engineering is Non-Negotiable Amateur stores slap together basic pages and wonder why they're not converting. My winning formula uses multiple pre-sell touchpoints with professional trust badges and thoughtfully orchestrated customer journeys. When we upgraded from stock Shopify templates to custom influencer photography throughout the funnel, our conversion rate doubled overnight. 3️⃣ Creative Testing Requires Brutal Honesty The difference between 7-figure operators and everyone else? I start with broad targeting but expect 11 out of 12 creatives to fail completely. When we found our single profitable angle, we didn't celebrate. We doubled fcking down. We immediately created 15 variations to maximize its potential. Thumbnails are difference between profitable and unprofitable campaigns in 2025. 4️⃣ Scaling Demands Methodical Discipline I duplicate winning audiences into CBOs, ruthlessly kill underperformers at both campaign and ad set levels, and expand horizontally through interest and lookalike audiences rather than just pumping more budget vertically. My filter-and-kill process happens daily, not weekly, creating compounding advantages over competitors who check metrics sporadically. 5️⃣ Creative Infrastructure is the Ultimate Moat Everyone obsesses over ads manager tricks. Not me. I invested 10-20% of profits back into content production. The single creative that generated $45K/day came after 11 complete failures. This is a systematic approach to creative development that treats content as your primary business asset, not an expense. 6️⃣ Team Building Accelerates Everything If you wanna go fast, go alone. If you wanna go far, go together. The moment we assembled specialized talent for creative production, ad management, and fulfillment, our growth curve went vertical. Specialization roles create exponential rather than linear results. Most entrepreneurs aren't failing because they lack information—they're failing because they aren't executing on these foundational principles with ruthless consistency. Want the detailed video breakdown of exactly how I executed this 0-to-$1M roadmap? Comment "VIDEO" below and I'll send you the complete tutorial. (must be connected)

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Two days ago, OpenAI clarified the transaction fee it will charge Shopify merchants with its Instant Checkout product: 4%. This reinforces my argument that (independent) agentic commerce is a mirage: many Shopify merchants run on incredibly thin margins (3-8% net) and simply may not be able to support this. Further, they aren't in control of it: if ChatGPT's Instant Checkout affiliate link system overwhelms or front-runs their existing organic discovery, it could be disastrous for their businesses. Compare this to an on-platform shopping agent like Amazon's Rufus or Walmart's Sparky, which benefits in a number of ways when a customer purchases through their platform, obviating the need for the agent to charge a direct transaction fee. This transaction fee stacks on top of the existing merchant and payment processing fees that retailers pay. For CPG retailers with fixed COGS, an additional, obligatory 4% fee on an unpredictable volume of sales could fundamentally compromise the durability of their business. It also highlights the value of advertising relative to Instant Checkout's affiliate model: advertisers control the margin they forfeit through advertising with their bid and can optimally price it. For many retailers, 4% may be unmanageable as a transaction fee, but some lower relative amount could be feasible in the form of a bid. This is the difference between endogenous pricing and an exogenous imposition of friction.

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Shopify is becoming the product layer of the internet and nobody noticed. While the spotlight was on AI-generated theme blocks, Shopify quietly rolled out something way bigger: a new infrastructure for AI-native shopping. Here’s what slipped past most folks: 1. Storefront MCP This developer tooling allows AI concierges built into your storefront. They can browse products, answer customer questions, build carts, and even kick off checkout. The possibility here is chatbots with deep store access. 2. Shopify Catalog Shopify cracked open its global product index. Now AI apps (like Perplexity) can tap into data from millions of merchants. This is Shopify becoming a search layer for ecommerce, not just a platform. 3. Knowledge Base App AI agents need something to say. This app lets merchants control the FAQ answers bots use across AI shopping tools. It’s already live in the App Store, you can install it today. Bottom line: Shopify isn’t just adding AI to commerce, it's becoming the product layer of the internet.

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DTC operators...would you rather hire: A) Two $65k / year creative strategists B) One $130k creative strategist My take? The $130k creative is usually worth 5-10x more. → They master new AI design tools before you even hear about them → They surprise you daily with creative ideas you hadn't considered → They operate at your level (sometimes ahead of you) → They leverage AI to multiply their brainpower and output → They figure out new creative tools 5X faster than others → They maintain quality while driving down costs The best part? They don't need to be actively managed. You just set clear expectations, then get the hell out of the way. But curious to hear thoughts of others... With a finite budget, would you choose A or B?

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New Substack 🚨 Shopify just integrated OpenAI directly into the storefront. This isn’t just a feature drop—it’s a signal. We’re officially entering the era where: ➡️ The shopper journey starts with a question, not a click ➡️ AI becomes the brand’s first point of contact ➡️ Personalization is powered by memory, not just segmentation In my latest Substack, I unpack: ⚡ 5 strategic signals from the Shopify x OpenAI partnership 🧠 How this impacts both DTC disruptors and legacy commerce platforms 🛠️ The A.I.D. Framework to build AI-native shopper journeys ⚠️ Key risks—from hallucinated recommendations to brand voice drift 📊 A board-level reflection: “If AI owns your storefront’s first interaction, who owns the strategy?” 👉 Read the full post here: https://lnkd.in/gXndMF3a 💬 I’d love to hear from fellow leaders: Where in your shopper journey is AI already showing up—and where is it urgently needed? Let’s design the next generation of commerce—intelligently, intentionally, and with conversation at the core.

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15 years in, and Conductor is betting everything on one truth: traditional search is over. AI is the new arena. Getting buy-in for SEO has always been hard (despite driving 30-50% of your digital business). Yes, some visionary leaders made this a priority…many became our customers. But, the formula for digital success has changed forever. Chasing Google’s ‘10 blue links’ will soon be a thing of the past. And, unfortunately, so will many of those website visitors. What remains is the largest opportunity in the history of digital marketing (IMHO). AI-driven search will become your customers’ most trusted advisor. How your brand shows up in AI results will define your digital future. AI will own more of the customer journey than your website—leaving your marketing tech obsolete and making AEO, GEO, AIO (whatever you call it) mission-critical. Fortunately for our customers, we’ve spent the last 5+ years investing 100% of their $ into one thing: building the most powerful technology for the future of digital. Over 3 years, we rebuilt our data infrastructure from the ground up leveraging our deep enterprise experience. And today, we launch Conductor AI…the next generation of our platform. Serious value includes: • AI Topic Maps: See your content the way AI does, identifying gaps and opportunities for an impactful content strategy–powered by our real-time web crawl, vector databases, and AI (this is over a year in the making leveraging our new data engine). • AI Search Performance: Understand your presence across critical AI platforms like ChatGPT and Perplexity. This isn't rank tracking 2.0—it's an entirely new approach providing insights into your market share, sentiment, and critical perceptions about your brand. • Best-in-Class Content Generation: Exceptional content creation made easy through a powerful combination of LLMs, expert prompt engineering, topic performance data, competitive insights, and your brand guidelines. No training required. • Automated Internal Linking: Leveraging semantic analysis across your content and powered by a vector database, these agents automatically create optimal internal linking strategies. It's incredible. 100% unique. • AI Bot Detection & Alerts: Measure & monitor how AI bots interact with your website. These engagements will become critical signals that influence digital strategy. All of this comes with a completely new interface/navigation, end-to-end universal search, a vibrant customer community, 24/5 expert support, and the most experienced/dedicated/hungry team in the space. We’re watching brand new startups make the same mistakes we made a decade ago—but this moment is too important to gamble on newcomers. Enterprise brands need the best. That’s why you choose Conductor. And that’s exactly what we commit to delivering. Lets go!

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The best product marketers don’t sell features. They sell stories that move markets. And in 2025, the best stories aren’t written from scratch. They’re co-created with AI. If you’re a PMM trying to stand out in a sea of sameness, here are four storytelling frameworks every marketer should master - and how companies like Amazon, Meta, Netflix, and NVIDIA bring them to life. 1. The StoryBrand Framework — Make Your Customer the Hero Most marketers position their product as the hero. That’s the first mistake. Your customer is the hero. You’re the guide. Use AI to analyze call transcripts, interviews, or G2 reviews. Ask: “What are my customer’s fears, frustrations, and victories?” Then frame your story around their transformation, not your technology. Example: Amazon AWS built its “Build On” campaign around this idea. Hero: Developers who crave speed and reliability. Guide: AWS’s cloud and AI services. Victory: “We help builders build.” It’s simple, human, and scalable across segments. 2. The Who-What-Why Formula — Clarity Beats Cleverness Positioning fails when it tries to sound smart instead of being clear. AI can help distill your message down to its essence. Prompt it: “Summarize our value proposition in one line anyone could understand.” Example: Meta reframed its mission statement this way: Who: We’re Meta. What: We’re building the metaverse. Why: Because connection shouldn’t stop at a screen. Agree or not, it’s instantly clear—and clarity drives conviction. 3. The Hero’s Journey — Comfort → Crisis → Quest → Conquest Every buyer’s journey mirrors this narrative arc. They start comfortable, face a problem, go on a quest, and emerge transformed. Ask AI to map your customer’s emotional journey: “What’s their before-and-after story?” Example: Netflix lived this narrative. Comfort: DVDs by mail. Crisis: Streaming disruption. Quest: Reinvent entertainment through AI-powered personalization. Conquest: 260 million subscribers and a new category of storytelling. AI didn’t just help Netflix personalize—it helped them predict which stories would resonate. 4. The Pixar Framework — Structure Emotion into Simplicity Pixar has a storytelling rhythm that works beautifully in B2B. Once upon a time… Every day… Until one day… Because of that… Until finally… Prompt AI: “Turn our product pitch into a 30-second Pixar story.” Example: NVIDIA could tell its story this way: Once upon a time, computers processed numbers. Every day, engineers hit performance limits. Until one day, GPUs unlocked parallel computing. Because of that, AI was born. Until finally, NVIDIA became the engine of the AI era. That’s not a product pitch - it’s a cultural story about possibility. Final Thought AI doesn’t replace storytellers. It makes the best ones exponentially better. Your role as a PMM isn’t to write more copy. It’s to orchestrate AI-powered narratives that scale empathy, clarity, and emotion. #ProductMarketing #Storytelling #AI Post your best stories below!

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Performance agencies sometimes think they need to differentiate by building proprietary tech. I’ve seen that story many times — and I disagree. I recently had a check-in with two C-level execs at a performance agency. We’d been delivering exceptional results for their clients, including a $33 CPA using our machine learning optimization engine, compared to $120 manually. But performance wasn’t their focus. They'd decided to build new tech in-house. “If other agencies can use tvScientific,” they said, “we’re not unique.” It brought to mind the New York Times’ decision to build its own ad server — a costly, years-long detour that ended with a move back to DFP. The problem was a lack of clarity about what business they were really in and what they were positioned to excel at. The same applies to performance agencies. They’re not in the business of building ad tech (which is a constantly evolving, capital intensive business and is an entire business in its own right). They’re in the business of delivering outcomes. That means using the best tools available on the market and winning on superior client service. Not rebuilding tools from scratch. The edge comes from execution — knowing how to evaluate, adopt, and apply best-in-class technology to drive better results. Trying to be both a tech company and a service business is a recipe for subpar results on both fronts. Instead, invest in identifying cutting-edge technology, use it better than your competitors, and deliver both superior results and superior client service. That’s the path to agency differentiation. Just my .02. More detailed thoughts on this topic in my weekly newsletter (see comments).

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I’ve been testing every workflow I can find. And this is the playbook that changed how I ship products: 1. Start with AI for velocity In 15 minutes, I can draft 5 landing pages or campaign frameworks. It’s the fastest way to brainstorm at scale. Other folks move fast, you need to move faster! 2. The stall point AI outputs aren’t production-ready. No integrations. No polish. No durability. This is where most teams lose momentum. 3. The unlock: hiring Fiverr experts asap I dropped my AI blueprints into Fiverr. Found devs + designers in under 48 hours. They shipped a fully functional build FAST (Hire here + get 10% with my code LINDSAY10!!! https://lnkd.in/gugD3Sdb) Allowing me to GTM, get in front of customers, scale further. So yes, but all means dive in with every AI tool out there. But don’t get stuck prototyping, prompting, vibing…. …and actual launch, partnering with leading pros. If you’ve been drowning in AI ideas but struggling to ship, steal this workflow. Fastest way I’ve found to get from raw concept → real product. #FiverrPartner

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DTC is not dead. It just grew up. Once upon a Shopify boom, pure DTC looked unstoppable. Then: 📉 CPMs spiked, iOS crushed targeting, and lookalike gummies flooded your feed. Now? The smartest brands are done chasing ROAS. They're using DTC as leverage, not the endgame. 🧪 Your .com isn’t the profit center. It’s the R&D lab Run micro-tests, experiment with bundles, pricing, and creative. Scale only what proves it can win. 📊 Retail buyers don’t care about branding mythos They care about SKU velocity heatmaps and LTV by ZIP code. Walk in with a dashboard, not a vibe. 🛒 Omnichannel does not mean being everywhere Real operators treat Amazon, TikTok Shop, Target and their own site as connected nodes. Inventory, loyalty, and pricing are fully synced. 🤝 Influencers are shifting to equity deals Welcome to influence-for-performance. If they don’t believe in your product long term, neither will their audience. 🤖 AI is now the operating layer From AOV optimization to creative generation to real-time CX agents, AI quietly powers the entire DTC engine room. The result? Brands that start DTC, but don’t stay DTC. They test, learn, and scale profitably across every channel. Being “DTC-smart” in 2025 means this: 💡 You don’t pick between marketplaces, retail or .com You make each one smarter with the learnings from the others. #ecommerce #dtc #marketplaces #retailstrategy #shopify #omnichannel #ai #brandbuilding #growthmarketing #channelmojo

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"Young people don't really make life decisions without asking ChatGPT what they should do. It has the full context on every person in their life and what they've talked about." This is a direct quote from OpenAI CEO Sam Altman at a Sequoia Capital Q&A event. His statement is deeply concerning on a number of levels, and although most people have their blinders on when it comes to generative AI and its overwhelmingly net negative effect on society, this highlights a much deep issue than intellectual property ethics... Picture this; your high school daughter is spilling her guts into ChatGPT. Everything that happens at school, with her teachers, among her group of friends...her parents. It's an extremely complicated age where kids are becoming young adults and discovering themselves. To OpenAI this data is worth more than gold, and teens using ChatGPT this way makes their eyes light up with product stickiness. What Sam Altman and his Silicon Valley cronies are bragging about is incredibly dangerous. A process of self reflection/critical thinking has now been offloaded onto a piece of software that stores every single detail about you, your friends, family, and emotional state. A report from Common Sense Media found seven out of 10 teens have used at least one type of generative AI tool. A Harvard study on AI companionship found that 30% of children who regularly engage with AI chatbots feel emotionally attached. This isn't my opinion, it's a fact. Altman's quote comes after his recent announcement that OpenAI will be launching a social platform - an advertiser monetization play after tens of billions of dollars have been invested in their tech with little to no ROI. I'm predicting the LLM's that power ChatGPT, Claude, Perplexity, etc. will be fully open-sourced in the next 1-2 years, leaving these companies with no data moat. Sam is 100% taking all of that deeply personal data your children share with ChatGPT and selling it to advertisers. It's the most rich contextual data that has been willingly acquired to date, and what will be done with it goes beyond most of our comprehension. Is this really the world you want our children to grow up in? So many people are throwing up their arms and bowing down to the tech overlords in fear of redundancy. They are the fastest growth machines for these companies preaching "adapt or die" striking fear into anyone and everyone vulnerable enough to listen. How productive is outsourcing our thinking to a bot that has no unique experience, empathy, or adversity? This isn't technological advancement, it's going to mark the biggest intellectual decline in history, in a society that already struggles to think for themselves. By allowing these "tools" to exist at all costs we're teaching our children that their worldview and personal judgement is meaningless. The safe thing is to ask ChatGPT... It's time to wake up and stop promoting these hacks as innovation. The next generation depends on us.

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