Davin YC Dong

Your next 90 days as a 7-8 figure DTC brand: (to maximize revenue & profitability in Q1) 𝗪𝗲𝗲𝗸 𝟭-𝟮: 𝗧𝗵𝗲 𝗔𝘂𝗱𝗶𝘁 Pull every ad that scaled during Q4 and dissect why it worked. Not just the surface-level metrics. The actual angle, hook, messaging, and emotional trigger that drove conversions. This becomes the foundation for everything else. 𝗪𝗲𝗲𝗸 𝟯-𝟰: 𝗜𝘁𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗦𝗽𝗿𝗶𝗻𝘁 Take each winning concept and create multiple variations. → New hooks → Different creators → Fresh visual styles → Less aggressive offer →Same core angle. 𝗪𝗲𝗲𝗸 𝟱-𝟴: 𝗔𝗻𝗴𝗹𝗲 𝗘𝘅𝗽𝗮𝗻𝘀𝗶𝗼𝗻 Q4 messaging was urgency, gifting, and deals. Q1 messaging goes in-depth on solving real problems, and why your product is the answer. Develop entirely new concepts built around these triggers while our iterations keep the account stable. 𝗪𝗲𝗲𝗸 𝟵-𝟭𝟮: 𝗦𝗰𝗮𝗹𝗲 𝗦𝗲𝘁𝘂𝗽 By March, you’ll have a full pipeline of tested concepts ready to scale into Q2. No scrambling. No starting from zero. Just compounding momentum. Most brands make the same mistake every January. They strip the offer from their Q4 winners and ride them until they burn out. Then they panic when February hits and nothing is working. By March, they're starting from scratch with zero momentum. This roadmap is how you prevent that.

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Speed up your CRO process with AI prompts that actually work. What used to take hours now takes minutes. Want higher conversion rates? These GPT prompts help you work faster and drive real results: → Analyze your user behavior with precision. → Generate creative test ideas backed by psychology. → Write better A/B test hypotheses. This process is fast and effective. Built on behavioral psychology, 3,300+ A/B tests, and proven frameworks. 𝗪𝗮𝗻𝘁 𝗮𝗰𝗰𝗲𝘀𝘀 𝘁𝗼 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗹𝗶𝘀𝘁? 1. Like this post 2. Comment "PROMPTS" and I'll sent it to you.

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Top DTC brands obsess over retention Using these 4 charts: 1. Cohort Reorder Percentage - Segment customers by the month they first ordered. - Track how many total orders that cohort places over time. - Each line in the chart is a different cohort. - Some cohorts average 1 order per customer. Some hit 3x. Why it matters: -> Removes AOV from the equation -> Shows if your retention is actually improving month over month -> Tells you which acquisition channels bring back buyers vs one-and-dones 2. Monthly Returning Revenue - In what month do customers come back? - Month 1? Month 3? Month 6? - Plot the returning revenue by month after first purchase. This tells you: -> Your natural repurchase cadence -> When to time email and SMS -> Where your lifecycle gaps are 3. Monthly Returning % This is the simplest view. - Stack new vs returning revenue each month. - Watch the blue (returning) grow. - It's cumulative. Non-cohort. - Easy to track and catch big changes/trends To think about: - You want to see returning revenue becoming a larger share of total revenue every month. - If it's flat or shrinking while you scale? Your acquisition quality is slipping. 4. Total Revenue by Cohort Similar to the first, but includes AOV. - Shows how much total revenue each cohort generates over time. - You can index this as a percentage too. - This is the chart your CFO normally wants to see. - Most brands pick one retention metric and stop there. Each of these 4 charts tells you something different: → Cohort reorder % = are we getting better? → Monthly returning revenue = when do they come back? → Monthly returning % = how dependent are we on new customers? → Total rev by cohort = what's the actual dollar impact? Track all four. Compare them. Decide where to focus How are you currently measuring retention? --- P.S. Going to write a long form Substack on this v.soon Excited to share it. (Subscribe in Featured Posts)

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Classical PM grew out of a world where simply understanding "what to build" carried enormous transaction costs. To formulate a hypothesis, you had to conduct dozens of interviews, manually synthesize insights, write a 20-page PRD, align it with five stakeholders, prioritize through RICE, compile a competitive analysis, and draft a roadmap. All of this was deeply artisanal work that demanded a very specific skill: the ability to translate the chaos of reality into structured artifacts. And it was precisely this ability that served as the main barrier to entry into the profession. Now LLMs are doing the bulk of this work: interview synthesis, user story generation, competitive analysis, spec writing, backlog prioritization. A startup founder who used to hire a PM because they couldn't structure their own product chaos now feeds their notes into Claude or ChatGPT and gets a perfectly decent PRD in minutes. The bulk of what junior and mid-level PMs did was essentially the work of a data entry operator. Packaging information into a polished format. Translating from the language of business into the language of engineering. Turning the obvious into Jira tickets. This layer is already visibly melting away. Why hire an associate PM to spend a week writing a spec when a GPT wrapper produces a draft in minutes and a senior PM polishes it in an hour? But there's a nuance. The real value of a product manager was never in the artifacts. It lay in three things: 1. Taste - an intuitive sense of what the market needs before the market itself realizes it; 2. Political navigation - the ability to push the right decision through an organization where everyone has their own agenda; 3. Ability to say "no," because 90% of product work is not about what to build, but what NOT to build. An LLM doesn't know how to say no, it's a yes-machine. It has no stance, no accountability for outcomes. And that's exactly why product management won't disappear, but it will thin out dramatically and transform — much like those camera operators who no longer need to understand the chemistry of film development, but still need to see the shot.

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ByteDance’s Seedance 2.0 is legit strong. Yes—many things will eventually get “swallowed by the platform/model.” But the time window before that happens is often where startups win. Every frontier model will ship its own agent. Honestly, using Claude 4.6 already feels less like a chatbot and more like an agent. If you took me back to late 2024: would I not build something like Manus? No. I’d still do it. Not because “wrappers have value.” Because stage wins are still wins—they compound into taste, iteration speed, and real product insight. Build.

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Retention teams are quietly impacting acquisition at the best DTC brands. Walk through the actual work happening inside a top 50 DTC brand right now and you'll see retention marketers making decisions about pop-up logic, opt-in software, landing page offers, and traffic-source targeting. That used to be exclusively growth's or paid's job. It's changing because the math changed. The brands that figured out retention could subsidize acquisition costs started winning more in paid channels. Not because their ads got better but because their post-click infrastructure got better. So now everyone wants that. And a lot of the people who know how to build it sit in retention.

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Thrilled to announce that Together Fund is investing in Sentra, alongside a16z speedrun! You track results in Jira. Decisions in Notion. Conversations in Slack. But the reasoning, the debates, trade-offs, and context behind why you chose A over B, disappears into what we call "Dark Matter." A decision made in March looks insane by July because no one remembers the constraints that made it smart. I lived this firsthand at Twitter scaling from 800 to 8,000 employees, and at Google while launching AI Overviews to billions at planet scale. The problem isn't process. Process is compensation for something deeper: organizational amnesia. An organization’s "Systems of Record" doesn’t solve this, they encode it. They store what happened, never why. That's why we are investing in Sentra. Sentra is the always-on collective memory that eliminates organizational amnesia by maintaining accurate context for all members and agents, functioning as an operational nervous system. It connects to every channel where work happens, meetings, Slack, email, code commits, docs, calendars, and treats them not as artifacts to search, but as living signals to synthesize. The fleeting and the permanent, unified into a memory that understands. The founding team is built for this: - Jae Gwan Park (CEO): Product-first founder, memory systems research at UofT and MIT - Ashwin Gopinath (CSO): Former MIT professor, created "Reflexion" (NeurIPS 2023), agents that learn from mistakes, 2x founder - Andrey Starenky (CTO): Early Vapi engineer, ex-IBM, built to process enterprise-scale data firehose Together is an operator-led fund. We invest in problems we've lived. This is one of them. Many congrats Jae, Ashwin and Andrey, we are so excited to partner with you! Read the full thesis: https://lnkd.in/gixj9cE4 Book a demo: https://www.sentra.app/ #OrganizationalMemory #AI #Sentra #TogetherFund #a16z #ContextGraphs

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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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𝐓𝐡𝐞 𝐏𝐞𝐫𝐟𝐞𝐜𝐭 𝐏𝐢𝐭𝐜𝐡 𝐃𝐞𝐜𝐤 𝐓𝐞𝐦𝐩𝐥𝐚𝐭𝐞 This deck shows the exact story flow VCs expect—based on hundreds of funded pitch decks. It’s not about design. It’s about sequencing. Key Takeaways: 1️⃣ Hook first – Capture attention fast with a clear problem and why now. 2️⃣ Prove it early – Traction, usage, and momentum beat feature lists. 3️⃣ Reduce risk logically – Team, advantage, economics, and competition should build confidence step by step. Bottom line? Winning decks don’t impress—they create conviction. PS. check out 🔔 for a winning pitch deck the template created by Silicon Valley legend, Peter Thiel https://lnkd.in/eQFrsUnE

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The relationship between paid and organic has always been complex. AppsFlyer just took a major step toward resolving that. Every team says they work together. But some companies still structure them as siloed functions with different KPIs. Paid might sit with an external agency while organic sits with product or growth. These teams might not share the same goals, leading to friction. Even when paid and organic sit together under one team, the measurement gap means there’s no clear picture. When budgets get tight, something predictable happens. Teams expect organic to absorb the impact of reduced paid. But these channels were designed to complement each other, not replace each other. Growth is strongest when both sides of the journey are connected. Meanwhile, paid is fighting to justify spend without the full picture. Everyone is staring at blended numbers that tell you nothing about how growth actually works. Yesterday AppsFlyer introduced something that can finally change that. Cross-Platform Journeys & Lifetime Value. What makes this meaningful is not the feature set. It’s what it unlocks for teams that have been trying to quantify influence with incomplete data. For years, we’ve known paid media has a halo effect on organic. We see spikes. We see patterns. We feel the impact. But we haven’t been able to prove it at scale. This changes that. By connecting mobile, web, CTV, PC and everything in between, this creates one unified user story. It surfaces the true source of revenue, not just the channel that gets the final credit. It shows where efficiency actually comes from. And it reveals where budget is driving value far beyond the first touch. AppsFlyer shared early results yesterday. Uplifts of 27% to 65% in attributed LTV. ROAS increases up to 50%. Entire categories discovering revenue that was sitting under “organic” because the attribution wasn’t there. As someone who has sat in leadership conversations where teams debate over the same incomplete picture, this is the unlock we needed. Paid finally gets credit for the growth it influences. Organic gets clarity around what is genuinely organic. And teams get the data they need to defend budgets with confidence. One team. One journey. One LTV view that finally removes the guesswork. Curious where you stand on this. Do you think a unified journey will change how your company invests, or will it take time for this shift to fully land?

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I was chatting with my partner Jackson Blackledge about the moves 7-8 figure DTC brands should be making to crush this BFCM. The same team that’s pulled in $195M+ in Q4 revenue for 100+ brands had some solid advice about Google ads: 1. Optimize, don’t rebuild Layer BFCM messaging on top of what’s already working instead of starting fresh campaigns. 2. Front-load budget so Google can fully participate in the surge of traffic without choking your ROAS. When BFCM hits, search volume explodes. If your daily budgets are tight, Google can’t spend enough early in the day to enter auctions, learn, or scale. So your ads either don’t show, show late, or lose to competitors with bigger budgets. 3. Optimize Merchant Center Promotions, discounts, and shipping details need to be spot-on for your ads to perform. Those tiny offer badges can make a huge difference in who actually clicks your ads. During BFCM, competition spikes. People search “Black Friday [product]”, and if your titles, promotions, or discounts aren’t updated in GMC, you lose clicks to competitors. 4. Use time-based creative Schedule your search and Performance Max assets to match the customer journey: early-bird, Black Friday, Cyber Monday, and last-chance messaging. 5. Warm up and retarget Build audiences early and hit them post-BFCM with short, targeted video ads to turn traffic into profit. All of this helps you win attention during BFCM. But attention only matters if you can hold onto it. The brands that crush Q4 make sure traffic sticks around with smart retention and lifecycle moves, turning clicks into loyal customers. To actually make sure your Google Ads account is ready for Q4, ask yourself these five questions: Q#1. Should you launch new campaigns for BFCM or optimize what’s already running? Q#2. Are your budgets and bids set to protect ROAS during high-volume spikes? Q#3. Are your Merchant Center promotions fully optimized to capture clicks? Q#4. Is your search ad copy scheduled and adapted for each stage of BFCM? Q#5. Do you have retargeting audiences ready to convert warm traffic post-BFCM? Here’s the breakdown from Echelonn on all five questions: https://lnkd.in/gS2xcVcu

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