The old GTM playbook is broken: - Hire a bunch of reps - Get legacy category-leading tools - Have sales and marketing work in silos The new-school GTM playbook is run by RevOps + GTM Engineers. Here's how the top teams are doing it: 1️⃣ ICP Analysis • Export Closed Won + Closed Lost from the CRM • Feed both into Claude Code to find the patterns • Build the ICP model on 3 layers: firmographics, account signals, technographics 2️⃣ TAM Map Map the entire market that fits the ICP: • Apollo.io's company database • Ocean.io for lookalikes companies • AI Ark for keyword search • Clay's database for extra companies 3️⃣ AI Account Research Enrich every account at scale: • Apollo.io for firmographics • Claygent + Claude for account-fit signals • Exa for deep web research • Sumble for technographics • Findymail for social signals 4️⃣ Tier + Score • Split accounts into Tier 1, 2, 3 • Score each one by awareness stage: • Identified → Aware → Interested → Considering → Selecting 5️⃣ Contact Sourcing Find and validate the buying committee: • Combination of Clay + AI Ark to source contacts • Findymail to find and verify emails • BetterContact for phone numbers 6️⃣ Demand Generation Only now do you turn on the channels, and all three run together on the same RevOps foundation: • Content: LinkedIn, X, Website • Outbound: LinkedIn, Calls, Email • Ads: LinkedIn, Meta, Google 7️⃣ Meeting Booked • Clay routes the lead to HubSpot • Cal.com books the call 8️⃣ Sales Process • Ergo for account intel before every call • Nooks for dialing • Apollo.io + HubSpot to run the pipeline • Qwilr for proposals • Claude as the copilot through all of it 9️⃣ Closed Won Every closed won account feeds the engine to find more lookalike companies. Save this for your next GTM build. Follow Fivos Aresti for more GTM playbooks. | 46 comments on LinkedIn

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Planning your GTM strategy for 2026? Here’s the ultimate cheat sheet ⚡️ From CRM and email finders to AI agents and outbound tools - this is the full-stack setup for modern GTM teams. We also added top LinkedIn experts, YouTube channels, and newsletters so you can learn and execute - all in one view: So check them out: ✅ Tools for GTM Operators CRM → Close, Attio, folk, HubSpot, Salesforce Email Finders → Clearbit, LeadIQ, Snov.io, Prospeo.io, Findymail Copywriting → ChatGPT, Claude, Gemini, Mistral AI, Perplexity Email Outreach → Reply, Smartlead, Salesforce, Unify, Hunter AI Agents → Jason AI, Clay, Persana AI, Lindy, Cassidy ✅ LinkedIn experts you must follow: 🦾Eric Nowoslawski Anthony Pierri Maja Voje Alex Fine🌲 Florin Tatulea Amy Volas Alex Vacca 🧠🛠️ ✅ YouTube Channels: GTMnow SaaStr.ai Lenny's Podcast ProductLed Drift, a Salesloft company Growth Tribe Dan Martell Refine Labs ✅ Podcasts: Go To Market The GTMnow Podcast Go-to-market Mavericks Go-to-Market Playmakers GTM Made Simple GTM Live Save it. Share it. Build with it✨

We are heading into one of the most profound demographic transformations in modern history, and it will reshape how we think about channels and partner ecosystems. The generational handoff is accelerating — by 2030, millennials and Gen Z will represent more than two-thirds of the workforce, and their buying preferences are fundamentally different. Today, millennials represent 51% of our buyers in the $5.3 trillion technology and telco industry. They expect digital, self-service, subscription- or consumption-based experiences, and they don’t follow the same linear paths to purchase that older generations did. At the same time, the demographic makeup of partners is shifting. The traditional VARs and MSPs that built their businesses on reselling hardware or managing infrastructure are expanding their businesses to serve the customer before, during, and after the purchase in 3.2 different business models. Younger buyers trust peer influence, community, and marketplaces more than direct sales. 75% of them don't want to talk to a human. They transact in multi-partner, multi-platform ecosystems, where value is co-created rather than sold. This means that success in the channel is no longer about a singular transaction at the point of sale. It’s about surrounding the customer with the right partners at the right time across their lifecycle. The vendors who win will be those who map, engage, incentivize, and co-create value along every moment of the customer journey. Now the data... The world just surpassed 8 billion people. Labor force participation is 54% (4.3 billion) with 1.7 billion employed by others/themselves and 2.4 billion self-employed or informal workers. Global unemployment (for those participating in labor force) is 5% or 229 million people (this number is rising daily). Many countries are expecting downward trends in population and labor force: -- China just peaked at 1.4 billion people and is expected to shrink each year (to 639 million by the year 2100). -- India will peak at 1.7 billion by 2060 and then shrink to 1.5 billion by 2100. The U.S. is expected to grow steadily from 347.6 million today to 421 million by 2100 but is dependent on immigration (supportive government policies) and not birth rates. Africa is expected to double in size. What does this mean for channel chiefs? -- In cybersecurity ($282 billion), 40% of the market TAM is in SMB/managed services. -- AI infrastructure, expected at $7 trillion over next 5 years, 81% will land in large enterprise and government. -- The $1 trillion software market is 2/3 large enterprise and government. -- Telco? (63% SMB). PCs and printers? (60% SMB). UC? (73% SMB). Demographics play a key role in how, where, and with who we win with. | 29 comments on LinkedIn

I built this Clay table that my reps love because they say it gives them an unfair advantage. It boosts win rates and saves hours every week. Here’s how it works: – Every time we close a deal, the table finds lookalike accounts. – It enriches those accounts with company data, key personas, and direct contact info. – Then the AI goes to work. It pulls top competitors, company highlights, open roles, and even writes cold email snippets tailored to each persona. – All of that gets packaged into a Google Doc dossier and automatically dropped into Slack so reps have everything they need at their fingertips. I’ve led ABM at 2 ABM companies (Engagio and Demandbase), so I know how powerful truly personalized outreach is. But I also know how brutal the research grind can be. This makes it 100x easier and faster. What used to take hours now takes minutes. I would have KILLED for this setup a few years ago. Now it feels like there’s no ceiling. And the best part is you don’t have to build this from scratch. I’m giving away the entire template so you can copy + paste it straight into your Clay instance. I’ll also show you exactly how to set it up, integrations included, in under 7 minutes. Check out my Stack & Scale newsletter for the full walkthrough. Or comment “Clay template” below, then connect with me (I'm out of InMail), and I’ll send you the link. | 789 comments on LinkedIn

The 250 Words That Make People Hit Delete (In 0.3 Seconds) Fall outreach season is coming. You know what that means - your inbox is about to get flooded with the same tired phrases everyone else is using. A sales training team just finished analyzing thousands of deleted cold emails. Want to know what they found? There are exactly 250 words and phrases that make prospects mentally check out before they even finish reading your subject line. Your brain is wired to recognize patterns. And these phrases? They're the pattern of every bad cold email ever sent. Most people don't even realize they're using these phrases. They just copy what everyone else does. But here's the secret: Your prospects delete emails in 0.3 seconds. That's how long it takes their brain to recognize the pattern. Training Your AI to Avoid the Death Phrases If you're using ChatGPT, Claude, or any LLM for outreach, add this to your system prompt: COLD EMAIL FILTER: Scan for these 250 death phrases [insert list]. If found, rewrite using: - Specific observations about their company - Direct value statements (no fluff) - Conversational tone (like texting a friend) - One clear ask - Zero buzzwords Red flag any email that sounds like it could be sent to anyone. The magic happens when your emails feel like they were written by a human who actually researched the company. What Works Instead Skip the pleasantries. Get specific. Be direct. Instead of "I was impressed by your profile" → "Saw your post about expanding into the NY market" Instead of "We help companies like yours" → "Helped [specific competitor] increase NY sales by 34% last quarter" Instead of "Quick question" → Just ask the actual question. Your prospects can smell generic from a mile away. But specificity? That stops the scroll. If you don't have that, why are you reaching out? As we head into fall outreach season, remember this: Everyone else will be using these 250 phrases. You won't. And that's going to make all the difference. | 69 comments on LinkedIn

Building your first sales team will be an endless series of mistakes. It’s OK.

There’s a big gap between the tools marketers are obsessed with and the ones they rely on daily. That gap is a major opportunity for disruption. In my recent survey on B2B marketing tools (via Typeform + LinkedIn), I asked: ❶ What tools are most critical in your stack? ❷ What tools are you obsessed with right now? 💓 A few tools that showed up on the obsessed list (that didn't rank very highly if at all on critical list): n8n, Warmly, Gamma, Lovable, Replit, Framer, Granola, Arcade, Lemlist 🧱 A few tools that showed up on the critical list (but didn't make the obssessed list): Salesforce, Google Suite, WordPress, Marketo, 6Sense, SEMrush, Tableau, Pardot Do you think this means that in a year's time more of the obsessed tools will show up on the critical list? | 70 comments on LinkedIn

Everyone says “prove marketing impact.” Cool. But how? Two weeks ago, I had a board meeting. We knew we would show pipeline results, of course, but I wanted to go deeper. Not just what we got… but why. So I started looking for signal instead. What actually predicts pipeline or revenue? - - - I ran this GPT prompt to analyze months of data: ✅ MQLs ✅ SQLs ✅ Website traffic ✅ Media ✅ Budget ✅ Events, webinars… ✅ ( Insert any of your input variables ) Then looked at how each input — and combo of inputs — correlated to pipeline and ARR. Lagged by 1–3 months. With interactions included. ( this is important! ) Built this with GPT o3. No PhD in stats. And honestly… not much time. RevOps was heads down on board prep. I needed directional insight fast. So I tried the whole thing by myself… After two hours, I had the answers I needed. Here’s the exact prompt I used. Yours to steal. 👇👇👇 - - - 𝑷𝒓𝒐𝒎𝒑𝒕: 𝑭𝒖𝒍𝒍-𝑭𝒖𝒏𝒏𝒆𝒍 𝑴𝒂𝒓𝒌𝒆𝒕𝒊𝒏𝒈 𝑰𝒎𝒑𝒂𝒄𝒕 𝑪𝒐𝒓𝒓𝒆𝒍𝒂𝒕𝒊𝒐𝒏 𝑨𝒏𝒂𝒍𝒚𝒔𝒊𝒔 𝐈 𝐡𝐚𝐯𝐞 𝐚 𝐝𝐚𝐭𝐚𝐬𝐞𝐭 𝐜𝐨𝐯𝐞𝐫𝐢𝐧𝐠 𝟐𝟒 𝐦𝐨𝐧𝐭𝐡𝐬 𝐨𝐟 𝐦𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐫𝐞𝐯𝐞𝐧𝐮𝐞 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞. 𝐈𝐭 𝐢𝐧𝐜𝐥𝐮𝐝𝐞𝐬 𝐦𝐨𝐧𝐭𝐡𝐥𝐲 𝐯𝐚𝐥𝐮𝐞𝐬 𝐟𝐨𝐫: 📥 𝐋𝐞𝐚𝐝 𝐈𝐧𝐩𝐮𝐭𝐬 • 𝑴𝑸𝑳𝒔 • 𝑺𝑸𝑳𝒔 🌐 𝐓𝐫𝐚𝐟𝐟𝐢𝐜 & 𝐄𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐒𝐢𝐠𝐧𝐚𝐥𝐬 • 𝑾𝒆𝒃𝒔𝒊𝒕𝒆 𝑻𝒓𝒂𝒇𝒇𝒊𝒄 • Content downloads • 𝑬𝒎𝒑𝒍𝒐𝒚𝒆𝒆 𝑨𝒅𝒗𝒐𝒄𝒂𝒄𝒚 𝑹𝒆𝒂𝒄𝒉 📣 𝐌𝐞𝐝𝐢𝐚 & 𝐏𝐫𝐨𝐠𝐫𝐚𝐦 𝐈𝐧𝐩𝐮𝐭𝐬 • 𝑷𝒂𝒊𝒅 𝑴𝒆𝒅𝒊𝒂 𝑺𝒑𝒆𝒏𝒅 • 𝑾𝒆𝒃𝒊𝒏𝒂𝒓 𝑨𝒕𝒕𝒆𝒏𝒅𝒂𝒏𝒄𝒆 • 𝑯𝒐𝒔𝒕𝒆𝒅 𝑬𝒗𝒆𝒏𝒕 𝑨𝒕𝒕𝒆𝒏𝒅𝒂𝒏𝒄𝒆 • 𝑺𝒑𝒐𝒏𝒔𝒐𝒓𝒆𝒅 𝑬𝒗𝒆𝒏𝒕 𝑨𝒕𝒕𝒆𝒏𝒅𝒂𝒏𝒄𝒆 🎯 𝐎𝐮𝐭𝐩𝐮𝐭𝐬 • 𝑴𝒂𝒓𝒌𝒆𝒕𝒊𝒏𝒈-𝑺𝒐𝒖𝒓𝒄𝒆𝒅 𝑷𝒊𝒑𝒆𝒍𝒊𝒏𝒆 • 𝑻𝒐𝒕𝒂𝒍 𝑷𝒊𝒑𝒆𝒍𝒊𝒏𝒆 𝑪𝒓𝒆𝒂𝒕𝒆𝒅 • 𝑾𝒐𝒏 𝑶𝒑𝒑𝒐𝒓𝒕𝒖𝒏𝒊𝒕𝒚 𝑨𝑹𝑹 1. 𝑺𝒕𝒂𝒓𝒕 𝒘𝒊𝒕𝒉 𝒂 𝒔𝒉𝒐𝒓𝒕 𝒄𝒂𝒏𝒗𝒂𝒔 𝒐𝒇 𝒕𝒉𝒆 𝒑𝒓𝒐𝒋𝒆𝒄𝒕 What we’re analyzing, why it matters, and what decisions it should inform. 2. 𝑪𝒐𝒓𝒓𝒆𝒍𝒂𝒕𝒆 𝒆𝒂𝒄𝒉 𝒊𝒏𝒑𝒖𝒕 𝒘𝒊𝒕𝒉 𝒆𝒂𝒄𝒉 𝒐𝒖𝒕𝒑𝒖𝒕, both: • Same month • 1, 2, and 3-month lag 3. 𝑨𝒏𝒂𝒍𝒚𝒛𝒆 𝒔𝒆𝒄𝒐𝒏𝒅-𝒐𝒓𝒅𝒆𝒓 𝒊𝒏𝒕𝒆𝒓𝒂𝒄𝒕𝒊𝒐𝒏𝒔, like: • MQL × Website Traffic • SQL × Paid Media • Event × Resource Volume 4. 𝑹𝒆𝒕𝒖𝒓𝒏 𝒐𝒏𝒍𝒚 𝒄𝒐𝒓𝒓𝒆𝒍𝒂𝒕𝒊𝒐𝒏𝒔 𝒘𝒊𝒕𝒉 𝒄𝒐𝒆𝒇𝒇𝒊𝒄𝒊𝒆𝒏𝒕 > 𝟎.𝟓, with lag + short interpretation. 5. 𝑰𝒏𝒄𝒍𝒖𝒅𝒆 𝒍𝒊𝒏𝒆 𝒄𝒉𝒂𝒓𝒕𝒔 for the top 3 correlations to show trends over time. 6. 𝑺𝒖𝒎𝒎𝒂𝒓𝒊𝒛𝒆 𝒕𝒂𝒌𝒆𝒂𝒘𝒂𝒚𝒔: • What are the strongest leading indicators? • Which combinations matter most? • Any high-effort programs with low signal? - - - If you’ve got a RevOps backlog, a marketing budget to defend, or just want to understand your own impact better, this prompt’s for you. It’s yours. Run it as-is or make it better. And if you’ve got your own favorite signal? Drop it below. | 34 comments on LinkedIn