Sales AI Tools & Tips

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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

Find out Thibaut's tip on how to deal with emotional buyers

The sales cycle is the step-by-step process by which you convert opportunities into buyers. Each of the 6 stages has its own skills worth mastering.

Most companies are blind to their biggest revenue growth lever - so we built an Agent to fix it 👇 So, your biggest revenue growth lever? → Not net-new → Not marketing → Not outbound It's expansion. But there's a problem: The signals are everywhere - Product usage, tickets, calls, stakeholder sentiment… But no system connects it together. And triggers action. So upsell gets missed. Again. And again. We fixed that. Raw Data → Context → Signal → Action → Continuous Learning It's the "Expansion Agent". ⚙️ Step 1: Turn Raw Data → Context Expansion signals already exist: 📈 Usage spike in a new department 🌍 Support tickets from a new region 💬 “Does this integrate with X?” 📞 Positive sentiment in transcripts 🙋‍♂️ Exec shows up unannounced to a call We connect to your raw GTM data: → CRM → Product usage → Support → Calls → Meeting notes → Emails Not to report. To understand what it means. And build customer models. That give each customer a "digital twin". So you can track "risk" and "expansion" potential. 🤖 Step 2: Deploy the "Expansion" Agent. It works 24/7 across your customer base. Signal → Action: 🧠 Identifies signals across every account 📬 Sends live alerts in Slack and your CRM 📊 Explains why it matters ⚡ Recommends action - generate email, collaborate with AE, prep QBR 🔁 Automatically updates CRM What I particularly love? 📌 The CSM and AE can speak to the Expansion Agent - in Slack. It's like "multi-player" mode. 🏃‍♂️ Step 3: Act Before the Moment Passes When a customer is ready to expand: 🔥 Slack lights up 🧠 CSM understands the context 📣 AE is looped in 📋 Next steps are clear 🟢 Expansion is landed The system spotted it. The team captured it. Before the customer even asked. 🧠 What Makes This Possible? GTM Intelligence Infrastructure. The semantic layer that: → Connects structured + unstructured data → Adds memory + context across accounts → Reasons in real time → Powers a "swarm" of GTM Agents This is how modern GTM scales: Less noise. More signal. Real action. ⚙️ We're releasing more hyper-specialised GTM Agents in Slack: → The Deal Agent → The Churn Agent → The Pipeline Review Agent → The Product Feedback Agent → The Win/Loss Agent → The Prospecting Agent Modern GTM Leaders know the best opportunities are hidden in their customer base. And they're building systems to signal → action expansion. 🔔 Follow for the latest on GTM and AI from Revenue Labs and our R&D Studio 📬 Rebuilding GTM with AI? Or thinking about it? I love to connect with forward-thinking leaders - drop me a DM.

Stop guessing your GTM. Steal our $2,530,000 playbook below 👇 At RevGrowth, we've generated $2.5M+ in new pipeline for just one of our customers in the last 3 months. (Results pinned in comments) So we decided to breakdown their winning playbook. From these insights, we were able to extract key levers and covert it into a replicable "GTM handbook" for B2B revenue teams to have in their back pocket. This handbook covers everything from: → GTM Strategy Development ↳ 3 AI prompts for deep market research, TAM mapping, and ICP validation. → Lead Sourcing ↳ How to use deep research for discovering niche databases & our go-to contact enrichment workflow. → Data Enrichment ↳ Breakdown of our Clay contact enrichment, web data scraping, and AI qualification workflows. → Infrastructure ↳ Best infrastructure tools and protocols for maintaining perfect deliverability. → Testing & Optimization ↳ Highest leverage metrics to track and best practices for optimization. → Messaging ↳ 6 plug-and-play messaging templates that have been validated across 20+ industries → Technology ↳ Top 46 tools and databases to leverage for advanced GTM motions. Want this GTM handbook for yourself? 👉 Like + Comment "Handbook" and I'll DM you the downloadable PDF. [ Must be connected to receive ] | 449 comments on LinkedIn

My friends' startup followed Jobs-to-be-Done (JTBD) religiously for 5 years. It almost ran them off a cliff. We just published our conversation with Troy Sultan and Austin Cooley (co-founders of Guide) who built 5 different products to $1M ARR over the course of eight years and two companies. For them, the JTBD trap looked like this: • Customers told them exactly what they wanted • They spent months trying to "uncover the real job to be done" • While they debated semantics, competitors shipped the obvious feature • Deals slipped away They told me: "We would hear customers telling us what they wanted for years. We'd be like, 'but what's the real job to be done?' We'd go spend cycles for months trying to invent some novel solution." What broke the cycle? They decided to put pragmatism over purity: just solve the problems, win the deals, and worry less about ideology. "We used to get energy from big visions. Now we get a lot of energy from winning deals week to week. Going to win that deal against that competitor really energizes us." How they operate today: ↳ Customer flags a problem? Ship the fastest fix. ↳ Deliver in days, not months ↳ Focus on tangible, real-world wins (actual revenue, not hypothetical product futures) ↳ Let the market pull you The biggest change in their approach: they stopped obsessing over frameworks and started caring about what actually closes deals. And they're growing faster now than any attempt before. My takeaway: frameworks are supposed to help you, not tie you up in knots. Sometimes what the team really needs is the energy that comes from customers paying you. Not from another vision deck. Where does your team get more energy: chasing huge visions, or from stringing together a bunch of real wins? Spotify: https://lnkd.in/exVJe4e6 Apple: https://lnkd.in/eUNXcv4j YouTube: https://lnkd.in/epTh56HJ Substack: https://lnkd.in/eR7D4ZRB | 56 comments on LinkedIn