I used to worry about silly things in my cold email campaigns. 5 years later, this is what I worry about and what I don't worry about. 1. Which tool I'm sending from. My brother and sisters in outbound, the underlying technology of how Smarltead and Instantly send email is the largely the same. Pick who you like the feature set of more and move on. 2. Does email warmup work and what are the perfect warmup settings. If email warmup didn't work, the platforms offering it unlimited for free would be the first people to ask you to shut it off so they could lower their AWS bill. I don't think there are perfect email warmup settings. As long as it's sending something and getting replies back it's fine. 3. Triple Validating Leads We validate our emails with million verifier before sending and enjoy the usage of bounce ban verified emails by using the Prospeo API. It's all going to be alright. 4. Spam words in my copy. Ok if you send "Bitcoin" or "jesus" or "oprah" you're going to have issues. But I see people asking questions in chats all the time about the word free or something. And it's ok in moderation. If you think you're having issues, pull it out and see if it improves. 5. The quest for email deliverability knowledge that no one else has. Any gimmick or strategy outside of the tried an true things we talk about on here all the time turns out to be a quick fad if it works at all or really not true. 6. 3rd party tools to tell if you're emails are going to spam Just check the reply rates of your domains... 7. Focusing on everything all at once in the copywriting vs spending 80% of my time on how I pitched the offer of what I'm helping to promote 8. Wondering if different email providers get better results than the others. Of course we use Hypertide.io and Zapmail.ai but if the provider you're using is fast and gives you access to the admin console, you're all set. 9. This might not fit as a worry, but you should run more tests than you think and see how the best brands run facebook ads. It's no different. Cold email is just a private ads network. 10. Working with a client where their website/case studies/social content wasn't dialed in. Yes that all helps but we run free tests where people can't look up the company and are just responding to the offer and it works all the time. What would you add to the list? | 16 comments on LinkedIn

We're cutting our AI token spend by over 90% with one platform. Taking screenshots of technical websites is all you need to know how to do. Vast(.)ai has made it really easy to upload any open source model (I went with OSS 120B and OSS 20B) and we are calling it with the API. On one GPU that I can rent for less than 75 cents per hour, I cranked it up to 16 requests per second with my test prompts that had about 10,000 input tokens in them. At these rates, 90% is actually an underestimate. It's probably approaching 95-99%. I can't even give you a tutorial because I literally just asked ChatGPT how to set it up and took screenshots along the way when I had issues so here's some use cases we are using it for. 1. Finding the business owner of a local business. They don't often have linkedin profiles but will tell their story on their page. Basically free to go 2-3 levels deep on the website and get the content for OSS 120B to find the owner's name. 2. ICP classification of companies. We can make the prompt as long as we want with as much input as we want in order to get the best results. 3. Org Chart Mapping Lots of data can be passed in to the AI with the JSON of linkedin profiles and connections can be drawn by department, location, and self reported team affiliation on their profile. 4. Finding the right target to reach out to. Now you can get every contact in a department and pick the best one in order of your preferences. 5. Keep going further than ICP Classification and get all of the content from websites and learn anything about your prospect's public facing content. With basically unlimited AI throughput, it feels that almost anything is possible now. | 20 comments on LinkedIn

What separates outbound that works from outbound that breaks? Three things. 1. STRATEGY ❌ Bad outbound: → Weak offer that sounds like everyone else → Too broad, no real ICP → Random messaging tests → Value saved for the call ✅ Good outbound: → Clear outbound-specific offer → ICP with buying pain → Defined positioning → Value delivered before meetings Your offer needs to work for cold contacts, not warm leads. How: Test your offer on 10 cold prospects before scaling. If they don't respond asking for more, your offer isn't strong enough. 2. SYSTEMS ❌ Bad outbound: → Poor inbox setup → Too many disconnected tools → No meeting metrics → Breaks when scaled ✅ Good outbound: → Strong deliverability infrastructure → Clean data → Clear metrics → Simple workflows → SDR and sales alignment You can't optimize what you can't measure. You can't scale what breaks at volume. How: Build infrastructure for 10,000+ daily sends from day one. Deliverability, domain rotation, reply handling. What works at 200 sends will kill you at 2,000. 3. EXECUTION ❌ Bad outbound: → Inconsistent volume → Burned inboxes → Replies with no intent → Meetings that go nowhere → No control over output ✅ Good outbound: → Consistent volume → Safe sending → Replies driven by the offer → Qualified meetings → Predictable pipeline Volume without quality is noise. Quality without volume is luck. Both need to work at scale. How: Track what qualifies as a real meeting. If your SDR and sales definitions don't match, your metrics are meaningless. ❌ Bad outbound tries to fix execution with better copy. ✅ Good outbound fixes strategy and systems first. Then executes at volume. Founders skip straight to execution and wonder why nothing sticks. We prove it works before you pay. 3-4 qualified meetings. You verify ICP fit. Apply for a pilot: https://bit.ly/C17Pilot Repost to help others fix their outbound. Follow Enzo Carasso 🧲 for infrastructure that scales. | 75 comments on LinkedIn

An underrated Clay benefit is “how it teaches you to think” A wide gap exists in almost every GTM org I’ve met with, between conceptual ideas of where they want to be Vs what their current day to day workflows and tasks look like Tools do not fix this alone, you need to learn to think differently Given the most powerful algorithm for calculating micronutrient deficiencies, most people cannot solve for “getting more l-theanine” on their own You could say that to them - and they’d move on - no benefit derived - even if it is true Had a convo today and was challenged by a customer: “what if their data isn’t better? What if their signals aren’t better than other signals?” It’s a fair impulse to ask this sort of thing, but highlights the gap in worldview Many companies today are nerfing themselves They are losing ground, because of ground gained in years prior What winning looks like today isn’t the same as 2025 and isn’t the same at all vs 2020 Back to Clay (not a sponsored post) Clay has changed the lives of more “used to be good at sales development and want to go to the next level” people than any other tool on the market The big crms aren’t doing this - the market was too mature already - revops technical solutions come from known Revops ecosystems Mature frameworks, copy pastable workflows, etc It’s comfy to buy a known future… contained boundaries Clay is wall to wall blackboard, a fresh box of chalk, and an eraser You walk up, you start from the first line, and over time you can do whatever you can imagine The limiting factor for sales dev people is often technical acumen - using the tool will guide you, with iteration, like those early cold calls you stumbled through Don’t give up The limiting factor for technical people is often creativity and tactical familiarity (aka all the stuff 💜 🔮 Will Allred posts, among many others) This batch needs to just send it - let themselves fall on their face - and iterate forward as well; similar to making those first cold calls, stumbling through the ups and downs, and one day finding yourself quite alright at this weird little skillset If your company doesn’t want to fund those early stumbles - that’s where this big bright ecosystem of service business exists - many inside GTMCafe.com where we convene weekly for a mastermind of GTM excellence (free to all, no better space) The future will be orchestrated by talented, in the know people, with more asymetrical impact than ever before Weapon of choice? Clay (among others - but this is sincerely where you should start) | 19 comments on LinkedIn

One of my clients texted me this picture of a post (actually an ad 😉) from my friend Hans and asked me if I agree with it. The answer is a definitive yes. I absolutely agree. Relevance and a high quality offer will ALWAYS beat personalization in terms of setting meetings and converting new opportunities. But they don't necessarily do the same thing. Relevance beats personalization in terms of generating legitimate interest in whatever it is that you're selling. This is why signal based outreach is so dang important vs. only completely cold outreach and high volumes (although this works too. Just varies by offer/company). Personalization definitely does help too, but it plays a different role. RELEVANT personalized lines make people feel heard and understood, which has a slight improvement on positive response rates. But more importantly, it helps from a deliverability perspective. It helps you bypass spam filters and land in the primary inbox more frequently when sending email campaigns. ESPs are using AI to determine whether you're a spammer or a legitimate sender. If you're reaching out to relevant buyers with relevant messaging, you are not a spammer. You're scaling your company through outbound sales. In fact, we're working a client that ONLY targets people using outlook as their ESP. If you know anything about cold outbound in 2026, you know that outlook is difficult to land in. But with a blend of personalization and relevant targeting, we're still seeing 9%, 6%, and 4% reply rates on multiple campaigns at scale. This is truly best-in-class. Shout-out to Mark Lim. So does relevance beat personalization? 100% yes. But you need both in order to maximize your success with outbound campaigns in 2026. | 29 comments on LinkedIn

Ads (!!) in Clay is happening. I'm really hyped about this product expansion 🔥 We are already seeing customers like Slack, Anthropic and Rippling hit 90%+ match rates against their paid ad audience on LinkedIn and 60%+ on Meta. This is 2-4x what they were getting before, which is a massive win for marketing teams. Even more, Clay can update audiences in real-time as new records come in. That means no more passing CSVs back and forth between systems. Update lists and suppress closed-won customers/CRM contacts automatically. Your ad campaigns are only as good as the people who see them. Now you can finally target the right accounts (the ones you actually care about!) and right titles across channels, without wasting money and time on the rest. Here's one example of a campaign you can run: 1. Setup website intent in Clay to deanonymize web traffic 2. Search in Find People for your ICP contacts 3. Enrich them to find their hashed advertising IDs using our ads ID waterfall 4. Create audiences in Ads to run ABM campaigns 5. Convert them deeper into the funnel where you can message them in a highly personalized way. If an account is cold, you show thought leadership and awareness ads. If they become aware, you start showing social proof / middle of funnel (think: webinars, case studies). If they are warm, you can try to convert them via leadgen ads and send direct to sales. All of this happens programmatically as engagement score goes up on an account. They get pushed by Clay to a different Ads audience and naturally start seeing different type of ads. Clay Ads is in open beta today for enterprise customers (check left sidebar of home page) and we are looking for feedback from marketers to make it best in class. Let us know if you want to try it. Learn more at clay.com/ads and register your interest in the beta here: https://lnkd.in/gfNbQ2Ku | 145 comments on LinkedIn

I think most people are wasting their LinkedIn outreach thinking of it like email instead of it's own channel. Here's the 3 strategies I'd do instead. I was speaking to James Winter about some suggestions I had for his portcos with Claude code and such and I brought up how one of their portcos wanted to sync LinkedIn outreach with email. "We think if we email them twice, we should move over to LinkedIn." In my opinion, that's a waste of the channel. LinkedIn outreach (especially using voice notes) 99/100 times has higher reply rates than cold email but lacks the ability to scale without fake accounts. If you only had 25-50 connection requests to send per day, why would you use the same strategy of email where the channel scales linearly. When you're doing LinkedIn outreach, I'd focus on these things first. 1) Use a tool like Trigify.io or some Rapid API endpoints to find your ICP engaging and connecting with customers you have permission to name drop. Find everyone engaging with your customer's employees posts and their company page. Don't say, "I saw you engaging with my customer's post" but instead send your regular message you usually would but leave a custom variable in your social proof line of your message to reference that customer. Instead of sending a message saying, "We help companies like {{company they have never heard of}}...." you can name drop that customer case study who they will of course know. 2) Install every website deanonymization software on your site with a free trial. if they do contact lookup, clean them up and make sure they are ICP. If they do company lookup, use Clay or Prospeo.io to find contacts. Target people and companies with a high likelihood of being on your site. Again, don't mention anything about being on the site. Just reach out like you normally would and put a little delay on it. Track which tools give you the highest reply rates/success and pay for them. Probably a whole post can be dedicated on why I suggest you try them all for your niche but it's free, so trust me on this one. 3) Reach out to people showing intent about your solution/problem/they are doing research/etc by targeting people in your ICP engaging with posts on the topic (or your competitor's post....) Same strategy here, just going a little bit more broad and using the last amount of capacity you'll have because of the limits of reaching out from 1 account. So instead of thinking about LinkedIn as an extension of email, remember you only get so many shots on goal and the reply rates are so much higher on LinkedIn. Use them to reach out to some of your hottest leads. | 22 comments on LinkedIn

$3.42 to find 49k Instagram profiles including their emails and some light ICP building ready to go? Let's break it down. Scraping Instagram is notoriously difficult but so many people want to target creators/contacts that really aren't on LinkedIn (thank goodness the LinkedIn engineers aren't as good at blocking scraping as Instagram). So we have to go to our favorite scraping partner on the internet. Hey there Google! Google has built you a search scraper that everyone company must let it in in order to be discovered. In this process, we used OpenWeb Ninja's google search api to do it. Let's try to break this down. Google scraping is great but you can only get a subset of searches at a time. So if you want a ton of contacts, you're going to have to run lots of different searches programmatically. For this search we were targeting CEOs, authors, founders, etc. Not necessarily professional content creators. I had Claude code build me searches for every state, every city, and then 200 keyword searches to pair with each base keyword. We would scrape Google searches where the search would be site:instagram.com "founder" AND "@" AND "Los Angeles" AND "Finance" vs. site:instagram.com "founder" AND "@" AND "Los Angeles" AND "MedSpa" (the @ is to have the highest chance that someone has an email in their bio!) If we only search for site:instagram.com "founder" no way we get the whole search. Then Claude code ran with the OpenWeb Ninja API and completed the searches for me while deduping in the process. Going to throw it in Clay to orchestrate some final mile Apify enrichment and email validation before launching the campaign! | 20 comments on LinkedIn

Most people start with Layer 3 (see the graphic below). They obsess over subject lines and personalization before they've even built an offer that works cold. That's backwards. There are 3 layers to outbound: → Layer 1: Outbound Strategy ICP definition, offer design, and positioning. If your offer doesn't deliver value density before the meeting, no execution will save you. If your ICP is too broad, you'll burn volume on people who'll never buy. This is where differentiation happens. Most people skip it because it's hard. → Layer 2: Outbound Marketing Plan Targeting rules, list-building logic, and channel mix. This is where strategy turns into structure. Segmentation by use case. Measurement frameworks. Qualification criteria. Without this, you're guessing at scale. → Layer 3: Execution & Scale Cold email sending, SDR workflows, and follow-up sequences. This is where everyone starts. That's why most outbound campaigns plateau early and can't scale past low volume. The reason this order matters: Skip a layer, and the next one fails. Skip Layer 1 → weak offer gets exposed at volume Skip Layer 2 → execution breaks when you try to scale Start at Layer 3 → polite declines, forever Outbound works when you treat it like engineering, not marketing. Ready to test this? Manufacturer or professional services company doing $2M–$3M+ with an LTV above $7K? Book a pilot. We'll get you 3-4 qualified meetings before you pay anything. Apply here: https://bit.ly/C17Pilot Repost this to help founders stop optimizing the wrong layer first. Follow Enzo Carasso 🧲 for more on outbound engineering, offer design, and controllable pipeline. | 104 comments on LinkedIn

The most dangerous and biggest BS lie in sales: “AI will fix our process.” It won’t unless the process is built for AI. Most teams don’t need more tools They need AI infrastructure with the inputs, signals, outputs, and systems that actually make AI useful. Here’s what a real AI-native sales engine looks like under the hood: AI Inputs → ICP, buyer context, triggers, tone AI Signals → stagnation, sentiment, leakage, engagement AI Outputs → personalization, timing, risk alerts, forecast checks AI Systems → outbound frameworks, coaching loops, pipeline intelligence When these pieces connect, AI stops being a writing assistant and starts being the operating system your revenue team runs on. Cleaner forecasts. Higher replies. Smarter coaching. Tighter pipeline visibility. DM me “AI” if you want to start working like a real SaaS Founder/CEO, using AI in the way it matters. If that’s you, then stop running your company like it’s 2022 and let’s implement a revenue machine together. 👉 Follow Alan Ruchtein for AI-native GTM systems that actually move revenue. | 76 comments on LinkedIn

I've always wondered what tools Ramp used for GTM. Turns out they use... Ramp? I saw an awesome post from Parth Gujare on X yesterday where he showed off some product screenshots of Ramp Revenue, the company's internal revenue orchestration tool. The product included signal aggregation, message drafting, data enrichment and more, all made specifically for the Ramp team. This particularly excites me because it harkens to the idea that GTM teams shouldn't be using out-of-the-box tools to get their work done. If a system isn't built completely custom for your company, it's probably not working as efficiently as it could be. For companies that don't have the internal resourcing to create their own GTM software, I've always felt that automation tools like Clay are their best bet. However, it's getting to the point where spinning up products like this doesn't take a 10 person engineering team, or really anybody technical. As the barrier to entry decreases for bespoke GTM tech, I think we'll see a lot more companies doing this. I've always felt that the Ramp GTM team is one of the best in the world, and now we know why after a look under the hood! Props to Parth for posting this, hopefully it inspires more people to take initiative over their company's stack 📚 | 28 comments on LinkedIn

Elon Musk bought X and implemented signal-based outreach to sell ads. And honestly, it’s not the worst play in the world: - The email looks human - It grabbed media from my post - They did some filtering to see I talk about business - They mention “testing” paid ads (lower-risk) - They emphasize the “free hands-on support” I’m sure there are ways they’re identifying business owners and automating a lot of the tedious work to set this up, but the end product still really isn’t bad. This is your signal that no matter how big your company, using the right signals for outreach likely isn’t a bad idea. | 34 comments on LinkedIn

Scale doesn’t break outbound. It reveals what was broken already. Most systems were never built to handle volume. You scale up, cracks appear, and you're back to manually fixing every piece instead of running an engine. Here's how to build outbound that survives scale: 1/ Account Sourcing Decide exactly which accounts you will and will not target. Most outbound fails because you're contacting people who will never buy. → Build ICP rules using firmographics and economics → Reuse the same account set instead of rotating lists → Precision at sourcing prevents waste at every step after 2/ Outbound Distribution Your message has to reach the market. Perfect targeting and a strong offer mean nothing if emails don't land. → Run high-volume sequences that maintain deliverability at scale → Keep in mind that infrastructure often breaks here first when you grow 3/ Offer-Led Framing Give them a concrete reason to respond. Precision without a superior offer leads to commoditization. → Anchor to a specific revenue problem, cost issue, or operational constraint → This is where most companies stall out 4/ Segmentation by Use Case Different buyers have different triggers. → Segment by use case and buying trigger, not persona or industry labels → One size fits all kills response rates at scale 5/ Content Reinforcement Support material validates your outbound claims. → Use case studies, teardowns, and proof points to reinforce credibility → Build a library of resources that moves deals forward 6/ Live Feedback Loops Most operators run outbound blind and wonder why results plateau. → Review replies weekly and tag patterns → Rebuild offers when data shows you're losing on value, not targeting 7/ Pre-Meeting Value Earn the meeting before discovery happens. → Deliver insight before a call is booked → The offer delivers something concrete before the first call 8/ Qualification Rules Reject meetings that fail firmographic fit, use case, or economic criteria. → If you book meetings with people who can't buy, you waste sales capacity → Qualification helps protect your time and close rates 9/ Back to Account Sourcing The flywheel repeats. Wins and losses feed back into targeting rules, offer design, and segmentation. Most outbound is built like a list of tactics. This is how you build it like an engine. Want to see it in action? We'll run a pilot campaign, book 3-4 qualified meetings, and prove the system works before you pay a dollar. Apply here: https://bit.ly/C17Pilot Repost if you're rebuilding your outbound system from scratch. Follow Enzo Carasso 🧲 for practical systems to scale your business with outbound. | 48 comments on LinkedIn

Half your lead list is just… missing (Not people, but missing emails you can actually send to) And that’s where most outbound motions quietly die… Because the typical loop looks like this: run one provider → blanks…run another → “valid” emails that still bounce clean the CRM → patch the list → repeat …and somehow we call that building pipeline 🫠 This is why i think Clay waterfalls + Icypeas is such a good combo Icypeas is built in a way that GTM teams actually use: Full Name + Company Domain → verified work email Then Clay does what it’s best at: waterfall across multiple providers until you get a real hit ... instead of betting your whole campaign on one provider. The setup is simple : Select Icypeas account → Clay-managed or your own API key Map inputs → Name + Domain (optional catch-all) Enable auto-update → refresh every 24h (less stale data) Add a condition → run only if email is blank (credit-efficient) Waterfall = higher coverage without extra tabs Verification = fewer bounces / healthier deliverability Auto-update = less stale data when titles change fast Conditional runs = you don’t pay twice for the same row Net result..more filled rows…Cleaner lists…Fewer bounces. ✌️ and reps start outreach with data that actually holds up. | 50 comments on LinkedIn

Outbound decisions are usually made with the same few words They show up long before emails go out While teams are planning, forecasting, and prioritizing These are the words that quietly guide where time goes What gets attention And what moves forward 👇A reminder of the GTM language behind those everyday conversations P.S. Might be worth saving as a quick memory refresh for later | 68 comments on LinkedIn

Bad deliverability will kill your outbound before your offer ever gets read. But everyone blames the copy. I've sent millions of cold emails. Here are the 7 deliverability mistakes that destroy campaigns: 1/ Using a Single Domain for Outbound → Running outbound from one domain concentrates all risk in one place. → If you seriously want to scale you need at least 100 domains. 2/ Sending Too Much From Each Inbox → High send counts create abnormal patterns that trigger filtering. → Cap daily sends at 15-20 emails per day and to never go above 30. 3/ Treating Warm-Up as a One-Time Step → Inbox reputation is shaped by ongoing behavior, not initial setup. → Maintain consistent sending for 2-3 weeks minimum and avoid pauses that reset trust signals. 4/ Scaling an Offer That Doesn't Get Replies → Low engagement trains filters to deprioritize your emails. → If nobody's replying, pause scaling and adjust your offer before touching infrastructure. 5/ Using Opens as a Performance Signal → Opens do not indicate intent. → Track replies and interactions at the inbox level and remove inboxes with sustained low engagement. 6/ Adding Infrastructure Before It's Required → Complex setups delay feedback instead of improving performance. → Add complexity only when manual limits are reached. 7/ Treating Deliverability as a Solved Problem → Inbox health degrades over time. → Rotate domains proactively and adjust volume based on engagement trends. Outbound isn't about clever subject lines. It's about engineering systems that survive scale. If you're doing $2M-$3M+ in revenue and want to see how we engineer outbound pipelines that actually deliver, apply for our pilot campaign. We'll book 3-4 qualified meetings in your calendar. You verify ICP fit. If they're good, we talk. Apply for a pilot campaign at https://bit.ly/C17Pilot Repost if you believe infrastructure beats tactics. Follow Enzo Carasso 🧲 for outbound engineering at scale. | 103 comments on LinkedIn

Here's how to automate 90% of your proposal generation with Clay and Google Slides: I made a video a few months ago where I used publicly available company info to auto-generate slide decks with Gamma. However, I had two small qualms with it- it was using zero first-party data, and the deck looked a little different every time. Luckily Akansh Gupta went ahead and fixed this for me with a v2. Here's what the table does: 1. Ingests a call transcript, and then enriches the person and company involved in the call 2. Uses the transcript to fill variables required by a Google Slides template we created 3. Sends the variables to a Google App Script, which duplicates our template proposal and fills it with the variable data 4. Voila, proposal complete! For anyone using Gong or other call recording software with a good API, I highly recommend giving a variant of this a try. Quick disclaimer- this was meant as an example table, it will likely look a bit different in practice as you'll want to use the webhook from the call recorder as the table source, not a "find people" integration! Quick video explainer below ⬇️

Deliverability is the hidden killer of GTM strategies. When your open rates dip, the immediate instinct is to rewrite the subject line or blame the lead list. But more often than not, it’s a plumbing issue, not a people issue. This is the specific gap Warmy.io - Email channel. Reliable. fills. It acts as a safety net for the things that keep founders and Ops leads up at night: The Blind Spots: → See your domain’s health in real time, no more guessing if SPF or DKIM broke. The Spam Jail Fear: → Simulated human engagement helps your emails land where they belong. The Ops Headache: → Bulk mailbox connections and API access make scaling painless. It’s simple: Fix the infrastructure first, and the revenue follows. Don’t let your best pitch die in the Spam folder. Try it free here: https://lnkd.in/gEq79hJP | 25 comments on LinkedIn

Most cold emails never reach the inbox. Here’s how to fix that 👇 Let's break down the 4 tiers every sender MUST master to hit 90%+ inbox placement: 1. Technical Foundation → Authenticate with SPF, DKIM, and DMARC → Diversify inboxes across Gmail, Outlook, SMTP → 3 inboxes per domain 2. Warm-Up & Volume Management → Warm up for at least 30 days to build sender reputation → Ramp up daily sends gradually → Fully ramp to 25 sends per inbox per day 3. List Perfection → Double verify your lists to remove invalid emails → Use a catch-all verifier to maximise validation coverage → Target high-quality, relevant audiences only 4. Content Strategy → Use plain text only (no HTML, links or attachments) → Use a ton of spintax → Write like a real human, not a marketer Nail all four tiers, and you’ll be in a good area. If you're still not seeing results and your inboxes appear healthy (check warm up % score is > 95% in Smartlead/Instantly) then you have an offer issue. Change up your copy and go again. StackOptimise ⚙️ | 17 comments on LinkedIn

8 AI Prompts That Actually Book Meetings (Cold Email Advanced Edition) (+ the exact wording I use to land 79+ meetings/month) ☑ ICP Research Prompt “Act as a sales analyst. Analyse CTOs in B2B SaaS (100–500 employees). Summarise their top 5 priorities, daily pains, and buying triggers in less than 200 words.” ☑ Personalization Hook Prompt “For this LinkedIn profile [link], draft 3 icebreakers. Keep under 20 words, avoid flattery, tie to their recent activity. Avoid jargon, buzzwords or being salesy.” ☑ Problem Hypothesis Prompt “Write 3 pain-point hypotheses for VPs of Sales in SaaS who missed quota last quarter. Keep each under 15 words. Make them relevant and give me a 1 line “Why it matters” for me to understand your POV” ☑ Objection Handler Prompt “Give me 3 tactical responses to ‘too expensive’ objection for SaaS buyers in X industry for Y role/title that are willing to buy [my solution]. Make it consultative, not defensive. Each reply must be under 25 words.” ☑ CTA Prompt "Generate 3 high-converting CTAs for a SaaS demo request email. Each CTA must be under 12 words, avoid pushy sales language, and emphasize clear, outcome-driven value that motivates action without pressure. Prioritize clarity, psychological pull, and alignment with a business decision-maker mindset." ☑ Follow-up Prompt "Craft a compelling two-sentence follow-up email for a prospect who opened but did not reply to my initial message [insert message 1]. Provide fresh value by weaving in a single new, research-backed insight or market trend that sparks curiosity and relevance, while keeping the tone consultative rather than transactional." ☑ Case Study Builder Prompt "Transform the following customer testimonial into a concise, two-line cold email case study. Highlight quantifiable ROI, specific numbers, and credible impact in a way that feels authoritative yet humble—avoiding overt self-promotion while ensuring the results command attention and trust." ☑ Multi-Thread Prompt "Identify 3 alternative stakeholders to approach if a VP of Sales does not respond. For each contact, justify their relevance by explaining their role in the decision-making ecosystem, their potential influence on the buying process, and how they could shape or accelerate a purchasing conversation." ♻️ Repost this so more people stop using GPT like an intern | 47 comments on LinkedIn