Jared R.

@channel Sharing today's newsletter because it's so killer. Mike Cubberly runs a LinkedIn outbound operation that most SDR teams would kill for. He’s the founder of Bottle Rocket Growth, a boutique growth agency. Average reply rates are 30–40%. Best campaigns see north of 60%. Here’s how he does it. The Problem Outbound email is very hard (deliverability, tons of competing messages, etc). LinkedIn is way easier. But, LinkedIn limits every profile to about 30–40 connection requests per day. That math doesn’t work if you’re trying to build serious pipeline. Most teams hit the ceiling fast, then either burn their founders’ profiles or accept the volume constraint as fact. Mike didn’t accept it. The Playbook 1. Build a sender network Mike runs outbound across multiple LinkedIn profiles simultaneously. Some are real employees from his clients’ companies. Some are borrowed profiles from real people who no longer need their accounts. Every sender gets LinkedIn Premium, which unlocks the connection request volume you need to make this work. Minimum five senders per campaign. 2. Keep your acceptance rate low on purpose This one surprises people. Mike targets a 10–15% connection acceptance rate. Every connection request goes out with a message, which naturally filters uninterested people out. He’s not optimizing for acceptances. He’s optimizing for replies. Those are two completely different things. 3. Write messages that sound nothing like outbound Under 300 characters. Two to three sentences. No hard sell. No “I noticed” or “I was so impressed by your work.” Mike’s best-performing message recently was: “Hey, I saw you’re selling courses on Gumroad. Gumroad takes about 10% of every sale. Is that right?” That’s it. 67% reply rate. The message says nothing about where he works or what he sells. 4. Use real signals, not intent data Mike pulls tech stack data, platform usage, recent hires — things that are actually observable. He uses Orange Slice to build and enrich his lists, then structures his personalization around what people are experiencing, not what a data provider guesses they’re “in market” for. Intent data, in his words, is stupid. 5. Three touch points, max After the connection request, he sends two follow-ups. All short. All conversational. He never increases pressure across the sequence. He opens a door. He doesn’t knock it down. 6. Manage replies yourself This is where most agencies drop the ball. Mike writes every reply personally, often as the persona. Typos included. Emojis when they fit. He treats every reply thread as a real conversation, not a handoff to a junior closer. His take: AI is useful for inspiration on a reply. Never for the reply itself. 7. Use your data platform mid-campaign Mike runs campaigns in Orange Slice and queries it throughout. If reply rates are high but conversions are low, he asks it to analyze why. If contacts are responding that they’ve left the company, he runs a pass to verify current employment and pulls anyone who’s moved on. He’s actively cleaning and adjusting while campaigns are live, not just at setup. The Results On his best campaigns, Mike is averaging 60–70% reply rates. For one enterprise client, a single closed deal is worth $500k. He’s building millions in pipeline across his book of business, and doing it with a lean operation — not a team of 15 SDRs on the phones. The thing he keeps coming back to: simplicity. The more stripped down the message, the better it performs. The more human the follow-up, the more deals move. Most people overthink outbound. Mike just does it differently. His Stack:

Mike Cubberly is the founder of Bottle Rocket Growth. Follow him on LinkedIn. Want to learn from more Revenue Creators like Mike? Join the RevGenius community and be part of the movement rewriting the GTM playbook. Upcoming RevGenius Events The SaaSpocalypse Debate: AI and the Future of RevOps Dive into the "SaaSpocalypse" and the shifting landscape of RevOps in the age of AI. Rather than just managing tool sprawl, RevOps leaders are now architecting the data models and automated workflows that define modern revenue systems. Join us to discuss whether the SaaS stack is truly shrinking or simply evolving, and learn what it takes to design systems that AI can reliably navigate. sign up - https://www.revgenius.com/events/the-saaspocalypse-debate-ai-and-the-future-of-revops[…]ecreator.com&utm_medium=referral&utm_campaign=60-reply-rates 5 AI Myths That Are Holding Your Revenue Team Back Von CEO Sahil Aggarwal recently challenged five widely held beliefs about AI and revenue teams at a conference and the audience reaction proved he hit a nerve. In this 20-minute talk and live discussion, he unpacks the assumptions keeping RevOps teams stuck: data readiness, headcount planning, and AI strategy that's already a year behind. Stick around after for a live conversation with RevOps leaders navigating these exact challenges in real time. sign up - https://www.revgenius.com/events/5-ai-myths-that-are-holding-your-revenue-team-back?u[…]ecreator.com&utm_medium=referral&utm_campaign=60-reply-rates QBRs Are Broken, AI Can Fix Them. Most QBRs never happen. Prep takes too long, context is scattered across a dozen tools, and lower-tier accounts never make the cut. When they do happen, they often follow the same tired formula: a dense slide deck full of historical data and a meeting your customer didn’t want to attend. sign up - https://www.revgenius.com/events/qbrs-are-broken-ai-can-fix-them?utm_source=www.revenuecreator.com&utm_medium=referral&utm_campaign=60-reply-rates Sauce shared (on how Mike gets 60% replies), any questions, ask Mike C. he's here. Images with receipts at bottom to show you it works. Read full article: https://www.revenuecreator.com/p/60-percent-reply-rates 🧵 feedback, questions, things you're doing that are working, etc. No selling!

@channel Question on my mind as I'm attempting to build AI workflows & use Claude code. As AI evolves — do you think GTM teams actually need to know how to build AI agents or just know how to use them? 🔨Build — if you can't build it you'll always be dependent 🖥️ Use — I don't need to know how the car works to drive it 🤝 Both — but most teams aren't there yet ⌛ Neither yet — the tools aren't ready for mainstream GTM 🧠 Depends on the role 🧵 your thoughts and how you're building/using ai