60% reply rates

The LinkedIn playbook Mike Cubberly won't put in a deck.

How Mike Cubberly Runs LinkedIn Outbound at 60-70% Reply Rates

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.

*Benchmarks: Belkins campaign data, SalesBread, EngageKit.
Mike's rates self-reported by Bottle Rocket Growth.

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:

  • HeyReach for LinkedIn Automation.

  • Orange Slice for outbound orchestration.

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.

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