How I Emailed 10,000 Businesses in 30 Days and Closed $15K MRR for Under $1,000
Nick Konsta ran a 10,000-lead cold email campaign, booked 36 meetings, and closed 4 clients in under 30 days. Here's exactly how he did it.
I set one goal before launching this campaign: sign three new clients and add $12,000 in monthly recurring revenue. The final number was $15,000 MRR, four retainer clients, 36 sales meetings booked, and $280,000 in open pipeline, all from 10,000 leads that cost less than $1,000 to reach. Cold email is still the fastest way to generate B2B leads, and this campaign is proof it's not luck.
Here's every component that went into it.
The Infrastructure: 100 Inboxes, US-Based IPs, One Sequencing Tool
Before a single email goes out, the plumbing has to be right. We set up 50 subdomains with two inboxes per domain, giving us 100 sending inboxes total. All of them were masked with US-based IPs to keep deliverability clean and stay out of spam folders.
For sequencing, we used Email Bison. It's newer, but it's been one of the better tools we've tested for inbox placement. If landing in the primary inbox is a priority for you, and it should be, it's worth checking out.
That's the unsexy part. Most people skip it or cut corners. Don't.
Finding the Right 10,000 Leads (Not Just Any 10,000)
The quality of your lead list determines everything downstream. We used Ocean.io to find companies that looked exactly like our best-performing clients. You plug in a customer's website URL, and Ocean scrapes the internet for lookalike companies based on keywords, site structure, and other signals. It even scores them by relevance.
We ran multiple lookalike searches across a few of our top clients, then pulled everything into Clay for enrichment and waterfall verification. The goal was a clean, verified list of people who were highly likely to want what we sell, not just a large list.
The difference matters. You can build a lead list in any data tool with a dozen filters applied and still end up with a mediocre audience. Lookalike modeling off proven customers is a different level of precision.
Intent Signals: Who to Prioritize Within That List
Once we had the companies, we used Perplexity AI to do deep research on each one, and on the individual contacts within them. We were looking for intent signals: recent funding rounds, leadership changes, new hires in sales or revenue roles.
A company that just raised a round is under pressure from investors to grow. A VP of Sales who just joined without a full SDR team might need an outside lead gen partner immediately. These aren't hypothetical scenarios, they're the exact situations where our offer fits best, and calling them out in an email creates a natural, credible reason to reach out.
We also researched the individual contacts, not just the companies, because the message that resonates with a founder is different from the one that lands with a mid-level sales manager. One email script sent to everyone is how campaigns fail.
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The AI Copywriting System: Claude Does the Writing
This is where the system gets interesting. We use Claude as our primary copywriting model, running it as a knowledge-based project loaded with:
Our company overview, case studies, and service details
Examples of emails we'd actually send
The Perplexity research on each target company and contact
With that context, Claude writes a one-to-one email for every single person on the list. At 10,000 leads, that's 10,000 individually relevant emails. No human team writes at that volume with that level of personalization.
The framework we used is a variation on "why you, why now." The first email in our two-step sequence opens by calling out a specific recent event tied to the company or the person, a funding announcement, a market expansion, a new product launch. Then it asks an engaging question that connects that event to a pain point we know our solution addresses. From there, we present what we do, back it with a case study from a company in their exact situation, and close with a soft call to action.
Here's a real example from the campaign. One prospect ran a conversational AI chatbot company. We opened by referencing their chatbot work, then asked whether they'd considered how to generate more qualified leads for platform demos. The pitch: we'd helped an AI agent company similar to theirs add $132K in MRR and book 125 sales calls in four months. The CTA asked if we could share how we'd adapt that for their North American expansion, which we already knew was happening. That last detail isn't filler. It's the thing that makes the email feel written for them specifically, because it was.
Email two is more direct. We acknowledge the first touchpoint, add context on how we'd fill a specific gap we identified through research, and push for a call. Two emails. That's the whole sequence.
The Results, Broken Down
The campaign ran for less than 30 days. The first client closed on April 10th. Three more followed on April 21st, 22nd, and May 8th. Four retainer clients. Thirty-six sales meetings booked. Fifteen thousand dollars in new MRR and $280,000 in open pipeline, off a list that cost under $1,000 to build and reach.
That's a 15x return on the list cost alone, before you factor in the time savings from running the research and copywriting through AI rather than a manual team.
Key Takeaways
Infrastructure first. Fifty subdomains, two inboxes each, US-based IPs. Deliverability isn't optional.
Lookalike targeting beats filter-based list building. Use your best clients as the model, not a set of demographic filters.
Intent signals narrow the list further. Funded companies and new leadership hires are higher-priority targets.
Deep research on both the company and the individual contact is non-negotiable. One script for everyone is how you get ignored.
Claude handles the copywriting at scale when you give it enough context: your offer, your case studies, and the research on each prospect.
Two emails is enough. A soft-touch opener tied to a specific event, followed by a more direct follow-up with a call push.
The whole campaign cost under $1,000 in list spend and returned $15K MRR plus $280K in pipeline.
Frequently Asked Questions
How many inboxes do you need to email 10,000 leads in a reasonable timeframe? For this campaign, we used 100 inboxes across 50 subdomains. That volume of sending infrastructure lets you reach a large list without hammering individual domains and tanking deliverability.
Why use Claude for copywriting instead of ChatGPT? We use different AI models for different jobs. ChatGPT has its place in the process, but Claude performs better for the actual email copywriting, particularly when you've loaded it with detailed context about your offer and the prospect. Perplexity handles the deep research on companies and contacts.
What intent signals are worth targeting in cold email? The two highest-value signals we look for are recent funding rounds and leadership changes, especially new sales or revenue hires. Both indicate a company that's under pressure to grow and may be actively looking for solutions like yours.
How do you find lookalike companies at scale? We use Ocean.io. You plug in the website URL of a strong existing client, and it returns companies that match based on keywords, site content, and other signals, ranked by relevance. We then enrich and verify those leads in Clay before anything goes into the sending tool.
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20-minute strategy call. We'll audit your ICP, show you which signals we'd track, and map out exactly what the first 120 days would look like. No commitment, no pressure, no pitch deck.
