ColdSend Logo
ColdSend
HomeFeaturesPricing
Contact UsGet Started
Nick Abraham

Nick Abraham

in
Follow

Founder of LeadBird.io

B2B Lead GenerationAdvanced

How to Copy Nick Abraham's Hyper-Personalization Framework: 40%+ Response Rates at Scale

Nick Abraham achieves 40%+ response rates using automated hyper-personalization. Here's his exact 3-layer framework that powers LeadBird's 1.5M monthly emails and how to replicate it with ColdSend.

Updated on: 18 July 2025

TL;DR: Nick Abraham's Strategy

Nick Abraham sends 1.5M+ cold emails monthly achieving 40%+ response rates through his 3-layer hyper-personalization framework:

Layer 1: Social Follow Intent - Scrape competitor/industry leader followers who show buying intent
Layer 2: Colleague Reference - Use scraped employee data to mention teammates, creating urgency
Layer 3: AI Personalization - Deploy tools like Quicklines for contextual personalization lines

Quick ColdSend Setup:

  1. Use competitor follower lists from LinkedIn
  2. Enrich with colleague data via Apollo/Clay
  3. Generate AI lines with custom prompts
  4. Deploy through ColdSend's infrastructure (no warmup needed)
  5. Target 2-4% reply rate, 20-40% positive rate

Key Insight: Nick proves personalization scales when you combine intent signals + automation + proven infrastructure.


Who Is Nick Abraham?

Nick Abraham is the founder of LeadBird.io, a B2B lead generation agency that has cracked the code on hyper-personalization at scale. With over 200 active clients and sending 1.5+ million cold emails monthly, Nick has transformed what most consider impossible - making every email feel personally written while operating at massive volume.

His Track Record:

  • 1.5M+ cold emails sent monthly
  • 200+ active clients
  • 40%+ response rates on personalized campaigns
  • Built and sold multiple SaaS tools (Quicklines, Scrubby, Golden Leads)
  • Recognized by Smartlead as #2 most-replied-to account globally

But what makes Nick different isn't just his volume - it's his obsession with making automated emails feel completely human. As he puts it: "The goal of personalization is making your prospect believe you manually wrote that email specifically for them."


The 3-Layer Personalization Framework

Nick's framework is built on a simple premise: layer multiple personalization signals to create the illusion of deep research without the manual work.

Layer 1: Social Follow Intent

The first layer identifies prospects based on their social media behavior that signals buying intent.

The Strategy:
"If your biggest competitor has 60,000 followers on LinkedIn, scrape all those followers and email them. We generated 450+ leads in under 3 months using this method - it was one of our best-performing campaigns."

Implementation:

  1. Identify Intent Sources: Competitors, industry tools (Clay, Apollo), thought leaders
  2. Scrape Followers: Use PhantomBuster or similar tools to extract follower lists
  3. Filter by ICP: Remove irrelevant titles/companies
  4. Craft Opening Lines:
    • "Noticed you follow [Company] - curious if you're dealing with [pain point]?"
    • "Saw you're connected to [Industry Leader] - working on [relevant initiative]?"

Layer 2: Colleague Reference

This layer creates urgency and social proof by mentioning teammates.

Nick's Approach:
"We mention we're not sure if this should go to you or [colleague name]. This creates urgency - they'll either respond or forward it to the right person."

The Psychology:

  • Social Proof: Others at their company might be interested
  • Reduces Pressure: You're not sure if they're the right person
  • Increases Response: They'll clarify or forward

Data Collection:

  • Scrape company employee lists from LinkedIn
  • Identify decision-makers in relevant departments
  • Reference uncertainty about correct contact

Layer 3: AI-Generated Personalization

The final layer uses AI to create contextually relevant personalization based on recent activity.

Tools Nick Uses:

  • Quicklines.ai: His proprietary personalization engine
  • GPT-4 + Cargo: For custom personalization at scale
  • Clay: For complex personalization workflows

Intent Signal Identification Methods

Nick's success comes from finding prospects already in buying mode rather than cold prospecting.

Method 1: Competitor Follower Analysis

The Process:

  1. Identify top competitors in your space
  2. Scrape their LinkedIn followers using automation tools
  3. Filter by job titles and company criteria
  4. Craft differentiation messaging

Nick's Real Example:
"We scraped all our biggest competitor's followers and ran campaigns saying 'They don't offer performance-based services, but we do.' We closed 450+ leads in 3 months."

Method 2: Tool/Platform Followers

The Strategy:
"Someone who follows Clay is likely interested in generating leads. Someone following HubSpot probably needs marketing help. It's about finding the right intent signals."

Implementation:

  • Scrape followers of tools in your ecosystem
  • Target users of complementary platforms
  • Reference their tool usage in personalization

Method 3: Job Posting Intent

Nick's Insight:
"If a 150-person company is hiring an SDR, they probably need lead generation help. That's a strong buying signal."

Process:

  1. Monitor job boards for relevant hiring
  2. Identify decision makers at hiring companies
  3. Reference their hiring needs in outreach
  4. Position as solution to their scaling challenges

AI-Powered Personalization Engine

Nick has systematized AI personalization to work at massive scale while maintaining quality.

Custom GPT Prompts for Specific Industries

App Development Prompt:
"Analyze [website] and think of an app idea that would be relevant to their business. Write in format: 'If we could build an app that [specific functionality], would you be interested?'"

SEO Services Prompt:
"Analyze [website] and identify 3 competitors outranking them for relevant keywords. Write: 'I saw [competitor] is outranking you for [keyword] - interested in changing that?'"

Salesforce Implementation:
"Analyze [website] and identify how they could leverage Salesforce. Write: 'Have you considered leveraging Salesforce to [specific use case]?'"

Quality Control Framework

Nick's 70/30 Rule:
"About 70% of AI-generated lines are usable as-is. The other 30% need editing or are unusable. But that's still way more efficient than manual writing."

Quality Indicators:

  • Specific to their business/industry
  • Sounds like something a human would say
  • Relevant to your offer
  • Generic compliments
  • Overly enthusiastic language
  • Weird AI phrases

Scaling AI Personalization

Tool Stack:

  • Cargo + Google Sheets: For bulk personalization
  • Clay: For complex personalization workflows
  • Quicklines: For LinkedIn-based personalization
  • GPT-4 API: For custom personalization prompts

ColdSend Implementation Guide

Infrastructure Setup

Unlike high-volume strategies, Nick's personalization approach requires quality over quantity infrastructure.

Recommended Setup:

  • Starter Plan: $50/month sufficient for testing
  • Domain Strategy: 1-2 domains for personalization campaigns
  • Inbox Allocation: 10-20 inboxes (quality over quantity)
  • Daily Volume: 50-100 emails per inbox

Why ColdSend Works for Personalization:

  • No warmup delays - Start personalization campaigns immediately
  • High deliverability - Personalized emails need to reach the inbox
  • Easy scaling - Add capacity as campaigns prove successful

Campaign Structure

Email Template Framework:

Subject: Quick question about [company]

Hi {{first_name}},

{{layer_1_intent_signal}} - {{layer_3_personalization}}

Not sure if this should go to you or {{layer_2_colleague}}, but figured one of you might find this relevant.

We just helped [similar company] [specific result] using [method].

Worth a quick conversation to see if it's relevant for {{company}}?

Best,
[Your name]

PS: {{additional_personalization_signal}}

Data CSV Format:

email,first_name,company,intent_signal,colleague_name,personalization_line,phone_number

Performance Benchmarks

Nick's Targets:

  • Reply Rate: 2-4% (vs. 1% for generic emails)
  • Positive Reply Rate: 20-40%
  • Meetings Booked: 1 per 350-500 contacts
  • Unsubscribe Rate: <1%

Advanced Scaling Strategies

The Tech Stack that Powers 1.5M Monthly Emails

Data Collection:

  • Ocean.io: AI-powered lookalike company discovery
  • Apollo: Contact enrichment and email finding
  • Golden Leads: LinkedIn Sales Navigator scraping
  • Drop Contact: Email enrichment for LinkedIn profiles

Personalization Engine:

  • Quicklines.ai: LinkedIn-based personalization
  • Cargo + GPT-4: Custom personalization workflows
  • Clay: Complex data enrichment and personalization

Infrastructure:

  • Smartlead: Campaign management and sending
  • Outlook-based: Primary infrastructure choice
  • 1:1 inbox-to-domain ratio: For maximum deliverability

Quality Control at Scale

The 3-Step Process:

  1. Account List Building: Use Ocean.io to find lookalike companies
  2. Contact Enrichment: Upload to Apollo/Clay for contact discovery
  3. Manual Review: Filter contacts for relevance and quality

Nick's Quality Framework:
"We build account lists first, then find contacts, then review each contact manually. It's the only way to ensure quality at scale."

Team Structure for Personalization

Key Roles:

  • Research Specialist: Identifies intent signals and builds account lists
  • Personalization Manager: Manages AI tools and quality control
  • Campaign Manager: Executes campaigns and manages responses
  • Sales Team: Converts meetings from increased response volume

The Bottom Line

Nick Abraham has proven that personalization and scale aren't mutually exclusive. His 3-layer framework - Social Follow Intent, Colleague Reference, and AI Personalization - achieves 40%+ response rates while sending 1.5M+ emails monthly.

The key insights:

  1. Intent signals matter more than perfect copy - Find people already in buying mode
  2. Layer personalization for maximum impact - Multiple signals create believability
  3. AI is a tool, not a replacement - Use it for efficiency, not authenticity
  4. Quality infrastructure enables quality personalization - High deliverability is non-negotiable

Why this works with ColdSend:

  • No warmup delays - Start personalization campaigns immediately
  • High deliverability - Personalized emails must reach the inbox
  • Scalable infrastructure - Add capacity as campaigns prove successful
  • Cost-effective - Focus budget on personalization tools, not infrastructure

Ready to implement Nick's hyper-personalization framework? Try ColdSend and see how our infrastructure can power your personalized campaigns without the traditional setup delays and complexity.


Want to discuss implementing hyper-personalization for your specific market? Schedule a call for personalized strategy development and campaign planning.

Ready to Implement This Strategy?

Get the same infrastructure Nick Abraham uses. No warmup required.

Join ColdSend Waitlist

More Expert Playbooks

View All Playbooks →

Nick Abraham's LinkedIn Insights

in
LinkedIn Post
Nick Abraham

Nick Abraham

Mar 13, 2025

HYPER personal cold email template that's 100% automated (steal it): If you have a somewhat decent offer, steal this. Why? 1. Subject line looks super internal. You never want your subject line to appear sales-y. This is a great way to make it look the opposite — like an internal email from a colleague. As long as your email is valuable, this is fair play. If it's not, you look like you're spamming....just saying. 2. First line "confirms" their ICP. Look at how this is framed — the way it poses a curious question instead of a hard pitch is super intentional. You appear more as a helper than a seller. 3. Case study call out + social proof. The previous line brings us into why we're here, and lets us easily tie in our relevant social proof. Notice how the first line nicely blends into the one about our social proof — which is exactly the point. 4. Soft CTA We are NOT asking for a call. We're simply asking to show them how we did something they should care about. If targeted right, the reader doesn't have much of a reason to say no. 5. PS looks very human. You can just pull phone numbers and add them to your lead list, then map it in Smartlead as a dynamic field to pull this off. But most prospects would see this as an email that looks very human! Try it out and let me know what you think.
👍 Like💬 Comment
View →
in
LinkedIn Post
Nick Abraham

Nick Abraham

Apr 3, 2025

This 3-layer cold email personalization tactic looks 100% human but is fully automated. Here's how it works: (for context, we are still sending this and seeing great results). LAYER 1 – Social follow We scrape a list of a certain company or entity's followers that might signal the person is interested in our services. In this case, someone who follows Clay is likely interested in generating leads, one way or another. LAYER 2 – Colleague reference After that, we mention we aren't sure if this should be sent to their colleague, and we name them. Again, this information is scraped, but they don't need to know that. It looks human. LAYER 3 – Quicklines AI-personalized line. Hate on these all you want...we have the data: They perform better than emails without them. You can see what the entire email looks like in the second half of the picture below. It looks like a short, relevant, personalized email written by a human. It's short, relevant, and personalized — but certainly not written by a human (at least not at scale). Any questions on this?
👍 Like💬 Comment
View →
ColdSend Logo
Cold email infra
without the infra.
EmailHello@coldsend.pro
© 2025 ColdSend. All rights reserved.