4 Easy Tactics to Use AI For Cold Email Personalization

Everyone is personalizing emails using AI, yet most people are failing because they only know the tactics and not the core principles of cold email personalization.

Imagine: You copy a workout routine from a fitness influencer, but see no results, because you don't understand nutrition or proper form. Tactics alone can't replace the core principles.

The good thing, though, is that today I'll explain to you all the core principles of cold email personalization and show you examples of how I am applying them in the real world.

Things I’ll Talk About

• The different types of cold email personalization
• Semi-personalizing cold emails for maximal conversion
• The 3 principles of cold email personalization
• How to use job offers in cold pitches
• How to personalize cold emails when you have no valuable data

The Different Types of Personalized Cold Emails

When you want to personalize a cold email, you should always think of why you’re even personalizing it, because cold email personalization has two different purposes which are:

1. Adding relevance: This includes signals, audience segmentation, etc. and involves writing messages that resonate with the recipient because of the mentioned offer, pain points, or needs.

2. Adding human touch: This involves writing a message that shows the recipient that the sender isn't a bot, an AI SDR, or someone who's just spray-and-praying.

Highly Personalized Cold Emails: Good for High-Ticket Sales

Usually, highly personalized campaigns convert extremely well because they demonstrate you've done your homework and you're writing specifically for them and only them.

Highly personalized emails are typically based on:

• A LinkedIn or X post where they communicated a specific need or challenge.
• A podcast interview where they revealed their priorities.
• A YouTube video they posted showing their thought process.
• A media publication where they were quoted or featured.
• Custom research conducted with AI agents to uncover unique insights.

Upsides of highly personalized campaigns:

• When done right, highly personalized emails can achieve 30-40% response rates.
• Creates more trust with the customer, leading to faster deals.

Downsides of highly personalized campaigns:

• Scalability: You often find only a limited number of prospects that fit the search criteria.
• Time investment: While you can automate the research using AI agents, you still have to write each email manually when creating highly personalized emails.
• Cost efficiency: The ROI can be questionable if you're spending 15-20 minutes researching each prospect for a low-value deal. I’d not recommend it for early-stage startups.

Semi-Personalized Cold Emails: The ROI Machines

With this approach, you segment your list into well-defined audience subsets and send them similar messages with a pattern of personalized variables.

This works because you understand their common challenges from previous conversations with similar prospects.

This approach is often called "ICP campaigns" (Ideal Customer Profile campaigns).

These campaigns consistently deliver the best ROI (return on investment) for several reasons:

• They're easy to set up and scale.
• They balance personalization with efficiency.
• You can create evergreen campaigns that continue to perform over time.

The Two Types of Semi-Personalized Campaigns

1. ICP-Based Campaigns - Segmented by:

• Common pain points in their industry.
• Company size or growth stage.

2. Intent Signal Campaigns - Triggered by:

• Job postings (indicates changing priorities).
• Funding announcements (new budget available).
• Technologies they use (compatibility & potential needs).
• Other business signals (acquisitions, expansions, etc.).

Added Human-Touch as P.S.

💡 What is an P.S Line? “PS” in an email stands for “postscript”, meaning “written after.” is the text you write after the main email content.

This approach works best for companies that don’t have enough data to know what their target customer cares about and haven’t defined their ICP well enough yet

👉 Read our article on defining an Ideal Customer Profile.

The purpose is simple:

Show you're human, not a spammer.

↳ Increase your chances of getting replies even when your messaging isn't perfect.

Some ideas:

1. Research case studies and refer to them in your P.S. line
2. Reference to their time-in-company in your P.S. line
3. Call out a topic that everybody in their area debates on

The bittersweet outcome?

You often get responses like: "Though I'm not interested in your offer, this is the best cold email I've ever received, thanks Habib!" — which leaves me with mixed feelings of disappointment and validation.

To sum this all up, you have 3 options:

• High-personalized cold emails: Research-heavy approach targeting high-value prospects with unique, custom messaging. Great for high-ticket sales but difficult to scale.
• Semi-personalized cold emails: The best ROI option that balances personalization with efficiency through ICP-based segmentation or intent signals. Easy to scale and automate.
• Human touch cold email: Adding personal touches (like P.S. lines) to show you're a real person. Works well enough when you haven’t found your ideal customer profile yet

Each comes with its own advantages and disadvantages depending on your business stage, resources, and target audience.

My suggestion: Run tests and see which delivers the highest ROI (start with semi-personalized).

📘 Contact Habib for Help with Your Cold Emails (Free!)

If you need help, contact me on LinkedIn, and I'll help you run these campaigns using Datablist.

The Core Principles of Cold Email Personalization

Just as scientists rely on core principles to explain our universe, there are fundamental rules that determine whether your personalized cold emails will convert or crash.

Here’s the breakdown.

First Personalization Principle: Your Data = Your Success

The quality of your data is the foundation of effective personalization, and relying on outdated database information that gets updated every 6 months won't help.

For effective personalization, you need deeper insights that require additional research - information that databases simply can't provide.

Without accurate data, even the most creative personalization will fail. Here's why quality data matters:

• It ensures your messages reach the right people at the right companies
• It prevents embarrassing mistakes like congratulating someone on a role they left months ago
• It improves deliverability by reducing bounces and spam reports

Second Personalization Principle: Have a Reason to Personalize

Having a reason goes beyond personalizing based on intent signals. It's about developing a mental framework where you ask: “What's the purpose of this specific personalization?"

The ultimate goal is always to get a response. You should also think of what impression your prospect should form when reading your email.

For example, you want them to think one of these things:

• "This person clearly did their research about me and my situation"
• "This sender knows what they're talking about and understands my industry"
• "At least this feels like it came from a real human, not a bot"

Not every recipient will react positively, but your intentions matter. Authentic personalization that will always outperform superficial tricks.

Third Personalization Principle: Sound Like a Human, Not Like AI

Look, this seems like a lot of work, but it’s actually really easy: Even with AI assistance, your emails should flow naturally and sound like they were written by a real human; otherwise, you'll end up in the spam folder or getting ignored.

This means:

❌ Don't just feed data to AI and ask it to "create a personalized line"

✅ Instead, create a framework that guides the AI

➡️ Use this framework to scale personalization to 1000s of leads

Remember: The ultimate goal here is not to create personalized messages, but to get a response. Personalization is just a means to that end.

Now that we have covered the different techniques and principles, I'll show you how I apply them to create personalized emails effectively and scale them using the ChatGPT integration inside Datablist

📘 Quick Explanation of Datablist

Datablist is an AI-powered spreadsheet that helps you collect, organize, and enrich data to automate workflows such as personalizing emails, all without technical skills. Imagine Excel, just better, with built-in data sources, automations, and AI agents that let you scale far beyond what traditional spreadsheets offer.

4 Examples of Personalizing Cold Emails and How To Use Them

In the next section, I'll show you 4 examples of personalized cold emailing:

1. Personalizing Emails Based on Audience Segments
2. Using Job Descriptions In Cold Email Personalization
3. Using a Case Study in the P.S. Line
4. Adding a Funny P.S. Line To The Cold Email

Personalizing Emails Based on Audience Segments

I will show you how to segment based on 1st time founders versus serial entrepreneurs to create personalized and effective cold email campaigns. My process is separated into phases:

First phase

1. Using Datablist to scrape the LinkedIn profiles of your prospects and get fresh information about their career history
2. Sending the data to ChatGPT and telling it to return "🔁 Serial Entrepreneur" or "1️⃣ First-time Entrepreneur" based on their previous roles

Second phase

1. Creating a messaging framework
2. Using Datablist to scale personalization for each segment

First Phase: Prepare Data For Cold Email Personalization

I already imported a list of prospects in Datablist, the next step is to scrape their LinkedIn profiles

💡 Quick Note About LinkedIn Scraping With Datablist

Datablist allows you to access up to 10 past roles for each prospect, and you should take advantage of this feature to gather as much data as possible. The more information you have, the more options you'll have for creating effective personalization. However, I’ll use only 3 today.

Datablist returned me their past roles, as next I’ll run ChatGPT 4o mini on each row to analyze their career history.

This is the prompt I’ll be using to make my list personalization-ready

These are the results Datablist returned. Now I'll go into the second phase of this personalization

Second Phase: Create Personalized Email

Now that I have segmented my list, I can go into writing my pitch. Here’s what I’d write if I were pitching our product Datablist to those groups:

• For first-time founders: “Datablist doesn’t allow you just to find prospects to sell to, but you can do it also without breaking the bank.”

• For serial entrepreneurs: “Datablist allows your team to launch cold email campaigns 3 times faster than usual since the process takes place in one platform”

• What I’d never write: "I saw you are a first-time founder / serial entrepreneur" — they know that.

• Now I’ll filter the list based on whether the person is a serial entrepreneur or a first-time founder.

After filtering my list, I use the bulk edit feature in Datablist to insert my personalized pitch at scale. This allows me to use the column name as {{variable}} in my email sequencer.

And now I have finished my cold email personalization.

Using Job Descriptions In Cold Email Personalization

Frankly speaking, using job offers for personalization isn't revolutionary. Everyone can do it, and good recruiters already are. The kicker is: most are doing it wrong.

💡 Job Offers in Personalization: How To Get It Right

When using vacancies for cold email personalization, the goal isn't to go into every little detail of the job offer but to make your message relevant and unique enough so they open and eventually reply to it. You can do this by mentioning the soft skills they're looking for instead of focusing on experience.

What this really means for you is that you are not just personalizing but doing it in a unique way that sets you apart from your competition.

Here's how I leverage job listings for highly targeted cold email personalization:

First, I scrape a list of job listings based on job titles, company industry, and funding stage

After scraping job listings, I use Datablist’s waterfall people search to get all contact data to send an email to a qualified prospect from the companies where I scraped the job offers.

Let me explain Datablist's Waterfall People Search in simple terms:

1. First, you tell Datablist exactly who you're looking for (like "marketing managers”).
2. Then, you can set up backup searches (like "marketing directors" or "growth leads") as fallback options.
3. Datablist will try your first choice, but if it can't find any matches, it automatically tries your backup searches.

Now that I've found some prospects, I'll create a personalized first line based on the job description using the ChatGPT integration of Datablist

Two examples of Cold Emailing with Human Touch

💡 What is an P.S Line? “PS” in an email stands for “postscript”, meaning “written after.” is the text you write after the main email content.

First things first, when creating a personalized "PS" Lines at scale, you should know a few things:

• P.S. lines offer a lot of flexibility.
• Not everyone will like it, and that’s okay.
• People will give you kudos for your personalization without being interested.

My favorite approach is adding a funny sentence as "PS" line since when you make someone smile, they're more likely to respond, even if it's just to politely decline. But first, let me show you how to build professional rapport by referencing case studies from their website in the cold email.

Using a Case Study in the "PS" Line

Mentioning a case study in the "PS" line of your cold email has many benefits, with the most useful being that the prospect recognizes that you aren't just a spammer but someone who invested time into crafting a personalized message, and this really makes a difference.

Once I have a lead list to send emails to, there are only 3 steps I need to take to create a personalized P.S. line with case studies:

1. Use Datablist’s AI Agent template to scrape the case studies

2. Filter down to the successful runs only

3. Create a new property and use Datablist's Bulk edit feature to create personalization at scale, which allows me to use variables when editing data in an easy way.

Adding a Funny "PS" Line To The Cold Email

There are many ways to add something funny I could choose from.

However, what I always try to do is find something universal, for example, mentioning a topic that locals from the prospect's city always debate about.

💡 Understanding The Purpose of This P.S Line

This P.S. line isn’t aimed to give the prospect any information, but to prevent the prospect from thinking “just another cold email”.

If you want to replicate this workflow, you need only three things:

1. The location of the prospect, which you can get by scraping their LinkedIn profile.
2. A powerful AI model that creates personalized P.S. lines at scale.
3. A prompt that you can find in our prompt library.

Conclusion

Personalizing cold emails isn't challenging, but quite the opposite, it's very easy as soon as you understand the core principles that we discussed in this article, keep it as human as possible, and have your intentions always clear in mind.

FAQ About Cold Email Personalization

How Do You Personalize a Cold Email?

You can personalize a cold email referencing relevant information like job postings, case studies from their website, or adding human touch through a debate relevant to their location.

What Are The Best Tools For Personalizing Cold Emails At Scale?

The best tools for personalizing cold emails at scale include data enrichment platforms like Datablist that can gather prospect information. These can be combined with email automation tools that support personalization variables.

How Much Personalization Is Needed in a Cold Email?

An effective cold email needs enough personalization to stand out, but not so much that it becomes inefficient to scale. A personalized first sentence typically yield the highest impact on response rates.

What's The Best Way To Find Information For Cold Email Personalization?

The best sources for cold email personalization include LinkedIn profiles, company websites (case studies, blog posts, team pages), job postings, and news articles about the company. Tools like Datablist can help gather this information efficiently.

Does Cold Email Personalization Actually Improve Response Rates?

Yes, personalized cold emails significantly outperform generic ones, with studies showing 2-3x higher response rates. The most effective personalization focuses on addressing specific pain points or goals rather than simply mentioning personal details.