Most B2B marketers are unaware of how impactful AI is in modern lead research. Lead research data can feed lead generation strategies, powering smarter segmentation, personalized outreach, and faster conversions at scale.
A name and an email are all you need to turn a newsletter sign-up into a fully enriched lead profile. Within minutes, you automatically pull their LinkedIn profile, job title, company size, industry, and even have tailored talking points ready for your next outreach sequence.
Sounds magical, but it’s probably a ton of setup, right?
It’s actually easier than it looks with a simple stack: Make.com + Relevance AI + your CRM.
This is the exact AI lead research system I use to transform anonymous sign-ups into fully fleshed-out leads without overwhelming people with long forms or burning hours on manual research.
In this guide, I’ll walk you through why leveraging AI for newsletter sign-ups matters, how the system works, what ai prospecting tools automate lead research, what it costs, and why this should become one of your first AI-powered habits as a B2B marketer.
TL;DR
- AI-powered lead research enriches newsletter sign-ups with company information, job titles, LinkedIn profiles, and other details that help B2B marketers personalize outreach.
- Liana Hakobyan’s workflow connects Relevance AI, Make, and a CRM to automatically research subscribers, update their profiles, and support lead scoring and segmentation.
- Segment enriched leads by role and company characteristics so executives, individual contributors, SMB owners, and enterprise contacts receive messaging relevant to their needs.
- Start with one automated enrichment workflow, then measure engagement, conversions, and time saved before expanding into more advanced lead scoring and outreach.
Table of contents
Why should B2B marketers automate lead research?
Automating lead research helps B2B marketers turn basic contact information into more useful prospect profiles without manually researching every subscriber. Enriched data supports better lead segmentation, more relevant email campaigns, and faster sales follow-ups.
Most lead research is broken. I’ve seen it firsthand across several marketing teams I’ve worked with. A new subscriber comes in, everyone celebrates the extra email on the list, and they get dropped into a generic welcome sequence. If someone’s feeling ambitious, maybe they’ll manually look up the lead on LinkedIn before a sales call weeks later.
The problem is that, by then, the engagement window has closed, and the excitement that drove the person to sign up in the first place is gone.
And even when manual research happens, it’s a productivity killer. That’s time that could be spent selling, strategizing, or building real relationships.
In reality, half the time, the research doesn’t happen at all. That’s when you end up sending the same cookie-cutter sequence to a Fortune 500 executive and a solo consultant, and wonder why engagement is flat.
This is where AI makes a huge difference.
It not only saves you hours of manual digging but bridges the gap between “just another email blast” and an outreach that feels tailored, timely, and relevant—at scale.
What does automated AI lead research involve?
Automated AI lead research uses a subscriber’s name and email address to find additional professional and company information. An AI research agent collects the details, an automation platform passes them into your CRM, and the enriched profile becomes available for segmentation, lead scoring, and personalized outreach.
The old way of lead research is slow, inconsistent, often neglected, and, quite frankly, a waste of valuable time and resources.
“Smart” lead research isn’t about asking subscribers for more information up front. People don’t want to fill out long forms; they want quick, frictionless sign-ups.
Instead, the smart approach is implementing automated lead research that runs quietly in the background without slowing anything down.
Here’s what defines it:
- Automatic: Research runs instantly without manual effort.
- Comprehensive: You get a full profile, not just a job title.
- Affordable: It costs pennies per lookup, not hundreds of dollars.
- CRM-Integrated: Data flows straight into your system of record.
- Privacy-Respecting: You’re enriching public data, not prying into private details.
The best part is that your leads never see the research happening. They just experience better communication: content that feels relevant, emails that speak their language, and outreach that addresses their world.
That’s the difference between being another marketer in their inbox and becoming the one they actually pay attention to.
How do I automate lead research from newsletter sign-ups?
I use a four-step workflow: connect the sign-up form to Relevance AI, configure the research agent, automate data transfers through Make, and use the enriched profiles to segment subscribers. This gives me the context to personalize outreach without asking subscribers to complete lengthy forms.
By layering AI lead enrichment into my sign-up process, I skip forms and still get the context I need for segmentation and personalization. Here’s the exact step-by-step system I use to automatically research every subscriber, without them ever knowing it’s happening.
Step 1: Set up your infrastructure
You’ll need four pieces to make this work:
- Trigger source: Your sign-up form (HubSpot, Kit (formerly Convert Kit), Mailchimp, or even Google Forms).
- Research agent: Relevance AI, which runs the enrichment.
- Automation platform: Make.com (or n8n.io as an alternative).
- Lead research data: A CRM like HubSpot, or a Google Sheet if you’re testing.
The beauty is that most of these tools have free trials, so you can experiment before paying.
Step 2: Create your research agent
In Relevance AI, I use the lead research agent template from Beni AI. It only requires two inputs:
- Lead name
- Lead email
From that, it automatically pulls:
- LinkedIn profile URL
- Job title and seniority
- Company LinkedIn profile
- Company size and industry
- Employee count
- Personalized lead summary
- Company overview
- Website and contact details
The agent cross-references multiple data sources, which makes it surprisingly accurate. It’s like having a research assistant who never sleeps and costs pennies per lookup.
Step 3: Automate the flow with Make.com
Once you’ve got your research agent set up, it’s time to connect the dots with Make.com.
Here’s the flow:
- Trigger: A new subscriber is added to your list.
- Action 1: Send their name and email to your research agent.
- Action 2: Receive enriched data back from the AI.
- Action 3: Update your CRM (or Google Sheet) with the new data.
- Action 4: Run lead scoring inside your CRM (HubSpot makes this easy).
- Action 5 (Optional): Trigger a personalized outreach sequence with your CRM or Lemlist (my go-to tool for outbound).
The entire setup takes about 30 minutes. After that, every single lead is enriched within minutes of signing up.
Step 4: Personalize with segmentation
Once you have rich data on every subscriber, you can finally stop treating everyone the same.
Here’s how I segment:
- Executives: I talk about ROI, strategy, and business outcomes.
- Individual contributors: I share tactical tips and actionable advice they can use tomorrow.
- Small business owners: I highlight cost-effectiveness and ease of implementation.
- Enterprise contacts: I emphasize scalability, compliance, and integration with existing systems.
This isn’t personalization for its own sake. It’s about making sure the value I deliver is actually relevant to the person on the other end.
How much does an AI-powered lead research workflow cost?
The cost depends on your automation platform, AI research agent, CRM, and the number of leads you enrich. Make and Relevance AI provide the core workflow, while HubSpot and Lemlist add CRM and outreach capabilities. Usage-based charges can increase as your lead volume grows.
Here’s the monthly cost breakdown:
| Tool | Plan | Price (per month) | Trial |
| Make.com | Core | From $12/month for 10,000 credits | Freemium |
| Relevance AI | Pro | $19/month billed annually, or $29 monthly | Freemium |
| HubSpot | Pro Hub | From $800/month billed annually | Freemium |
| Lemlist | Email Pro | $55/month billed annually, or $69 monthly | Free trial |
Now, I know what you’re thinking—HubSpot skews this table. But you can start lean with just Make.com + Relevance AI + Sheets, without paying for HubSpot or Lemlist. Your actual costs will depend on your billing plans, usage, and the number of leads you enrich.
And when you look at it logically, if this system saves you just 30 minutes of manual research per week, it pays for itself many times over. That’s before you even factor in the increased engagement and conversions that come from more relevant messaging.
How can B2B marketers start automating lead research?
Start with one automated workflow that enriches new sign-ups and updates your CRM. Once that’s working, use the additional information to segment subscribers, personalize outreach, and measure whether the automation improves engagement and conversions.
With AI lead enrichment, every new sign-up instantly becomes a fully profiled lead ready for personalized outreach. Here’s your checklist if you want to implement this system:
- Audit your current process. How much time is wasted on manual research? Where are you missing personalization opportunities?
- Pick your tools. Start lean with Make.com + Relevance AI + Sheets. Add a CRM when you’re ready.
- Set up your research agent. Use the Beni AI template to get started fast.
- Automate the workflow. Map the trigger → research → CRM update → lead scoring → personalization.
- Define 3–4 meaningful segments. Executives, SMB owners, enterprise buyers—whatever fits your business.
- Run it for a month. Track engagement rates, open rates, and conversions.
- Iterate. Refine your sequences based on what works.
Most marketers are leaving money on the table by treating all subscribers the same way.
Leveraging AI in B2B lead generation isn’t about fancy dashboards or flashy AI copy generators. It’s not about replacing marketers either. It’s about systematically understanding who’s raising their hand to hear from you and meeting them with relevance from the very start. And by removing friction, it gives us the space to do what humans do best: build trust, tell stories, and sell with empathy.
By making lead research invisible, automatic, and actionable, you don’t just save time—you create a better experience for every single subscriber.
Start small, set it up once, and let your AI lead research system compound value over time.
Smart lead research today is invisible, AI-powered, and instantly actionable. It moves beyond just collecting email addresses to understanding who your subscribers really are…When you automatically research every lead, you transform generic email blasts into personalized conversations. You turn cold subscribers into warm prospects. You start speaking their language from day one.
– Liana Hakobyan
Frequently asked questions
What is AI-powered lead research?
AI-powered lead research uses artificial intelligence to collect and organize information about potential customers. It can enrich basic contact records with job titles, company details, LinkedIn profiles, and other information used for B2B segmentation and outreach.
How do you automatically enrich newsletter sign-ups?
Connect your newsletter sign-up form to an AI research agent through an automation platform like Make. When someone subscribes, the workflow sends their details for enrichment and updates the resulting profile in your CRM.
Which AI tools can automate B2B lead research?
Relevance AI can run lead research agents, while Make connects those agents to sign-up forms and CRM systems. HubSpot can manage lead records and scoring, and Lemlist can support personalized outreach sequences.
How does AI lead enrichment improve B2B segmentation?
AI enrichment adds company size, industry, job title, and other attributes to subscriber profiles. Marketers can use those details to group contacts into relevant segments and tailor their messaging to different buying roles and business needs.
How do you measure the success of AI lead research automation?
Track the percentage of leads successfully enriched, time saved on manual research, email engagement, and lead-to-customer conversion rates. These metrics help determine whether the workflow improves both operational efficiency and lead quality.
What to do next
If you want to connect lead research with personalized outreach, CXL’s Build an all-bound marketing engine course covers using AI for prospect research, outbound personalization, and connected acquisition campaigns. For making better use of enriched subscriber data, the Email Marketing course covers segmentation, automated nurture sequences, and campaign optimization.
