The 7 step framework that booked 50 qualified meetings in 6 weeks.

Before you start hunting for prospects, you need to understand exactly who you want to find, what signals are relevant to them, and the key data points you want to collect.

Locating a founder at a startup, or a C-level executive at a 200 person company, is going to drastically change where you start prospecting and the pain points they are facing.

This isn't about plugging away at a few messages.

This framework isn't about opening up Apollo or Clay and sending a handful of messages. It's about turning manual prospecting into a scalable demand gen system that fills up your diary.

We then break this down into a very specific profile, so we can build a super detailed approach for the scraping and enrichment stage.

This is one of the single biggest mistakes companies make when building out lists.

The list building part of lead generation is not about creating a list of ICP contact details. It's about building a reason to talk to them based on a specific pain point they are facing.

As an example, instead of grabbing a list of law firms from Google Maps, find a list of law firms that are running Google Ads, so you know they are already spending money on marketing. Then reach out with something helpful about how they can optimise their campaign.

We lean on the buying signals from the ICP stage to narrow down where to pull info from, so we can feed it into the enrichment and personalisation stages later on.

This step is not just about getting a clean list. It's about protecting your reputation from sending messages to non-ICP matches that slipped through the net.

The truth is, when you start grabbing data at scale, it's going to get a bit messy.

That's why we separate the scraping from the enrichment, so team members can check and clean the list before we waste credits on an enrichment platform.

LLMs are a fantastic way of filtering out profiles, so we use them as validators in our workflows.

The power of LLMs in workflows

Each model has its own strength, so we give each one a specific job.

• ChatGPTLogicLeverage the logic for building workflows, like validating whether a company matches your ICP.
• PerplexityResearchScraping intelligence. Great for deeper dive research on companies and contacts.
• ClaudeContentCreation and intelligence for content, like writing icebreakers in your tone of voice.

Now you have a clean list, you can start building out the enrichment to find emails, LinkedIn profiles, and additional decision makers you can reach out to.

This is where tools like Apollo come in. They have a great API setup for matching people and enrichment, so you can build out the list in minutes.

The enrichment stage is also a chance to piece together any missing data. Sometimes Apollo doesn't find an email for a contact, but Hunter will, so you can add a secondary step to maximise the list.

The more personal and specific you make your outreach, the better the reply rate will be.

We're not saying let AI write you an entire email. But when you're drilling down on activity across 500 people, picking out key highlights to show you've done your research is a lengthy process.

Personality from you. Icebreakers from automation.

If one award is for Residential PropTech of the Year and another is Scale-Up PropTech of the Year, you need a way to dynamically create those personal intros. We feed multiple company data points into LLMs, so they read, understand, and produce personalised icebreakers in your tone of voice at scale.

Instead of feeding this straight into the outreach system, we do it in Airtable or a Google Sheet, so someone can QA the quality and make sure AI didn't miss anything. AKA: human in the loop.

The quick and dirty way would have been to run outreach from the start without checking the list.

This is exactly why founders come to us and tell us something is broken or not working.

Before you feed a list of contacts into LinkedIn or email, you need to make sure you have a top notch list that meets all of the criteria. Otherwise, every step before it breaks down.

To get this rocking in a platform like Smartlead, set up custom tags to pull the data into an outreach list, and build the personalisation lines into a template you've created.

That's it. You can now build campaigns for a range of different buying signals while one campaign is live, and measure success campaign by campaign.

Reporting can turn what looks like a losing campaign into an absolute game changer for lead generation.

Instead of only looking at outreach metrics, look at the entire funnel from where you started prospecting, so you can trace everything back and fix the issue. We break this down into specific numbers to gauge volume, quality, and strategy in one place.

The breakdown quickly tells you if you scraped from the wrong place, didn't maximise enrichment, or if the list cleaning step is throwing up an error. Looking at what went into the system and what came out builds a clearer picture of what to do next.

The human in the loop stages

This is why we always have a human in the loop, so a real person verifies the quality of the lists, rather than everything running from a black box with no oversight or approval.

1. Checkpoint 1Research sheetScraped profiles checked before any credits are spent.
2. Checkpoint 2Enrichment sheetContacts and emails QA’d before they hit a campaign.
3. Checkpoint 3Icebreaker sheetEvery AI opening line reviewed for tone and accuracy.

Breaking it into three stages means your outreach runs with confidence, quality, and human oversight, while scalable systems take away the heavy lifting of lead gen.

Every tool we use across the framework, grouped by job. The highlighted tools are our core picks, with proven alternatives alongside so you can build with what you already have.

• Automation

  • MakeCore
  • Zapier
  • n8n

• AI models

  • ChatGPTCore
  • PerplexityCore
  • Gemini
  • Claude

• Enrichment

  • ClClayCore
  • Apollo
  • HuHunter
  • ZoZoomInfo

• Prospecting

  • ApApifyCore
  • PhPhantom Buster
  • ScScrapingBee
  • RaRapidAPI

• CRM / DB

  • HubSpotCore
  • Airtable
  • MSMS Lists
  • Google Sheets

• SEO / GEO

  • AhrefsCore
  • Semrush
  • ScScreaming Frog
  • SiSitebulb