10-15 qualified leads a day,
delivered without touching a single ad.
Our acquisition cost is a fraction of what competitors pay, because robots do the entire hunt for us. They pinpoint the exact decision-maker, enrich every data point, verify the professional email, and send a personalised message built from real company data. Our salespeople open every call with a warm, ready-to-talk lead already in the CRM.
Salespeople spend their day on admin, while the pipeline sits empty and targets get missed.
A salesperson is there to sell. But most of the time they are doing research, scrolling through LinkedIn, looking for an email address, getting through gatekeepers, writing cold messages from scratch. By the time they reach a real decision-maker, half the day is gone. This machine changes that equation entirely by taking the first three steps away from them completely.
Who it’s for
Any business that sells to other businesses and wants a steady pipeline of warm, verified contacts without paying for ads. Agencies, consultants, service firms, and any team where salespeople waste hours on prospecting instead of closing. If you can describe your ideal client, the machine can find them and contact them while you sleep.
What goes wrong
Without it, salespeople spend most of their week on profiling, qualifying, and finding contact information. The pipeline is thin, unpredictable, and dependent on whoever has the most energy to prospect that week. When the prospecting stops, the leads stop, and the revenue dries up. The machine makes acquisition consistent.
How the machine works
It runs in three parts: segment definition (the exact person you want), enrichment and verification (social data, company data, confirmed live email), and personalised outreach (a three-section message built from their specific data). All results go into the CRM automatically. Salespeople only step in to close.
What you get back
A consistent flow of verified, enriched contacts who receive a message that reads as if it was written by someone who genuinely researched them. Acquisition cost drops because there is no ad spend. Salesperson capacity doubles because there is no prospecting to do. The pipeline fills on autopilot, every single day.
We built this to cut our acquisition cost, and it works so well we now offer it as a service.
This is one of the most powerful systems we have ever built in the business. It handles all our client acquisition without paying a single dollar on ads, which means our cost to acquire a new client is a fraction of what most competitors pay. That gap is our advantage, and the machine is why it exists.
It works in three parts. First, we define the exact segment we want to attract. Not a broad category, the precise person. The CEO of a marketing agency in Beverly Hills who has been in business for ten years, turns over more than a certain amount, and employs a certain number of people. We create that profile once, and from that point the machine goes and finds exactly that person.
Second, it enriches everything it finds. It cross-checks social media, our internal databases, and public records to confirm this is the same person, not two different profiles mixed together. Then it finds their professional email and verifies it actually exists using one of our tools. Only addresses that pass that check move forward. The machine then looks at all the data, the social signals, the company details, the objectives a business at that stage would have, and builds a personalised email with three sections: a first line specific to them, a value proposition matched to their company and goals, and a call to action written for their role.
Everything lands in the CRM automatically. Salespeople spend an enormous amount of time on the first three steps of acquisition: profiling the person, qualifying them, and getting contact details past the gatekeeper. This machine takes all three steps out of their hands. They only focus on converting and closing, which is the one thing they are actually there to do. An empty pipeline from wasted prospecting hours is the main reason sales targets get missed. This fills it consistently.
We use it every single day in our own business to bring in clients. When we saw how reliably it worked, we opened it to a small number of clients as a done-for-you service. Proof point: I have documented how I built multiple income streams from systems like this in my YouTube breakdown of 28 income streams running in parallel, and the bigger picture behind all of it in my series on the road to 10 million, so the numbers on this page are checkable and grounded in what I actually run.
Three stages that fill the pipeline while the sales team closes
What made this work was treating prospecting as a machine problem, not a people problem. Most businesses hire more salespeople to fix a thin pipeline, which adds cost without fixing the root cause. The root cause is that salespeople are doing two jobs: finding people and closing them. This framework gives them back the one job they are brilliant at.
Define the exact person, then find them automatically
The machine starts with a precise client profile, not a broad category. You describe the role, the industry, the location, the company size, the years in business, and any other filters that separate the right person from everyone else. Once the profile is set, the machine searches public databases, professional networks, and company directories to surface only the contacts who match every filter. There is no spray-and-pray. Every name that comes out of stage one fits the profile you defined at the start. This is the part that used to take hours of manual LinkedIn scrolling, now done automatically for every batch.
Enrich every data point and verify the email is live
Finding a name is only the start. Stage two takes every contact found and builds a complete, verified picture. The machine cross-checks social media profiles, company data, and internal databases to confirm all the signals belong to the same person. Then it locates their professional email address and runs it through a verification tool to confirm the address exists and will actually deliver. Addresses that fail the check are dropped before anyone wastes time on them. What passes through is a contact with full enriched data and a confirmed live inbox, exactly what a salesperson needs to make a confident first approach.
Send a personalised message built from their own data
The final stage is the one that gets replies. The machine builds a three-section email for each contact using the data collected about them specifically. The opening line is written around something particular to their company or their recent activity, not a generic opener that reads like a template. The value proposition is matched to the objectives a business at their stage and size would be working toward. The call to action is framed around what makes sense for someone in their role. Every message reads as if it was written by a knowledgeable person who did their homework. All of it lands in the CRM automatically, ready for the salesperson to follow up and close.
Once those three stages run together, the pipeline fills consistently without anyone on the team spending time on prospecting. The machine finds the right people, confirms they are reachable, and puts a personalised message in their inbox. The sales team steps in at the only moment that actually requires human judgment: the conversation that turns a lead into a client.
Before the system
- Salespeople spent half their day on research and profiling
- Pipeline was thin, unpredictable, and easy to neglect
- Cold emails were generic and often went straight to the trash
- Acquisition cost was high because paid ads covered the gap
- Missing targets blamed on effort, not the broken process
After the system
- 10-15 verified, enriched leads arrive in the CRM every day
- Salespeople focus entirely on conversations and closing
- Every outreach message is built from real data about that person
- Acquisition cost dropped to a fraction of ad-driven competitors
- Pipeline is consistent, predictable, and independent of mood
Prompt 1: define the exact client profile the machine will hunt
The whole system depends on a precise profile. A vague description gives you a list full of the wrong people. A sharp description gives the machine filters it can apply exactly. Use this prompt to write a profile that the machine can actually act on.
Ideal client profile builder
Act as a B2B lead generation strategist. I want to build an automated system that finds my ideal clients and contacts them without any manual searching on my part. About my business: [describe what you sell and the problem you solve for clients]. Build the profile: what role title to target, what industry and sub-industry to focus on, what company size in headcount and revenue to filter by, what geography to cover, how many years in business is the right signal of maturity, and what one or two extra filters separate a genuine fit from a near-miss. For each filter, one line on why it matters and how to apply it cleanly.
The output is the exact profile the machine uses on every search run. Define it once and every lead that comes out already fits the person you actually want to talk to.
Prompt 2: map the enrichment sources for a complete contact picture
Knowing the name is not enough. The personalised message is only possible because you have full, verified data behind it. Use this prompt to plan which sources to check and what to pull from each one.
Lead enrichment planner
Act as a data enrichment specialist. I have a contact found by a lead generation machine and I want to build a complete, verified picture of that person before reaching out. About the contact type: [describe the role and industry of the typical contact the machine finds]. Map the enrichment: which public sources to check for company and personal data, what signals on social media confirm this is the right person, how to cross-reference two sources when the data conflicts, what fields to capture so the personalised email has enough to work with, and how to flag a contact as incomplete rather than passing bad data forward. For each source, one line on what it gives you and how to pull it without manual work.
The output is the enrichment map the machine follows on every contact. Run it once at setup and every lead that passes through arrives with the full picture a salesperson needs to open a confident conversation.
The 3-minute overview of how this works
Before the build steps, watch this short overview. It is the exact video from the Automations Made Easy page, and it walks through the mechanics behind machines like this one. 1,000+ students have used these mechanics to save two hours a day, with zero coding.
Want to learn the mechanics behind lead generation machines like this?
I teach the same mechanics that power this acquisition system inside Automations Made Easy. 1,000+ students have used these mechanics to save two hours a day and build little machines that fill the pipeline without ad spend. No coding required.
Week one: your first verified leads in the CRM, pipeline moving on day one.
Most people put off building a lead machine because it sounds complicated, so it stays on the list forever while the pipeline stays thin. Week one is not about perfection. It is about getting the first real, verified contacts into the CRM so you can see the machine doing its job and trust that it works.
Week one looks like this. On Monday you write the ideal client profile and confirm the filters are sharp enough to exclude the wrong people. By midweek you map the enrichment sources and set up the verification step so only live, confirmed emails pass through. Then you connect the personalisation layer and confirm the three-section message is pulling real data about each contact. By the end of the week the machine is running its first batch: finding contacts, enriching them, verifying the email, and dropping a personalised message into each inbox, all without anyone on the team lifting a finger.
The goal of week one is not volume. The goal is confirmation that the machine finds the right person, the enrichment is accurate, the email verifies, and the personalised message reads as if a knowledgeable person wrote it. Once you confirm those four things on a small batch, you scale the daily run and the pipeline fills on its own from there.
From there the numbers compound steadily. Say the machine delivers 10 qualified leads a day. That is 300 a month arriving in the CRM with a personalised message already in their inbox, at zero ad cost. If your close rate on a well-qualified, warm contact is modest, even a small percentage of those turns into real clients. Over six months the pipeline is full, the acquisition cost is a fraction of paid channels, and the salespeople are spending their whole day on the work that actually generates revenue.
All of this runs while you sleep, while you are in meetings, while you are working on other parts of the business. The machine finds the people, builds the picture, confirms the email, and sends the message. Salespeople step in at the conversation stage and close. The pipeline is no longer dependent on whoever has the most energy to prospect that week. It just runs.
Prompt 3: write the personalised email that gets a reply
The enrichment data is only valuable if the message uses it well. A generic cold email with the first name swapped in gets ignored. A message that references something real about their company and their goals gets a response. Use this prompt to write the three-section email that does that job.
Personalised outreach writer
Act as a B2B cold email copywriter. I have full enriched data about a prospective client and I want to write a three-section personalised email that reads as if a knowledgeable person researched them, not an automated template. About the contact: [paste the enriched data fields: role, company, industry, size, recent activity or milestone, specific goal or challenge their stage of business typically faces]. Write the email: an opening line specific to them that proves I looked, a value proposition that connects to their company objectives and the problem my offer solves for a business at their stage, and a call to action that asks for something small and appropriate for their role. Keep the whole message under 150 words. No filler. No flattery. Every sentence earns its place.
The output is the message the machine sends on your behalf. Settle the formula once and it fills in from real data for every contact, so every email in the batch reads as genuinely personal.
Prompt 4: hand the verified lead to the salesperson at the right moment
The machine does the prospecting, but a real person closes the deal. The handoff between machine and salesperson matters. A lead dropped into the CRM with no context is still a cold call. A lead with a full picture and an already-sent personalised message is a warm conversation. Use this prompt to plan the handoff.
Lead handoff protocol planner
Act as a sales operations advisor. My machine has found a verified, enriched contact and sent a personalised outreach email. I now want to hand that lead to a salesperson at the right moment with the right context so they can have a confident, warm conversation. About my sales team: [describe how many people handle follow-up and what CRM or tool they use]. Plan the handoff: what data to surface in the CRM record so the salesperson has everything they need in one view, when to trigger the handoff notification so they follow up at the right moment after the outreach lands, what the opening line of the follow-up call should reference so the conversation feels warm, and how to flag a lead who engaged with the email versus one who has not yet responded. For each step, one line on why it matters for the salesperson's confidence.
The output is the handoff protocol that turns a machine-generated lead into a warm human conversation. Set it once and every lead that arrives in the CRM comes with everything the salesperson needs to pick up the phone and close.
The exact build, step by step
Write the ideal client profile and set the search filters
Everything starts here. Before any robot searches for anyone, you write down exactly who you want to reach. Role, industry, company size, location, revenue, years in business, any filter that separates a real prospect from a near-miss. The more precise the profile, the cleaner the output from every search run. A vague profile gives you a long list of people you would never actually call. A precise one gives you a short list of people who are genuinely worth talking to, and every name that comes out of the machine already matches the person you described.
Send the robots out to find the exact person
With the profile locked, the machine searches. It queries public databases, professional directories, and company data sources looking for anyone who matches every filter you set. Not close matches, exact matches. When it finds a candidate it checks every filter again before passing them forward. The result is a clean list of real people who fit the description you gave, built automatically, with no hours spent scrolling through LinkedIn or guessing whether someone is senior enough to be worth contacting. The machine does this in the background while the team works on the conversations already in the pipeline.
Enrich the contact with every available data point
A name and a company are not enough to write a genuinely personal message. So the machine goes further. For each contact found, it cross-references social media profiles, company websites, news mentions, and internal databases to build a complete picture. It confirms the data belongs to the same person, not a mix of two different profiles with similar names. It collects recent company milestones, team size changes, product launches, and anything else that might be relevant to a first message. By the time enrichment is done, you know more about this contact than their own competitors do, and the message you send proves it.
Find and verify the professional email address
Social data and company information are useful, but you still need a confirmed live inbox to reach anyone. The machine locates the professional email address for each enriched contact using a combination of pattern matching and directory lookups. Then it runs each address through a verification tool that checks whether the inbox exists and will accept mail. Addresses that bounce the check are dropped, so nothing that passes through this step is guessable or dead. Every email address leaving stage four is confirmed deliverable, and every message sent to it arrives in a real inbox rather than bouncing into the void and damaging your sender reputation.
Build the three-section personalised email from real data
This is the step that gets replies. The machine takes all the enriched data for each contact and builds a message in three sections. The opening line is specific to that person, referencing something real about their company or their recent activity so the first sentence proves someone looked. The value proposition is written for a business at their size and stage, connecting what you offer to the goals they are most likely working toward. The call to action is appropriate for their role, asking for something small and easy to say yes to. The whole message is under 150 words and reads as if a knowledgeable colleague wrote it. Because the data is real, it does.
Drop everything into the CRM and hand off to the salesperson
The final step is the handoff. Every contact, enriched and with a verified email, goes into the CRM with the full data record attached. The personalised email is logged against the contact so the salesperson can see exactly what landed in the inbox before they pick up the phone. A notification triggers when it is the right moment to follow up. The salesperson steps in with a complete picture: who this person is, what their company looks like, what message they already received, and what angle to open the conversation with. There is no cold call here. There is a warm conversation started by a machine and finished by a person who knows exactly who they are talking to.
Profile and find
The machine takes the ideal client profile and searches databases automatically to surface exact matches.
Enrich and verify
Every contact is enriched from multiple sources and the email is confirmed live before the message goes out.
Personalise and send
A three-section email built from real data goes to the inbox, reading as if a colleague researched them.
CRM and close
The salesperson steps in with the full record and a warm lead already expecting a conversation.
Build your own lead machine inside the same playbook 1,000+ students use
Automations Made Easy teaches the mechanics behind lead generation systems like this one. Step by step, no code, plain English. Save two hours a day and own a machine that fills your pipeline on autopilot while you spend your time on the conversations that close.
The six months after we switched it on
Here is the shape of the first six months after we ran the lead generation machine at full speed. The chart tracks the monthly value of pipeline created from leads delivered by the machine, all at zero ad spend, compounding steadily as the machine ran every day.
Monthly pipeline value from machine-delivered leads
Three things matter on this chart. The pipeline value climbs steadily, not in a spike that falls away. Every dollar of pipeline shown here came from leads delivered at zero ad cost. And every one of those months ran while the salespeople spent their whole day on conversations, not on prospecting admin.
What other students built
I teach the simple skills behind machines like this in Automations Made Easy. Students who built their own version sent back what changed in their first month.
“My salespeople were spending half their day on LinkedIn looking for the right person to call. Now the leads arrive in the CRM already enriched and with a message already in their inbox. The team just closes.”
“The email verification step was the thing I had not thought of. We used to get bounces that damaged our domain. Now everything that goes out lands in a real inbox, and the reply rate is completely different.”
“I told my salesperson we were going to cut prospecting time to zero. She did not believe me until the first batch of leads landed in the CRM with personalised emails already sent. She is now focused entirely on closing.”
“Three months in and our acquisition cost is about a third of what we were spending on ads for the same quality of lead. The pipeline is more consistent now than it ever was when we were running campaigns.”
What’s inside Automations Made Easy
AME isn’t a library of pre-built automations. Every business is slightly different. What’s reusable across all of them is the underlying mechanics: how to set up little machines that find, enrich, and contact the right people while you sleep, and how to wire the pieces together without writing code.
The program walks you through six modules: The Right Tools (the cost-effective, no-code stack I actually use), Task Selection Mastery (which automations are worth building first), Design Secrets (mapping an automation before you build it), Zero to Hero (complete beginner to confident automator), Real-World Application (we build a full automation together, end to end), and Monetization Mastery (turn the skill into a side-business).
It also includes done-for-you templates you import in two clicks, over-the-shoulder training videos, and the same playbook 1,000+ students have used to save two hours a day. No coding required. If you can copy and paste, you can build this.
The lead generation machine: common questions
Pulled from what readers and Automations Made Easy students ask most.
Do I need a sales team to use this system?
No. The system works with a single person who handles outreach and closes deals. What it changes is where that person spends their time. Instead of spending hours on prospecting, finding contact details, and writing cold messages by hand, they step in at the moment a verified, enriched lead is ready in the CRM and the personalised email has already landed. Whether you have one person or a team of ten, the machine handles the front end and they handle the close.
How does the system find the right people to contact?
You define the profile of your ideal client once, things like industry, company size, location, role, and years in business. The machine uses that profile to search public databases, LinkedIn data, and company directories. It is not a broad spray. It only surfaces the people who match every filter you set, so the contacts that land in the CRM are the ones genuinely worth talking to, not a list padded with random names to hit a quota.
What does email verification actually do here?
After the system finds a contact and locates their professional email address, it checks that the address actually exists before sending anything. An address that bounces damages your sender reputation and wastes the salesperson’s time. The verification step removes that risk. Only addresses confirmed as live and deliverable pass through. Every email you send goes to a real inbox, which is why the open rates on this kind of outreach are so much higher than a bulk-spray approach.
How personalised is the email the system writes?
The message has three sections, each built from real data collected about that specific person. The opening line references something specific to them, a recent post, a company milestone, something that proves you looked. The value proposition connects to their company and the goals a business at their stage typically has. The call to action is framed around what matters to someone in their role. The result is a message that reads as if a knowledgeable person wrote it just for them, because the data behind it is genuinely specific.
Can this work in any industry or niche?
Any industry where you can define your ideal client clearly and where that client has a professional presence online can run this system. It has been used for marketing agencies, consulting firms, software companies, and service businesses. The profile definition at the start is the key step. The more precisely you describe who you want to reach, the more accurate the machine is, and the higher the quality of the leads that land in your pipeline.
More Money Makers like this one
Built from the same handful of mechanics. Each one captures, converts, or earns money that would have walked out the door.
Build this lead machine yourself, or learn the mechanics inside Automations Made Easy.
If you want to learn the mechanics behind lead generation systems like this and build your own at home, Automations Made Easy is the playbook. Step by step, no code, plain English. If you want to talk through how to define your client profile, set up enrichment, and personalise outreach at scale, I take a small number of consulting clients each month.
€497 one-time · Lifetime access · 1,000+ students
