Steal This AI Lead Generation System | No Code Tutorial

... Watch this. I'm going to enter a

search query, let's say, real estate in the United States, and

click Submit. Now, keep your eyes on the Google Sheet. In just a moment, you're

going to see a blank spreadsheet come to life. Row by row, it will automatically

populate to fresh, qualified leads. I built this no-code system to scrape,

verify, and deliver thousand fresh leads for just one dollar fifty cents.

We're getting the exact decision makers, their verified

email address, and even an AI-written icebreaker for each one, personalized

directly based on their company website. What you're watching is a system that just

saved me hours of manual work. In this video, I'm

going to show you step by step how I built that exact system from scratch, using

only no-code tools. No prior experience required. And if you want to skip the

setup and start getting leads in minutes, you can get the exact same workflow in the

description box below. And by the way, inside my community, I show you how to

contact these leads on autopilot, automate replies, and book calls without landing

in the spam folder. So if you're interested in that, make sure to join my

community. And by the end of the video, I will also do a detailed price breakdown.

[cash register ringing] But before we start building, let's take a quick look at

the big picture. This is the automation that we are going to build today from

scratch. It's built in n8n, a no-code platform. Just go to n8n.io and click Sign

In. Then you should see this window, and here you can click Create Workflow. Then

you have the same canvas open like in our AI automation here. Everything is here,

drag and drop, and easy to adjust by double-clicking on the nodes. And here's

how it works. When I click here, Execute Workflow, a new pop-up appears here. Here,

I can select the seniority level, for example, founder, owner, director, or

partner. I can select the company size here and the industry, for example, real

estate; the country, for example, United States;

and the lead number, for example, one hundred. When I click now here, Submit,

this whole automation starts running. First, the lead agent figures out how to

configure our scraping agent, then the scraping agent is running and get us all

the leads. Once we receive the leads, they're going through this automation

here. For each lead, we get the website and the website content, and based on

this, we create an icebreaker line for it. Then, this whole thing is saved in a

Google Sheets document here, and like you can see, it's getting updated here

regularly. And without further ado, we will now build this whole thing from

scratch. Make sure to open up the free instructions provided in the description

box below to follow along. Here, I also provide a template for the Google Sheets

document that you can use. Now, we will build the whole automation from scratch.

We will start with the input. First, you go to your overview and click Create

Workflow. Then you give this workflow a name, like Lead Scraper, and add your

first step by clicking here. Then you select On form submission, since we want

to start our workflow with a form submission. Here, you can fill out the

form title, the description, and add different elements. For example, seniority

level. Here you can select Type, for example, Drop-down, and here below, you

can provide different options. For example, founder, owner, director, and so

on. And you can add more form elements by clicking here, Add form element. If you filled out everything correctly, it

should look like this. You can click Pause to copy and paste everything, but

make sure it looks exactly like this here. Once we've done that, we can go back

to the canvas by clicking here, Close, and click Save. When I click now Execute

Workflow, this pop-up appears here. Let's quickly fill it out and click Submit. What will happen now

here is when we double-click on this node, we see here on the right side, the input

we gave. The great part is, in the next node, we can use this output as the input.

Let me show you how. First, you click here, the plus icon, and select AI, then

AI agent. For source for prompt, you select Define below, and here you can type

any prompt. And the great part is you can drag and drop here the different elements

here that will be then used in your prompt. For example, when I type in here

company size, I can reference the company size we gave in the form. But for now, you

click here, Expression, click this little icon, then you go to the instruction, and

under Lead Agent, you copy and paste the whole prompt and then paste it here. Then you close this, close this, and click

here, the plus icon under Chat Model, and type in OpenRouter, and select here,

OpenRouter. The model you can leave as it is, and you need to provide credentials.

For that, you click here and click Create new credential. Then you go to this

website, openrouter.ai, create an account here, and then click here, Keys. Then you

create a new key. Give it a name like n8n. Click Create, copy this key, and paste it

here and click Save. When everything worked fine, you should

see here, "Connection tested successfully." And make sure to add five

to ten bucks here, so you can use this service properly. OpenRouter is a unified

interface for LLMs, so it gives you access to all LLMs like Gemini, ChatGPT, or

Claude, and they even provide free AI models. So once you've done that, you

click here, Close, you close this here, too. Then you double-click here on the

agent and click here, Execute Step. When everything worked fine, you should see

here this output. This output will be used in the next node. But what it basically

does is, it takes our industry here, here, this user-selected industry, and based on

this industry, it looks up what is the closest match out of this available

industries. For example, in this case, for real estate, it's of course, real estate and commercial real estate. But let's

improve it a little because this output we cannot use in the next node so easily. To

improve that, we click here, Require specific output format. Then we close this

here again and click here on the output parser, the plus icon, and select

Structured Output Parser. Then we go to our instructions and copy this snippet

here under Output and paste it here. Then you close this

here and click again, AI Agent, and click again, Execute Step. What happens now is

we get a structured output that you can easily use in the next nodes. Last thing

you have to do is to rename this agent to Lead Agent. Then you close here and click

Save. Now, we got already these two parts finished of our automation. The next part

is the scraping engine. For this, we're using Apify. It's a scraper marketplace

where you can use different scrapers. They're called actors. For this specific

automation, we'll use the Leads Finder. That gives us one thousand leads for one

dollar fifty.... So basically, instead of building our own engine with proxies,

headless browsers, and the other complicated stuff, we prefer to use this

service here because it's pretty affordable and much cheaper than building

it everything from scratch. And now we will be building the scraping engine. When

we're using an external service like Apify, then the process is pretty much

almost the same. First, we send to Apify a job, so it's basically scraping in the

background. Then receive back a job ID. With the job ID, we check if this job is

already finished. If it's not finished, we wait a few seconds and check again, and

we do it so long until it's finished. When it's finished, then we continue here and

get the results first, so the leads, basically. Once we got the leads, we check

if for our search query, we found any leads. If so, if so, we're doing the

personalization. But now let's build this part. Click here the plus icon and type in

Apify and select Apify. If this node is not installed yet, install it quickly and

then select here, Run an Actor. First, we need to provide here our Apify key. For

that, click here, Create new credential, and click Connect my account. Once you've

done that, in Actor, select by ID, and then go here to Apify and select this ID

here, or you can also find it in the instructions. Then paste it here, go back

to the instructions, and copy this snippet here, and paste it

here. When you open this input here, then you see what we are basically sending to

Apify. We want leads for real estate and commercial real estate, the location is

United States. We want only validated emails, and for now, we want to catch only

ten. And now we can click Execute Step. What it basically does, it tells Apify

what to scrape for us. Now, we receive from Apify the status Succeeded, and the

job ID here. This job ID we can use to get our leads. Let's go back here, click the

plus icon, type again, Apify, select here Apify, and select here under Run, Get Run.

For ID, you select here by ID, and drag and drop this element here. And now we can

click Execute Step. Since the status is already succeeded, it means it finished

already the job. Let's go back here, but first, let's check if the job is really

finished. For that, we click here If and select here the If branch. Then we drag

and drop the status here, Succeeded, and make sure it's only true if this status is

equal to Succeeded. Now we click here, Execute Step, and like you can see, the

output is in the true branch. If the output is false, we hit the Wait node. We select this Wait

node, select here five seconds, so it waits five seconds, and then checks again

if the job is finished. Now click here, Save. So once the job is finished, we want

to get the results. For that, we type in Apify, select here Apify, and select here

under Dataset Actions, Get Dataset Items. And here, you need to provide a dataset

ID. For that, you go to the Run an Actor node, and here you simply drag and drop

the default dataset ID to the dataset ID and click Execute Step. If everything

worked fine, you should receive the similar output like this with ten items,

if you selected ten items. So then close this, click the plus icon, type in If,

select this. Then you go to the instructions, and under Results Found, you

copy this, you paste this here, select under Object Exists, and click

Execute Step. We do this to check if we got any results, because there's an edge

case where you don't get any results for your search term. And now we can continue.

We want now to build the personalized engine. For this, we click here the plus

icon and type in loop, and select Loop Over Items, and click here, Execute Step.

What it basically does is it takes these ten items and loops them one by one over

this workflow. The first thing we have to check

is that the lead really has an email. For that, we type in here, If, select here

If, then drag and drop this email here, and select here under, and select here under String Exists, and click Execute Step. This will

make sure we only take leads that really have an email. If they don't have an

email, we just loop over to the next item. By the way, best practice is always to

name your node. For example, here, Has Email. Next, we want also to check if they

have a website. If so, we want to make an icebreaker line. For that, we click here

the plus icon, select again If, but this time, we're drag and dropping the

company website here, select under String Exists, and click Execute Step. Then we

give it a name, Has Website, and close this. If it does not have a website, just

loop over to the next item. If it has a website, we want to make an HTTP request

here. Under method, we select Get, and here we simply drag and drop the company

website here. Then we click Execute Step, and we will receive here an HTML. The

problem is our AI agent cannot read this so well. That's why we want to extract

text. For that, we click here the plus icon, type in code, and select here code,

Code in JavaScript. And now we go to our instructions and select the snippet under

Extract Website Text Content, and paste it here, and click Execute Step. And now we

receive the full website's text content that we can use to create a personalized

icebreaker line. Let's close this and click here the plus icon and type in AI agent, and select here AI agent. Source or

prompt, you select Define below. Then you click here Expression and this little

icon, go to the instructions and copy and paste what's under Icebreaker AI agent,

and paste it here. So this prompt basically provides how we want to make the

icebreaker line, and we have here some examples. I highly recommend to use

examples of high-converting icebreaker lines. Just give the example some

placeholder like here, and let the AI fill out the blanks. Let's close this for now.

Close this again and click here on the chat model, Open

Router. Since we connected it, we don't need to do here anything. You can here

select a different model if you need. For now, we close this. Double-click again on

the AI agent and select here, Require Specific Output. Close this again, click

here, Output Parser. Select here, Structured Output Parser. Go to the

instructions, copy and paste the snippet under Output, paste it here. Double-click

again AI agent, and click Execute Step. Now our AI agent made the perfect

icebreaker line based on the information he received from our scraper. And like you

can see, we created this whole part. The last thing we have to do is to save

everything in a Google Sheets document. For that, you click here the plus icon and type Sheets, and select Google Sheets.

Here, select Append Row in Sheet. First, add your credentials by creating Create

New Credentials and sign in with Google. Once done that, you go here to Document,

select By URL. Open the template provided in the instructions. Click File, Make a

copy, so you have your own copy in your own Google Drive and have access to it.

Then you copy this URL... Then you copy this URL from the Google Sheets document and paste it here. Then you can select

here in the dropdown menu, the Leads sheet. And now it's easy. You take here

from the left the information, like company name, and drag and drop it to the

right field. For example, the company website is in Website, and you fill it out

for all these columns here. In the instructions, I also provided to you all

snippets that you need to make this all work. Just make sure to click Expression,

and then paste the snippet there. Once done that, it should look like this. When

you click now Execute Step, then you should see a new entry in your

Google Sheets document. Now close this here, click on this element and remove it,

and click Save. Congratulations, you are finished. Now you created the exact same

workflow like this one, and it will work the exact same way. Just make sure to

unpin this element here, so when you click Execute Workflow, you

start from scratch. Now let's talk quickly about pricing. So the Apify service costs

you around one dollar fifty per thousand leads. To create thousand personalized

messages with GPT 4.0, it costs you around sixty cents. And to host n8n monthly, it

costs you around twenty-eight dollars if you're hosted by n8n, or you could

technically self-host this whole thing for five dollars. I hope you like this

tutorial and see you in the next one.