Today I'm going to show you three boring AI automations you could sell to recruitment agencies, HR departments, and anybody doing hiring for 2. 2K a pop and up. I built these in a combination of make.
com and naden, as well as a few thirdparty platforms like Phantom Buster and Ampify. And I'm going to run you through how all of them work in a second. If you guys want these templates, get everything you need in Maker School, my 0ero to1 accountability roadmap where I guarantee you your first paying a automation customer in 90 days.
So the very first system is composed of a few Make. com automations. To make a long story short, what these do is these modify a hiring pipeline built in ClickUp.
Now, ClickUp is just a standin for whatever pipeline, CRM, or project management software you want to use, but in my case, I like using ClickUp. It's pretty straightforward and pretty easy. What I've done here is I built a hiring pipeline that you can very easily slot into any sort of recruitment or HR workflow.
On the lefth hand side here, we have the names of the applicants. I'll show you guys how people get into the system in a second. Then, we have the date that their records were updated.
From there, we have the status, and I'll show you guys a number of statuses in a moment. a portfolio, email address, a source because you can hire from multiple different places, the role that you're hiring for. You know, if you're a tech recruiter, then obviously these are probably going to be techreated.
If you're a services recruiter, they're probably going to be services related. The location, and then finally, a rating. Now, the way that this pipeline works is this is just an organizational tool that allows you to keep on top of all the people that are coming into the recruiting flow.
And so, what we're doing is we're separating them into a number of statuses. What I've done is I've built up a pipeline that's composed of a new applicant status for people that just fill out a form, which I'll show you in a second, a reviewed status, a request, trial, review trial, onboarding, hired, not a fit, and then complete statuses as well. The way that this works in a nutshell is there's a form that you fill out.
Now, I'm using an example from literally my own company. So, this is what I get people to fill out when they want to work with me. That includes an application.
What you do is you select the role you're applying for. You learn a little bit about the person that you are doing the work for. You enter in a bunch of contact details.
You link to your best work. So, usually that's some sort of portfolio, Google Drve, website, whatnot. You then have some specific questions about your availability.
You then put in questions related to where you're based. You then do some textual based questions where you answer questions about your experience. And then I also like getting people, and this is just something that I do for my own business.
You don't have to sell this to recruiters. I like getting people to think a little bit outside the box and give me a specific idea or improvement that they would implement in my business. Now what happens when I click submit is this then fires a watch responses type for module which gets that event.
I then sleep a little bit and then I list those responses. This is just a design pattern in make. com.
It makes it a lot easier to test flows. You don't technically need either of these steps but I like to have them. Then there's some custom logic that allows us to select roles.
Then finally what we do is we actually create the task inside of ClickUp. So now if I go back to my hiring pipeline you'll see that I've now been added as an entry. Okay, including my email address, my portfolio, and a bunch of other relevant info.
Now, the reason why recruiters love this sort of stuff is because you're automating a big chunk of most of their work. For instance, if I were to have a second automation now that monitored this pipeline, what I could do is I could set up rules where when I move their status from new applic, I automatically trigger an automation that then gets the project information and then sends it over via email to the prospect. So, now you have some sort of two-way communication going on.
Then, for instance, I might send them an email saying, "Hey, we really liked your portfolio, and I'd love to have you put together a paid trial for us. Here's a link to a form which explains the trial, gives you the brief, and tells you how to upload the finished product. " So, a lot of recruiters now have multi-step flows where it's not just an interview.
You'll actually ask them to do something for you. So, in this case, I'm just giving you guys a simple example with a video editor trial, but I'm sure you guys can imagine you guys could build out any sort of trial logic whatsoever with the tools that I'm giving you. So, first, we track your time using Clockify.
Your task is to do a 15 to 30 second clip. Here is a bunch of information about the specific task. And now all you do is you just upload the link before export.
Recruiters love this sort of stuff again because you were just automating actions based off of a pipeline. All we did was you just change the status from new applicant to request trial. Then it actually went and sent an email to our person with a link to another form that they can fill out.
Well, as I'm sure you can imagine, what you could do is you could hook up logic so that when that other form is filled out, they move to another stage of the pipeline and so on and so forth. This next system is built in NAND and what it does is automate the sending of connection requests with customized ice breakers using a thirdparty platform called Phantom Buster that actually connects directly to your LinkedIn account, uses your cookies and then automates actions like the sending of connection requests. The way that it works to start is if you click this test workflow button, a form will pop up and it'll ask, hey, what sort of audience are you looking to run a campaign on?
So here I can actually specifically say I'm looking for digital marketing agencies in the United States with 1 to 10 employees. When you click submit, what ends up happening is now we feed into AI a request to generate a search URL. What we do then is this is a customized search URL in a platform called Apollo that allows us to look specifically for digital marketing agencies with a range of 1 to 10 employees in the locations that we've specified.
And then we actually feed this directly into a platform called Appify, which allows us to run a scraper based off of an Apollo URL and then go onto this platform right over here and then generate giant lists of people including their email addresses and importantly for us, their LinkedIn profiles. If you go into the Appify back end, you can actually see legitimately email addresses being generated as we speak alongside LinkedIn URLs. And we're going to use these LinkedIn URLs to automate the sending of our connection requests with Phantom Buster.
From there, what we're doing is we're exporting those 500 items. And then in my case, I just wanted to test this for you. I'm limiting it to three items.
All you guys need to do is just delete this and everything else works the same. And then we're actually personalizing outreach based off of their Apollo and LinkedIn information. Queuing it up in a good output format for us to add to a Google sheet.
This Google sheet just contains a giant list of all of the information that we put in. We're aggregating this. And then we're triggering a Phantom Buster agent next.
Now, Phantom Buster, as you guys might be aware, is similar to Appify in so far that allows you to automate actions on various accounts. But whereas Appify is mostly about scraping things. So, it's sort of one way, Phantom Buster is a little bit more unidirectional.
What you do is you provide it your cookie and then Phantom Buster can actually go and take actions on your behalf on LinkedIn. And that's what we're doing right now. Essentially, we are now processing those LinkedIn profiles that I just shot over and then we're sending them a customized icebreaker along with that connection request just to significantly improve our odds of actually landing them.
As I'm sure you guys can imagine, recruiters love this sort of stuff because they spend most of their time on LinkedIn anyway. The average recruiter is on LinkedIn basically 247, both to post jobs for hiring purposes, both to, you know, connect with people in various industries that I think might be good fits and then also to source employers as well. So, this is a very cool way that they could actually source clients for their own business.
This last system is what I call the search intent scraping system. If you guys want a detailed example of me setting up this exact system live, like I actually walk you through the logic from zero all the way to one with a completed system, just check out the video that I'm linking right now. This is a summarized version of it obviously, but I want you guys not just to know what the end product looks like, but also know how to recreate it if you're forced to.
Anyway, the way that the system works is we rely on Appify once again, and what we do is we feed in a LinkedIn jobs or search URL. So this is for instance a search for BDR which stands for business development representative where we're looking specifically for companies that are hiring business development reps. Why is this valuable for recruitment agency?
Well, if a company's hiring business development reps and if my whole job as a recruitment agency or a recruiter is placing qualified candidates in companies that are hiring for particular roles, isn't that pretty serendipitous? I mean, now I have a big list of people that I could basically pitch my services to, right? So what this system does is it takes the output of that search and I'm going to run that right now.
passes it to a scraper, in our case Appify, then it runs that scraper, exports the data, and then allows us to enrich and get the email address of the CEOs and decision makers that are posting these jobs in the first place. From there, what we do is we do automated research using a AI tool called Perplexity. There are a variety of other AI tools you could use for this purpose as well.
Then we generate automatic ice breakers again customizing the first step of our outreach before finally automatically adding them to a cold email campaign in our case instantly. But you don't have to add them to a cold email campaign. You can just add them to a database.
This is the database right here. And so it's already filling with companies, their names, the locations, specific information about the salary. Then most importantly for us, it's filling with the email addresses, full names, and a bunch of other information of the CEOs and basically the decision makers that are responsible for putting this job out there.
From the first scenario, now we're researching the decision maker. And so we actually ended up with a bunch of information about the person that we were doing the research on behalf of. We're feeding that information into AI, asking it to write us a customized oneline icebreaker using the information that we just got as a result of that perplexity search.
Then what we're doing is we are automatically adding them to a campaign and then you know as you've seen populating a spreadsheet. So that's it. Thanks so much for making it to the end of the video.
Hopefully you guys got value out of these systems. I built them as I've mentioned in a variety of no code tools but this isn't the only way that you can build the systems that I've talked about and it's not certainly the only systems that you could build to sell to recruiters. My goal here is just to make your life really easy.
I just want to give you systems out of the box that I know already have value and that I and many other people in my communities have sold. Speaking of communities, the most recent win was from the lovely Lisa Pilot, who just landed a $4,800 deal 18 hours ago. She joined the community just a few weeks back and is already generating multiples on what most people can realistically do with full-time employment.
So, if you guys want to achieve results like that yourself, definitely check out Maker School. It's my 0ero to1 accountability roadmap where I legitimately just walk your hand through a series of daily steps to take you from somebody that's never sold AI and automation before to somebody that has now successfully achieved their first, second, or third clients. Regardless of background, regardless of where you're coming to the program from, thanks again.
Please do me a solid like, subscribe, do all the fun YouTube stuff that gets me to the top of the algo. And I will catch you on the next video. Backs.
