In the digital age, automation has become the cornerstone of efficiency and productivity in various industries. TaskMagic, led by founder Jeremy Redman, is at the forefront of this automation revolution, showcasing how AI prompt engines like Gemini and ChatGPT can transform lead generation processes.

Introduction: Unveiling TaskMagic's Automation Capabilities Jeremy Redman, the visionary behind TaskMagic, introduces a groundbreaking approach to automating workflows using AI prompt engines. This automation not only streamlines processes but also revolutionizes lead generation techniques.

Automated Flow for Lead Generation TaskMagic's automation process involves seamlessly navigating websites, capturing screenshots, and analyzing them using advanced AI technologies like Gemini and ChatGPT. This innovative approach allows for quick decision-making based on visual cues, enhancing lead generation efficiency.

Lead Generation Filtering and Decision-Making Through intelligent filtering mechanisms, TaskMagic identifies SaaS products offering demos or free trials, crucial for determining potential leads. The automation process is designed to target specific criteria, ensuring that only the most relevant leads are pursued.

Automation Steps and Processes The step-by-step automation process employed by TaskMagic includes website scraping, analyzing matches, and categorizing leads based on predefined conditions. By leveraging AI prompt engines, TaskMagic simplifies the lead generation process and enables rapid decision-making.

Manual Validation and Communication While automation plays a significant role in lead generation, TaskMagic also emphasizes the importance of manual validation and personalized communication. This human touch ensures that leads are not only identified efficiently but also engaged with in a meaningful and personalized manner.

In conclusion, TaskMagic's innovative approach to lead generation showcases the power of automation combined with AI technologies. By automating repetitive tasks and leveraging intelligent algorithms, businesses can streamline their workflows, enhance efficiency, and ultimately generate high-quality leads. TaskMagic's integration of AI prompt engines opens new possibilities for lead generation, paving the way for a more efficient and personalized approach in the digital landscape.

Step 1- Click on Algomo web address

Step 2- Go to the page— Scrape list — Scrape links

Step 2- We can see the list of automations done here

Hey everybody, Jeremy Redman here, founder of TaskMagic. Uh, we have, I wanted to make a bumper to this quick video, and I wanted to show you how cool and an amazing use case TaskMagic is in automating your flows with AI prompt engines like Gemini or ChatGPT, you can automate your entire flow. And in this video, We show you what a customer runs through taking a screenshot of a website.

Automatically, it navigates, it prompts us, it navigates to the URL that they enter in there, screenshots it, then uploads that screenshot to Gemini in this case, I do believe. Correct, Kyle? Okay. And then, or you can also do this with ChatGPT and any other prompts, prompt engines. But, and then it makes decisions.

based on what it sees in the screenshot. And this is all automated. Any color or context to that before we see the video, Kyle? Yeah, so he trained his Gemini, I don't know what it's called for Gemini, their Gemini conversation that bot on looking at the screenshot of a website, which takes the like entire, uh, entire site screenshot.

He determines if that, If that SaaS product is offering demos or free trials, because if it's a demo, it's not good for his services. If they're free trials, it's a great fit for his services. So that's his lead gen, uh, filtering right there. Literally, for lead gen, that is a mi Thanks, Kyle. That is an insane way.

to generate leads based on something visual that you see. And you can set up as many conditional filters and formatting as you want. Simple, but beautiful and elegant flow. Great work. Uh, thank you so much. Check it out. Can you go through, I guess, what you're trying to do here? Um, and then we can go through the automation as well.

So these are my filters. It's like people in AI software. Um, with one to ten employees. certain date range, um, with a certain amount of web traffic every, every month. So, so this is, this is my process. Okay. Typically I would click on this, right. And when I get here, I'll be looking for the words, tried free and pricing.

And no demo, like if it doesn't say demo anywhere. So really you're just looking for SAS products that are not demo to get started is what it looks like. Pretty much. Yeah. Because, um, I do like churn. So typically things that have like demos and stuff typically, uh, it's, Because they do demos to, to onboard people nine times out of 10, they also have like customer success teams for if you cancel and all that stuff.

Right. Right. So, yeah, so I would typically come on this page, look at pricing, if it has pricing and try it for free, they're probably optimizing for growth and they don't have demos, which is like perfect for me. Okay. And I will come back here. If that matches and I'll press this and I'll save it to the list that says companies that actually match.

So what this automation does is it goes on the websites and it sends a screenshot of it to Gemini so that Gemini could analyze whether the site has the words free trial pricing and demo. If it has the word demo, it's instantly a bad match. If it has free trial and pricing without demo, it's a good match.

Uh, if it has the word, get the app. Or download the app. It becomes an ambiguous match because. nine times out of 10 app websites do not have the words, do not have pricing and free trial and all down their website. So then here goes the automation. So there were two different automations. I think you had made, right?

It was one of them was scraping crunch space. So with this one, I would go to the page and then I would scrape the list. Then I'll scrape the links. So this one basically runs through and copies everything and pastes it in the On in a Google sheet. And then this one is the one that you have that goes over all of those.

Yes. So, so then let's go through this, for example, please. Yeah, sweet. Okay. So then this is the website that you're screenshotting to try finding out if they have demos, free trial pricing, anything like that. Exactly. And this website should normally come up as an ambiguous or bad match just because it doesn't have the word pricing at the top.

Got it. So then it uploaded. Then it typed this one and then it's going to send it. Okay. So now it's set. Then I have a 30 second delay just so that it gives Gemini a chance to come up with the answer. Okay. So as you can see, it's scraped the stuff like this on the screenshot, you said it's a bad match and it probably just found out that it is a bad match.

Uh, and so I have a filter that sends it to delay. And then the next loop can we can we look at those steps really quick on the right also just to kind of see the logic if you scroll down there, I believe, yes, that's right here. Okay, so it went to the website, took a picture. It changed the URL in the uploaded the file and type this one.

Perfect. Sent it, you know, clicked, sent it, and then it's great, the result, right? And obviously there's the word bad match here. So in the filter, it was looking for the condition of the word bad match. And it found that that was true. Cool. And then if it was a good match, or if the condition wasn't met, you have a bunch of steps that go through the process of like adding it to your crunch face list that basically validates that person as a lead.

Exactly. Exactly. So. Uh, if the conditions were met, it would add them to a list, uh, which I typically manually check later. Um, because I use that list to figure out what to text or email the person. So I don't, I don't make my message to the people, but, uh, definitely automate, uh, automating. 50 percent of it is automating.

This is great then. Um, yeah, I think we're good. I think, I think that's finally, there we go.