# Sell These 3 Simple AI Automations for $1.7K to B2B Agencies ## Метаданные - **Канал:** Nick Saraev - **YouTube:** https://www.youtube.com/watch?v=T9diMzLIpqQ - **Дата:** 17.05.2025 - **Длительность:** 13:21 - **Просмотры:** 27,572 ## Описание Join Maker School & get automation customer #1 + all my templates ⤵️ https://www.skool.com/makerschool/about?ref=e525fc95e7c346999dcec8e0e870e55d Want to work with my team, automate your business, & scale? ⤵️ https://cal.com/team/leftclick/discovery?source=youtube Watch me build my $300K/mo business live with daily videos + strategy ⤵️ https://www.youtube.com/@nicksaraevdaily Summary ⤵️ 3 simple yet high-value AI automations—like proposal writing, follow-ups, and content generation—that B2B agencies and coaches will gladly pay at least $1.7K for. They may sound boring, but they solve real problems and sell fast. My software, tools, & deals (some give me kickbacks—thank you!) 🚀 Instantly: https://link.nicksaraev.com/instantly-short 📧 Anymailfinder: https://link.nicksaraev.com/amf-short 🤖 Apify: https://console.apify.com/sign-up (30% off with code NICK30) 🧑🏽💻 n8n: https://n8n.partnerlinks.io/h372ujv8cw80 📈 Rize: https://link.nicksaraev.com/rize-short (25% off with promo code NICK) Follow me on other platforms 😈 📸 Instagram: https://www.instagram.com/nick_saraev 🕊️ Twitter/X: https://twitter.com/nicksaraev 🤙 Blog: https://nicksaraev.com Why watch? If this is your first view—hi, I’m Nick! TLDR: I spent six years building automated businesses with Make.com (most notably 1SecondCopy, a content company that hit 7 figures). Today a lot of people talk about automation, but I’ve noticed that very few have practical, real world success making money with it. So this channel is me chiming in and showing you what *real* systems that make *real* revenue look like. Hopefully I can help you improve your business, and in doing so, the rest of your life 🙏 Like, subscribe, and leave me a comment if you have a specific request! Thanks. Chapters 00:00 Introduction 00:25 AI proposal generator 04:34 Automated followup system 07:44 Cyclic content generator 12:46 Outro ## Содержание ### [0:00](https://www.youtube.com/watch?v=T9diMzLIpqQ) Introduction Here are three boring AI automations you can sell right now to B2B agencies, digital marketing companies, and SEO businesses for 1. 7K a pop or up. I built these using a combination of nadn and make. com. And in this video, I'm just going to walk you through how they work and why you might want to sell them. Obligatory. I have all these templates hosted on Maker School, my online community, where I guarantee that you'll get your first paying AI automation customer in 90 days or your money back. There's no risk involved, so definitely check that out in the description when you have a chance. The first system is a ### [0:25](https://www.youtube.com/watch?v=T9diMzLIpqQ&t=25s) AI proposal generator Google Slides AI proposal generator and a Panda do AI proposal generator. I offer two options here just because in order for the Panda doc AI proposal generator to work and it's a lot higher quality, believe me, you do have to pay a fair amount of money. Google Slides on the other hand is completely free. So I just wanted to give people here options on what to use. In a nutshell, the way that this works is for those of you that are unfamiliar with agency sales process, usually it involves some sort of discovery call or a closing call. basically some sort of transformation event where the salesperson or the agency tries to guide a prospect through their pain points and why the agency is the perfect fit to solve those pain points. And in order to do so, usually they have to generate some sort of proposal. Now, proposals are very laborious and typically if you want to do them by hand, they take a fair amount of time. You got to get the wording right. There's also a fair amount of design involved. What this system does, both of them, is this automates that process almost completely for you. So that all you need to do is get a proposal template and then we have AI generate everything in the prospect's own tone of voice and words so that by the end of a call or hell, even before the end of the call, the salesperson can have a beautiful looking high-quality proposal all ready to go to put immediately in the prospect's hands. And the reason why this is valuable is obviously you save sales administration time which helps the company because now your salesperson's time is spent doing things that matter like talking to customers and not things that don't matter like generating proposals. But more importantly, the sooner that you can get something to a customer typically the higher the conversion rate in a nutshell. Okay, enough talking. How does this actually work? Well, first you click test workflow. And as we see there's a sales call logging form over here. So the way that this works is on the call with the prospect what the salesperson will do is they'll ask them a few questions. They'll say, "Hey, what was your website? " "Okay, awesome. So, run me through what your problem is. " Right? Then you'll press on their pain points and then you'll position some sort of solution. While you position that solution, if it's a custom project, you usually come up with some sort of scope and then in your head as a salesperson, you'll have some cost and you'll also know how soon you can generate it. So, I've actually had AI just help me template out this stuff cuz I don't want to actually have to jump on a sales call in order to get all this data. So, let me just copy and paste the problem. And the problem in this case is client spends 10 hours a week manually processing inbound form submissions, triaging leads, and updating their CRM. Our solution as an AI automation agency is going to be an automated workflow that captures form submissions, scores, leads, and then updates the CRM. I'm going to paste the scope. in the cost. And then I'm also how soon. And when I click submit, what's going to happen is this is now going to pass the form that we filled out to AI. And now it's going to generate a bunch of proposal copy for us. What does the proposal copy look like? Basically, this we have a bunch of variables like proposal title, description name, one paragraph, problem summary. This depends on the way that you set up your particular template, but I'll give you guys a free template that you guys can screw around with to edit to your needs. And once we have all of these variables here, all we do is we replace fields inside of a pre-existing Google Slides template. And the end result, if I go to my email is you send an email to the prospect alongside a Google Doc. And if they open it, it looks something like this. So, automated lead management for 1 second copy efficiency boosting workflow automation to streamline lead capture and management. So, I just got this template directly off of Google Slides. Feel free to do whatever the heck you want to it, but here we have the automated lead management for 1second copy. Efficiency boosting workflow automation to streamline lead capture and management. As you guys can see, this template's quite pretty. And yeah, the text all fits. It's pretty sexy. Imagine receiving this as somebody that's suffering from this exact same problem. And having everything written out in such a way that makes it seem as if the person was reading your mind the whole time. That's sort of the energy with this. We even go as far as to have like pricing connected and then give people next steps. That's how the Google slides generator flow works. This is an example of the pandoc flow. The pandodoc flow works the exact same. It's just when we generate the proposal copy, we do so with slightly different format. Regardless, then what we do is we send it to pandoc using a panda API call. This is the slightly different part versus the Google slides. Like Google slides actually has this built-in to naden whereas with pandoc you have to kind of do a more circuitous path. But the end result is if we go back to our email and then we open up the panda doc, we have a highquality proposal generated in a slightly different template that looks something like this. that includes basically like a customized letter that we've written to them alongside a bunch of additional work here. Okay, so as I'm sure you can imagine, you guys can customize this to your own liking and make this even better than you guys see ### [4:34](https://www.youtube.com/watch?v=T9diMzLIpqQ&t=274s) Automated followup system here. The second system is a completely automated follow-up system that's perfect for B2B agency sales processes. So this is the system. The way that it works is you basically have a CRM as the data source. Now, what CRM am I using as the data source? I'm just using Google Sheets. The reason why is because Google Sheets is simple. It's straightforward and is free. You don't have to use Google Sheets, though. You could swap this out for whatever you want. Trello, ASA, ClickUp, what have you. This is what my CRM looks like. So, we have a first name field, a last name field, an email field, company, phone, lead status, source, industry, notes, and then the important one here is the last touch field. And this just represents the last time you've had some sort of back and forth with the prospect. A lot of CRM track this stuff for you automatically. I just built a custom last touch column here in Google Sheets to show you how this would work. And the essentially the way that the system works is every day we're just going to check this field, evaluate the last touch date, and just see how many days has it been since the last time we talked to the prospect. If it's over a certain number of days, well, then we just follow up with them. And then that field also gets updated. So, what does this actually look like? To start, we search the rows. Then we set a variable. Well, this variable is just the date. So, we use a little bit of custom date logic here. And the parsing is nowhere near as big of a deal as it looks like. This looks really scary from the outside end, but it's not. And then what we do is we actually grab all of the email history that we have with the prospect and then feed that into AI. The reason why we grab the email history from the prospect and feed it into AI is so that we know in what context the follow-up message should look like and seem. So, this is a big prompt that I put in. This is some more text where I'm providing it. the conversation history here which I'm aggregating from the get sent and get received. Then ultimately in my case I'm creating a draft but I'm sure you guys can imagine in your case you guys can do whatever you want. You guys could even automate the sending of this. So I'm searching through all the Google sheets. It identifies one of these records as not having been followed up with or touched in 4 days. And then what we're doing is we're grabbing all of the history of the email address communications that we've had. So basically, every email that I've sent to this prospect and received from this prospect just pops up immediately here. Then we feed all that into AI. And once this is done, now all I have to do is go back to my drafts, open them up over here, scroll up to the top, and just say following up. And as we see, we now have a customized email. This specific email doesn't reference anything in prior emails, but the system does. And all we're doing is we're just checking in after the chat, seeing if they have any other questions or if Tom, in this case, is ready to move forward. So, the reason why systems like this work so well is because they take into account the context. For one, two, the email follow-up isn't always going to be the same email follow-up. It's going to be dynamic. unique. And then three, this is probably one of the simplest formulations of an email follow-up system. You can set two or three routes. In my case, I've done 4 days, 8 days, and 14 days. And then just have this run once per day. I'm saying every day here at maybe 8:04, so it doesn't always seem like you're doing it at exactly 8. And yeah, the value in this is now you just have a system that automatically follows up, takes into account the last follow-up as well, and it'll just always be different. It'll always be unique. And this is a very simple and straightforward way to squeeze another 10 to 15% out of a ### [7:44](https://www.youtube.com/watch?v=T9diMzLIpqQ&t=464s) Cyclic content generator salesunnel. The third system is a cyclic content generator. This is something you could sell to any contentbased business, any SEO business, really any sort of like brand as well that needs to generate content with any regularity. So the way the system works, and I've actually already triggered this cuz it takes a fair amount of time, is a simple form pops up asking you for a keyword. So I put in the term AI automation. It also asks for an email and I put in Nicholas@gmail. com just my private email. From here we have a number of things that occur. The first is we actually feed an open AI call using the web search API that goes and it finds outlines of content on AI and automation. Okay. The reason why this is really valuable is using the outlines we then grab citations that allow us to have statistics basically relevant to the pieces that we're going to generate. So instead of us just hallucinating things, now we're actually going off of real data. From there, we extract and format these two pieces of information just using AI into an intermediary format that's good for us. And this is really the juice of it. What we do is we feed all that information into an open AI call that says your task is to generate a high-quality comprehensive outline for an article on a given topic. The topics provided to you along with three outlines of other articles that we scraped from web as well as a bunch of citations with oneline conclusions. your job, digest these articles, understand the citations, generate a new outline, make sure your outline is significantly better, then ensure you're not repeating what the outlines are, but you effectively encapsulate the concepts and ideas they're talking about in your new mega outline. Okay, we then generate the mega outline. So on the right hand side, as you guys can see, we've now generated the mega outline. I don't know why I don't use the schema view, I guess, so that I can actually scroll through this. This mega outline is written in markdown format, and you guys can see it actually includes a bunch of links, and the links there are super valuable. And a lot of people include links in AI generated content, but the second you have citations, you both significantly increase the discoverability because it's better for SEO. And two, you also just ground the content in fact. Now, the real juice aside from the outline that's being generated is we will take this whole outline. Then we just separate it based off the headings. And then for every heading, what we do is we just write a section specifically for that heading. So usually when you generate content, you have to trade things off. It's always a trade-off between how much content you're going to generate and then the depth that you're going to be able to go into in any one individual part of the content. But this cyclic content generator allows us to get by that. We don't have to do that anymore. We can just actually generate every section super deeply, okay? And then generate the next section super deeply and the next and the next over and over and over again. And then the final piece you can just weave together. In this case, we don't even weave it together because the quality is good enough that you don't have to. From there, I have a limit node. And you'll notice that I put a lot of limit nodes in NAN flows just because they make testing a lot easier. Then from here, what we're doing is we're actually taking the previous section and we're feeding it into another AI call. And the purpose of this AI call is basically just to summarize the below article in three sentences. The value there is we can then feed it into an OpenAI image generation node which then goes and it generates us some image. So in our case, we've generated this Aentic AI cute little bubbly thing and we're actually going to put that in our article. So, not only are we going to have citations and sources and links, we're also going to have high quality images. From there, we do a little bit of data formatting and logic. And then we do a bunch of Google Drive steps. We create from HTML file, download it to NAD, reupload it to drive, delete the HTML file, and then share the link in the email. Why do we have to do these? This is just a quirk of the way that the Google Drive API and NAN work together. The end result though is if I go to my email, you'll see there's an item shared with me, AI automation, navigating the future of intelligence. And unfortunately, you can't see the HTML render as markdown here, but if I click open with Google Docs, we then have our whole article. Now, this article doesn't look super sexy. You see, we got that cute little bubble um right off the bat. So, you can apply a couple of formatting changes if you want. You can also just do this procedurally using the API, but as we see, we actually get some citations. Artificial intelligence is rapidly evolved from a supportive role, functioning primarily as a helpful co-pilot, enhancing productivity to systems capable of autonomous decision-making, effectively placing AI in the pilot seat. This transition has brought forth the concept of agentic AI defined as systems capable of independent decision-making and actions without direct human oversight or intervention. Then we say the shift towards greater autonomy underscores an exponential growth trajectory in a automation market projections here's the citation estimate that the A automation sector will surpass 237 billion by 2025. Now aside from just some minor sizing issues here which again you can call the API for if I just make these a little bit smaller you know it looks a little bit better. I'm generating images in a very particular style. I wanted something that was just like universally okay. As you see, there's a bunch of images and links in the article, if I click on some of these links, these are actually like real live citations. And then so, you know, instead of it just being like a bunch of hallucinations, we actually have like real data here. So, in this case, it was exemplified by adaptive tutoring systems like Khan Academyy's Conigo, which supports both individual students and educators. And then it links to the time. com article for KIGO. So, yeah, that sort of system can be extraordinarily valuable in the right hands. I obviously have my own way of prompting and asking it for things. And this is by no means the best way of prompting it and asking for things. You can also generate much higher quality images than the particular implementation I'm doing here if you just call like the GPT40 image generator. I'm just doing this to save on token costs and stuff. But yeah, that's another really powerful system that you could sell to basically anybody in the digital space. Hopefully ### [12:46](https://www.youtube.com/watch?v=T9diMzLIpqQ&t=766s) Outro you guys found that valuable. Definitely if you want to sell AI automations and make a living off of it, check out Maker School. Our most recent win was from Salvador Stoce, who just landed his first client at age 15 in two weeks after getting started with the program. I guarantee your first a automation customer in 90 days or you don't pay a scent. That's kind of like the promise of the program assuming that you follow the steps. So yeah, we're a great community and I'm increasing prices every 100 members to reflect the increased value. So definitely get in while you can. Aside from that, if you guys could do me a big solid like, comment, subscribe, do all the fun stuff that bumps me to the top of the algo and I'll catch you on the next video. Thank you very much for making it to the end and have a lovely rest of the --- *Источник: https://ekstraktznaniy.ru/video/12017*