Steal this n8n system that will 4x your conversion rate (free template)

What's up guys? In this video, I'm gonna be showing you how to build two very, very simple systems in NAN that allow you to drastically increase the conversion rates on your sales calls. Just quickly, if you don't know who I am, my name's Rory Ridgers and I run an AI agency where we find and eliminate operational bottlenecks in 14 days to keep business owners working on the business rather than in it. So if that sounds like something you might be interested in, then I'll leave a link to my website in the description and you can go ahead and book up a free discovery call. Anyway, let's get straight into the video. By the way, free templates are available. It'll be linked in the description. So if you wanna go ahead, grab the free template and get started with this straight away. Just head over to the description and you can grab it for free. Okay, so we've got two systems to go over here. This is the first one. I'll show you the other one afterwards, but this is the first one. And as you can see, it's pretty simple. I'm going to give you a quick breakdown of what's happening and then we'll run it through and then we'll have a look what actually happened inside. So the first step is just going to be a Cal.com trigger and you can switch this out for whichever kind of booking tool you use. For me it's Cal.com, but it could be Calendly, could be HubSpot Forms, it could be anything. Um, but basically it's just going to trigger this workflow when a new inquiry comes in, when someone books up a call. And then we have an AI agent here. This is why the workflow looks so small, because this AI agent is doing a lot of the heavy lifting. It's connected up to an MCP server, which is connected up to Explorium. And if you don't know what Explorium is, it's basically a platform that it just allows you to do all different kinds of research on companies and individuals to get you back all kind of data. It's kind of like Apollo, but it has all of that data on leads and companies that you can access. So this AI agent is just gonna research that new lead, research their company and give us all of the relevant information that we need on them. And then we have an LLM step here that has context on our business and the kind of things that we sell and how we usually run through meetings. And what it's going to do, it's going to take all of the information that this AI agent here has gathered and it's going to craft an email body that's going to go to the sales rep. And in there it's just going to have all of the company's details that we wouldn't have got from the inquiry. So things like their location, annual revenue, employee count, industry, that kind of thing. And then it's going to give us a unique sort of analysis on what to focus on, on the call. So for example, I might say something like, you know, this company has more employees than the type of clients that we usually deal with. So ask these kind of questions on the call or take the call this kind of direction. It's gonna do that with all of the different data points. So it's gonna be completely unique email body that's gonna prepare the sales team for the calls so they know exactly what questions to ask and what direction to take the call. And then this wait node here, basically what this does is this just waits and it makes sure that the email sent over an hour before the meeting. And you can change this, it's completely up to you. You could do it a day before, you could do it 10 minutes before, 5 minutes before, whatever. But I've done it an hour before. So this brief is going to get sent over to the sales rep an hour before the meeting actually starts. Then of course we actually send this over. So what we're going to do is we're going to hit execute workflow and we're going to do a test event here. So if we come over to our form, let's just book a random time. Let's put in my details. Then the website for this, we're going to do Gymshark just because it's a pretty big company and I do it in all of my videos. And the demo sort of company that we're portraying as is a marketing agency. So we're just going to say something like, I want help getting more sales through Google Ads. Let's say I want more help getting sales through Google Ads. Let's hit confirm. And then once this schedules, let's give it a second. Yeah. Okay, cool. And you can see this is now triggered inside of NAN and it's running through this agent is gathering all of the information on Gymshark. And then now we're crafting the email body. And then what I'm actually going to do is I'm going to get rid of this node here, and I'm going to connect this straight up because as you can see, this is now going to sit and wait, um, until it's an hour for that meeting that I just scheduled, which is tomorrow. And obviously I'm not going to sit here and record until tomorrow, so we're just going to remove that. And then we're going to just manually run this step so we actually get the email. So of course, like I said, this would actually be running when you're using this system Uh, but just for this demo, I'm gonna get rid of it because I'm not gonna be sitting here recording for a full 24 hours. Um, I'm waiting for that email to come through. Cool. And then this is the email that we receive. So if we was the sales guy doing this call, we would receive this an hour before the call. So it says, hey Rory, just quick reminder about your meeting with Gymshark in an hour. So the company's Gymshark. This is their industry. These are their employees, annual revenue, and then their location. Key observations: Gymshark is a mature, high-growth e-commerce brand in the competitive athletic apparel market. Operating at scale with thousands of employees and hundreds of millions in revenue. Cool, it's given us some more data here. Focus area: advanced data-driven marketing strategy, integrating paid media across Meta, Google, and potentially LinkedIn for B2B partnerships or athlete endorsements. Cool, and it's given us a few other focus areas here. Then questions for the call: what digital marketing channels currently drive your highest ROI, and where do you see opportunity gaps? And then I'm not going to read all of these out, but you can see it's given us all of these different questions to ask on the call. Based on this company. And then suggested offering positioning. And then you can see here it's given us a suggested offering positioning. And then red flags/conversation strategy. Assume existing marketing teams and campaigns are in place because obviously it's a bigger company. Be sensitive to Gymshark's likely prior agency relationships because again, big company. GDPR and multi-market compliance are important, um, for a third time because they're a big company, right? But you can see it's tailoring this because Gymshark is obviously a massive, um, you know, multi-billion pound company. So it's tailoring these different things and making sure that we're compliant. And we're wary that they've worked with other agencies and they already have a marketing team in place. That's really cool. You can see this hyper-personalized to Gymshark, and this is going to give your sales rep all of the information they need going into the call on exactly sort of how to position their offer, uh, where to take the call, what kind of questions to ask. So if we have a look in here, what's actually going on— so our Cal.com trigger, this is just really, really simple. It's Cal.com, the event is going to be booking created, then every time a booking is created, it's going to trigger. And this is the kind of information that we get through. So it's like the attendee's information, Rory, uh, my phone number, my email address, uh, how can we help you, I want to get more sales through Google Ads. Cool. So basically just everything we put in there, as well as the time that we booked up the meeting. And then we have our AI agent here, and it's actually not showing up what it put in the MCP. So if we go to executions, it'll be a better way to look at this. Okay, cool. Yeah, so I just got the information from the executions. Now we can actually see what happened here. So basically in here we just give it the URL because that's all it really has to go off to research this company. So we give it the URL that we would've put into the form when we booked up the call. Then we just said, you'll be provided with the company information including domain. Your task is to research and extract the following key business metrics for this company. So then we've laid out exactly the different metrics that we want. Um, so name, website, annual revenue, number of employees, location, industry. I think these are pretty relevant, but of course when you're using this, you can do whatever you like. You can just add down here. Make a list of the other data points that you want to get, uh, for this company. So then I've given some information on how to use the Explorium tools. And the way it does it is first use Match Business to find the business ID, then use Enrich Businesses Firmographics to get the company details, and then return the data exactly in this format. And then what I want to show you quickly is actually Explorium, which we're using here. Okay, so this is Explorium. And like I said, this is basically just a platform where you can enrich businesses and individuals. And the way it works— this is the API docs here. I'm not going to run through the entire API docs because you don't really have to worry about it because we're using the MCP server rather than just HTTP requests. But I just wanted to give you sort of an overview on how it works. Basically how it works is Explorium just has like a massive database of different companies, and what you do is you first send off a company. Uh, so you do businesses/match, you send off a company by their domain and then you get back an ID if it's in this database, which it probably will be because the database is huge. So you get back an ID, and once you have your business ID— so Gymshark would have a unique business ID with Explorium— then we can use that business ID to do things like, if we go to business enrichments, we can enrich their firmographics, technographics, uh, social media presence, ratings by employees. And we do all of this once we have their ID. So it's just really simple, two-step process. You send it off, get the ID back, and then use that ID to do any of these kind of things that you can see here. But what we've done is we've hooked up to an MCP server, which is really, really cool. If we come in here, all we have to do is— I've already set up my Explorium, um, auth credentials, which is literally just an API key. So like you'd set up any other credentials, you just go to credentials in NAN, type up Explorium, and then you can just put in your API key from Explorium. And then the SSE endpoint is just going to be this here. So you just put this in, link up your authentication. Now it's going to be linked up to your Explorium account. And this is an MCP server. So basically just means the agent can use it to do whatever it wants inside of Explorium, which is so cool. Um, he's going to do any type of enrichment and pretty much do anything. So like I said earlier, this is why the system looks so small because this agent is doing so much here. You're able to enrich and get any data using this MCP server, which is awesome. So you can see what it inputted here. It just inputted gymshark.com. And then it would have got back somewhere in here their business ID. And then after that, it did the firmographics, so enrich their firmographics, and it got back all of this data. And then the way we get it to output in this structured format like this is we go to require specific output format, flick that on, and then we add down this node here. And then in here, we just put an example of how it should look. So name, website, annual revenue, number of employees, location, industry. And then we can just put test values in all of here. and then every single time it's going to actually output it like this. And to be fair, we don't actually need to output it like this, but it's just nice having it as separate variables. So you can see here, uh, these variables are now separate that we can do whatever we want with individually. So that's that first step. And then crafting an email body, essentially all this is, is just we've given it the data from the step before and we've given it a big prompt. Uh, so the prompt that we've put in here, the user prompt, is just gonna be all of the information from that step before. So name, website, annual revenue. Number of employees, location, and then industry. And then we've given it a system prompt down here that just says, you are part of a system that sends a detailed summary of a new lead over to the sales rep before they meet with that lead. And then we've just given it kind of context. So Pulse Wave Marketing is going to be like the fake marketing agency that it's working for, um, and we kind of said what Pulse Wave Marketing does— specialize in B2B and tech companies, sort of an overview of what we do. The goal of the AI assistant is to analyze incoming lead data, understand the company stage, industry potential challenges, and then produce a sales briefing for the rep taking the discovery call. And then each briefing should contain all of these different things. And then what we've done is we've given it some kind of logic. So we've said, first, look at that company size that came in. If it's less than 50, then it's probably founders wearing multiple hats, limited market capacity, emphasize automation, outsourcing, and done-for-you growth systems. And if it's sort of 50 to 250, internal marketers, Black strategy, depth, focus on funnel optimization, uh, blah blah blah. $250,000 to $1,000,000, and you can see here it just goes down. And based on the number of employees, all of the different angles and the different things to go in with. And then the second one, revenue tier, we've done the exact same thing. If it's around $5 million, bootstrap growth, ROI clarity, cost control, automation to reduce manual work. Then $5 to $50,000, $50,000 to $500,000, and we've given these sort of like exact things, these different marketing angles and opportunities based on these different firmographics that we've got here. And then same thing with industry, And then same thing with location as well. And then we've given it an example output with the key observations, focus area, uh, questions for the call, and suggested offer positioning. Then I just said try to keep it within 300 words. So then it just takes all of that and it gives us an output that looks something like this. Um, and obviously you saw it in that email. It's a little bit harder to read here, but you saw it in that email. That is what it gives us. And then we would usually have this wait node here. And this is really, really simple with the wait node. A lot of the time the wait node is kind of just used for, um, waiting, say, like 5 seconds or 10 seconds or whatever. But if you come up here, um, usually it's on after time interval and does what I just said, but you can do it at a specified time. And this just means it's going to do exactly what it says— it runs at a specified time, which is something that's kind of underutilized, but it's actually a really cool thing you can do. And what we have in here, you can see this big long variable, and all this is, is if we come to the Cal.com trigger, we have the start time of the meeting. So this is the start time here as you can see, which is 24th of October at 5:15. Cool. And then what we have here instead is basically we've taken that expression and then we've added a little bit on the end. You can see this bit is the part on the end. All this does is take 60 minutes off of that time because this is a time variable. You can see it's laid out like this, which is a time. It means you can sort of adjust it and do things to it. So you could add time, take away time. All we do is we take away 60 minutes, as you can see. And then it gives us the time, 60 minutes before the start time, which is how we're going to get it to send 1 hour before. So you can adjust this to whatever you like. All you have to do is change these numbers here. But right now, as you can see, it's on 60 minutes. And then of course we run that through, and then it comes to the send a message. So Gmail, so we've got the Gmail node set up, and then it's just going to me. So I've just put in my email, the subject, I've just done the name of that lead and then meeting prep. So Gymshark meeting prep. And then what I've said is, hey Rory, just a quick reminder about your meeting with, and then the name again, which is Gymshark, in 1 hour. And then I've literally just given it the entire output from craft email body. So json.message.content. I've just given it this entire body here and this is what it looked like. And then like I said, this email is what we receive in the end. So this pretty simple system, but if you're someone who does sales, which I assume you are if you're watching this video or you have some kind of sales team, you'll know how important this is because all sales reps are going to be researching companies before they get on calls with them, especially when it's B2B kind of stuff. You're going to be researching these companies, you're going to be looking them up, and you're going to be sort of changing your strategy and your offer and your positioning a little bit ahead of the call based on the size of these companies or their location or their revenue, anything like that. You're going to be kind of changing your approach a little bit, but this part does it all automatically before you, which means you're aligned. This is the biggest thing— you're aligned on the call. You know exactly what you should be offering them. Because I'm sure if you know, if you're in sales, uh, not aligning with your customer or your lead is going to be a massive downfall and you're going to lose out on so many sales by kind of just offering— what you're offering them could be great, but it could be something that is just not relevant to them. For example, like if you said with Gymshark, massive company, already has a marketing team in-house. If he was offering them this really, really good package where you take over their entire marketing operations and you're gonna do a really, really good job, might be a great offer, but for Gymshark that's not really going to be aligned with them because they already have that marketing team in-house and you wouldn't that unless you've looked them up. So this does this all automatically for you, sends this brief to make sure you're aligned on that call. Cool. And then the second one is even simpler, which you might be happy about. Um, or both these templates going to be completely free, by the way, so you don't have to build any of these. But what this system basically does is it just takes your meeting notes and then it does kind of the reverse of what it does before. It was sending you a prep ahead of the meeting, and now after the meeting it's just going to send you over an analysis and some action items and maybe what you could have done different. So same thing again, we're just gonna have a brief overview of it, run it through, and then look a little bit more in depth. So we just have a Google Drive trigger because for me, when my meeting notes— I just get them automatically done by Gemini because I use Google Meet— they get added to a Google Drive folder, and then we just extract that information from the Google Doc. And then we just have an agent here with a big prompt in it that we just give it that full transcript or summary and then it takes all of that information, summarizes it, and then gives us action items, things we could have done different, everything like that. And then it simply sends that over to us, and it's gonna happen pretty much instantly after your meeting. So, you know, after you've done the meeting, if you left the call, you've gone and made another coffee, by the time you come back, it's gonna be there ready for you. So we're gonna run this through quickly. I've done a demo sort of meeting notes I've put in this Google Drive folder, which is what it's running through now. So we're just gonna let this run through. It's gonna send me over an email and then we'll have a look at it together. Okay, cool. So it's finished running through now, and this is what it gave us. And by the way, this isn't for Gymshark. This is just demo meeting notes for a completely different company for this fake marketing agency. So this is what it said. Subject: Apex Core call debrief and next steps. So the company was Apex Core that we had a call with, obviously. Short summary: they've got 420 employees, $65 million ARR. And then a little bit about them. They have basic digital activity. Again, they're deceptive to attribution-driven program. Cool. Company overview. Current marketing situation. So their channels, their systems, their sales processes. Their goals and priorities: increase qualified inbound leads, implementation, attribution, analytics, align sales marketing workflows. Key insights and opportunities. And then our action items: so send short proposal requests before next call. And then budget range as well. And then recommended for us: marketing performance audit and attribution setup, HubSpot automation, AI lead scoring plus lead routing. And then 3 months LinkedIn, Google Ads pilot with CRO on landing page, reporting dashboard, tying campaigns, opportunities, revenue, So it's basically given us all of these different things, a massive overview of their company, their current situation, their goals and priorities, their key insights and opportunities, the action items for us, and then the recommended next steps for what we should offer them. Awesome. So all of this stuff your sales rep would have to be doing anyway. Um, but now this is all completely automated and it takes off maybe 10 seconds. So let's have a look inside of here and see what actually happens. So first of all, we have a Google Drive trigger, and for me, this is just linked up to the meetings recording folder, which looks like this with all of my meeting recordings. These are my actual real meeting recordings, by the way, with, uh, leads and clients. So all of them in there, I'll put a demo one in there for this though. So it's set up to that every time a new document is added to there, it's going to trigger this workflow. And then all we do is, because every single time, as you can see, they're Google Docs, they're not PDFs or spreadsheets or anything like that, we just do a Get Document Google Docs node. And over here we will get a JSON ID. So you can see, yeah, ID, we can just drag that in. Awesome. And then yeah, we extract the information from that document. You can see this is the information. I'll show you the document actually. This is what it looks like. As you can see, just sort of a summary of that meeting that Gemini automatically does. And then we get all that information back and then we send it to our note-taker agent. So just content, json.content. This is just the full Google Doc. And then we've given it again quite a big long prompt. You are an AI sales insights assistant for Pulsewave Marketing. 'a data-driven growth agency that helps B2B and tech companies scale through paid ads, automation, and funnel optimization.' And then we've given it a bit more context. 'Your objective from the meeting notes provided: identify, summarize the company overview. What do they do? Who are their customers? What stage of growth they're in? Current marketing situation? What channels are they currently using, if any? Pain points, challenges, or inefficiencies? Any signs of digital maturity? Goals and priorities?' Uh, key insights and then recommended next steps, action items, uh, what follow-ups are needed, and then guidance for contextual understanding. And then we've just given it some guidance similar to before on like the company size, the revenue, the industry, the location, what sort of like next steps should we have and what sort of, and what sort of things should we be offering based on everything. And then the summary, this is how it should actually output. It should do it like this. So key insights, goals mentioned, challenges and pain points, action items, next steps, recommended pulse wave focus areas. And then we've just given it some information on the tone and style, and then it's going to output something that looks like this. And then we simply just email that over to myself. So, to myself, subject: post-meeting analysis, and then, hey Rory, and then I've just given it the entire output. And like you've seen, it looks like this. So as you can see, these are both pretty simple automations. I mean, there are only a few nodes, both of them. But I hope this kind of highlights for you that you don't need these crazy complex mega automations that do like everything in order for them to provide value. The way you're actually going to be able to solve real problems and provide real value isn't by just creating crazy complex systems. It is literally just going to be finding real problems and real pain points that real businesses are actually going through and then creating a system to solve that. Doesn't matter how complex the system is. It could be 4 nodes, it could be 400 nodes, it doesn't matter. People only care about those problems actually being solved. So yeah, I hope this kind of opens your eyes and sees that you don't need to build crazy complex systems. As long as the system solves the problem, which it does in this case— it solves both of these problems of not being prepared for the meeting and also not doing your analysis after the meeting and not knowing what to do after a meeting in terms of next steps and action items. So it solves both of these problems and it does it in a simple way, so everyone wins.