Wedding Business Solutions

Abed Elsamna - What are AI Agents and should you use them for your business?

• Alan Berg, CSP, Global Speaking Fellow

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Abed Elsamna - What are AI Agents and should you use them for your business?

Are you letting AI work for your wedding business, or is it still just a mysterious buzzword? What if an intelligent agent could answer leads, schedule appointments, and handle objections—without you lifting a finger? In this episode, I interview Abed Elsamna to break down exactly what AI agents are (and aren’t), how they’re different from chatbots, and why they’re about to transform how you run your business. What pain points could you solve by handing off repetitive tasks? And are you ready for a world where every lead gets instant, personalized attention—while you focus on what actually sets you apart?

Listen to this new episode for real-world scenarios, key differences between AI agents and chatbots, and a look at the future of automating your sales process—without losing your personal touch.

About Abed:
Abed Elsamna is the founder and CEO of VenueX AI, a platform transforming how wedding and event venues sell. Its AI agents engage leads the moment they inquire, follow up and book tours on auto-pilot—helping venues focus on doing what they do best - hosting world class events.

Visit www.venuexai.com to learn more

If you have any questions about anything in this, or any of my podcasts, or have a suggestion for a topic or guest, please reach out directly to me at Alan@WeddingBusinessSolutions.com or visit my website Podcast.AlanBerg.com 

Please be sure to subscribe to this podcast and leave a review (thanks, it really does make a difference). If you want to get notifications of new episodes and upcoming workshops and webinars, you can sign up at www.ConnectWithAlanBerg.com  

View the full transcript on Alan’s site: https://alanberg.com/blog/


Want to see about joining an upcoming mastermind (bring together some industry friends to have me spend a day with you all) - or arranging one of your own (yes, I'll come to you!)? Reach out to me at Alan@WeddingBusinessSolutions.com or text or call +1.732.422.6362

I'm Alan Berg. Thanks for listening. If you have any questions about this or if you'd like to suggest other topics for "The Wedding Business Solutions Podcast" please let me know. My email is Alan@WeddingBusinessSolutions.com. Look forward to seeing you on the next episode. Thanks.

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©2025 Wedding Business Solutions LLC & AlanBerg.com

AI agents? Are they secret agents? Listen to this episode and find out. Hey, it's Alan Berg. Welcome back to another episode of the Wedding Business Solutions podcast. I am so happy to have my friend Abed El Samna on to talk about AI agents. Don't worry, we'll explain that what that is. Abed, how you doing? I'm doing well, Alan, how about yourself? I'm doing well. And you know, full disclosure, I've been, you know, consulting with you on the AI agent that you're developing right now, and that's live right now. But you know, you hear about these headlines, right? AI agents, AI agents and all these things and people are like, like, what do you mean an agent? You know, like, like what kind of an agent is this thing? So, so tell everybody what is an AI agent and how is it different than just using ChatGPT? Let's say. Sure, so get that question all the time. Especially as AI is becoming a lot more prevalent in, in, in society. Everyone's using it day in and day out and this new concept of AI agents is starting to hit the headlines and that's going across every industry essentially, especially with customer service and sales. So in the most simplest form, an AI agent is really just a very intelligent software program that can understand information in real time and process it in real time and then do things on your behalf. So there's so many different examples that we can use, but it's just technology that can do things for you on autopilot. So again, how is this different than I go to ChatGPT and I ask it a question that answers the question, right? So that's not an agent. What is that? Yeah, that's not, that's not an agent. So that's just, that's just kind of what, two way chat between you and, and what we call large language models. So a chat GPT a perplexity a Claude, there's so many of them out there now and you're asking it a question and you're prompting it to provide you with a response back, right? So it taps into a knowledge base of a whole bun of data points and it spits out a result. Now on the flip side, an agent does kind of two things at the same time. Number one, it has a knowledge base of information that it can use to perform your task. And that task is built around a whole bunch of predefined parameters. So you know, one of the things that our company VenueX AI does is we provide an AI agent that's specifically for the pre booking Sales process. So the agent can understand everything about a venue's pricing, packages, availability, and everything that they offer, and then take that information and then respond back to leads in full conversation and book appointments and do a whole host of other things. So it can automatically just take over a full conversation for this example and, and do it on autopilot. Right. So the difference there is someone is inquiring on someone's website or through the knot or wedding wire or whatever, and then the agent has that conversation. Not with you, who is the owner of that technology. Right, right. You, the venue. It's having that on your behalf, scheduling the tour, which is another activity that it's doing on your behalf, responding to what someone's saying objections like, you know, that price is more than we wanted to spend, or, you know, we really wanted a Saturday, or, you know, can I bring my dog to the ceremony? Or whatever. Right, okay, I get that. So. So the chatbot that I've created, is that an agent or is that just like Another version of ChatGPT, but specifically on. Trained on my stuff? So that's a. Another version of chat GPT, but specifically trained on your stuff. Now with chatbots, you could extend them out to become, to have what we call agentic workflows, which is that whole concept of doing things on your behalf. Like, okay, if your chatbot had the ability to schedule an appointment with a particular lead in lead in, in real time, that becomes an agentic workflow. Right. So it can take your knowledge base of information, it can look at your calendar, understand all the parameters that you've set in place about when to schedule an appointment and how to schedule an appointment, and then it automatically will schedule that appointment, put it on your calendar, send it out to the, the leads calendar as well. So you can apply what we call these agentic workflows to a lot of different scenarios. And that's certainly one you can do. Okay, so. And it can do multiple different tasks. It can, because I think Perplexity just had something where it's got an agent, but the agent can then tell another agent to do something to tell another area. So is that, that's this agentic? Right, so agent. Agentic workflow there, Right? That's right. And the agentic workflows happen. You know what we call the front end, which is like a venue Xai style, the lead communicates with an agent. But also it gets even more complicated behind the scenes. So I'll give you a prime example. You know, we're. Our business is built around agents as well, right, so we have four or five different agents that are talking to each other to produce the front end agent experience as well. So one agent looks at available dates, the other, the other agent produces an output of how it can respond back. It should respond back to leads and then they all kind of talk to each other and what, it's, what's going to end up happening I think probably within the next 12 to 18 months where Agent workflows become. So consumers get so used to agentic workflows that a lot of companies are going to be adapting that behind the scenes as well. So there's a very, very large shift that, that's happening in real time and it's such an amazing time to, to see that and live through it. So back in the stone age we used to talk about macros, right? So your macro was. You entered one command and a bunch of things happened. Could happen in a spreadsheet could happen, you know, somehow like that is this the, the next version of that? And you're spot on where this is the kind of next wave of that. Right. So the, the biggest difference between kind of the scenario of like the macro level models essentially in Excel compared to like an agentic workflow is that is the, the decision making capabilities, right? So AI agents are able to consume large amounts of data and in milliseconds based off of the parameters, decide on what to do next. Right? And that decision of what to do next becomes that agentic workflow of. Here's what I'm going to do on behalf of the. The, the structure that I have in place for my agent versus the macros are predefined, right? It goes through a very series of algorithmic steps to get certain steps done and it doesn't have decision making capabilities. Okay, so, so using, I'm going to use Venue X AI as an example. So you have preset templates and then you have the AI. For instance, somebody makes an inquiry and you tell it, let's say it's a pretty standard inquiry, right? I'd like to get pricing and packages and we can have a pretty standard pre written first response because you're going to respond pretty much the same way every time. If someone doesn't respond, we've then told it, this is your second response, your third, your fourth, your fifth, your sixth, because the other person isn't responding, therefore there's no communication. But once they do, then the agent reads what they wrote and says okay, I'm going to respond not in a predefined way, but based upon predefined parameters. And that's where it's different than the templates which are fixed, don't change. You're going to get this message on this day and that's it, right? That's right. You're spot on. So, and the biggest, I think, advantage to having an AI agent and this goes across anything, customer success, sales, etc. Is exactly what you talked about, the historical context of a conversation so that it can spit out a very personalized response. And one of the examples I like to use all the time, if, if a lead is asking about a specific type of event and a theme for that event, a bohemian themed wedding, and that was in the first couple exchanges, but they haven't responded back and the agent's following up, it can tap into that theme and mention that in the conversation. So that is completely personalized. Right. So it reminds the lead that hey, we, we care about your theme, we care about what you're asking about and we're going to mention that in the conversation. Now, when you compare that to just kind of standard automation drip campaigns that a lot of folks use in their CRMs, where to your point, you have the specific cadence of day one, day three, day five, day seven, etc. And you have those templates, they're not personalized. Right. And when they do get sent out, they may be irrelevant to what the person was asking about. Right. And it may be just be too general of a response through a template that, you know, the, the lead themselves feel like they're just getting dropped into a campaign. Right. Even if you try to not make it sound like copy paste, it all of a sudden does. And a great example of that is a few years ago a client of mine in the UK had their first response set which said, hey, thanks for reaching out, we'd love to make your wedding amazing. Please let us know if email or phone is better for you. Sure. And they got an inquiry and the inquiry in there in the message box wrote, hey, by the way, I can't talk during the day, email's better for me. And then they got an email that said, let us know if email or phone is better for you. Right, Right. So this is a great example of where the AI agent could read that and say, okay, don't say is email or phone better? Because they just told me email is better, I can't talk on the phone. And it could adapt where this couldn't. That's right. So just this morning I was talking to Verizon Wireless's AI Agent, because I called, it was outside of hours. I got up early this morning, went to take a walk and. Whereas I think they used to have 24, seven people, but now they don't. And it said, it said it was the AI and it, you know, it was really weird as I'm calling and it said, are you calling about international data? And, and calling. I was like, had. How did it know that? Like, did it read my calendar, like to see that I'm going away? So I said yes, which was kind of weird. Like, how did you know? And, and then I'm talking and it's, it said, you know, here's the different plans. You have this One plan that's $12 a day included. Would you like to find out more about that? I can send you a text message. I said, no, it sent it to me anyway, right? And then I said, no, I want to find out about monthly plan. So then it finally, I thought, understood and it sent me another text and eventually I got it done. Not exactly through there. I ended up clicking through and in the app and, you know, now know it, you know, for $100 a month, it's better than $12 a day when you're going to be away for 16 days, you just do the math. It's half of that. So I did get it done a little frustratingly, but I got it done speaking to their agents. So I can only imagine these will get better, you know, as they, as they go along. Does the agent learn as it goes? It depends, you know, it really depends on the platform where the agents are built on, on top of. But some platforms allow what we call machine learning, where it understands over time and it just gets better and better using the more data it's receiving. Some platforms don't. They allow the user to go in and adjust the type of responses or anything that's built around the agent to improve on its own. But I guess to your point about the improvement of the agents, they are certainly getting better and better over time. And the reason they're getting better and better over time is because the agents are powered by these large language models, right? So OpenAI just released a ChatGPT5 and they're rolling up essentially all of their models into, eventually into chat GPT5 because they want the most powerful one to be presented to their consumers or to their users. So the smarter these LLMs get, the better the AI agents get. Okay, so when, when folks were building AI agents six months ago and they're using, you know, a different version of a Open AI or Chat GPT, they probably weren't as good as they were as they are today. And we also saw that with the AI agent that we built, the better the models, the, the better the agent gets and, and the better experience both like the venues plus their leads are getting with, with the models. So does that happen automatically, like my, you know, Ask Alan Anything Chatbot? If the people that are powering that, if they're, whatever model they're built on goes to the next level, will that automatically make my Chatbot smarter? Absolutely. Oh, that's very cool. Thank you. Yeah, yeah, yeah. And the way that works, Alan, is that you would have to select the most updated model. So whatever platform you're using to build out, you know, your chatbot, if you have it powered by 4o, like GPT4O or Claude or one of the other ones, you would just select the most updated model. Now, one of the most important things to think about, though, is when it comes to using those types of models, there's a cost difference, meaning some of the newest models tend to be a little bit more expensive if they are built for reasoning, if they're built for a little bit more of a nuance. And that's called compute. So the higher, the smarter the, the model, the more expensive it's going to be. Okay, well, and again, I guess they'll have to tell me, you know, what my annual plan is next year or something like that. So the training really is this, this is what I found out. It's actually why I went through the exercise of trying to create Ask Alan Anything is because I've heard, you know, we all get frustrated when that chatbot on somebody's website cannot answer our question. And you know, you're thinking sometimes, hey, my question isn't really that unusual. Why can't you answer that? And that's what I've learned. First of all, I used Chat GPT. I asked it to be my thought partner. And we, it interviewed me and we went back and forth and I was able to create this and I keep adding new stuff in, but then I find questions. So a, a friend of mine said, you know, I want to ask it what's, what's Alan's favorite place to speak? And I said, I don't think it's going to be able to answer that. It's not in my books. It's not, it's not in the training of it. But I did when we were beta testing this, somebody typed in what's Alan's favorite Bourbon. And of course it couldn't answer that, but if you ask it that now it does answer it. It actually says, you know, Alan could talk bourbon all day long, but I think if you asked him, he would say his favorite bourbon is the next one. So it actually answers that way now because that's, first of all, my sense of humor. And second of all, it's actually how I answer because people ask me that all the time, what's your favor? Favorite whiskey. And I'm always like, the next one, you know, the one I haven't had yet. The, the, the. The new discovery that that's the favorite one. But it wouldn't know that because it can be trained on that because I didn't write about that in a book or speak about that in a podcast. That's it. Well, I guess I just did. Now maybe, maybe to learn from that, now we can say that. So when, when you're creating the agent, so somebody is listening here, wants to. Is thinking about, hey, how could I use an agent? What are you. Some of the things that a wedding or event pro, besides what you're doing, which is just, you know, which is great. And again, I'm advising you on, you know, the best practices. You trained it on my books and stuff like that. What are some of the other things that an agent could do that might be helpful for somebody listening? Sure. So I would always. I always like to start off with pain points. Right. So agents have the ability to do a lot of different things, but in some cases, it may not actually work for the, the problem that somebody's trying to solve. Right. It always comes back to, I have a problem that I want to solve, and can software or agents or anything help solve that problem? So that's a, That's a good starting point. There are so many different ways to use agents. I think one of the most kind of critical ways to use an agent is for the sales process. Like, like what we're doing for VenueX AI, but really just finding out, you know, a lot of folks use agents for, you know, travel, trying to put together, like full travel itineraries. So that's kind of on a personal level. Some folks will use agents to, you know, build out a customer success. Right? Yeah. To help kind of drive that. And there's. I'm blanking out. No, but again, it's. So it's repetitive process. Right. Is that, that's the thing is with an agent is what are things that you have to do multiple steps, again and again, and then is it an agent or is it Just, you know, a zap through Zapier where you're connecting this to that so you don't have to type the data a second time and things like that. And I think probably where most people listening, including me, are going to get the most use out of it is when somebody like you creates this specifically for this need. Right. Like you've created this for venues. I'm sure eventually it'll roll out to other businesses. Right, but you've created it for venues because what's the pain point? The pain point is I'm getting so many inquiries I can't keep up with them. And not only the ones that I'm getting in now, but the ones from last month and the month or last week and the week before that and the week before that. And then, you know, I don't have enough time in the day to go back and forth or I'm doing a wedding. So how can I possibly respond to somebody right away when we always say the first one to respond? Right. So it's you finding that pain point and saying, and this was in a book I read called the AI Driven Leader. It's not what can I do for me, but what can I help me do? That's right. And the tool, like I use chat GPT for reasoning, I use Perplexity for my research and I'm actually researching. We're about to head on vacation and some of the excursions from this cruise we're taking, they're just too early in the morning for us. We're on vacation. It's like, I don't want to be walking off the boat at 8:30 in the morning. I'm sorry. No, I want to be in bed or having breakfast. Right. So we're looking up and saying, what is there to do? Okay, and then how do I do that? And I just had this one where I was able to book a walking tour in Amsterdam. And not the one that the ship is offering, but walking tour in Amsterdam after we get off the boat. Found the person, did. That's all through Perplexity. Right. And it gave me the links in there. Was able to go in there and do that and paid and done. But again, I'm using a tool that existed already, which is Perplexity, as opposed to creating this because it's not an everyday thing, it's not something I need to do every day. So when you say it can perform, it can do things for you, what can it connect to? Like to do like, you know what, what can, what is it? What the capabilities of an agent. Sure. It can connect to a lot of different things and there are different platforms. You mentioned Zapier. There's another platform called make.com where a lot of folks will have, they do have the ability to create their own custom AI agents to do really anything, especially the manual kind of tasks that they're doing day in and day out. Cleaning up spreadsheets, anything that's typically manual. So you can build your own custom AI agents in one of these automation tools or you know, where. Again, coming back to the pain points of like the specific thing that you're looking to solve, there are so many different companies out there now that are offering AI agents for particular, very specific problems. And I think finding those out of the box solutions typically are the best ones to use because they are, they handle all the nuance. Right, right. When you're doing it through an automation tool, you have to really understand the nuance and be, you know, be a little bit more technical to build it out and make it work. Right. So I guess theoretically you could go to Perplexity and say, I want you to help me build an agent. This is what I'm trying to do. And it could come back and say, can't do that. Right. Or you need this tool. And this is what I did with my chat bot is I went to ChatGPT and I said, I want you to. I'm thinking about creating a chatbot called Ask Alan anything where 247 someone can ask a question. You know, they don't have to pay my $400 an hour for consulting and it's 11 o' clock at night. What would Alan say? I want to ask it. I don't know how to do that. So I said, you know my audience because I've trained ChatGPT in my audience. I said, interview me one question at a time. So it asked me a question. We went back and forth, back and forth. It said, okay, you need to do this. I said, I don't know how to do that. How do I do that? And it said, here's some platforms. They said, well, you know my business. Which one is right for me? It's a. Well, this one's for enterprise level. You don't need this. This is you. Right. There's the free, but you know, the free one's not going to do what you want. There's. This one is $40 a month or whatever it was. Okay, great. All right, now how do I get the data in? This is what you do. And we had this conversation Air Quotes. Here was real conversation back and forth. And it's live now. And it's live, but it wasn't free, right? I'm paying chatgpt, I'm paying the chat base, I'm paying member press and paying all these. And that's fine. And then now I'm actually about to do something else. Brian Lawrence and I were here the other day talking about wedding MBA and how I always have a line of people, you know, waiting to talk to me and then people are trying to buy books at the same time. And I'm in the process of creating something, not an app, but where you'll go on your phone, like scan a QR code and it'll quiz you and it'll say, okay, so are you a wedding and event business or not? Okay, yes, you prefer English or Spanish or French? Okay, which of Alan's books do you already have? And then it'll suggest based upon what you say, which ones. And then you could buy them right there, show us the paid screen and we'll hand you the books and you're off and running. Or you could do it on art, but we did. I did this again, just using AI to help me how to do it. But that was, again, that wasn't an agent, that was me reasoning, brainstorming, if you will, with that. So, so it's, I think that's where I had to get my head around. That's not an agent, right? That is me just using ChatGPT at what it does well, which is this, you know, let's kick some ideas around, let's brainstorm. But then handing me off and saying, here, you need to use that platform, you need to use that, use that over there. But yours is a self contained and you know, I've watched you along the way of pivoting into this and seeing this as the future. And you and I spoke about this, you know, I don't know if the spark was already there or whatever, but you and I had spoken, I said someone that can create a system that can respond to the inquiries and that from their website, from the Knot, from Wedding Wire, from some of the other platforms that you have connections with, right? To free up the time that this is the biggest time suck, right? If you're a, if you're a venue or anybody listening, you're a dj, you're a photographer, you're a florist, you're trying to do your work, you're trying to have a life, you're trying to have a family and you're trying to respond to inquiries as soon as possible. And what do you find yourself, you know, you know, you find yourself on your phone when you're at your kids, you know, dance recital or you're at the soccer game or you know, when you should be spending time with your significant others. Sure, sure. And that, that whole concept that, that Alan, you taught me of speed to lead is so critical. So being, you know, being able to engage with a lead in, in real time when they're already in inquiring. So if somebody's sending an inquiry at 2 o' clock in the morning, they're engaged, right? They're sending that inquiry because they're awake and they're ready to go. So if something could respond back to that immediately and have that full kind of agentic conversation that makes a significant difference. And I think just kind of going back to this, the idea of like building AI agents and in the whole workflow either through the automation tools or through like out of the box solutions like ours, it's that business logic, right? It's, it's the business logic and a lot of stuff that you've been involved with in the best practices agents only work really well when it understands the full blown parameters and how to work. Right. And how to perform that task. If it doesn't have the parameters in place that are in the best interest of the, the folks using the AI agent, it's never going to really work that well. Right. That's why, you know, I tell a lot of folks if they, you know, they're thinking about building their own AI agent in some automation tool or and this is even outside the weddings, weddings and events industry is make sure you have, you understand the business logic completely about how this thing should operate and if you're unable to do that, go to the out of the box solutions. Those are typically the best, best paths to take because from there all you have to do is just train it up. And you train it up really just by filling a knowledge base of information. Right? So in our case it's a knowledge base of pricing packages, available dates, you know, all the, all the basic things and then the agents take it from there. Right. But you also trained it on best practices for how to respond to inquiries and when to follow up and objections and how to handle them and all those things. And that's the same thing I was doing with mine is, you know, it when I asked my, I was having my conversation with Chat GPT and I said, well, how do I train it? And it said, well you do chunks I said, okay, what is that? Well, chunking is basically questions and answers from the information. So we took each of my 13 books and created over 100 different questions and answers from each book. And then 200 plus podcast transcripts just by solo ones, and then a dozen from those, because those are short. Okay, well, there's thousands. That's thousands of questions and answers, but yet it's still not everything somebody's going to ask. And that's where that LLM, that large language model, is going to say, okay, I have all this information. What can I. How can I answer this based upon that? How would Alan answer this, even though I don't have that exact question? And then of course, I can give it exact questions like, what's Alan's favorite bourbon? Or, you know, whatever that is to train it. And it's an on. It's an ongoing process. You know, as I record new podcasts, I'm uploading the transcript. Why? That's my most current information. I mean, literally that happened this week. That's the current information. So what do you think is next? Like what, what comes after this? It's a great question. And something that I think a lot of people are talking about is, you know, what is the world going to look like at, at least in the next 12 months? Right. AI is moving so unbelievably fast. I think consumers are still getting used to the idea of talking to an AI agent. Whether it's on voice, like through voice, through email, sms, or any of these channels. I think it's going to become a. Such an important part of everyone's life. And now I think eventually folks are going to become used to speaking to an agent because they're looking for information right away, and they get that information extracted right away. And I think about airlines as an example. Right. A lot of, you know, one of the most painful things to do is try to call an airline to, to change a flight or go online, try to change a flight and something happens. But imagine having to call American Airlines, sit on hold for X amount of time, talk to somebody, talk to them about their day, and they're gonna ask you about your day. And then you just want to get your flight changed immediately because a lot is going on at the same time. So if you're able to connect immediately with an agent who's smart enough to understand all of your information historically, like your flight, your details, all that, and then ask you a few prompted questions to change your flight or details within seconds or minutes, that's game changing. Right? And I think we're starting to see the beginning of that where people are getting used to it. But I think it's going to be a massive part of our. Part of our lives in the next 1212 to 18 months or so. Just like how the Internet transformed everything, AI agents are going to be that version of AI, you see, for me. Is I don't mind talking to someone's AI agent if it can help me. It's frustrating when it can't or when it doesn't understand. So the platform I'm using, chat base, their support agent, is phenomenal. Everything that I've asked it, no matter how obscure I thought it was, it answered. It pointed me to right answer. And that did that one. And I have no problem talking to their AI agent. No problem at all. Right? We have a problem talking to one that can't answer us, just like we have a problem talking to a person that can't answer us. I could think right now that the. Who is it? Was it the irs? Yes. The IRS needs a really good AI agent because I had a situation where it was when my dad passed and it was a tax refund and we didn't get it. And I called and it was almost an hour on hold to get to someone to find out that I'm not in the right department so I can get to somebody else. And I had to wait another half an hour on hold to get them, and then I had to wait all this time. Whereas theoretically, it could have known this and said, okay, here's the issue. This is what's going on. I could have had that answer in minutes instead of almost two hours. Or you mentioned airlines. I. Last time I called Air Canada for something, it. It was. I forget what was going on, but it said your expected hold time is 2 hours and 40 minutes. That's crazy. That's crazy. Yeah. Now, United, I don't get that because I'm a. I fly 100,000 miles a year, so I get a different phone number. I still think it's the same people that answer any of the ones, but it pops up and says, okay, you put this guy through quicker, so I have less friction there. But I'm sure everybody doesn't get that treatment if you have no status, just like I had no status on. On Air Canada, you're going to get that. So I think we will become more comfortable with it when it's doing what we want it to do. Because, you know, sometimes I want to talk to a person, but most of the time it's I just want my question answered or I want my problem solved or whatever. And if you can do that, I don't care if it was your agent. It did it. It gave me. Gave me the result. Um, and, you know, everybody listening has heard me talk about this. You know, we. We don't sell our products and services. We sell the results of the products and services I mean, that. That's what venue x AI is. It's. It's not the responding to your inquiries. It's that it made the tours for you. Right. It answered the objections for you and it freed your people up. Right. This is. That's the results that you're selling. You're not selling an AI agent. Right. You're selling the results, which is, hey, I walk into my. I come into work in the morning to my venue, and I find out that I have three tours scheduled for me, you know, since I walked out yesterday. That's a good day. It's a very good day. And it's. I love that you said that because, you know, the two main metrics that we. We ask a lot of our customers is when you look at the analytics page and you see that inquiry to conversation ratio. That's something you and I have talked about at length. Yeah. And understanding that that metric and figuring out, out of all the inquiries that were sent in, how many of them actually engaged with the agent and had a conversation. And then looking at the other metric alongside that, which is like the conversation to. To ratio, out of the ones who've engaged, how many actually booked an appointment. And those two metrics allow us to understand if the agent is working or not. And when we have visibility into that, we can see, okay, the agent's doing its thing really well, or they may need some tweaks here and there to. To make sure it engages even better. Having that visibility is awesome, you know. So, yeah, and that was the whole thing when you were building this and you said, okay, let's talk about analytics. And one of the problems that I know you've been having, because I've referred, you know, quite a few of my clients to you, is we don't have the old data. Like, they don't have good data to say, like, people will say, okay, you know, we made. We got this many inquiries. We made this many tour appointments. Okay. Or if you're not at. Not a venue, we got this many inquiries. We had this many zoom calls or phone calls or whatever it is, but the number that's usually missing is the ghosts. It's like how many people have reached out that haven't told you no yet? And most people like, I don't know because they pay attention to those. Another thing, and I just had this yesterday with a client, they admitted that they don't follow up, as I would say assertively with their wedding wire leads as they do with the ones through their website. And of course they're not getting as much conversion as they are from their website leads. I said, well, it's kind of a self fulfilling prophecy, you know, you're not following up as well, therefore you're not getting as much conversion. Are you really blaming the leads? Or maybe we should look in the mirror here and say maybe if I gave them equal effort, maybe I could see and this is something also where I know that you built it into the analytics is you can see not only how many leads came in, how many of those had conversations, how many of those made tours, how many of those made sales, but from what sources. And you'll have really complete visibility to say this because you know, I've had people who say, oh, I think this is where my business is coming from. And then if you really look in the numbers, they're like, oh, I didn't realize, I actually am getting business from this and I didn't realize. But I love the fact that every lead is going to get equal weight and that that's again the, the AI. If you're building your own agent or buying something out of the box for something you're doing every thing, every effort is going to be equally done and there's no human, you know, intervention which is like, well, you know, maybe that lead isn't as good because. Or I had somebody say, well if they don't give me as much information, you know, if we don't follow up the same because it's not that good of a lead, this isn't going to care. And then you all of a sudden find out, maybe those people don't don't give you more information. Maybe that's just their personality type, maybe that's just the way by I had a client in Mexico, five star all inclusive resort. They lengthened their contact form thinking if people took the time to fill it out, they were more interested. I said no, they just have more time and they're not turned off by a long contact form. So totally wrong metric for that. And again, this will not be hindered by how much information you did or didn't get. It's going to go out there and it's going to say, I'M going to work this lead until we tell it to stop working the lead. So there's no picking and choosing. You know, it's answering everything 24 7, 365 and and it can because there's no, there's nothing holding it back. Yeah. And again it's doing it. If you had to put a person in place, and this is when you're thinking about employing an agent, whether it's Venue Xai or any agent, if you had to pay somebody to do this, how much would you be willing to pay somebody to do this? How long would it take to do that? How long would it take to train them? I think this is the other advantage here is, you know, if you had a person that left, all of their institutional knowledge goes with them. So now when you put a new person in place, you step backwards because you have to train that person. Whereas this, once it's trained, it's only going to get better. Right. And I say this meaning Nai agent is only going to get better. It doesn't get tired, it doesn't get sick, it doesn't complain. Right. You know, and, and it doesn't forget. Right. Because we're humans. We're humans and we make mistakes. The other thing that humans do is we assume this lead is better than that lead. Right. Or we, so it's not do that. So, so again, just circling this back. What is an AI agent versus what is chatgpt or whatever large language model? It's having a, you're having a two way conversation, giving you information based upon what it knows, but it's not taking a series of steps and actions based upon that. It's just like the next level of a Google search. Right? That's correct. That's correct. Decision making capabilities, workflow, automation on, on your behalf. And that's where that power is. And again, the, they only get better over time. Once these large, large language models continue to get better. And it's, it's an incredible thing to be, to be living through. Okay, so if there's somebody listening that's very scared right now about the potential of these, talk them off the ledge. Don't be scared. It takes a little bit of time to allow the agent to do things on your behalf. A lot of folks are used to doing things every single day. It's a part of their job. The way to think about it is your job or anything that you're doing, the tasks that you've been doing will get transformed once you apply AI or an AI agent for the better, most importantly, to free you up to do higher level things. Right. So specifically for our customers, spending more time with their customers, better client service, doing what they do best, like hosting world class events. I always talk about that. And higher level things. Let the AI, AI agent handle all the mundane kind of day to day stuff that you, you typically do, which. You know, we, we say as speakers that my job isn't speaking. My job is getting the gig, all the paperwork, all the preparation, all that kind of stuff so that I can speak at that, you know, at that gig. It's the same thing with your photographer or florist or videographer or whatever. Getting the lead, following up with the lead, doing all that, getting the paperwork, collecting the money, all those things, right? That's the job, right? So you get to do the rest. And I'm going to talk about this on another podcast, but I'm just going to look it up because it was a great quote I heard in a book where somebody referred to another book actually. And the quote is from Tim Grover, author of Relentless From Good to Great to Unstoppable. You don't have to love the hard work, you just have to crave the end result so much that the hard work becomes irrelevant. Love it. And you know, doing the wedding is the payoff for doing all the work. What can you take off your plate? Like I have a virtual assistant has taken some stuff off my plate and I suppose some of the things that, that they do, an agent might be able to do, but I also like, I want their brain involved and I want them to be reasoning on this again, I suppose some of this stuff they can do, but taking that off my plate freed me up for what I want to do, which is spending more time with my wife and family, creating more content. You know, those are the things I can't outsource. And last thought is, and I, I forget who to attribute the quote to, but AI isn't going to take your job. Someone who knows how to use it might love it. There you go. And the last thing, Alan, if you don't mind, just one thing you want to say is that I think in, in hospitality it's extremely important to have that human touch with folks, right? And that's something that AI can never take over, right. So you know, in our case, the agent just handles all the communication, books, the appointments, and then there's a point in which it stops that communication once they go in for a tour or they have that appointment because there's a human touch and the human element that people want to have when they're hosting weddings and different types of events that AI again will never take over. So that's the beautiful part about hospitality is that combination of AI to handle the day to day Monday tasks, but just making sure that human element of hospitality is always in the mix to have a good experience across the board. Yeah. AI could create your seating chart for you, but you know, you need to know that Aunt Sally can't sit next to Uncle Charles, you know, and do things like that. And again, doing the tour and all. Absolutely. You know, it's not going to take the pictures for you. It, it's, it, it's not going to play the music and read the room and adapt and do all that, you know. Again, could it do some of that stuff? Sure. Would that be like a party trick? Yeah, that, that, that'll be fine. But the reality is no weddings and events. The reason we're bringing people together is because we want to have a people in person experience and they want to know that you're the one that's going to help them do that. If you do some of your back end stuff with AI to make your job easier, great. But it's still the forward facing stuff. So thank you so much for helping to explain this. We'll put into the show notes if anybody wants to contact you. And if you have a venue and you're flooded with leads and you want AI to be able to respond and make tour appointments for you venue. Xai Abed will certainly give you a demo on that. And I'm Alan Berg. I look forward to seeing you on the next episode. Thanks guys. Take care.

I’m Alan Berg. Thanks for listening. If you have any questions about this or if you’d like to suggest other topics for “The Wedding Business Solutions Podcast” please let me know. My email is Alan@WeddingBusinessSolutions.com or you can  text, use the short form on this page, or call +1.732.422.6362, international 001 732 422 6362. I look forward to seeing you on the next episode. Thanks.

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Alan Berg, CSP, Global Speaking Fellow

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