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ChatGPT and other forms of AI are really making airwaves, and in today's episode, we unpack how this relates to the rental housing industry. Joining us for this conversation are market research and advertising expert Adhiraj Brar and digital marketer Miguel Vasquez, both from Mainstreet Equity, a leading Canadian real estate and property management company. They’re here to shed light on how you can integrate AI and ChatGPT into your marketing strategies and use it to reduce your workload. Tuning in you’ll hear more about what ChatGPT is, how it functions, and some of the ways that it is helping property managers, landlords, and marketers in the rental housing industry. You’ll also learn how it has been used to create the National Demand Report by Rentsync before we hear about some of the helpful things this evolving technology will soon be able to do. Apart from talking about its many valuable use cases, our guests also share a word of warning to users of these tools and talk about some of the errors they have noticed while working with them. To find out more about how to make the most of AI and ChatGPT, tune in today!
Key Points From This Episode:
Links Mentioned in Today’s Episode:
AB: "At this moment, the cases that we've discovered were – Quite simply, we could describe them in three words; and that is reduction, simplification, and data analysis."
[00:00:11] ANNOUNCER: Hello, and welcome to Sync or Swim, a weekly podcast, brought to you by Rentsync, where we take a deep dive into the PropTech, multifamily, and rental housing industry. In each episode, we uncover the technologies and strategies used to help overcome operational challenges and increase the value of your multifamily investments. So let’s get into our conversation today!
[00:00:35] MH: All right. Welcome back to another episode of Sync or Swim, a podcast where we take a deep dive into the PropTech, multifamily, and rental housing industry. Today, we'll be discussing an interesting topic, AI and ChatGPT, and I'm sure many of you are wondering, how does ChatGPT have anything to do with the rental housing industry? Well, we're going to let you know today how it does.
We brought in two experts on the subject. Joining me today, we have Adi Brar and Miguel Vasquez from Mainstreet Equity. For those who don't know, Mainstreet is an industry-leading Canadian real estate and property management company headquartered in Calgary. Adi, Miguel, thank you so much for joining me today.
[00:01:12] MV: Thank you for having us, Matt.
[00:01:14] AB: Thank you, Matt.
[00:01:15] MH: No problem. So before we get into today's topic, why don't you tell the listeners a little bit about yourselves and what you do at Mainstreet? Adi, why don’t we start with you?
[00:01:24] AB: Awesome. So my name is Adi, and I have been with Mainstreet for about eight years now. Currently, I handle their advertising and market research, primarily focusing on iOS advertising and dealing a lot with Rentsync. I also handle market research and pricing strategies, and signage and branding strategies.
[00:01:43] MV: Hi, my name is Miguel, and I'm the digital marketer here. Mainly, my tasks are everything related to digital marketing, as you know, search engine optimization, social media strategy, content creation, and stuff related to all the digital side of Mainstreet.
[00:02:00] MH: Awesome. I always love having some fellow marketers on the podcast. So as I said off the top, we're here to talk about AI, ChatGPT. It’s a subject that's really making airwaves. A lot of people are talking about it, how it's affecting different industries, what its main purpose is. I know you both are really experts on the subject. So just for the listeners who aren't super familiar with ChatGPT, I'm hoping one of you can explain a little bit about how ChatGPT came about and really how it functions.
[00:02:30] MV: Absolutely. May I start? So ChatGPT, like GPT stands for Generative Pre-trained Transformer, which is something when you hear it is like, “What is that?” The first time that I hear it, I was like, “Sure.” So let's go to pretty much what it does. So ChatGPT was built on top of so much data, data like books. It has Internet access up until 2021. So after 2021, it cannot tell you anything. If you ask it for something like news or something, it’s going to tell you like, “I just have access up until 2021.” So pretty much, this machine was built on top of all this data. I will say millions of books, articles, everything that you can think of.
Then it was turning to a chat. So if you asked it something, it would be like if we – Something we’re familiar with, Google. You go into Google, and you type something, and then it comes hundreds and thousands of results. Then you can click on one and read. The way that ChatGPT works is that you ask it something, right away it replies to you as if you were having a chat with an expert, pretty much.
[00:03:41] AB: Yeah. I'll just build on that. Just like Miguel has explained, this is a generative trained model that is, essentially, it's a computer program that talks like a person. It's been made to read a lot of websites. It's been made to read a lot of books in a lot of languages, and it can very well understand how people talk and write.
Now, when you ask it a question, it thinks really hard, and it gives you a response back in the form of a text. A great example to explain this would be think googling. When you search and acquire, you're googling. Then you get a search result. Then you have to find what you're really looking for. Whereas a thing like chat GPT, which has access to that information, is doing the googling for you, giving you response in a very human-like chat-like fashion.
[00:04:29] MH: That's very interesting, very sci-fi in some of these ways. I'm seeing all sorts of articles these days, “University student wrote their essay with ChatGPT”. I never really thought about how it could really affect the workplace. The two of you are really the first ones that put me on to how ChatGPT can function in different industries. So what really led you to start exploring how AI and ChatGPT can help in the workplace?
[00:04:55] MV: Well, I think once you start, I say, to train your algorithms in social media, like Adi, myself, and the rest of the team, we follow a lot of pages related to marketing to stay on top of things and how the tech industry is moving and everything. So between the three of us, we're starting to look at this ChatGPT thing that many people were starting to talk in around November. So we were like, “Okay. So let's see what this is about.”
Once we enter, let's say it was like going through the rabbit hole. It was just amazing what – As soon as you start playing around with the chat, it just takes you to places that you didn't know existed before for a machine like this because, okay, so I'm going to use it for work, but it's not only work. You can use it for recipes, or you can use it to create a song. There are so many different ways that you can use the tool.
So pretty much, it was, okay, people are talking about this. Marketers are talking about this. Let's give it a shot. I'm talking about just one week after launch. Remember that ChatGPT grew a million users in less than a week, which is something never seen before. So once that happened, it was like, okay, just that very five days after launch, we started playing around. Then it just became something that we use on a daily basis now for everything related to work and also stuff from home.
[00:06:24] AB: Just like Miguel was saying, it's a very, very great description. Most of us will be browsing social media on the weekend. Like he was saying, our social medias are trained in a formal way, where we are getting the latest marketing news or whatever is happening in marketing channels. I got introduced to ChatGPT, started playing around with it on the weekend. At first, it was just quite simply intellectual curiosity. Okay, what is this machine? What does it do? How does it behave? I got it to write a poem, an essay, things like that.
Then came the weekday, and I was still obsessed with this thing, and I was like, “Okay, today is my work day. How do we use it at work?” We were having discussion earlier, Miguel and I, and one of the first easiest examples I can give you is how do you respond to an email. There's a complex email. You want to respond, and you want to respond in a very mellow yet professional tone that responds in five sentences or less. There you go, ChatGPT right there. Bam, spit out an email.
Then it sort of expanded that thought process. What else can this write? Then then we took it further, and we just explored it. I guess we can get into some use cases further on.
[00:07:41] MH: Yeah. A really good segue into my next question was really we're here to talk about the rental housing industry. So what are some ways that ChatGPT is helping property managers, landlords, and even just marketers in this industry?
[00:07:55] AB: It's a great question. Right now, we feel the technology is so new and fresh, and we’re still discovering the use cases for this. At this moment, the cases that we've discovered were – Quite simply, we could describe them in three words, and that is reduction, simplification, and data analysis. So you could feed it vast amounts of data. It could reduce it or summarize it for you. It could simplify it for you. It could simplify it for you to explain it to somebody else further, or it could do vast amounts of data gathering collection and then summarize those key highlights for you.
A great use case would be just the National Demand Report by Rentsync. It is quite a lengthy report. There's one by rentals.ca as well, and there's a lot of data on it. It is national, whereas Mainstreet’s Western Canada-focused. So I need to focus on Western Canadian cities. You specifically give it the data of the demand report. You ask it and talk about those Western Canadian cities, and it summarizes the information specifically for the information that you're looking for. That is a great use case scenario.
But now, let's talk about this a little more broadly for the industry, specifically the rental housing industry. I think the use case scenarios are in marketing, advertising, communication writing, ad copywriting, keyword market research, Google reviewer responses, tenant communication, social media marketing generation ideas, SEO content ideas, and again data analysis for the general wider industry, I would say.
However, this is just cases right now. This is an evolving technology. In my opinion, we could see this technology evolve to completely take over it and in communication processes or chatbot communication processes or predictive pricing models, in my case, where we're feeding it vast amounts of rental pricing data, and it can analyze it at a very quick, faster speed and spit out your recommendations.
It could also take over tenant screening processes. It could transform the tenant screening process. It could take it to a matchmaking of sorts, where we're matching tenants with landlords based on a preset criteria. Yeah. The applications are quite immense. There are some cases that we've noticed specifically for marketing that we can use in the rental housing industry, and that would be, quite simply put, enhancing capabilities of existing teams that may be small in size or with limited budgets or capacities or capabilities.
Currently, there are AI tools that are based off of AI video generation, there’s soundtrack generation, there’s brand logo and design generation. So this could really help and alleviate the marketing for a lot of landlords and a lot of rental housing marketing teams.
[00:11:00] MV: Exactly. As Adi was saying, the applications that you can use these AI tools that are coming are unlimited. Just to give you an example, I was working actually this week on updating our renter personas. So I was diving deep into Stats Canada, looking everything related to the census. Yeah. We can talk about this later because there are some errors that ChatGPT is giving. It’s not perfect. But the level of detail from some sort of the question that I was asking it, it will say so rich. So the way that I was doing this, it was, okay, so I have all this data. Then I was analyzing the data. I was asking it if can like this machine or asking in the chat if he or she or it agrees with me. Sometimes, it’s no. This is what I'm noticing. Then, yeah, you're right.
Also, yeah, for the renter persona building, just to create or to update a renter persona, it was, okay, this is the background of the company, this is the market that we're serving, this is the demographics that we have, as far as our users, these are the characteristics that we have. It was like more broad than just a specific because the whole idea was to, okay, we know who our renters are. I just want to create personas. Give them a backstory. Give them a name. Like all these data was coming from our own data and also from CMHC and Stats Can. Then at the end, I ended up creating together with ChatGPT something like with a backstory, just say, “Okay, Suzanne is a 37-year-old professional living in downtown Calgary. She moved from India eight years ago.”
So just giving these prompts, which is the most word that you're going to be hearing a lot is prompt, prompt and prompt engineer. There is even now companies searching for prompt engineers, which is a very high level of skill that we're creating, it’s because what you ask is what you get. If you ask like very well thought of questions, they're going to give you like the perfect answer. If you just ask some random question, it’s just going to give you some random answer.
But, yeah, at the end, just coming back to it, the possibilities for marketers are unlimited, and the possibilities for every single person in the industry, based on their occupation, they can say, “Okay. So what about if I use this ChatGPT to do my work easier, just try a couple of things?” They do end up just being amazed of what the capabilities of this AI are.
[00:13:41] MH: Yeah. I think you touched on a couple of key points there, Miguel, and one of them even Adi mentioned. It's really reduction. We're using it right now to reduce some workload, but in no way is it replacing jobs or removing any work because, like you mentioned, prompt is such a major thing of this right now.
You mentioned there's still errors with ChatGPT, so there's still a lot of onus on the user to feed it the right amount of data, give it the right prompts. We're not at I-Robot, Ex Machina stage yet, where they're just completely taking over our jobs. Really, the user can still dictate a lot of the quality responses that it's spitting out to us. So by no means is it really getting rid of jobs, it’s just kind of reducing some mundane work and creating some creative responses that maybe one have thought of before.
So you mentioned errors there. There's probably going to be some disadvantages and things to keep an eye out for when using ChatGPT. So you mentioned a couple of them there. But what other kinds of errors have you noticed through your times with ChatGPT, and what are some kind of warnings to offer new people that are maybe just kind of start trying it out?
[00:14:53] AB: Matt, I'm so happy you asked that question, and it's a very important question. Up until now, we've been talking about how awesome this technology is. There are people who don't know about ChatGPT, but those were using it are, quite frankly, in awe of it, and the cases that they're being able to use it for have been able to save them a lot of time and effort. Yeah. This is quite ingenious what's coming up. But there's disadvantages, and some of them are, quite frankly, very surprising.
So ChatGPT is known to create a level of bias, so it could extend your echo chamber or keep you within it. It can conform to your fairness. So if you don't think something is fair, it will agree with you. It can also cause something we've recently started discovering called a hallucination. How I'll describe that is, simply put, it's expressed in such a way that a machine delivers a convincing but completely fictitious answer. At this moment, ChatGPT’s hallucination rate seems to be somewhere around 20%.
Now, let me explain this a little further. What that means is it is giving responses, and 8 out of those 10 responses are absolutely correct. However, two are incorrect. But just based on the advantages I’ve given you, it saves you time reduction at data collection. I've mentioned that as an advantage here. But to think about it, because it has earned your trust, you are not fact-checking the responses of ChatGPT. Essentially, when you get those two incorrect responses, you take them to be true and correct, causing a hallucination where you have accepted that completely incorrect, no fact-checked answer as truth. Then you could use that further on.
Now, ChatGPT is a situation where it doesn't have access to the Internet. However, there are AI tools like the one that Google is also trying to introduce. But ChatGPT is also introducing an Internet-connected version. There has been a feedback loop where it is feeding its own hallucinations back. So it's known to now believe that the hallucination it just created is fact. That is something that is of slight concern.
Now, I'll give you a great example of this use case scenario. One of our Head of Communications, Jesse, here at Mainstreet just typed in a simple prompt in ChatGPT Pro, which is the Internet-connected version that just got accessible in Canada last week. He just quite simply put who is Bob Dylan? Who is our CEO? Clearly, it spit out an answer within two seconds. It was a two-paragraph long answer. The first part had an incorrect date of birth, place of birth, and an origin story. The second part of the story was absolutely correct.
Now, if you were a layman, Matt, and if you were using ChatGPT for ‘Who is Bob Dylan?’, you would perceive its answer to be true because that's what it gave you. However, our team knows who Bob Dylan is, and we know that all of that is factually incorrect. So there's this cause of concern that we don't know where it's pulling this information from. So we touched bases on it's being fed vast amounts of data. We just don't know what it's referencing when it's giving a response back. So there's a lot of caution to be advised at using ChatGPT for factual information at this moment.
[00:18:20] MH: Now, you mentioned 8 out of 10 are correct. If you log on every day and give it the same prompts, you're getting different answers every single time. Correct?
[00:18:30] AB: For the most part.
[00:18:33] MV: It depends also on what you're asking it. So there are some commonalities that at the end is like it's been proven that it's 100% right. It’s also that we have to keep in mind this machine is always learning, is always constantly learning. The prompt that you're using, the answers that it gets, like every chat is just being pretty much fed into it or getting this feedback about everything that is happening within the application. So it also depends on what you're talking about. Maybe there is some fact, like as far as opinions, that if you go dive into not facts, but what's your opinion on, then you can just go as a person would, just having this information, and this is what I think. It doesn't mean that it's actually a fact.
Also, there is another thing that it’s not that good in math either or just capturing, I will say, numbers. I was able to see it myself because I was feeling it charts from the census because I just wanted a straight up answer. I was working on this chart and just a lot of charts, a lot of numbers, a lot of data. Then I was just feeding it. Just give me the only thing that I need pretty much. It gave me those answers, and I was like 100% sure those answers were right. It was almost at the end of the day.
But then at the next day, with a fresh mind, I started looking at the work I was doing, and I was like, “This is not right. That's not the highest number of renters between 20 to 25 in the Calgary area.” Because I know that that's not the number because I got the number from yesterday, and I went back, and it actually was not right. It was just taking a random number and then was getting into forums and Google. Yeah. People were saying math is not it's forte. You have to keep that in mind.
Also writing code, it writes code but is not 100% right all the time. But still, the interesting thing is that it's learning and learning and learning. This is what we're talking about in November. God knows what's going to happen in the following year, two years, five years into the future.
[00:20:39] MH: Yeah. We're still at the very early stages of this. Adi, you mentioned something, and we didn't say really off the top here, but ChatGPT is a free service offered by OpenAI. But you mentioned the new pro version that just came out. Have you noticed any major differences with the pro versus the free version yet?
[00:20:56] AB: Yeah. So that's a great question. Obviously, let's talk about OpenAI being a nonprofit company in an organization when it was initially created. The plan is to make AI capabilities accessible to the general public. However, given the explosion in the popularity of ChatGPT-3, even a nonprofit has had to find funds for the resources to keep things online and live.
ChatGPT just started to have a lot of errors, crashes. You couldn't get a hold of the website. It was giving you a waitlist. So given the explosion of the popularity, many people were not able to use it, so they created a whole separate track, which is ChatGPT Pro. I believe the Canadian version is also approximately $20, USD. That's the price at this moment. However, it gives you uninterrupted access and never just a priority queue. It personalizes your account for you, so all your information is there. So those are the major stark differences.
For our business, a pro version would definitely be helpful because you don't want to be stuck waiting to get a question into ChatGPT or not getting your responses in time.
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[00:22:22] MH: Now, we've been talking in the last few minutes about some disadvantages, really making people aware that it's still going to require a keen eye when using ChatGPT. It’s definitely not going to be able to go unchecked.
Going back to some other advantages you already touched on for the industry, tenant email replies, property descriptions, Google review responses. When we spoke earlier, you mentioned a couple other really creative ways that this industry might be able to utilize ChatGPT, and one of that was helping employees where English isn't their first language. Canada's a massive multi-culture nation there, with immigration on the rise there. There's a lot of requests these days for translations and things like that. So did you notice any use cases for ChatGPT in helping with that at all?
[00:23:11] MV: Well, I think if we move into a year more in the future, and now like there is applications people are creating because ChatGPT has an open API, and chatbots is going to be a huge one for an industry. Because at the end, if you go into the website, once we get to connect this, like the API with our systems, then it's just know about availability. It’s just chatting with a very smart person, which also knows a lot of languages too.
So if you type in Spanish, and it’s going to reply back in Spanish. Even if you type in Russian, it’s going to talk back in Russian. That's one of the applications. So pretty much, it's going to be just not choosing the language. It just goes straight up and just feed that information in the language that you want, and it’s just going to get back to you in that language. Yeah, examples like that.
[00:24:04] AB: Yeah. Building on to Miguel, like you were saying, Matt, Canada is a multicultural country. At this moment, even though we've not used this methodology for translation services, there is a wide area of use cases, where you would be able to and there could be situations where you're having a language barrier with the tenant base, where you would want to establish communication in their language as well. Like Canada is a bilingual country. When you're getting a government letter, you get them in two languages. A sort of methodology could be employed by teams that do have difficulties in those areas.
[00:24:39] MH: Yeah. Really, just the services are out there now. But translation services can be very costly. You might need another tool to implement. You even mentioned before like something that people may not think of that it could help with is lawyer fees and different contracts, where legal fees can get quite expensive. But there may be a future with ChatGPT, where it might not replace a lawyer, but it can help with some of those redundancies where you're writing contracts and fact-checking.
Really, the goal is reducing workload, reducing costs where possible. But at the same time, it's not taking anyone's job away because there still needs to be that fact-checker at the end of the day.
[00:25:18] AB: Correct. At this moment, I do not feel that technology is set to replace jobs. But I do feel it will evolve to a stage where it starts to take those spots, where it starts to do a lot of coding, and it starts to do a lot of writing, and it starts to do advertising. It's a possibility. We just don't know yet. We're still monitoring this.
[00:25:43] MH: So if you were to say a property manager is out there listening today, and they're intrigued by the idea of ChatGPT, other than, obviously, keeping a keen eye, what other advice would you give to new users that are just experiencing it for the first time today?
[00:25:59] MV: I will say the most important thing is to keep it simple at the beginning because the industry is growing so fast that you're going to get overwhelmed. The amount of applications that are coming live every single day are huge. I just was learning that there is about 600 applications right now. That's the ones that pretty much people were getting into. So, yeah, applications for copywriting, email marketing, video creation, just for fun, photography, design. Like as property manager, keep it simple. Start with one, which in this case, the one that we started with was ChatGPT.
Then once you learn how to properly prompt and how to use this, then start trying to master another one. Because if you fall into the trap that happened with social media too, like you see your competition, you see people getting into all these social media outlets, and you want to be in, I’m missing out, the fear of missing out, and you start to jump into everything. Then it becomes overwhelming, and you just end up being like, “This is too complex. I’m just not going to do it. This is not for me.” Start with the basic. Start with something as easy as ChatGPT, and then build on top of that.
[00:27:15] AS: Yeah. Adding on to that, just like we have been experimenting here at Mainstreet, I'm sure there are going to be cases where a landlord is going to find even more cases. I'm sure there are going to be creative marketing teams across Canada that are experimenting with this. You've just heard from one team that is the Mainstreet team, but I am sure that their experimentation is now starting to happen. With more popularity for ChatGPT, there's one coming up by Google. You're going to see, like Miguel was mentioning, 600 applications to put that into context. It might seem very few right now. But at one point, there were 600 websites in the world, right? Now, look where we are.
It's a technology that's still growing. A lot of teams are going to find very creative ways, depending on their needs. But, yeah, start small. Start just learning how to prompt it. You can take those prompts to other AI tools, where you want a certain art or a certain soundtrack. You can use ChatGPT to create that prompt for you in the future. So, yeah, go from there.
[00:28:16] MH: I think that's really good advice. Keep it simple. You don't need to look at overhauling your entire marketing and copywriting processes today. Pick a couple of small tasks and see what it can do for you.
As we kind of just start wrapping up here, I know you've sprinkled in some future applications for AI and ChatGPT, sound, music, video. What are some use cases that your team is quite excited to try in the future, as the technology kind of advances, and you become more used to how the response to these requests?
[00:28:51] MV: I will say content creation is a big one. Content creation is one of the big ones because since you have like ChatGPT, you can just create 10 social posts for the following week. Then you can jump onto a video creation. Okay. So now that you have this 10, then create videos with this 10. Then you can connect APIs, and there's different tools that pretty much you’re just going to start with ChatGPT and just with a click. Then you pretty much are going to go through the whole process up until the point that that's posted. Then once people are starting to reply back, there's going to be AI replying back to them.
So that's just something that we're looking forward to. It's still early in the stage, but it's definitely happening. So we have to keep on a keen eye in order to be on top of things. Otherwise, you know what happens, then you're not surfing the wave, you're just wondering what happened.
[00:29:48] AB: Yeah. I think he sums it up pretty well.
[00:29:50] MH: Yeah. There's a lot of opportunities for this. Well, I appreciate both of you joining me today. I think we're going to start wrapping up here. I think you left the listeners with a lot of good advice to start out with ChatGPT, let them know a lot of the use cases.
If somebody is looking to kind of learn more about ChatGPT, you mentioned marketing forums and things like that, or have you found any couple like really good resources where somebody can keep up to date with what's going on in the ChatGPT AI kind of world?
[00:30:18] MV: Well, now in this connected word, I think the way that I did it is once you start looking for things, like TikTok is a huge source of information, Facebook, Instagram, and these have algorithms. So start going into them. Just type what is ChatGPT, for example, or latest news on AI. Then start looking through information. Watch a couple of videos, like them, bookmark them. What's going to happen is that, okay, now the algorithm got that you were keen to [inaudible 00:30:49], that you like that type of content, it starts just giving you more and more and more.
So now, what I do is pretty much it's not that I'm searching for news. The news are coming to me through all different social media outlet that I’m in. At the end, it’s the latest news. They're the ones that come on top. These people are commenting. They’re the ones that are getting the most engagement, the most fresh content.
So pretty much is that's what I will say, is just train your algorithms to serve you, not the other way around. So the way that you train them is like this is the information that I want. I like this. Watch the whole video. Like the video. Comment the video. Bookmark the video. Then you train the algorithms to give you exactly what you need.
[00:31:31] AB: Yeah. Social media is such a rabbit hole, Matt, that once you start somewhere, it is going to adapt to you and what you're looking for. Yeah. It’s really a question of starting somewhere. Now, you did mention where do we go from there, and Miguel quite simply just says prompt it. Prompt it into a social media query, and that is so correct at this moment. You can go to Twitter. You can go to Facebook. You can go to Instagram. You can go to TikTok. On all four different social media sites, you're going to find different content. But it will be up-to-date, and it will start to conform to your behaviorbehaviour. So you'll start to get more of that content served to you.
[00:32:08] MH: I think that's really good advice. Well, Adi, Miguel, thank you so much, again, for joining me today. Letting the listeners know a little bit more about ChatGPT and how AI can really help this industry. For anyone out there, make sure you keep an eye on Mainstreet. Follow them on social media. They're doing some great work and may be putting out some more content in the future about this topic. Hoping you guys can join me again maybe in six months, as this technology really progresses.
[00:32:34] AB: Yeah, we'd love to.
[00:32:34] MV: That would be awesome. We’d love to, Matt. Thank you for having us.
[00:32:37] AB: Yeah. Thank you, Matt.
[00:32:37] MH: No problem. All right, everyone. Have a great day.
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