M&A Murders & Accusations: The Good the Bad and The Ugly of Selling Your Business
M&A Murders & Accusations: The Good, the Bad, and The Ugly of Selling Your Business! We dig deep into what you MUST know when selling your business. Learn how to NOT kill the sale of your business. Rick J. Krebs, the mastermind M&A Advisor (Mergers & Acquisitions, not Murders and Accusations) and expert at selling businesses, has transformed the lives of countless business owners by helping them secure the right buyer at the right price. You have only one chance to sell your business and this podcast will provide the vital information you need to know.
Brace yourself for mind-blowing discussions with industry experts and business owners who have already sold their businesses.
M&A Murders & Accusations: The Good the Bad and The Ugly of Selling Your Business
Using AI To Prepare to Sell A Business with guest Jacob Andra, CEO and Founder of Talbot West
Learn how AI can help you better prepare your business to sell with AI guru Jacob Andra, Founder & CEO, of Talbot West.
In this episode we unpack how to align perception with reality when preparing a business for sale and how targeted AI can boost efficiency, clarity, and valuation. Jacob Andra shares a practical path from messy systems to credible growth stories buyers will pay for.
• mapping systems first, then selecting the right AI tools
• reframing flaws and gaps as well-defined buyer opportunities
• RFP and ERP case study that turns days of reading into minutes
• security and governance for sensitive data with private models
• what LLMs do well versus other AI methods
• building toward total organizational intelligence, not silos
• simple starting points that produce measurable lift pre-exit
Subscribe to The Applied AI podcast on all major platforms, or reach Jacob at jacob@talbotwest.com and talbotwest.com
Visit us at www.bsalesgroup.com or email Rick at rick@bsalesgroup.com
Visit us at:
Bsalesgroup.com,
DesignMySale.com,
Hello and welcome to MA Murders and Accusations. The good, the bad, and the ugly of selling your business. We dig into what you need to know and how not to kill the sell of your business. Now here's our host, Rick J. Krebs, Mergers and Acquisitions Advisor.
SPEAKER_02:Hello, everyone. This is Rick J. Krebs, the MA Cowboy, coming to you from Kieber City, Utah, with our next episode of MA Murders and Accusations. The good, the bad, and the ugly selling your business. And today I'm really excited about our guest today, Jacob Andra. Welcome to the show, Jacob.
SPEAKER_01:Thanks, Rick. It's great to be here. Thanks for having me on.
SPEAKER_02:You're welcome. Jacob and I just met recently and I thought his business is so cool. The name of his business is Albert Web. And his business is so cool because it's on the cutting edge of technology. A lot of people are talking about AI these days. And uh we're gonna dive into that in a minute. But before we do, the listeners know I like to learn a little bit about you personally. So tell us a little bit about your personal life. One, how you got into doing what you're doing, two, and then three, something cool about yourself that the listeners may not know, but would find interesting.
SPEAKER_01:Okay. Uh so here's an interesting thing about me. I am 50 years old and I have 40 years of experience in business systems and processes. I don't know how many people can say that. Um my dad made a choice to keep me out of school and keep me working in a family business. I was involved in pretty much every part. It was a manufacturing business. I was involved in pretty much every part, inside and out. And I did, I taught myself how to read and like all the stuff. I was always like probably ahead of my peers in terms of academics, you know, just on my own initiative. But um yeah, just working in the business, learning business systems inside and out.
SPEAKER_02:Wow, that's interesting. He took you out of school at 10, put you to work in school of hard knock.
SPEAKER_01:Well, yeah, so to be clear, he didn't he didn't take me out of school. He never put me in. He believed school was for making people dumb and that people should learn in the real world. Uh I don't think he's 100% wrong, but I think probably that's that's a little bit extreme, also.
SPEAKER_02:I love it. Obviously, your word. You're a very smart man and you're running a successful business. So, so how did you get into the AI aspect of what you need? How would you get started with your boot?
SPEAKER_01:I've always been an early technology adopter. So, even in this family business I grew up in, um, we were adopting the latest technologies, you know, computer database technologies, internet technologies, um, various types of high-tech systems, you know, for testing and compliance. Uh, so very much always just on the cutting edge of adopting whatever was out there. And uh always um, you know, I'm an entrepreneur, so I've grown multiple businesses and always adopted the latest and best tech, including AI machine learning technologies, in those. And so this is just a natural progression uh where I got my good friend Steve Carfiat to come from Oracle. Um, he ran their entire developer innovations team. So when I got him to come over and join me to do this Talbot West initiative, um, it was a natural fit because I have the background in business systems and processes, knowing how to apply these technologies, and he has a background in how to architect uh, you know, solutions architecture for enterprise, uh, plug in the latest AI ML in terms of building this stuff so it's a nice fit between the two of us.
SPEAKER_02:Gotcha. Gotcha. That that's really cool. So I have a few questions. I'm just gonna dive right in. Yeah. Uh you and I were on the phone the other day, and we were talking about perception versus reality. And there's a saying out there, and and you you really made me think because I I've said it oftentimes. I'm like, perception is reality. And I think sometimes that's true, but what I'm learning is more often is it's not true. What people perceive to be true is not true at all. And I see that with selling a business, right? People are like, oh yeah, my business is ready to sell, it's 30 years old, but it still has pimple grapes still at the prom. You know, they're they got business puberty, they're not ready. And so let's talk a little bit more about this perception versus reality as it pertains to AI and technology.
SPEAKER_01:It's a conversation that's very dear to my heart. Uh, I think you have a variety of situations or dynamics. You have situations where, like you said, people are completely out of touch with reality. So their percept perception is completely unmoored from reality. And really what they need is a reality check. Um, you have uh situations where people's perceptions are very aligned with reality. And then you have situations where perception can influence reality. And and sales is a good one of the uh perfect example of those where a good salesperson can uh sort of alter the reality of the person they're selling to, um, get them to really see how that the solution they're selling is the answer to the person's problems, you know? And so um, you have all this going on. I think when it comes to business exits, um the way to think about it is that you have a certain amount of ability to influence reality. It, first of all, as the buyer, you don't want to be unmoored from reality. You want to be very tethered and clear-eyed about the actual nature of your business and what it actually is, how um, you know, warts and all, you want to have a very good perception of that. But then you do want to be able to position kind of a best foot forward to influence the buyer's perception to, you know, get more money for your business and not in a deceptive way, you know, never, never like deceiving the buyer, because most of that's gonna come out anyway in the in the due diligence process. But there is a certain aspect of knowing what the buyer is looking for, positioning your business to be that taking the actions that are going to uh move it in that direction and then packaging it up, packing packaging it up and presenting it in a certain way.
SPEAKER_02:Yeah, a business sales group, we we use this analogy. It says the dog has fleas, every dog has fleas, but when you sell a dog, don't lead with the fleas. Yeah, right? You're gonna let them know about the fleas, you're gonna you're gonna tell them how cute the dog is, and this is an amazing dog, and on and on. And and by the way, the dog has some fleas, and we're gonna tell them how cute the fleas are and why they're neat, why they want them. So that that's one of the things we do. I love that.
SPEAKER_01:There's another there's another piece to that as well, which is at Talbot West, we help business owners implement the right technologies that are gonna make their businesses more valuable and also tell that story to buyers. Your business is always gonna have some things you wish you had done that you haven't. We like to present everything you're doing right in your business, you present it as an opportunity to the buyer. Everything you're doing wrong in your business or that you haven't gotten to yet, you present that as an opportunity to the buyer. So you're transparent about what it is, but you actually present it as the buyer has an opportunity to buy this business, implement these new uh initiatives, and create tremendous value, and you're laying that out for them.
SPEAKER_02:Dr. You've identified those opportunities. They connected the dots. I love that. I was selling a business, it was an oil pill business years ago, and we had we had presented opportunities for growth, but we hadn't fully connected the dot in the in the offering memorandum. We hadn't connected those dots. And so we had buyers coming around and they were kicking the tires, but no one was really lifting the hood and looking underneath, right? They didn't want to really look deeper. And once we connected those dots, then the buyers were clamoring. We had multiple offers within a few weeks. So that's a really good point. We're able to identify those opportunities for the buyers and they can see them. And and they're gonna ask, well, why didn't the the sellers do it? Well, they're selling the business, right? They won't have time to do it, but they wanted to identify these. I want to call them jewels.
SPEAKER_01:Exactly. Or one way we position it is if there's A through Z to be done, maybe the buyer has done A through E and they've left, you know, uh F through Z uh for the for the buyer. I think I said buyer, but I meant seller. Um, you know what I mean. Yeah. So you can show, hey, they have taken these actions, but they don't want to be in the business seven years from now. This is a long, a long game, and we've roadmapped it out for you. So you, as the buyer, can take over where they left off and do the rest of these, and um, it's a great opportunity for you.
SPEAKER_02:Yeah, yeah, it's spills opportunity. I love it. So I've been dying to dig into the AI portion of what you do. Um, tell me how you work with business owners and identifying AI solutions for them in their business.
SPEAKER_01:Yeah, this is a good one because there are so many AI solutions providers now, and I think most of them have very shallow understanding of business systems and processes. And so for us, it it starts with mapping the business systems and processes, identifying those opportunities we were just talking about and the leverage points, and then pairing that with the right technology that will that is going to remove the bottleneck or you know, create the uh advanced capability. So the problem is so many companies have the car before the horse. They are selling us a technology and they're coming in trying to shoehorn that into every business, and that may not be the right fit. Um, there's another dimension, which is that AI goes far beyond large language models. Everybody is obsessed right now with large language models. Um, we love large language models too for the things they're good at. Uh, they're good at one set of tasks. There's a lot of other things they're not good at. And so again, we have this huge toolbox to draw from. And it's about it's about really identifying those leverage points within the business and then matching that to the right tool in the toolbox. And then the final dimension we bring to bear is wrapping that all in a holistic view of the company, seeing the company as a complex dynamic system that overall can grow towards greater and greater efficiency rather than just, you know, oh, we have a solution for HR, or we have a solution for finance, or we have a solution, you know, kind of these siloed approaches, treating on each part of the company as its own little thing, but not looking holistically. Uh so I think um mapping the company as a holistic entity and plugging the right solution in where it's going to make the most difference is how we approach it.
SPEAKER_02:Gotcha. And there's multiple tools. You're talking about lots of companies that are developing AI tools. Give us an example of a recent engagement and what you did and how it worked.
SPEAKER_01:Yeah, so there's one we're uh we're currently in right now. This is with a mid-market engineering company. Um, so there's a massive, a massive ERP slash project management system they built with a team in India, built it over time. It's a little bit of a Frankenstein. They wanted us to do a deep technical dive on how good the system actually is and what are the capabilities for bringing some AI automation, some integration with the rest of their business and that sort of thing. So we're doing that. Um, we are bringing an initial pilot project into their ERP where it's going to automate a bunch of stuff and do some AI capabilities for their teams. Um, and then later we're gonna roadmap how that can be tied into a lot of the other areas of their business for much more expanded AI capabilities and much more uh much deeper integration into the rest of their business.
SPEAKER_02:Gotcha. So so manual processes. Talk to me about the manual processes that AI has taken over.
SPEAKER_01:Yeah, so manual processes is only one element of what to think about with AI, and I will get into some of those. Another is just expanding what your business can offer, its capabilities, making use of its data, um, bringing new insights. So there's a lot of other areas besides just streamlining manual processes. But in terms of manual processes, I mean, the sorts of things AI can do, especially if you're if you want to talk about large language models, which are the average person's easiest access to interacting with AI, anything involving complex information, the summarization of it, the creation of it, the um synthesizing of it. Um, and and this is you know, throughout a lot of businesses today, just managing knowledge, um, reporting on it, um, taking in complex technical documents. I mean, here's a perfect example from, and this is from the same company I was just talking about, where they have to respond to uh RFPs put out by different, you know, public or private entities. And these RFPs are huge and complex and full of technical documentation, and often there's discrepancies even among the different documents. One document might describe the project one way, and another document might disagree with it. And you've got to actually understand across the entire scope of these documents what you're even looking at before you can even create a proposal. And it it takes many days of reading, and even then, are you gonna remember it, you know, across this body of information? So we showed them how to drop those into um an easy AI tool that uh we created for them that basically just you can ask it, um, show me any discrepancies and give me a breakdown of the entire project scope and flag anything else I should be aware of. You can, you know, you can query it, you can ask different things, but essentially it'll just immediately spit out any discrepancies. You know, this addendum disagrees with this over here, describes it this way. Uh, it'll give you the entire project scope across all the documents. And and it might be broken up. So one document might have these elements and another document might have these other elements, but it synthesizes all of it. So it's like here's the entire project description and scope. Here are the areas the documents disagree here, and then you can ask it other questions like um like any number of, you know, anything you want to ask of it, and it can like give you that visibility into these documents. And so incredibly valuable. And you can extrapolate that type of um functionality across a lot of business functions. Um, so uh yeah, working with complex dense information is is it is a big one. There are a lot of others interesting.
SPEAKER_02:So taking the complex, and I I'm familiar. In fact, I think many business owners are using the open source AI now. Different ones that are available to them. So, how do you utilize it when you have um documents that are sensitive? Like when we've got some I'll scrub the names and that, but is there is there other ways we can use it in sensitive documents to make sure they don't go out there?
SPEAKER_01:Yeah, this is an important point. And uh every company has to come up with their own governance policy around this. Um, so with all these large language models, you should definitely opt out of using your information for training. Um, but then you're kind of you have to decide are you trusting these companies who have a huge, potentially a huge financial incentive to still store and use your data? Are you trusting them that if you opt out, they're actually not going to do it? And are you trusting them to keep it secure against a future breach? Um, if you want to be really safe, you should never put like highly sensitive information, PII, um, you know, the kind of stuff that you would cover by an NDA, you would never you should never put that into these commercial models. Uh, then there's a lot of information types that are more of a gray area. Um, but there are ways you can spin up your own private instance. You're talking about more cost and complexity, and we certainly can help clients with that, where it's your own private instance, it's not going out to a commercial cloud. You control exactly what happens with that data, and you're still getting all the same functionality. Gotcha.
SPEAKER_02:Yeah, I I would think that would be very beneficial for business owners. You know, we're always looking to document whether it's an invoice or a contract or whatever. And you're like, okay, well, do I put it out there? Do I scrub all the names and then put it out there? But to have an internal tool that you know is never gonna get out that still has the functionality and the usefulness where you can do that and know that your data is safe, that'd be huge. I'm gonna have to talk to you about it with mine. Yeah, 100%. Yeah, love that. So um where do you think AI is going? I mean, everyone's talking about it now. Where is this headed? I mean, we're all gonna have robots and be out of job, and where do you think it's headed?
SPEAKER_01:Yeah, my business partner Steve and I just did a podcast episode about this. And the short, the short version is um no current AI capabilities are going to completely replace humans in any role end to end, but they are going to make humans much more efficient. So you need fewer humans for the same job in a light of uh in a lot of the knowledge work that's happening. So, what that means if you're a human is you want to be get really good at leveraging AI so you can be really efficient at your job. Um, so you're not one of the ones displaced, because a lot of people will be displaced. Um, but again, these AI tools are not good enough to just completely replace an exit planner or an attorney or a you know an accountant, but they are good enough to do a significant portion of their job so that one accountant can now be far more efficient and you just need fewer accountants in the world. And so that will be a there will be some social spillover, and it's nothing new. I mean, we've seen this time after time with technological disruption, and those people will now uh need to find uh you know new new employment or whatever, and there's there's some social cost to that, but also it's kind of cool because isn't the goal ultimately for humans to have to do less drudgery? I mean, we're not uh, you know, not to minimize the social cost, but I mean, do we really want everyone out there digging ditches by hand when a backhoe is so much more efficient? I mean, it's cool when technology can do a lot of this stuff for us.
SPEAKER_02:Absolutely. So, so where do you go? Um, if you want to get knowledgeable about it, we know that we need to do it. There's not a university where do you go? What are some resources people can utilize to learn more about it?
SPEAKER_01:Yeah, well, subscribe to the applied AI podcast, which is my podcast. Um that's a great start. Uh hold on. It's called Applied AI. The Applied AI podcast. Uh go subscribe to that. Okay. Yeah. The Applied AI podcast. It's on all the major platforms, including YouTube. Um, so you can find that. Um tons of great content out there. I mean, literally anything you want to learn. In fact, you can literally ask Chad GPT if I want to uh be really good at, you know, tell tell it what your role is or your job. And if I want to be a superstar at this role, leveraging AI to be far more efficient, um, what are the skills I should learn and what things should I learn? And you can have a conversation with it. It can it can show you um a lot of ideas and you can go out and find the YouTube videos and the different tutorials. There's a lot of stuff out there for free. And if you're just willing to put in the work, you can train yourself on a lot of that.
SPEAKER_02:Gotcha. So we were just talking. I I'm gonna turn 60 this week this week. So I'm gonna start considering myself myself an old guy. And the last thing our old guys, us old guys, want to do is learn something new. It's like, hey, we've been doing it for 30 years, we want to keep doing it. A lot of these business owners are my age or older, they're in the same boat. You know, they don't want to learn it. But I'm I'm hearing that we have to learn it. If we don't learn it, it's gonna clobber us. I mean, it's gonna run us over like a Mac truck and we'll wonder what happened, right? So that there's really no choice of should we? It's like how do we?
SPEAKER_01:Yeah, and the the good news is it keeps your brain young to learn new skills anyway. So just embrace it. But yeah, it'll be the equivalent of like, you don't want to be the old guy that still doesn't have an email and you know, uh doesn't know how to navigate the internet. I mean, that's what it's gonna be with all this AI stuff if you don't embrace it.
SPEAKER_02:Yeah, yeah, I I think so. And um I I agree with you that it's going to change the way we do business. And we need to let it change the way we do business. Look at what we do, you know, the mundane tasks that the repetitive items that we're doing over and over. You know, take those away, and then we can be ultra focused on the things that we need to focus on.
SPEAKER_01:Yeah.
SPEAKER_02:I'm excited about the potential efficiencies of it that it's gonna create um not just within my business, but within business as a whole. Me too. Yep. So what else um what else do you have to share that might be interesting that people should know if they're thinking about selling?
SPEAKER_01:What should they know about a we have a thesis at Talbot West that says in the future, we think maybe around 2030, but that timeline is uncertain. But in the future, businesses will converge on what we're calling total organizational intelligence, which just means that they'll operate very different from the siloed model you have today, where a business is this kind of cobbled together, you know, mess of like siloed systems, processes that don't even talk to each other. Um, there's so much inefficiency built into businesses, and it's okay because we haven't had the technology to make them more efficient. But with AI, we think that there's going to in the future be much more integration and much more kind of like intelligence built into the fabric of the business itself. Um, and that will drive a ton of efficiency. So we advise business owners to start taking steps and we help them understand what the right steps are to take in that direction, where um maybe they're not building the whole house, but they're at least building uh a good foundation and starting to grow in that direction. Um, and that um buyers, you know, if you're talking in terms of sell side exit planning, that sort of thing, buyers, if you can tell them that story that, hey, in the future, this business is going to be super integrated and super efficient. And we're not there yet, but we've we've done these steps in that direction. We've laid these foundational things in place. And here's how that maps. And here are the steps you can take to build on the foundation we've laid. That is incredibly valuable.
SPEAKER_02:Hmm, gotcha. So do you see businesses, you talk about them being siloed, you do you see businesses being more integrated, even though they're competitors? Is that what you're talking about?
SPEAKER_01:I'm talking about internally to a business that a business is a mess of uh different siloed systems that hardly interact or talk to each other.
SPEAKER_02:Okay, like sales and marketing, or sales, marketing, and accounting, right? Sales, marketing, accounting, legal, and they're all siloed, not talking to each other. Oh, got it. I was thinking outside the organization.
SPEAKER_01:Yeah, and potentially, you know, there could be some stuff to integrate across businesses. I mean, especially if like a let's say uh somebody owns a portfolio of companies, they might want to do a lot of integration across them. Uh, absolutely. But yeah, speaking specifically within a business, I mean, can you imagine if a business was so integrated that you could have a central console where you could ask an AI anything you wanted about your business, and it could reach into the different parts of your business and pull out information and tell it to you, or even make correlations across the business. You could say, why are sales down for product X in the second quarter? And it could say, well, this supply chain disruption and blah, blah, blah, and this. And, you know, this competitor launched a new product and and it's correlating insights from all these different sources, and you're kind of like, oh, yeah, that makes sense. Well, what's the best course of action? It could say, well, here are uh several different options, and then you could have like a back and forth with it. And well, what what would be the spillover effects if we took uh plan A and kind of pursued that? Okay, it could play out in some of the I mean, can you imagine like the level of efficiency you could start to get if you have that level of integration in your company?
SPEAKER_02:Wow. And I'm thinking about the tool reading everyone's email and processing the data, right? And then and and taking that data and putting it in a reasonable format so we can understand it. I mean, there's there's power in that, right? It's like wow. And I start thinking about that because right now, again, perception and reality. All the business owners sitting there and may not be, you know, they're not in the trenches every day with the salespeople. They don't know what's going on. They might perceive something is happening with why sales of product A is down or down, but then that perception is has nothing to do with what's really going on. But then the tool will give them raw data synthesized in a in a manner which they can understand. One thing that gets me um with AI, and I don't know how it does it, is the tone. It seems like when you're questioning it and you go in and you do a query, if your questions are good, the tone of what comes back to you is like exactly what you were looking for. And I don't know how it does that.
SPEAKER_01:Large language models have gotten very good at kind of hitting that right tone and that right um yeah, just like you say. And there are lots of types of AI that don't even interact in natural language, they're more like pattern matching engines and finding correlations, and those all could be working beneath the surface of your business too. Um, so it's not all just about the large language models that you have a conversation with. There are many different types of AI and machine learning that can be brought in to make things super efficient.
SPEAKER_02:Wow. You know what I'm thinking about, like a sales team. If you're a sales manager, it's monitoring the actions of your sales team. Take your top salespeople. Well, why are these people overperforming and these people are not? What are they doing? Right? What are their emails like? What are their contact with their people? It's synchronized their calendars, their emails, all of the information internally to give the managers and the owners better decision-making power. And I'm excited. I'm excited to see where this thing goes.
SPEAKER_01:It's an exciting time to be alive and be in business.
SPEAKER_02:Yes, it certainly is. So, um a couple of questions here. Um you had mentioned something about AI. Why do you emphasize that AI and LLMs are not the same thing? First of all, I don't even know what an LLM is. Start with the basics and help me with that one.
SPEAKER_01:Yeah, you know, and I don't I don't know how deep in the weeds we want to get, but LLM stands for large language model. That's a type of generative AI. Generative AI as a whole is a small subfield of the entire discipline of AI. So there are many different uh branches of AI and different applications of them. Uh large language models are built on what's called a generative pre-trained transformer. And um, they're utilizing what's called deep neural networks, and they're very good at uh kind of associative type thinking and making connections. That's how they know um how to string language together because they've just been trained on so many. They get a little loosey-goosey with um large bodies of context. Uh, they're not as good at a lot of like data-heavy tasks. That's why we want to bring in other types of machine learning or AI or other capabilities. But large language models definitely have a strong role in the toolbox. It's just that you don't want to you want to apply them correctly for the right types of tasks they're good at and know their strengths and their weaknesses and they're all of that. It's about scoping correctly.
SPEAKER_02:So when I think about AI, I want to just put it all in one bucket. But what I'm learning from you, Jacob, is that that's not the case.
SPEAKER_01:Yeah. It's like it's like transportation. It's like saying, oh, I want to use uh I need transportation from LA to New York. And it's like, well, what do you need to do? Do you need to move five tons of cargo? Do you need to uh get one person there? Do you need to ship a a package this big? I mean, what does it mean when you say you need transportation to go? Uh, what is the transportation supposed to do?
SPEAKER_02:Wow. I just you're blowing my mind. I'm just thinking about this how how differently I'm thinking about it now. That sounds great. Is there anything else you wanted to share with the audience?
SPEAKER_01:Oh, I just love working with uh exit planners, business owners, anyone in the ecosystem. So, you know, anyone can reach out to me at any time. My web, my website is talbotwest.com. My email is jacob at talbotwest.com. Reach out if you have any questions about any of this stuff.
SPEAKER_02:Well, I appreciate it. It's something, it's a topic we could go on for hours and hours, but we didn't want to do that. We want to do high level this this uh podcast and and just Scratch the surface a bit, whet people's appetite about the future of AI and how it helps business owners, not just in the exit, but in the running of their business. I sure appreciate your time today, Jacob. Thank you for joining us on the podcast. And once again, give us your email and your company information so we have it.
SPEAKER_01:Uh company is Talbot West, TalbotWest.com. Jacob at TalbotWest.com is my email. It's been great to be on. Thanks for having me, Rick.
SPEAKER_02:You're sure welcome. Thank you, and thank you to our listeners. Until next time, MA Murders and Accusations. Today I'm going to call it the good of selling the business. All right. Have a great day. Thank you, everyone.
SPEAKER_00:Thank you for attending our podcast. We invite you to join us for future episodes of MA Murders and Accusations, the Good, the Bad, and the Ugly of Selling Your Business. You can also visit us at www.bsalesgroup.com or email Rick directly at rick at bsalesgroup.com.
