Latest / Mortgage Marketing Radio / Target Smarter, Close Faster: The New Way to Grow Agent Referrals

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Target Smarter, Close Faster: The New Way to Grow Agent Referrals · Mortgage Marketing Radio

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Have you ever spent hours chasing down leads only to realize you've been focusing on the wrong agents?
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The ones who aren't sending you any real business is frustrating, right?
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You know that you need to grow, but time and energy are in short supply.
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Well, imagine if you could pinpoint the agents who are already closing deals,
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some that are even tied to you right now and know exactly where to focus your outreach to maximize results.
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You're listening to Mortgage Marketing Radio.
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The podcast that helps mortgage professionals ditch the old school tactics and get real results in a modern market.
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My name is Jeff Zimffer. I'm your host and coach in this journey of modern mortgage marketing.
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And today on the show, we're diving into one critical question.
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How do you stop wasting time on the wrong people and start focusing on referral partners
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who are truly aligned with your goals?
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And to help us answer that, we're joined by Eric Levin, co-founder of Model Match,
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a platform built from the ground up by recruiters and business developers who understand
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the real estate and mortgage game from the inside out.
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In this episode, you can look forward to learning three key things.
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Number one, how to identify hidden referral opportunities in your own past deals.
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Number two, why most loan officers are leaving business on the table without even knowing it.
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And number three, how to build a smarter, more intentional outreach strategy that actually sticks and produces.
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And there's something surprising we'll uncover.
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How a quick data search revealed a top agent was unknowingly sending government loans away
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from their preferred loan officer, simply because no one asked the right question.
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So if you're ready to stop guessing and start connecting with the agents who can actually
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move the needle, then stick around for this episode of Mortgage Marketing Radio.
1:43
Eric Levin, welcome to the show.
1:45
What's up Jeff?
1:46
Thank you for having me, my man.
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Hey, you know, just two amazing minds gathering together to talk about.
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Where are they?
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Where are they?
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I see one with you.
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I don't know where the other one is.
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We're here to talk about all things.
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Mortgage real estate data, big data, perhaps AI.
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We're here to talk about how model match helps make my life easier as a mortgage loan officer.
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How's that for a setup?
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I love it.
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Are we done?
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Is that it?
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Drop them high?
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Let's put a link in the show notes.
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Go check it out at modelmatch.com.
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What else do you need to know?
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No, seriously, this is a really timely conversation.
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I was just talking to somebody earlier about being focused with your sales-related activities,
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because we're all strapped for time.
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We all want to work more efficiently.
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We all want to be more productive, right?
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And we don't want to spend our wheels working with people that we're not well matched with.
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So I think that's the first entry point for me setting you up for this conversation.
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And for those who may not be familiar, how would you describe what model match is and does?
2:44
Yeah, model match.
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I mean, I like to describe it as full funnel business development.
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You know, whatever you're attempting to do, especially within this industry that we call
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housing real estate finance, you name it mortgage, from identification of opportunities through
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engagement, through a process of action steps, through better conversion, reporting, visibility,
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collaboration, all of the above.
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You know, my partner Drew Waterhouse and I started as recruiters.
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I mean, we were 100% business development.
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You know, eat what you kill kind of thing, right?
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And along the way early on, 20 years or so ago,
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I think both of us independently of each other were probably sitting in little cubicles
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just working really hard and then thought there's got to be a better way to do this.
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And not only that, but reaching a point where you think the people that were helping
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should be better at doing this themselves.
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This doesn't have to be rocket science.
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And so, you know, the concept of model match really just started off as,
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how do you visualize business development when you're a human human, right?
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People in our industry like to say that one of the things that separates mortgage banking
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and real estate sales from maybe other types of sales is that there's such a trust factor involved.
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And I'm curious to get your take on that because obviously you coach and support a lot of high
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producing and successful originators and leaders in this industry.
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But, you know, if that's the case, well, then the process of business development is probably
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a little bit different than if I'm knocking on your door and selling you a widget, right,
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or something that you have to have.
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The consumer has options, the originator has options, the agent has options, and so it takes time.
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But when we started developing this concept of model matching, which was really a process and a verb
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before it was a SaaS platform, a software solution, it was let's take core competencies of an
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organization and match them up with opportunities. So the opportunity could be a loan officer.
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It could be a wholesale account executive. It could be a branch. It could be an acquisition.
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It could be non-sales for that matter. But you're taking six specific core competencies and
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matching up those two things. And then once you identify people that somewhat match,
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enough for you to feel like you should get to know them. How do you follow a process to ensure
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that you can convert and retain those opportunities? Well, why not manage it the same way you manage
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a loan traveling through the LOS? You know, when you identify someone through intelligence,
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and when I say intelligence, I don't mean my lack thereof in my head, but I mean data as intelligence.
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Well, that's like a prequel. If I'm looking at it like a loan, right? It's not a loan yet.
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It's a prequel. Once I'm in conversation with someone, I talk to Jeff for the first time.
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Maybe at that point, I consider them sort of in processing. They haven't agreed anything yet,
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but we're getting to know each other a little bit better. Once they start agreeing to meet,
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a time, a date, and a topic. Now you're an underwriting. The value of the person at that level
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and the funnel is different than the value of the person that's at prequel. It's very different.
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Same way you track a loan traveling through the LOS. Like I said, once you're at the offer stage,
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now you're at clear to close. You know, once you hire someone, now you're at servicing, retention,
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right? And there's different things that have to happen along the way. Conceptually model
5:55
match was designed to create better efficiencies within that process. Where the gasoline got thrown
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on it, though, is when our users came to us and said, I love it. It's holding me accountable.
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I have better efficiency, better conversion, better visibility into the value of my pipeline,
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but I don't know who to call. And so how did we solution that? Well, we went and invested in the
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animal S data, the real estate data. We didn't set out to be focused on being top of the food chain
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when it comes to data and market intelligence, but that is what happened. So the market kind of
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directed the product roadmap. The market directed the product road, man, I love that you said
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that too, because I was on a call with a company this morning who we partner with, but it's not
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not full enterprise. It's relatively big company, well-known company. And the president of that
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company is now we need to go enterprise. How do we how do we pull this together? And there was a
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comment that he had made from one of the other executives that said, maybe we should build it.
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And his comment was, and I took the I'm trying not to say just promote model match, but I do
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think it's something to think about when you think of yourself as a trusted advisor, maybe. Yeah.
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What he said was what I love about model match is we kind of get the value of both, because who
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they've become is because of the feedback from their enterprise and partners. And I love that he
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said that because that is true. It's where it we're not a static platform where we're selling you
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numbers and then you go about your business. Hmm. I love that love that setup six core competencies.
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That was a bit of a bit of a glimpse into that. Let's, let's dovetail this back into as I'm having
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a lot of conversations with people around the country the past several weeks were now, you know,
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entering Q2 of 2025. You know, there seems to be a lot of this narrative around what's working and
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it seems to be and I don't want to sound cliche, but the word fundamentals comes back, right?
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Always does. And some people bag on that and I get it, right? Because we're in this new world and AI
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and things are changing so rapidly. But the bottom line is you opened up with talking about what is
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what you said about this is a relationship business. What was that line? Do you remember? I'm putting
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on. That was awesome, but I can't remember what it was. Anyway, but the point being is like this is
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still when it comes down to it in terms of like your referral partners and if you want to differentiate
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yourself, look, there's a transactional type of an approach in a relational, right? And I myself,
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as well as many of our listeners are relationally focused, meaning if you're, you know, a transactional
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would be your buying leads big box, you know, you're running running big funnels and spending money
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and got your systems and all the and there's it's a volume game. And not to say that you don't
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do volume as a as a relational person, it's just a different approach, right? So it's like rich
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Carlton type volume. But what am I, what is this, what am I really saying? I'm saying is I want to
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use this conversation today to help loan officers be more focused and intentional with who their
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outreach is to who they're looking to partner with. And I think you guys really help save a lot of
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time and effort with that. Well, that's the focus, right? Let's put you in a position so that you can
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go into a platform and you can type in some key criteria and it's going to show you these are the
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agents that you need to be connecting with in your market based upon any number of things. But who
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they're with, where they do their business, what type of product mix they generally focus on,
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is most of their business cash or is most of their business finance? So where are the percentages
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in those case? For sure, you know, what we've also found is, you know, you talk about AI and AI
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can mean a lot of different things. But what I like to think about is how much can we continue to
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listen to the user and then curate information for them so that they don't have to go search for it.
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So for example, if all they have to do is plug in their NMLS ID as an example and then a system will
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say, here's the 20 agents in your market that you have some direct indirect property buyer
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relationships with some connections. So when I show you the property details on the connection
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with that agent, it tells a story that you can then go tell to help either convert that agent into
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a new relationship or better yet, pick up more market share with someone you already have a
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connection with where you don't have to reinvent the wheel. So that's one example of efficiency.
10:03
No, I love that and that's a great example because I want to kind of go deeper on that because
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there are several solutions out there for acquiring data on realtors, loan officers, etc.
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But what I think that I love about yours that I've seen through previous conversations and
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through what you just highlighted there is like in another world, if I perhaps wasn't using
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model match, to find that those associated relationships, I would have to run some search queries,
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I would have to go through a list and I would have to spend some time and effort finding those
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associated relationships. What you're saying is I can just enter my NMLS and that will immediately
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connect me with deals I've closed on the listing agent side, the buy side, right? Other things?
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Right. That's right. Property connections, buyer connections over the last several years. So for
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example, you did a deal on a property several years ago. That property has now changed again.
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There's an agent that was involved as the property changed, but you didn't, you weren't involved
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in that transaction. Well, it's going to show you that story so that you can go back to that
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agent and maybe reference that property or reference that buyer to be able to engage.
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You know, our brains are constantly thinking, how can we create and deliver that type of information?
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But then how can we also put the power user in a position that once they start going down the
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rabbit hole, they don't have to go anywhere else to keep going down the rabbit hole? You know,
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for, I'll give you an example. We, I heard a fun use case the other day where a user was utilizing
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model match to just identify agents that maybe they had some indirect connections with that they
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hadn't communicated with in the past. And it was, it was working well for them. But then all of a
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sudden they had, they had pre-qualified a buyer that was a disabled veteran. So we thought to
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himself, well, I need to get this veteran an agent that they can feel comfortable working with.
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I, you know, I have an opportunity to refer this to an agent. Well, instead of just picking an
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agent that they've done business with in the past, he went into model match. He searched for agents
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in that area. So he took a pin on the map, stuck it on the map right where this neighborhood was,
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looked at the agents that had done transactions in that neighborhood, then filtered it by the type
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of agency because he felt like he knew which agencies that he felt more comfortable with.
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And then he filtered it by VA. So he found the agents that are comfortable with VA lending,
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right, and buyers. And he referred this person to three agents and let the, let the buyer make
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the decision. Well, so he ends up getting obviously an agent, a new referral. But he made a connection
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with two others that are now referring him business. But he went down the rabbit hole just one extra
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step. Yeah, well, that's called using data smartly. And it saves you all the, you know, manual labor
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of searching and getting on profiles or getting an Instagram and all that kind of stuff. That's
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really, really cool. Oh, man, can we talk about that for just a second? I love that you just said
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that because I definitely agree that a platform like ours, which it does, should show social media
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links, like we should pull those things in the background so that you can go to their LinkedIn page,
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their website, their Facebook page, you name it, and also contact information, email addresses,
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phone numbers, and all that is happening. But I sometimes get a little sideways when I hear about
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the importance of that connection to social media because the connection to social, in my opinion,
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isn't important at all. If you don't have a plan for them, what you're doing within that social
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media connection, what are you actually accomplishing? Or do you just get to look at their great pictures
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and videos and now you have a new friend on Facebook or whatever? So, you know, that goes back to your
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comment right about the fundamentals. Those things should help you build a story so that when you
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do engage with them, your further down the trust funnel is really where you are. Yeah, I love
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that. So, I'm on your website. Well, of course, link this up, modelmatch.com for people who want to
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learn more at the end of this. But you have something on there and I might be putting you on the spot,
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so I apologize. But you're talking about giving loan officers the carrot and the stick and where
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the closest dollar is right now. Might be something that we were already talking about. Rekindle
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forgotten arrangements, find agents sending buyers to other brokers and remind
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strain ones about prior agreements. Can you tell me a little bit more about what that is?
14:10
Well, it kind of goes back to, wouldn't you like to have visibility into those that are cheating on you,
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right? The ones that the agents say I send you all of my business. One, in fact, they're not sending
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you all the business. The funny thing is sometimes, sometimes they actually think they're sending you
14:22
all the business and they're not. Here's an example. I think you and I talked about this the last time
14:26
we spoke. The user of modelmatch calls me up one day and says, I'm really happy with you about
14:32
something and I'm really ticked off about something. So I said, all right, which is it going to be,
14:35
like give me the good news first, right? So the good news was that he went into modelmatch and he
14:41
saw that his top agent was not sending him all of her business. And this is a pretty big producer and
14:46
a pretty big agent. And as he drilled down, he realized that all of the guvvy business was going
14:51
to other companies. He was getting all the conventional essentially, but the guvvy business was going
14:55
somewhere else. So we picked up the phone and he called her and he said, hey, I thought I was your
14:59
guy. What's the problem? Is there something I could do to better compete with these companies?
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And she said, I don't know what you're talking about. You get all my business. And he said, well,
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I'm in modelmatch right now and I can see clearly that I don't get all of your business. And he named
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the companies where he sees the business going. And her comment was, I didn't know that you wanted
15:17
that business because he had never presented himself that way. And she had remembered from the past
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how he presented. So I said, well, this sounds great. What are you ticked off at me about? And his
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response was, well, I looked at her volume over the last two years and I did the math. I said,
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well, don't take off at me. You take off at yourself. Just be glad that you can fix that going
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forward. So that's one example. You know, another example that we're seeing huge lift from right now.
15:39
And you mentioned something earlier about, you know, big, big box consumer direct call centers.
15:45
You know, the beauty that if you own your own data, you own your own intelligence, you now have
15:51
the ability to compete with those companies as well. You really can be your own servicing retention
15:55
portfolio. You can be your own consumer direct. What we discovered, you know, a while back was
16:01
that we were, we were giving all the transaction details to our users. So you can go back to 2017,
16:07
essentially, the beginning of one NMLS was being recorded and see all properties you've ever
16:12
done a transaction with custom date ranges. You name it. And then you can filter by agent filter
16:17
by market filter by type of product. Okay, that's great. Well, this was really cool for rebuilding
16:22
your database or going back and refreshing your database. We're also showing things like,
16:26
has the, is this person still current in their property? Have they refinanced? Did they refinance
16:31
with you? Did they refinance with somebody else? And if they did refinance of somebody else,
16:35
you can do the drill down and see where you lost that opportunity. But better yet, why not put the
16:39
originator in a position to ask for one more thing? I'm going to build a list for my past transactions
16:44
hypothetically. Go back to 2019, pull all of your FHA VA loans, see the ones that are still current
16:51
in their home, and then be able to see things like rate loaned value, equity, payoff amount.
16:57
What are the, what's the valuations in their neighborhood? A number of email address, phone numbers,
17:03
contact information for the borrowers. So you could then pull 10 or 20 that meet very specific
17:08
criteria, pick up the phone, make 20 phone calls. There's a pretty good chance you're going to get
17:13
a new loan out of those 20 phone calls. And so instead of model match or a data tool just being
17:18
about identifying new opportunities, what about taking advantage of all the old opportunities
17:23
that you can make sure that you never lose and pick up a new loan along the way?
17:27
Hey, are you tired of cold calling realtors and feeling like you're getting nowhere?
17:31
With my agent classes, you don't have to chase agents anymore. We hand you a done-for-you system
17:36
of ready-to-teach presentations, plug-and-play marketing, and even 200 producing agents to invite
17:42
so you can double your agent referrals in 90 days or less. Plus, you'll get weekly coaching
17:46
and a community of loan officers sharing exactly what's working right now.
17:50
Here's a quick win from one of our members.
17:52
Been part of my agent classes for a little over a year and totally changed my business. I
17:59
grew at least 25% and that was during a pretty down market and have only grown every single month
18:07
that I've kept doing it. Community is great. Jump to the Friday calls. It's awesome. Have fun with
18:12
that. Teach as many classes as you can. Just do more. Do better.
18:16
Are you ready to stop chasing and start attracting agent referrals on demand?
18:20
Book a call at mortgagedmarketing.pro or hit the link in the show notes now back to our show.
18:25
You mentioned housing data in your local area. What are some of the things you can assist with
18:29
if I'm a loan officer? I'm looking for deals, opportunities, and just give a bit of context on it
18:34
quickly is I think of in the past working with title companies where I can pull housing data
18:39
based on how long somebody's been in the house. There's certain algorithms that allegedly
18:44
determine when somebody is more likely to sell those types of things, but what kind of housing
18:48
data could I get using your system? That's a great question and very well timed. We're very close
18:53
to an update within model match that's going to allow the user to do geographic property searches
18:59
in a particular market. You can go in instead of just looking at your transactions or any
19:05
animal SID transaction or any real estate agents transactions to now go into the market itself
19:10
and say, hey, show me every property in Charlotte, North Carolina that meets this criteria
19:16
within any customized date range. Then be able to look at those properties and take action on those
19:21
properties. What we're not pulling in right now are life events, but that is something that we're
19:25
looking at doing down the road. What would be some of the criteria? Is there like NODs? Is it
19:30
assumable loans? Is it loan type? What is it? These are more things like product rate, loan
19:35
to value. Are they still currently in the home? Have they refinanced already? Who is the original
19:40
lender? What was the original specs on the loan? What's the current loan to value? What's the
19:44
current equity? What's the current payoff? What's the valuations within the neighborhood of the
19:49
market that they're in so that you could really do a very pinpointed approach on these are properties
19:55
that I want to start taking action on in a particular market. All right. Let's get a little bit
19:59
tactical back to the referral partner side of things. Maybe keep going with a couple of use cases
20:04
or examples of I'll give you the same scenario. Let's just say I wrapped up Q1. It wasn't where I
20:09
wanted it to be in terms of numbers. I got a long runway ahead of me to finish out 25 with some
20:14
big goals. I know I need to grow my I always ask this question of loan officers. Do you need more
20:19
agents or better agents? The answer is both. If that's where I'm at and I need to get better at
20:26
identifying the agents that are doing the business and then I'm going to develop some type of an
20:31
outbound strategy for that. Take me into your world. How would I log in? What would I do in your
20:36
system to help with that? I'll give a use case that came up recently when I was traveling and
20:41
speaking at an event in Idaho not that long ago. This company was talking about their goals for
20:47
the rest of the year. How much they want to grow in volume for the rest of the year and that
20:50
was going to be a combination of new headcount, new loan officers, new branches, as well as an
20:55
uplift with the originators that they currently have. I threw up a statistic on the screen and
21:01
the statistic was in major metro markets, so decent size MSAs. The top 20 agents in those markets
21:09
refer on average to almost 18 different originators. Pregnant pause on purpose? Exactly. I can tell you
21:17
the owner of the company where I was speaking. I sort of felt him choke a little bit. Here's the
21:22
beauty with that statistic. The gap between you and your goal might actually be just as simple
21:29
as looking at the agents who are already referring you business and increase your market share
21:35
by 5% with each one. That's it. How is that going to work? You drill down, you look at the properties
21:42
that they're generally involved in, you consider what's your value proposition. If you're really
21:47
strong VA and you're only picking up a small percentage of this agent's VA business, target VA.
21:53
If there's something else that you're doing with co-branding or co-marketing campaigns, target
21:57
those campaigns. If you feel like doing a lunch and learn and providing some additional education
22:02
might get you one more unit of quarter, do that. You should know your agent's well enough,
22:07
but the data will kind of be the roadmap or the guide to show you what to focus on. Jeff,
22:14
if you think about it as an originator, let's say there's 20 agents that are on that list.
22:19
If those 20 agents would send you two more units a year, there you are. You probably just
22:26
surpass your goal. It doesn't have to be rocket science. It doesn't always have to be. I need more
22:30
agents. Many times it's as simple as you just need to get more market share from the agents you
22:35
already connected with. You've done the heavy lifting. They trust you enough to send you loans.
22:40
Such a great point. I've definitely proved that out with various conversations I've had with
22:44
loan officers who do 100, 200 loans a year. If you look at their production count from how many
22:50
realtors did they get those 100, 200 loans from? It's about 150 agents. Sometimes half of that,
22:58
but to your point earlier, most of the high unit loan officers work with a large group of agents.
23:08
They're not getting 20 deals a year. In most cases, they're getting 3, 4, 5, 8 times. However,
23:14
many agents they're engaged with. Going back to the how can you pick up more market share,
23:19
there was a user that told us they were putting a campaign together where they were pulling all
23:23
the agents that they had done transactions with over the last 24 months. Then they scrub that
23:30
against the agents where they actually physically went to the closings and they were able to identify
23:35
a fair amount that they had not gone to a closing with yet. All they did to start was, these are
23:41
the 10 agents where I'm going to start going to the closings and what did they find? They found
23:46
that that agent started referring them more business. That's a good play for sure. Let's take
23:52
this a step further. We're talking about leveraging your platform, scrub, data, fine, targeting,
23:57
agents. Who are you aligned with? All the stuff we talked about already. I know this sounds like
24:01
a layup for you easily, but I really geek out on this stuff and I think in a continuum,
24:07
meaning we've got somebody who can access data and agent information and do all the things we
24:12
talked about. But then for many, there can be a drop off because it's like, well, what do I do with
24:16
that now? How do I manage it? How do I organize it? I think whether they're using your CRM,
24:22
you've got one built in or they're using their own, how are you seeing LOs now use that data once
24:27
they have it? Yeah, great question. So we started off without data. We started off no
24:31
NMLS data, no real estate data. It was fully actionable. It was 100% actionable first. Identify
24:38
opportunities in other ways. Many times looking at the other side of a transaction, getting a name
24:42
and contact information, typing it into a pipeline, into your funnel, so to speak, and then
24:48
beginning to take action on that. When the data came after, it really became very easy to identify
24:53
opportunities and then push them into what we had already built, which was a contact management
24:57
platform that really was the foundation of model match. Where now you can segment by projects,
25:03
you can segment by the type of people. Once you pull them in up at those projects,
25:07
you're picking up contact information, social media links, we're fully integrated with Gmail,
25:13
with Outlook, so you can text directly from the software, you can build text sequencing from the
25:17
software, you can make phone calls from the software. So if you're really a power user and you want
25:22
to now manage everything you're doing inside of the same environment where you're pulling
25:26
in intelligence, you can absolutely do that. You can filter, you can sort, you can report
25:31
by any number of things. What stage they're in, tags that you may be adding, you know, tag somebody
25:36
priority, tag somebody guvy, tag somebody, you know, top agent, whatever you want to tag them.
25:43
But then also partner with everybody on your team inside of that pipeline. Be able to communicate
25:48
with each other inside. Again, Jeff, think of it like the loan traveling through the LOS, right? You
25:52
wouldn't be in a system where the loan officer can't communicate with the underwriter. You wouldn't
25:57
be on different systems. So same concept with the contact management platform and the reporting
26:02
environment that we built. However, this, you know, this is the mortgage industry. What we also
26:07
recognize is there are CRMs that companies have invested in and they like to use some of them,
26:12
they've built themselves, some of them off the shelf. So we've opened up integrations to be able to
26:16
directly plug in to those CRMs as well as well as, like I said, Gmail, Outlook and other
26:23
functionality also. You know, the power users aren't just identifying opportunities and then on,
26:29
by the, you know, flying by the sea of their pants engaging with them, they're actually tracking it
26:33
and then looking at their conversion rates and then building validating stories out of those things.
26:38
So that when they communicate with the next agent or the next recruit for that matter,
26:42
they actually have a story to tell. Wow. Very, very cool, man. What's on the roadmap for you guys?
26:48
You've got some releases coming. There's a little stuff. I think maybe behind the scenes,
26:51
you guys where you and I were talking about on the last call, AI, something related there. But
26:56
what do you want up for listeners who are now curious? They're salivating. They're like, okay,
26:59
I'm curious. We're going to talk about like pricing and how this builds out in a second. But
27:03
anything you want to share before we switch into that. Everything we do moving forward is another
27:08
step towards greater efficiency towards the ability to do more business in the same amount of time
27:14
or the same amount of business and less time towards the curation of information. We're also building
27:19
out pretty large reporting platforms inside of model maps so that you can go in and do comparative
27:24
analysis from geographic market to geographic. So think of the enterprise now, a CEO, a president,
27:30
maybe ahead of digital marketing that wants to work on some campaigns, all of that happening inside
27:35
of the app. Something else I'm really proud of. And Jeff, remember, you're talking to a dude that
27:40
could barely use his iPhone however many years ago. This was the concept and the idea might have come
27:45
from myself and from Drew, but it's the wizards like our head of product, Thomas Hillbinder and his
27:51
development and engineering team all in the United States, all W2 employees that understand this
27:56
business and understand the user. What I'm actually most proud of is that our platform never has a
28:01
summer break. We're always evolving. We're always adding new features, but we've also made some
28:06
really hard decisions, financial decisions, timing decisions to be able to build and rebuild in
28:12
such a way that puts you the user in a position where you have no performance issues. I think I
28:17
just saw that we are pulling in over 400 million transactions into model match right now. And so
28:25
for the user to be able to say, I want to see this, this, this go. And for it to populate quickly,
28:31
you can't do that if you're not built from the ground up on your own, SaaS. It can no longer be
28:37
just data visualization. Right. Okay. So let's do this for the listeners who want to learn more,
28:43
right? There's a link in the show notes model match.com. What I like about this is that is that you've
28:48
got various options for people across the board based on where they're at, whether they're just
28:53
wanting to start out and get access to data. And of course, depending on who's listening,
28:57
maybe you have a platform available from your company. That's great. Hopefully you're using it.
29:02
But if you don't, this is why I wanted to bring Eric on is because I've seen probably most of
29:06
the platforms and it's very impressive the way you guys have integrated it all into one seamless
29:11
like your user dashboard, the UI is like crazy, easy, simple, beautiful. So shout out to your
29:16
designers and engineers for that. But you've got different plans of people can interact. So I
29:20
want to encourage people to go check it out. Like it's, it's like if you want to get started just
29:23
on a, you know, on a base level to get some basic transaction data, it's definitely there. And
29:28
if you want to scale up and do other cool automations and integrations and texting and all that,
29:31
well, that's there too. Depends on where you're at and what you need. But I think my headline is
29:35
why I wanted to bring you to the conversation is again, go back to what I opened up with is,
29:40
you know, how efficiently are you working with your time, right? We only have certain amount of time
29:44
in the day. I think you said this earlier is working with the right people who are doing the right,
29:48
the transactions, right? And so that's the first place you got to start with is your outbound
29:53
efforts are there was going to be right of your highest and best use. Yeah, for sure. Are they
29:57
matched to you, your criteria and your company's criteria? And thanks for bringing up the various
30:02
plans. You know, we, we don't have a sales team. You know, we're completely product focused
30:07
right now. We were not at conferences spending 20 grand to set up booths and hand out kuzis. Like,
30:14
if you want a kuzi Jeff, I'll go get that created and I'll send you a kuzi, my man. But I'm not,
30:19
you know, that's not we're spending our money on the technology. We're trying to make all of our
30:22
investments pushed back into the app to create more efficiency for the user. And along the way,
30:27
what we found was we had people calling us saying, right, I'm not with a company that has an enterprise
30:32
solution with model match. I need just need these couple of things. It's like you go to the pizzeria
30:37
and you're like, I don't need the whole pizza. I need, I want to slice the cheese right now.
30:41
Well, our wizards on the engineering and development side were able to permission control our
30:45
technology in such a way where we could offer that. If all you want is local real estate data as
30:50
an example, well, you could sign up for that and you could get it. What we find though is that
30:55
around 80% upgrade within the first 30 days because they start using and adopting the platform
31:01
enough where they want the other things, Jeff, right? They want the integrations. They want the
31:06
export functionality. We also provide full export functionality in our premium level. So the
31:12
other thing that we offer is a 14 day free trial. So if somebody wants to go test drive the machine,
31:16
they can do that. 100%. That's what I recommend y'all go do model match.com. Link in the show notes.
31:23
Eric, thanks so much for bringing this technology to life for our colleagues in this industry.
31:28
And then for making time from your busy day. Thank you. And look, Jeff, I lean on people like
31:33
you and you hear from from those that you coach and you consult and you think, boy, it sure would be
31:37
cool. If model match did X, a lot of times I find out that the answer is, well, we actually do that.
31:43
I just need to show you how you can do it within the platform. But sometimes it's that we don't do it.
31:47
And that becomes a use case that then we stick on the road map and before you know it, voila.
31:52
Voila, there it is. Well, listeners, you know what to do. Check the link in the show notes and
31:55
hope you enjoyed this episode. We'll see you on the next one. Bye for now. Okay, that's it for
31:59
today's episode. Before we wrap up, I just wanted to remind you about my agent classes.
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And while you're there, don't forget to check out the success stories from other mortgage
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bros who've already seen incredible results. Thanks for listening and I'll see you on the next episode.