Changing the Multifamily Industry with Technology

[Dani Black] (0:00 - 0:19) Our industry tends to be dominated by the larger players in the technology space, whereas the smaller players and the newer ones are actually the much more innovative technologies out there. And they're having a hard time cutting through the budgets of the big conferences and the bigger advertising opportunities in the industry.

[Dani Black] (0:19 - 0:28) We're all so focused on bringing solutions to the multifamily industry that really impacts the day-to-day of our users.

[Adrian Danila] (0:29 - 0:42) It could be frustrating for someone, for anyone that's in management, to look at a team and say, well, our only way of telling you, you know, Jimmy's doing a good job is that if we're hearing great things about Jimmy, right?

[Dani Black] (0:42 - 1:03) If we're not capturing the data at the user level at the time that it's done, then we're not getting trustworthy data. You're not getting the information to know that your property is really bad with leaking pipes. We're reading the actual description that the resident types in about the work order, and we're assigning it appropriately.

[Dani Black] (1:04 - 1:11) Every single work order needs to be completed by the technician, and it requires a photo and a comment when you complete that work order.

[Adrian Danila] (1:12 - 1:20) Do you mean to tell me that I could just set up profiles with, like, you know, what they're great at and your application will, like, do that for me as a service manager?

[Dani Black] (1:20 - 1:25) We're actually using AI to do that, and so it's one of the ways that we...

[Adrian Danila] (1:27 - 1:33) So I'm curious about your background in multifamily. How did you end up working in a multifamily space?

[Dani Black] (1:34 - 2:25) Yeah, so I went to law school, actually, and I like to call myself a recovering attorney. So after law school, when I was looking for roles, I kind of made a list of a couple of my dream companies to work for, and one of those companies was Zillow. And I happened to be lucky enough to be living in New York City at the time.

Zillow had an office there, and I applied for a role. I wasn't really trying to get into multifamily. I just wanted to work at Zillow, and the role at Zillow happened to be on the rentals team there.

And I fell in love with the industry. I've always had a passion for real estate, and the multifamily industry just kind of grabbed hold of me. And ever since then, I've really been very interested in staying in the industry and helping and improve using different technology.

[Adrian Danila] (2:27 - 2:30) Zillow's a huge company. What was it like working for them?

[Dani Black] (2:30 - 2:56) Oh my God, it was amazing. Zillow's one of the best places I've ever worked. The support that they provide for their employees, the culture that they've built there, and honestly, I believe in their product.

We've had great results for our clients, and so it was a great spot to work. If I didn't want to try my hands at something smaller and building something from the ground up, I might still be there today, honestly.

[Adrian Danila] (2:58 - 3:01) So from Zillow, what was next for you in multifamily?

[Dani Black] (3:02 - 4:01) From there, I actually did take a very short stint outside of the industry. I went to a social media influencer agency, and so I spent some time there. It was really interesting because I actually did still have a couple of multifamily clients at that agency, but I was also working with companies like Google and Amazon and Facebook to run their multimillion-dollar influencer campaigns.

I ended up stepping into a leadership role at that company and running the sales team for the first time, so it was my first big leadership role. I ran a team of about 12 between sales and SDR team, and it was a really huge learning experience that allowed me to step in and understand exactly how to manage folks or really how not to manage people. I think that's the thing you learn first is how not to do it, and then hopefully it gets better over time, which I think it has.

[Adrian Danila] (4:02 - 4:31) I'm glad that you brought up this particular part of your journey because I'm seeing some immense opportunities in multifamily with content creation, with influencer marketing. What do you see? Just having that experience and being in the space for so many years, do you see opportunities for the industry to embrace more influencer marketing, more content creation, organic type of educational type content?

[Dani Black] (4:32 - 6:36) Yeah, absolutely. I think one of the things that makes influencer marketing so special is it's basically word-of-mouth marketing at scale. It's your best friend that's telling you about a service or a product, and it's someone you trust, but then with the influence of social media and the influx of that, it's that at scale.

So instead of just them telling one person or two people, they're able to tell a thousand people all at one time. I think that is something that in our industry we've been... I wouldn't say slow to adopt.

I think especially with LinkedIn, we've been doing a lot of it for a long time, but I think we're starting to see more of a rise, like people like yourself, Adrian, of more content creation, more focus on content creation. And it builds a level of trust among people in the industry, and you have a voice and a platform to share interesting information, news, products, spark conversation. And that's really what influencer marketing is at its base level.

Big consumer companies have tapped into this for years and years now, and they have huge budgets around it. And it's very focused on brand awareness and somewhat on conversion. But with us, we're so niche that there's a huge opportunity for companies like Appwork even to tap into influencer marketing in a way that hasn't been done.

And doing it more strategically and actually putting budgets and a plan around it, I think has a huge opportunity to giving voice to products that are lesser known and really good products. I think our industry tends to be dominated by the larger players in the technology space, whereas the smaller players, the newer ones are actually the much more innovative technologies out there. And they're having a hard time cutting through the budgets of the big conferences and the bigger advertising opportunities in the industry.

And influencer marketing is a way to kind of level the playing field.

[Adrian Danila] (6:38 - 6:53) Yeah, that and I think organic content, like creating content organically, not clickbait or trying to actually sell sales-related content, just meaningful content that actually people want to consume.

[Dani Black] (6:54 - 7:57) Absolutely. I mean, I think one of the things that everyone agrees with in our industry, I think, is that the need for education is huge, especially on some marketing education, but also maintenance education. And those aspects, if you can figure out a way to how to tap into and create that content, like what you're doing, Adrian, I think that is going to be hugely impactful and just continue to snowball and have that snowball effect of viewers and listeners and everyone who can really trust what you're saying, because you're not trying to sell a product.

You're not constantly trying to advertise something. You're trying to provide information that's valuable and build that trust with your audience. And I think that's what influencers do best.

And doing that at scale is just hugely beneficial, not only to the companies that are sponsoring, but also to the actual viewers and listeners who need these solutions.

[Adrian Danila] (7:57 - 8:00) Dani Black, welcome to the show. Dani.

[Dani Black] (8:00 - 8:03) Hey, thanks, Adrian. How's it going?

[Adrian Danila] (8:04 - 8:19) For those that don't know you yet, you're the chief revenue officer for Appwork. Going back to your journey, what was the next step? What did you do next after working with a company that promoted influencer marketing?

[Dani Black] (8:20 - 8:54) Yeah, absolutely. So after working 80-hour weeks and going through a lot during COVID, I raced back to the multifamily industry. And since then, I have been on or led sales teams at a couple of different tech startups and most recently landed here at Appwork.

So very excited to be in this position and have the team that I have and also the opportunity to build and expand and grow Appwork from a pre-millionaire company to very much beyond that.

[Adrian Danila] (8:55 - 8:58) What makes it great working for Appwork, Dani?

[Dani Black] (8:58 - 10:38) There's a few things. There's a real synergy of the team. We have a fantastic, talented team here.

We're split across different areas of the world. So we've got people all over the US, but also all over the world. And the way that we work together and the way that we're able to come together, even with the challenges of being so remote from each other and having different time zones and such is just something that I haven't really seen before.

Everyone's super smart, very, very specialized in what they do. And we're all so focused on bringing solutions to the multifamily industry that really impact the day-to-day of our users. And we're all working towards that common goal.

And I think that's something that's incredibly special. Also, I think we're coming into a really nice time in our industry where people have completed a lot of centralization projects on the marketing side, maybe they're looking at office next, and they're starting to think about, well, how do we improve efficiencies in our maintenance operations? And so I think that working at AppWork right now is really exciting because we have an amazing product, I think the best product out there on the market.

And we're in a place and in a juncture in our industry that is the tide is turning. You can see it in the conversations that we're having, the level of excitement that we're generating from the product. And so it's just that really just kind of perfect blend of amazing people and product at perfect timing.

[Adrian Danila] (10:39 - 12:49) I'm glad that you brought up the product, the quality of the product. I myself have been exposed to it and I could state it's amazing, like it's truly amazing what the product does. What we're used to in the industry in general, what we've been used to is that the big tech companies, they're like a one-stop shop for everything, right?

So you have accounting, you have management, collections, and maintenance. And maintenance is kind of like part of that particular environment, but you only get the basics, right? Create a work order, type in some notes, close the work order.

A lot of times, as you and I both know, those particular work orders are being closed with a click of the button. So there's no notes in a system, there's nothing. When you try to pull those numbers, right, you try to get some KPIs, or like you're trying to gauge some individual technician's performance, those numbers just aren't there.

So it could be frustrating for someone, for anyone that's in management, a service manager, regional maintenance manager, or even a regional property manager or property manager to look at a team and say, well, our only way of telling if Jimmy's doing a good job is that if we're hearing great things about Jimmy, right? If a resident picks up the phone and calls and says, hey, I want to give Jimmy some love here, or they send an email, or they do something, unless that feedback is available, it exists, there's no way for someone in management to actually say, well, service manager probably is, because they just kind of know, they work hand in hand with a technician. But when it comes to an annual review, a community manager, and then you also add into the mix the fact that community managers don't stick around for, you know, three, five years nowadays.

Sometimes, you know, you might have like two or three managers throughout a year managing Jimmy, and at the end of the year, you had to come up with an end-of-the-year review for Jimmy. And then how are you going to come up with that review in a meaningful way, right? Because, you know, anybody like, you know, now Chad GPT could do anything for you.

[Dani Black] (12:50 - 12:52) But I can't do that, I can't do that.

[Adrian Danila] (12:53 - 13:42) Why is it for you, but is it accurate? Does it really represent Jimmy's, you know, work for the entire year? So all those things are things that, you know, I've been seeing, and I've been talking about back in 2019, 2020, I went to this exercise, and I actually worked for a company that, you know, used a big software name company, but we didn't have, I couldn't even get like that particular company to create a report that shows me every single morning how we start for all the properties.

Like we have this many pending work orders, right? On Monday, on Tuesday, on Wednesday, Thursday, and on Friday, they start and they end. So I had to pull those numbers manually.

Fortunately for me, there were like less than 30 properties, but still, it was a job.

[Dani Black] (13:43 - 13:56) A lot, like close to 30 properties, that's a lot of reporting to have to pull manually on an individual property basis regularly. How many hours do you think that takes? I mean...

[Adrian Danila] (13:57 - 14:54) It took, well, let's just say, so let's just say 30 properties just for the sake of the argument, right? And then you had to pull like six sets of data points because you have Monday to Thursday once and Friday twice. So it's 180 data points that you actually have to manually pull in a week.

180 data points just to show the numbers. And then I had columns that were dedicated showing how many were less than 48 hours, between 24 and 48 hours, and over like 72 hours, things of that nature. How did they compare?

How did they fare against their previous week? So you're talking about close to 300 data points that some of them, I had to do them on a calculator. I literally had to calculate that number.

There was not a way for me to just automatically build a... Well, probably there was a formula. I wasn't too great with Excel.

Let's just be honest. But in all reality...

[Dani Black] (14:54 - 15:43) Which, why would you be, right? Adrian, your background was coming up through the ranks of maintenance. Why would you have been trained on Excel early on in your career?

You wouldn't have been. So why are we asking you to do that without the help of other technology or at least training on how to use those things? I mean, with the numbers you just shared, you're talking about 15,000 data points a year that you have to calculate, oftentimes manually with a calculator.

I mean, if it takes you even 40, 50 seconds, even a minute per data point, I mean, think about all of that time. I mean, if we're talking... That's potentially 250 hours.

Now, probably a little less than that, but that's a lot. That's a lot of time.

[Adrian Danila] (15:44 - 16:36) Let's just say it's 200 hours, right? And I wasn't paying minimum wage, honestly, as a director of maintenance. I was being paid a solid salary.

Well, imagine how much that amounted to. And fast forward to 2024. It's so exciting that I don't have to do that.

If I was to go back and do the same thing, I wouldn't have to do that. So I want you to share a little bit about the automation and the data that's available, the KPIs that are available with your software, with your app, because I've been super impressed. I want to give you the opportunity to speak on the KPIs that you think are the most relevant for team performance and for individual performance.

What are the ones that you're finding most impactful?

[Dani Black] (16:36 - 21:16) Yeah, absolutely. So I think one of the big tenants of the development of app work was a focus on data and data points and providing that relevant information that operators need to efficiently manage a property. Like you said, one of the...

And if you've ever met Sean, our CEO and our co-founder, he can talk about this for days, but one of the things that was painful to him is that at any given time, he could go in and he could find all of these stats and all of this information about his leasing agents and his leasing team. And he could tell you exactly how they are performing. And he had zero visibility into maintenance technicians, and they make up 50% of your team.

And honestly, such a huge part of the operations of the property, they're the people that are actually interacting with your residents the most on the property. And there's no insight into how they're doing that or how they're performing. And so app work was really born out of that need to have an understanding of how are teams actually interacting.

And he discovered when they were building is everything started to track back to maintenance, whether it be occupancy issues, whether it be resident satisfaction scores, turnover times. I mean, everything was tracked back to maintenance. And so without the data on the individual technician performance, he had no way of solving for training issues, understanding retention issues, looking to see who his top performers are and giving them the adequate recognition that they should get beginning.

And so with app work, when the system was designed, it was designed from day one to not only capture data on work order information and unit level work order information, but also tracking that data back to your technicians. And I think it was really interesting. You mentioned earlier that the technologies that are out there today are property management systems.

They they have a little bit of everything they cover. They go very wide. And what they don't do, though, is they don't go deep.

They have really basic systems, surface level systems that you could run your properties on. But it's not going to give you that optimum efficiency that that maximizes the day to day for your teams. It's not going to provide impacts to your NOI.

It's just going to give you kind of baseline information. And what app work has done is we've come in and we've said on maintenance, we're going deep. Everything that touches maintenance, whether it be work orders, make readies, inspections, technician data, vendor information, we're going deep on that.

And we're building a system that is an operating system just for your maintenance team. And with that, we we track KPIs on your technicians, things like work order completion times, total number of completed work orders. We're looking at how many each technician have assigned on a given time frame.

We also track that by skill set and you have complete control over the skills that that technician can receive work orders. And so if you only want a technician who's HVAC certified to receive HVAC work orders, but you do want them but but you also want him to be able to change AC filters, you can get granular and you can say, I want all my technicians to change AC filters, I'm going to turn that skill on, but everyone else is not going to be able to touch HVAC work orders except for these certified technicians. We also track callbacks.

So for us, anytime a resident says that a work order wasn't completed, we call that work order back and we track that against the technician. And it's not in a negative way, it's really for a training aspect, because we track that on the skill set. So now you can go into app work and look at, oh, you know, Johnny here, he needs to have an appliance training because he's had 12 appliance callbacks in the last three months.

So we're going to get him that appliance training he needs. And now he's going to get rid of all those callbacks. And he's going to be a much better, higher performing technician because of it.

We also do a lot from a retention standpoint for the technicians. Retention is a huge problem. And so we built gamification systems so that we celebrate the work that they're doing.

We're constantly recognizing, Gallup has done studies that show that employers that regularly recognize their employees have a 31% lower voluntary turnover rate. I mean, a 31% lower voluntary turnover rate could solve the retention issues that we have in maintenance across the industry. So just by more regularly recognizing your employees.

And so that's been the focus of app work from the beginning is data and the technicians and making sure that technicians are excited to use the product every single day.

[Adrian Danila] (21:16 - 21:21) So much to unpack here. So I'm going to go back a little bit.

[Dani Black] (21:21 - 21:22) A couple of tangents.

[Adrian Danila] (21:23 - 22:39) Yeah, yeah. I'm going to go back a little bit. And I will just say that I've seen quite a few products.

A lot of them that are maintenance related. You know, I've been asked to look at, you know, certain pieces of software that's being developed. Feedback.

Could you tell us what does look like here? And what I'm learning, even with companies that are like very specialized like yours, not yours, but others, you know, some of your competitors is that this product is being built without the operators being on the table. In other words, someone, a very intelligent, very smart person, right?

That knows how to write code. He imagines how things are being run at a property. Or also uses maybe random feedback from the operators, but it's not a consistent feedback, right?

To maybe do a tweak here and there. But at the end of the day, like what they're putting out on the market for the end user is not something that has the end user involved. And I know the story of all app work, if you wouldn't mind spending a few minutes there on like telling how, how was app work created and what's the relationship between a operator and the technology part?

[Dani Black] (22:39 - 25:53) That's a great question because I think our story is very, very different than most prop tech companies out there. We were created by a, by an operator and we were created not to sell, go sell a product, not to be launching it and selling it to others. We were created to solve their own problems internally.

And so the biggest problem that they were having was maintenance and the visibility into maintenance. And so they went directly to their teams, their technicians, and they built a technology that they would actually use because we recognize that from day one, if they're not using it, we're not getting the visibility. Nothing will be accurate.

So we have to build something they're going to use. And so Sean, our CEO and co-founder was actually the VP of ops at the operator. And he went to his, the way he tells it, he went to his technician that was going to be the hardest to convince.

He actually told them, Sean, I'm never going to use this. I hate technology and this is never going to work. I'm never going to use this.

And his goal was to build a product that he would use that you could convince the, the most tech like inept person that was so against everything to use it and get excited about it. And that was their goal from day one at app work is get everyone to use it. And, and they did it.

I mean, he, the, the technician that had said, you know, he was there, he was about to retire. He said he'd never used technology. He loved app work before he retired.

He used it every day and he was excited about the gamification and he was a convert. And I, and part of that is because he gave feedback. He was our strongest critical technician and the feedback that he gave was completely like, so, so valuable to how we develop technology, because if we can develop something that he will use, anyone's going to use it.

And so that's what we did is we, we went straight to the source and got direct feedback from them. They were our, they were our beta testers. They were our users from day one, and they were telling us everything that was wrong, everything they hated about app work.

And we just would keep iterating and fixing it. And we continue that process today. When we launch a property or a portfolio, we're, we're launching.

And then each week we're meeting, not just with the property manager, the regional manager, the VP, we're meeting with the technicians each week and we're getting their feedback and we're cataloging it and we're looking where the similarities are. And then we're, we're making updates to the tech app in real time for our clients. And we're continuing to improve on the technician experience.

We want, we, and we've created a huge focus too on really figuring out how to design a product for the technicians that they don't even need training on. So many consumer apps are out there like Uber or Lyft or Uber Eats or, you know, DoorDash, any of those, you don't get trained on how to use those products. So why should we have to have extensive training for our maintenance technicians on how to use the tool that they're going to use every single day for their job?

We shouldn't, we should just design better and make it more user-friendly. And that's what we're doing.

[Adrian Danila] (25:54 - 26:22) Yeah. I've been saying until I probably got boo in my face, you know, don't, don't show me your ability to sell a product, even though that's very important, right? Because ultimately I do want to say, right, a lot of times it's not about the best product that's out there, it's the best well-known product, the most well-known in the market that actually wins, right?

And sometimes that's not like the best, the best quality product.

[Dani Black] (26:23 - 26:33) Yeah. I think Sean might disagree with you. I saw a LinkedIn post that he posted the other day on someone, the best product always wins.

And I would, I would, I would disagree with that statement. I would agree with what you're saying.

[Adrian Danila] (26:34 - 27:28) I had some thoughts about commenting on that too. Right. It's, you know, and there's stories out there, you know, the big companies, the multi-billion dollar companies that are throwing, you know, hundreds of millions of dollars behind their brand and their product to actually get it in front of people to become, to create that ubiquity type of like feeling where every time you turn around, you know, there's Coke or, you know, there's Nike, there's Apple. Of course, you know, we're talking about a niche and we don't have to like go all that way, but relevance, it's important. Now talking about the quality of the product, great, amazing product, but then how did you come up with this idea that, why is it important?

Why was it important in process of building this product that to make it like so easy to use? Why, why is user adoption important ultimately for a product like yours to be successful?

[Dani Black] (27:28 - 29:19) It goes back to what you were talking about before is a lot of technologies that are in the space, they talk to an operator and they get some feedback from the operator and they think that they're building it based on the feedback of the client, but their product's not in use when they're building it. They're building it from an idea. That idea might be coming from a couple of people that don't actually use it day to day, right?

So I think most products in the maintenance side have been built with the VPs of operations or the regional managers in mind. They're built from a reporting standpoint. It's very, it's very data driven, data heavy, which app work is as well, but the way that we do it is based on getting the data because bad data in is bad data out.

And so if we're not capturing the data at the user level at the time that it's done, then we're not getting trustful, trustworthy data. You're not getting the information to know that your property is really bad with leaking pipes, right? We don't really know that because you're not getting that information.

Maybe, maybe two, you're not like, it's not leaking pipe issues. Your residents are miscategorizing the work orders that they come in and they're not getting updated in the system because there's no notes and there's no real time information, but actually a leaking pipe work order that came in is actually blinds issue. And that someone was just trying to get someone out there faster.

There's a lot of these things that can corrupt your data, but if you go directly to the source and you build something that technicians are actually going to use, it's a lot cleaner and it's a lot more likely that the reporting that you're relying on to make huge monetary decisions for your properties is significantly better. And you have a lot more, not only more information, but you have better information.

[Adrian Danila] (29:20 - 29:49) So true on all the points. And I'm going back again to what I was saying earlier, right? With a big, big software companies that you could go like print the work orders, hand them to the technicians.

They bring them back with some notes and someone, a lot of times it's a leasing agent in office clicks a complete button. And then when you try to pull some specific reports, they just aren't there. What are other things that app work does to protect that data integrity?

[Dani Black] (29:50 - 30:56) Yeah. So within app work, the only people that can close a work order are the technicians themselves. The technicians are the ones that have to say that this was completed and that happens within the mobile app.

There's only one exception to that. And it's if a work order was assigned to a vendor, then an admin can close that work order out. But otherwise every single work order needs to be completed by the technician.

And it requires a photo and a comment when you complete that work order. So every single work order now goes from maybe being entered into the system. Maybe the leasing agent puts a note in, probably not because they probably can't read the handwriting that's on the paper.

Or they're just not going to do it because they're trying to enter 30 work orders in between all of the other tasks that we've asked leasing agents to do. And they're just going through and completing those work orders. Now with app work, you have the work orders are being completed by the technicians.

So that's them verifying that it's actually work done. And they're adding a photo and a comment for every single work order. So now you have a huge, much larger set of data and information on those work orders and what actually took place.

[Adrian Danila] (30:57 - 32:01) Love it. Also going back to something you were saying earlier that I picked up on. You said, hey, you could set up each technician based on their strengths of what their capital of handling.

And just say, John is great at HVAC. So we're going to put that in John's profile. And then he is going to be one of the technicians they're allowed to receive.

I'm thinking about, I'll say not always, because it's still like the current way of doing things for most of the industry to where a service manager has to either print and go through those service requests and see what's what and distribute them to the tax based on their ability, right? Their abilities of completing those particular work orders. Or best case scenario, they're using an app and then on an app, they are to assign them to particular tax.

Do you mean to tell me that I could just set up profiles with what they're great at and your application will do that for me as a service manager that I don't have to actually spend a minute?

[Dani Black] (32:02 - 33:09) Oh yeah, it will. And to take it even one step further, we're actually using AI to do that. And so it's one of the ways that we use AI in a more unique way with an app work than what I think has been traditionally thought of as AI use in our industry.

And so the AI actually analyzes not only the skill sets in the profiles that you have control of as a supervisor to set up for your team, but it also looks at how many work orders have been assigned to that particular technician. So we're load balancing so that there's not one technician receiving, you know, 20 work orders and one has five. We're making sure that there's some balance there.

We're also looking at aspects of work order priorities. So is an emergency versus a regular work order. We're looking at completion times of the technician to take that into account.

So the AI is looking at a lot of different aspects and more efficiently assigning the work orders versus a supervisor just going through and trying to just kind of think through or, you know, every other type of assignment. We're actually looking at the data and assigning appropriately.

[Adrian Danila] (33:10 - 33:21) When it comes to using AI to provide extra resources for the technicians to to be able to travel, is Appwork doing some of that as well?

[Dani Black] (33:22 - 35:52) Yeah, so Appwork uses AI in a couple of interesting ways today, and there's a lot of plans to use it in a few other ways that are really interesting in the future. But today we use AI in our auto-assign functionality. We also use AI to actually read the description of the work order as it comes in and classify that work order appropriately so it is appropriately assigned to the right technician, as well as you're getting the data on that.

That's one of the ways that I think we, you know, like really impact and help the technicians with their efficiency throughout their day is we're just making sure that they're getting the right work orders. You know, that something that's coming in as a leaking pipe really is a leaking pipe, and it is an emergency. They're not on call and they're getting, you know, a notification about a leaking pipe when it's not actually a leaking pipe.

We're reading the actual description that the that the resident types in about the work order, and we're assigning it appropriately. And then we also use AI to actually analyze all of the data within our system, and it's looking at negative values but also positive values. And so this is really, really handy for the supervisor because if you're running a daily or a weekly meeting, we're sending you a report, an insight report, on various aspects of the data that you need to know to manage your team better.

And so we look at things like whether a technician completed any work orders. So we say things like, if, you know, if Johnny was at work today, check into why he completed zero work orders. We also flag when one of your technicians gets a really a good five-star rating from a resident after a work order was completed.

We flag those positive actions as well. We tell you, you know, what your work order saturations are and make sure that you're kind of on track with your metrics. And so we give you a lot of actionable data that instead of, like you said, Adrian, you having to pull 300 data points every week, we actually probably provide most of that in these insight emails that we send you.

And you now have actionable insights to use to manage your team. That makes not only the supervisor's role more efficient, but it actually makes the technicians more efficient because they get information feedback more in real time and know how to correct something that they've been potentially needing work on.

[Adrian Danila] (35:53 - 36:32) So if I'm a community manager, right? I'm not a person that's like on a daily basis, like too involved with maintenance. I have a limited involvement with the maintenance team, but I still want to know like what Jimmy does, what Johnny does.

Sometimes I feel like, you know, maybe they're like too often in the office. What's going on? How do I get like a, you know, better idea, a better feel?

Like based on what you just described, me as a property manager, how would I get some information, some, you know, verbiage? How is the information delivered to me that I kind of get a good feel about what's going on out in the field without actually micromanaging or being behind that technicians all day long?

[Dani Black] (36:32 - 37:24) So those insight reports are definitely one of those things. Those can be emailed to pretty much any admin on the team that wants to subscribe to them. They can get them daily in their inbox.

The other thing is throughout the AppWorks system, pretty much all of our data is exportable via PDF and CSV. But to take that one step further is you can actually subscribe to pretty much any data. So you just use the filters within our system and you subscribe to it and you can subscribe to it on a frequency that you yourself choose.

So for instance, Adrian, those 300 data points that you had to pull every Monday and Friday, you could just use filters, set it up, and it's automatically delivered to you in CSV or PDF format exactly how you need it. And now you've done all the work once to pull those reports and you're getting it consistently.

[Adrian Danila] (37:24 - 37:34) That's quite amazing. I love it. And is it coming in a form of like an email, like a person will communicate that to you, like a real person?

[Dani Black] (37:34 - 37:37) It gets emailed out to you. Yeah.

[Adrian Danila] (37:38 - 37:40) And it's actually written by AI, right?

[Dani Black] (37:40 - 37:54) Yeah. It's all written by AI. Yeah.

It's sentence-based format, saying like, hey, Tony got three five-star reviews this week. Make sure to congratulate him next time you see him. That's a phrase that you might see in one of these emails.

[Adrian Danila] (37:55 - 38:27) Yeah. It's definitely something that I've been watching closely. I've been using quite a bit lately in my work.

And I know that it's disrupting the entire, not just multifamily, but the entire world is being disrupted as we speak. There are some amazing applications that are being built out there. What are some exciting advancements in AI that you foresee influencing multifamily maintenance in the next few years?

How do you see app work playing a role in taking advantage, preparing for those advancements?

[Dani Black] (38:28 - 41:26) So I think that's just such a good question. Where we are now versus where we can be in three years with AI is, I mean, honestly, like kind of unpredictable in the sense that there could be so many more advancements. And part of those advancements happen because of AI that we may not even be able to foresee that where we might be five years from now.

However, in our minds, we have a few very distinct thoughts on where we want to take app work. Just how ChatGPT is starting to become like a search engine for everything pretty much, like it's starting to replace. And you even see this on Google.

Google uses this AI now to summarize search results. So instead of having to go through and do the research yourself, you're able to get those summaries right at the top. And that's how people use ChatGPT as well, in addition to writing things for them or polishing different documents, they're using it as search.

And that's something that I think we at AppWorks see as a step in innovation, right? Is how can we make AppWork be communicative with teams? And all they have to do is go ask it a question and it's going to spit out what they need.

And instead of you having to go in and add the filters to the reporting, can we just allow you to ask AppWork a question, and we just deliver the reports that you need with just one question. So that's definitely something that we see as a potential future for AI, which I'm very excited about, think about how much time that'll save. But I also think that it's important to note that we're talking about where we want to be in a couple of years with AI and maintenance technology.

But there are so, so many companies out there that aren't even like where we are now, right? So, so many people that I talk to are still using pen and paper to run their work orders. And we've already talked a little bit about how much can get lost in the shuffle when you are using pen and paper and how little you're taking advantage of efficiencies.

I would love to see in the next two or three years, not only our advancements in AI, but also just as an industry, better adoption of technology on the maintenance front. I think, you know, 10 years ago, we were in a different place with technicians and folks, you know, not every technician had a smartphone. I don't think that's the case now.

I think pretty much everyone has a smartphone, and they know how to use apps. So if we're in that space, like we can get everyone to using a mobile app to run technology. And once we get there, then we can get excited about where AI is going to take us.

But until we bridge the gap of actually getting the technicians to use the technology to input the data, we're never going to get to that next spot where we can be truly, truly innovative with AI within maintenance.

[Adrian Danila] (41:27 - 41:54) Are you currently having any type of parts of your application helping the technicians directly, not just through the data that, you know, shows me as a manager, these numbers are low here, callbacks and whatever. So we need to focus on this, but actually taking a step further and say, we could actually like help with the training itself in such a way. Do you have anything, any part of your app that does that, or is it something that, you know, you're considering in the future?

[Dani Black] (41:55 - 43:10) Yeah, absolutely. So we have a lot of exciting features coming very, very soon around training for technicians, something that I am excited to share in a couple of months. It's still a little early for us to announce it fully, but it's going to be impactful, not just for the technicians, for training of technicians that use app work, but for training of technicians as an industry, it's going to bridge the gap.

I think something definitely to look forward to and keep an eye on as we continue to develop. I'd say today, what, where we're still focused though, on providing that training and, and focus for our technicians really involves the ability to actually see where that training is needed. Today, you know, we're providing that visibility, which was never provided before.

I don't think anyone else on the market has the visibility into what training is actually needed for your teams. We're going to take that to the next step and not only provide the visibility, but also have the ability to provide that training in app, but we're, we have, and we have a big, big announcement coming this year in 2025. So I think stay tuned and definitely be on the lookout for, for when we, when we launch that.

[Adrian Danila] (43:11 - 44:16) I'll definitely be on the lookout, but I also want to share my ideal situation when it comes to AI and training, right, for maintenance technicians. This is what I envision. And I think something is happening out there, you know, maybe this is something that, you know, you're working on or others are working on, but to me, the future of training is going to be AI training body for a maintenance technician, a training body that actually you could ask questions, like you ask Siri, and then you could ask your training body, Hey, this light switch right here, like it's not operating, like what are the things to check? Like, what am I checking first?

And that training body, AI training body will actually walk you through, through voice and everything will actually be the thing that you have on your phone. Like you have it with you and that it'll tell you what to step-by-step through how to troubleshoot a light switch, an HVAC, whatever that might be. And it will just kind of like not eliminate, but minimize all the other, like, you know, ways in which, you know, we've been training for decades, forever.

[Dani Black] (44:17 - 45:51) That will be a monumental step forward for training. The interesting thing about AI is that you need the data to be able to create the language models and the positioning for the AI. And because we've lacked some of the data and some of that information for so long, I think we're now in the, the explosive area of being able to start to gather all of that information and input that into the AI so that we cultivate a language model that is specific to multifamily maintenance.

And so that some of those things can develop a lot of the other, and a lot of the other AI technology that's in the multifamily space has now been operating in multifamily for a number of years, specifically on the marketing side. So I actually used to work for Elise AI, and they were the first multifamily specific AI communication tool on the market. And their AI is so powerful now because the longer that the AI exists for that specific purpose and for that niche, the better that the AI gets and the more data that it has to feed in and pull from.

And so the way that we're using AI today to pull in information on the descriptions and train AI models there is going to feed in into those next steps of AI and training for something like what you're, you're describing. And we're still just in the infancy of where we're going to be able to go with AI in the maintenance, in the maintenance side of things.

[Adrian Danila] (45:52 - 45:57) So basically, you're just telling me patience and bring me one day and I'll build a game for you.

[Dani Black] (45:58 - 46:37) That's right. That's right. I mean, I think, I think that's a fantastic idea.

And we've had some of the building blocks of that. We have a tool that we're working on called HandyAndy. And that is our AI assistant for maintenance.

And so we're building these things, but we're, we need the data to make them significantly more powerful, impactful. You wouldn't want to tell, and like something like what you're describing is so, so important to get right because it's dangerous if you don't quite, quite frankly. And so I think we understand that and we're taking our time to get there because we want to deliver something that's amazing, just like the rest of what we've delivered with AppWork.

[Adrian Danila] (46:38 - 47:18) Danny, super amazing conversation. I really enjoy having you on. I learned so many cool things about what you guys do and what you have in the works.

I want to give you the opportunity to share with me and share with the audience. What are some things, what's your vision for the future of technology in apartment maintenance? Why are we looking at 2025 to 20, you know, maybe 28?

I don't want to go too far out because, you know, like year after year, there's more wow, like, you know, on a daily basis, more jaw dropping stuff that's coming up. And obviously that's going to impact what you're doing and what, you know, your competition is doing. What's your vision about, you know, what we should be expecting in the next, you know, two, three years?

[Dani Black] (47:19 - 49:18) Yeah. So I think we're going to see a huge change in the way that maintenance teams operate on property with the implementation of technology. And once we get there, which I'm hoping is in the next year, we're going to be able to see various strides that come from having that data, things like these AI developments that we've been talking about, but also a lot of other innovations that are coming out and that we're spearheading, things like new and interesting ways to visualize data, map-based technology and map-based data visualization. So it's just easier to recognize patterns across properties.

We're looking at including things like an LMS directly into app work. We're looking at developing additional communication tools for your teams, better language representation across our platforms. So I think there's a ton of even just minor iterative advancements that we're going to see in the next few years that's going to change the game for maintenance teams.

The name of the game for us is let's get everyone to baseline now as quickly as possible so that then we can use our technicians' information and what they're seeing on property to develop those next innovations and those next tools. We have ideas and we think we have an understanding of where things should go. But at the end of the day, app work is still dedicated to actually building tools with our users in mind and with their feedback.

And so we can have all kinds of ideas about the innovations and the needs of the industry, but we have to validate that with what the technicians actually want to see and need. And so we do that by understanding what their problems are and trying to come up with unique innovative solutions for those problems.

[Adrian Danila] (49:18 - 49:23) I love it. Dan and Black, thank you for taking the time to be with us today.

[Dani Black] (49:23 - 49:26) Thank you, Adrian. I appreciate it. It's always a pleasure.

[Adrian Danila] (49:27 - 49:45) Everyone, thank you for watching us today or listening to us. If you're interested in more details on great things that are in works at app work, please feel free to reach out to Danny directly. I'm sure that you will be impressed.

And take care. I hope to see you back here soon. Have an amazing day.