← Personal Injury Mastermind w/ Chris Dreyer
Personal Injury Mastermind w/ Chris Dreyer
293. Start Converting w/ TopDog Law: Lessons from a Data-Driven Intake Machine
00:40:12
When TopDog Law discovered they were overstaffed but still missing calls, they knew something had to change. In this episode, James Helm reveals how they transformed their intake from a traditional answering service into a data-driven powerhouse, converting at elite levels.
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Transcript38 lines
- [00:00]
A
We moved from 25% to 29% conversion rate. But when you're talking about a ton of money being invested in advertising and thousands of leads, it's like 4%. Moves the needle a ton.
- [00:17]
B
Real numbers and real systems. Get real results. Stop guessing and learn from one of the fastest growing intake teams. Top Dog Law. James Helm gets brutally honest about what worked, what didn't, and most importantly, why. Welcome to Personal Injury Mastermind, the show where ambitious attorneys come to learn, implement, and get results. I'm your host, Chris Dreyer, founder and CEO of Rankings IO, the SEO agency of choice for elite personal injury law firms. James and his team are fielding thousands of calls a month now. If you're thinking, I'm not handling that kind of volume, Top Dog does start with last week's episode with Yanni Smith, then come back to this one. Together they lay out exactly how to level up. From outsourcing your intake to bringing it in house, to scaling it like James has. This is your roadmap for modern intake. From starting out to running a full scale operation. Let's dive in.
- [01:07]
A
When we first started, we were using a third party call center. If you're somebody who isn't getting huge volumes of leads and or just wants someone to consistently answer the phone, a third party call center is a great option. Obviously they're not your people, so you can't train them the way you can if they're your own employees. And also it can get expensive depending on the kinds of minutes and whether it's a pay per sign model or they're billing you per minute. Really for us, the impetus to want to bring it in house was more about the quality though, than the cost. The basic idea was, okay, we're spending, you know, tens of millions of dollars advertising to get these leads. If we can convert just 5% or 10% more of these leads through a better intake process, that's going to make us millions of dollars. So it's worth the headache and cost and difficulties getting that intake center set up. Because once you have that infrastructure, you can one, improve quality and two, continue to scale.
- [02:17]
B
Your team's evolved, right? So now I think today you've even got an outbound team that's like really hitting, like making sure nothing slips through the cracks. How has the team evolved since you started?
- [02:28]
A
Maybe it would be helpful to outline kind of the org chart. So right now we have 32 intake specialists. So we have 32 people that are actually the agents that are on the phone. And then we have a layer of kind of managers that sit atop of them. So like we try to keep seven to 10 agents under one manager, like one intake supervisor. And then we have someone at the top that manages the agent side. So it's kind of like a pyramid, right? So you have like 32 agents on the bottom and then you have a handful of, you know, managers and then you have one person sitting on the top kind of owning the whole system. What we've learned is what complements that is actually operations team that are folks that aren't on the phone but are in charge of the quality of the call center. So we have a director of operations and then under them there's four departments, Training, quality assurance and operations manager. And then we have a workforce specialist which is only in charge of scheduling for all the agents.
- [03:36]
B
Let's start with the training side. Are they doing like a boot camp? Like what, what kind of things are you doing? What's involved there?
- [03:43]
A
If you're managing your call center appropriately, you have those agents at 80% occupancy, which means they're on the phone for 80% of their work day. Any less than 80%, it's deemed that the agents are kind of being inefficient with their time. So usually how that looks in practice is they're on the phone and then there's a gap called after call work time, which usually is about 45 seconds. And then you want the agent back on the phone. Agent turnover across every industry, call center agent turnover is something like 30%. And the cost to replace a call center agent is like $20,000. If we really want five to six good agents, we probably need to hire 10 people. As it pertains to the training, what we do is we try to do the training in classes so we have someone who's a trainer. Think about it like a teacher, right? They're building out top dog university, top dog call center course. And then they have 10 agents that all start at once. And then the basic idea is we're going to put them through the four to six week training program, get them on the phones, and our historical data suggests about five to six of them what end up sticking and being long term call center fits for us. And four of them will get through the training, get on the phone and at some point decide, hey, this isn't a role that's good for me.
- [05:09]
B
Have you like surveyed these individuals to determine are they just burning out or are they just. Obviously you're going to fire the individuals that aren't performing because you, your firm is phenomenal at KPIs. What's some of the main reasons why they just don't work out?
- [05:25]
A
I. I think, you know, we measure happiness score and the call center folks generally score pretty high, but it's just not quite as high as some of the other departments. Like, it's a tough job to say I'm going to be on the phones all day and everyone's going to be perfectly happy. Is. Is probably unrealistic. And so we see that turnover for a couple different reasons. First is they're just below their benchmarks on KPIs. And we're, like you said, we're trying to have less subjectivity and more objectivity. So an example is like missed calls, right? We try to set a benchmark of like, what is an acceptable amount of missed calls. Now, when someone misses a call, that doesn't mean that our whole call center is not picking up when someone's calling us. Because we have a software system where if someone doesn't pick up within three rings, it rings to another agent. So I'm not talking about someone calling us for a car accident and then it like going to voicemail. I'm just saying the first agent that the call rang to didn't pick up. We measure that like the software system measures why they didn't pick up. And you obviously see fluctuations from different agents. And what we've tried to do is control the Internet and the other factors. Because some of the missed calls when we first got started was due to our technical issues, like being a remote call center. You can't standardize the devices and the wifi. We've had to learn how important those things are because one of the biggest reasons our agents were missing calls in the beginning was just bad wifi connection, which really isn't their fault. But now it's like we're providing a stipend. We're using tools to actually check everybody's wifi connection throughout the whole day. One thing that we prohibit is them actually working anywhere from outside of their homes where they're directly plugged in, because we need to maintain that connection, which, again, that's ideally a remote job. You wish you could work from your mom's house sometimes, but in this role we just need that controlled. And so, you know, to get back to your question, missed calls is probably one factor why an agent wouldn't work out for us. Another factor is, you know, measuring the amount of calls they take that result in signed cases. Right. Obviously there's some type of benchmark there. If you're seeing, you know, one agent who's taking 3x the amount of another agent or, you know, one of the agent is kind of below the minimum threshold that we, we set. That's another one. Another reason might be that their empathy on the phone, like, it's less about them hitting the missed call or signed case goals, and it's more just about like our quality assurance has reviewed their calls and they're not treating our clients appropriately. That's obviously something you want to talk to them about. Put them on a performance improvement plan. But ultimately, if they don't have the degree of empathy or communication skills to work. So those are kind of the things on our end now. On their end, like we said, it's a tough job. There's some people who get into a call center role and then just say, you know what, like, I'd rather drive for Uber or I'd rather do something else. I mean, obviously we're trying to hold them accountable. So they have to want to be here and want to be on the phones and really feel like they're helping people by speaking to them on the phones. And it's not a job for everybody.
- [08:50]
B
James walks us through how artificial intelligence is transforming intake quality control. He explains their use of the Amazon contact lens to flag critical calls, with special focus on catastrophic injury cases, where just 5% of cases drive 50% of revenue. This shows how AI can enhance rather than replace human expertise.
- [09:08]
A
So quality assurance tracks a bunch of things. Just to zoom out, the way we have our system set up is we have Salesforce and then we have Amazon Connect, which is the call center software we use that sits. It's a soft phone that sits within Salesforce. And so our agents can just work right within Salesforce to take all of their calls. All the calls that they take are recorded. And so we have a, you know, recorded log of every single call every day that one of our agent going through all of those calls. When there's 400 calls in a day or 500, whatever it's at, right, that's challenging. So there's actually good AI tools that can flag calls. So Amazon has a product called Contact Lens. There's Meet Record. There's probably like four or five of these tools that actually do the same thing where essentially the AI flags problematic calls. And it can be based on, like, tone. So like hostility. The other thing is, you know, erroring out reps. So for us, we're working with partner firms all over the U.S. if a lead is inappropriately routed to the wrong person, maybe it's a med mal in New York and they send it to a med mal in Michigan. Then it's like, ah, you sent this to the wrong person, that's an error, right? And we ding them for the errors. Now we've built the conditional logic is what it's called around the software so that the agents don't actually have to think anymore. That was the biggest iteration we went through when we switched to Amazon Connect before it was like our staff had to remember the decision tree of like if a case comes in and it's a slip and fall in Oregon, they needed to know who the partner was. And obviously that's not a scalable solution. And so we've programmed the conditional logic and you can, you know, weight it or you can have it all go somewhere, you can have it round robin where essentially the agents, we just want them asking the questions. And then the system ultimately says what's the best firm for us to partner with? Or what's the deal we have with a firm in this state? The challenge is that there's still some discretion for the agent to select the case type. So if an agent doesn't understand our business or doesn't understand the caller and marks the case as premises liability and it turns out it's a work injury, that part we haven't automated. And so there is human error from them selecting the wrong case type because they misunderstood, you know, what the caller is saying. And those are the things you want the quality assurance team to do. We also want them reviewing the catastrophic calls. I mean that's every lawyer who does PI. You know, your top 5% of your cases generate 50% of your revenue. So one of the things that I want our quality assurance team doing is reviewing all the catastrophic calls. And we even want to set up something at some point where some of our most experienced agents start listening as soon as a case gets marked as catastrophic. So that they're almost like a backup. Right? Because we don't have a system where, you know, leads are scored in terms of quality, like all the agents are taking all the leads. But I'd love if when a agent checks catastrophic during the call, someone else is headset would live jump into that call and be able to make sure, okay, this agent's doing a good job. If there's any issues in trying to get this client on board are more kind of seasoned agent could come in and take it over.
- [13:00]
B
What started as a simple question about web form conversions revealed a game changing insight. While inbound calls were converting in the mid-30s, web forms lagged at 25%. James explains how a single operational change implementing immediate outbound dialing drove their conversion rate up to 29%, showing how data driven decisions can transform lead conversion.
- [13:19]
A
Inbound calls are the easiest calls to take because you know, they're calling you, they're looking for you, their phone's ringing. They tend to have the highest conversion rates. If you look at your data, your law firm around the country, I would guess that your inbound call sign up percentage is higher than your web form signup percentage. That's true of most people.
- [13:42]
B
Do you have data like what, what should an inbound. What percentage? Just general average. They should be signing on an inbound call versus like a form.
- [13:51]
A
Yeah. So some of it obviously depends on like if your law firm is taking soft tissue cases or if you're ca, if you're NPI and you know what your kind of threshold is. But what we see for kind of the folks that take soft tissue car accident cases is usually something like one in three. Right? Like one in three leads, you know, as a signup. Now that's using some pre qualification criteria to kind of filter out a little bit of the junk. But on the web form side, like, I'll just share our data, I don't mind. You know, on the web form side we were at something like 25%, whereas on the inbound call side we were like in the mid-30s. So it was like we were seeing about a 10% delta on inbound calls, verse forms. And so what we did was this was a big, like quarterly initiative. And it was a dual project between the software development team and the operations team is we build an outbound dialer so that as soon as a form hits our site, that lead then populates into an agent's screen and begins outbound dialing, you know, from SEO, right. It's all about speed to contact. And so we were thinking like, part of the reason our web form conversion percentage might be lower is that by the time we get the form, we might be forwarding that form to our partner in whatever market that is. Then by the time they call, it's like a whole delay, right? It's like an hour long delay. And so instead, if we could outbound dial as soon as that form comes in, what would that do to our conversion rate? And so this was something where our op, our director of operations, working with our operations coordinator, they were in charge of taking this new piece of software, putting it into production, and then measuring over the course of Two or three months. How did this affect our web form conversion rates? And the thing we saw, which, you know, you play out the tape on how this affects the overall business performance, we moved from 25% to 29%.
- [16:02]
B
Wow.
- [16:03]
A
Conversion rate. Just by building in that outbound dialer.
- [16:06]
B
Right.
- [16:06]
A
We gained 4 percentage points. And I know that might not sound like a ton, but when you're talking about a ton of money being invested in advertising and thousands of leads, it's like 4% moves the needle a ton. Just by building that outbound dialing piece of software and then live transferring the clients to the partner firm we're working with for that case type. And that's the.
- [16:30]
B
That's incredible. That's incredible. And I like how you're taking back control. Re engaging so you can do a live phone call transfer as opposed to the form, because who knows, like, if they have the outbound dialing team.
- [16:42]
A
Yeah, I mean, I. Look, I always say for all the folks that are, you know, managing litigating law firms, building and operating a call center is a business of itself. Right. It's hard. And. And I can only imagine if you're, you know, managing your attorneys in litigation, you're overseeing trials going on, and then you're also simultaneously trying to get the operations and technology right. You know, it's challenging. And so for us, like, we want to make it as easy as possible on the people we work with. And so that ops coordinator function is something that, you know, came out of failure, which was like, we were taking way too long to implement new software changes. When. When they were going in, we were making changes. There was no measurement of, like, what was happening. And finally we were like, okay, we have a bunch of these new projects where we're, like, trying to improve. Let's have, like, one position within the operations function of the call center that's measuring, like, when does this go in? Are all the agents are trained, they're knowing that this change is happening, and then, like, what's the effect of the change and how do we measure it?
- [17:50]
B
And then that allows you for new emerging tech, whether it's AI, you know, we know you're already utilizing AI a ton, but, you know, something emerging to implement it quickly.
- [18:01]
A
Yeah, like, well, I'll give you another one. So we just launched Amazon, has a AI ivr called Lex. So, like, you know, when you call the bank or whoever else and you call and they say, For English, press 1, for Spanish, press 2. For a new client. I've always hated that. I've Always wanted our phones to ring and then them to speak to a real person because I was just afraid like what if somebody gets that in the very beginning and then they just are like, I don't want to deal, I want to speak to a human. And they just hang up and call the next person on Google. Right. But I finally gave in because I will say the reason why you do that is because you have cues. So I could have a team within our call center that's just dealing with current client experience that only gets the current client calls. And I can have a separate team that only does with new signups that only gets the new signup calls. And those people are trained differently and, and obviously by segmenting it, the agents can know what to expect. So there's a lot of like positive efficiencies that come out of doing that. But we finally implemented an AI tool where it's actually sounds like a human. Where it's a human that a human sounding voice that puts people in the English, Spanish new client, current client queue as opposed to like a robot. So it's, it's hard to tell whether it's a human or not.
- [19:24]
B
That's incredible. That's incredible. And then you get cost efficiencies there too because not having to just throw additional labor there.
- [19:32]
A
So we used to have a receptionist queue that then would live transfer it to our actual intake agents and then our intake agents would often live transfer it to a partner firm's intake agents. Think about the client experience they've now gone through speaking to three people. They've gone through telling their story three different times. It's annoying. And so, so the more that you can put yourself in their shoes and say what experience do I actually want? And so that's why I'm so big on. Even with our partner firms, like we have an API connection. We want all the data that our agents get on the phone to be in their system because I don't want them asking the background, what's your email address? What's your address? Like if our agents collected that information. Let's not ask people that a second time.
- [20:19]
B
So, so funny here. You know, you said the bank thing. Every time I get on the bank, I'm like representative, representative, representative. I like just repeat it over and over. So, so this, this individual is like super N. You can't even tell. And it's like the seamless.
- [20:34]
A
Yeah. So it's, it's pretty good. I could show it to you. You ever wonder if they, if they listen to your recordings like, their quality assurance listens to their recordings and just hears you screaming about representative. Because we've had, we've had a bunch of companies I. And I'm super interested in the AI stuff in this space. And we've had a bunch of companies approach us about AI doing more of the intake process. And, you know, they'll set up these tasks and I'll call the number and like, I'm constantly trying to mess up the AI. Like, I'll be like, oh my God, my girlfriend, she just fell in the other room. What do I do? Like, you know, try to, like, take it off its script and like, see how it reacts. And I'm like, oh, yeah, what if they listen to this? They're like, this guy's such an idiot.
- [21:17]
B
Let's face it, being a great lawyer isn't enough to succeed, you need to generate consistent leads. Personal injury is the most saturated niche, competition is fierce, and differentiation is everything. When the deck is stacked against you, you need a comprehensive resource to beat the competition. My latest book, Personal Injury Lawyer Marketing, is your roadmap to consistent leads and exponential growth. It is a masterclass on marketing for personal injury firms. It's packed with actionable strategies on where to invest your marketing dollars for maximum impact. No more guesswork, no more wasted ad spend, just clear, proven methods to transform your firm from good to go. Grab your copy of Personal Injury Lawyer Marketing on Amazon. Link is in the show Notes. If you're seeing a bunch of dropped calls or an increase in call volume, your first instinct might be to throw more bodies at the problem. We've all been there, right? But what James discovered was fascinating. They were overstaffed while still missing calls. The solution? It wasn't what anyone expected. This is the kind of insight that can save you hundreds of thousands of dollars in hiring costs.
- [22:18]
A
This is probably out of all the dumb mistakes we've made in building the call center. This is probably like the biggest blunder. The way our system is set up is like I said, it rings to one agent for two or three rings. If they don't pick up, it rings to a second agent. And these are agents that the software deems are available, right? So these are people on a phone call, but it rings to one agent for two or three rings. Then it rings to another agent for two or three rings. And then it rings to Smith AI, which is our overflow service. If every agent that is available at the time is on a call, right. None of them are available. They're all the system sees. They're all on calls. Then it rings right to Smith AI the overflow service during business hours. Because basic idea like we don't want to miss any calls. Well, we were noticing like every day Smith AI sending this report that like eighty or a hundred calls were going to overflow. And I'm looking at like the expenses of the agents and the staffing. I'm like, dang, man, like we're working so hard to get this call center going. Why are all of these calls going to overflow? And so we looked at it and we're like, Mike's just not have enough staffing. So we went and we hired like 15 to 20 people to sh up these like staffing deficiencies. And then what we realized was, oh no, we actually now are way overstaffed by like, you know, a half dozen agents, maybe even more. Because we made the blunder of thinking that it was an understaffing issue when it was really a scheduling issue. And so what a workforce scheduling person does is they look at a piece of software that looks at your historical call volume. And it's like a factory line. The call software tells you exactly how many reps you need at each 15 minute interval throughout the day. And then you have to be much more dialed on scheduling, including breaks, to make sure that you have the number of agents available. Like give you an example, like 7am to 8am Eastern. We were staffing four agents and we needed seven. And then you also have agents that sometimes call out because they're sick or they're a parent of a child that's sick. Having a full time position that really is just managing like the factory line and the schedules. They're doing it all of a piece of software that actually uses algorithms to tell us exactly how many people we, we need at each 15 minute interval.
- [25:01]
B
That's amazing. And listen, I appreciate your candor, but I gotta tell you, I wouldn't have thought of that either without experiencing that. Literally yesterday I was talking to Harlan Schillinger. I had this like what I thought was like a good idea. I'm like, you know what I'm gonna make? And I think I told you this, James. I was like, I'm gonna make this third shift, this night shift, so that, hey, we're doing SEO while you sleep, while our competitors sleep. And I had this like. He's like, well, why don't they just pay for more on the, on the front end, like, and you could just staff up during your regular hours and deliver it. And I'm like, so it just made no sense at all for my business model. And like I got logic back, you know, but like I just, I like the value prop. And there's these things like you said, you just, you never know in terms of utilization until you experience it.
- [25:48]
A
How we would have caught that problem is looking at occupancy rates. I said earlier in this podcast, occupancy rate measures how often your agents are on the phone relative to the hours that they're logged into your call center software. And so if we were really understaffed, that occupancy rate would have been like 95, 100%. Right. It would have showed hey, when agents are in here, like they are on the, on the phones the entire time. And so you need more agents. And instead our occupancy rate was where it was supposed to be, if not lower. But we weren't looking at the right metric to determine what the problem is. How I see lawyers doing this across the country is it's just too manual. I think it, you know, for 10, 20 years most law firms, even the ones with an intake center were doing their scheduling and based on, you know, spreadsheets and then or you know, just regular payroll scheduling software and like not measuring KPIs. They're not using call center tech. They're kind of just saying, oh, we're graded intake. And it's like, what's your occupancy rate? I don't know. What's your after call work time? I don't know. Like in every other industry there are KPIs for how to run an efficient call center. But most law firms don't have the tech stack that actually informs the management of their call center KPIs. They're just kind of like, oh yeah, we, we're great at intake, we sign all the cases we want. It's like eh, no, you don't like, what's your abandon rate? Oh, we don't like the way you measure whether you're picking up calls fast is abandoned rate after 10 seconds. Right. That's a standard call center benchmark. How many people who call you wait for 10 seconds on the line and then hang up. But you need a piece of software or the technology that's going to like feed back your supervisors that data so you can measure it.
- [27:51]
B
Let me play. Maybe on the firm side, some of the individuals, like I consider you very tech savvy, tech embracing. And like you take something like Salesforce on its own. You know, you've got this integration to Amazon Connect, you've got this other AI based tool. If you're going to make a decision to use what I call Salesforce, like the big boy CRM, I mean, are you hiring a dedicated sales enablement type tech person to run that? Like, like what goes into making a decision to, to go all in? Even on the tech side here we.
- [28:28]
A
Have an internal dev team. We built out Salesforce and I used a consulting agency and I paid something like $200,000 in hourly fees for like 200 bucks an hour or two, 50 bucks an hour. And they weren't bad guys, right? But like, I just couldn't understand the issues because as much as I'm tech forward and believe it's an important part of how this industry is going to mature, you know, I'm not a software engineer. And so I got so frustrated, I'm like screaming. I'm like, these guys, like, they're just billing me like this is never going to get done. And I had to like mentally come to the realization that this is an ongoing thing. I would pay this consultant, the Salesforce consultant forever. Like, like it literally the bills would never end. And so it was like, okay, at some point I need to bring in like a tech leader, like a software developer, and also bring in a Salesforce admin, which isn't quite a developer, right? They don't code, but they're well versed in like building what are called flows in Salesforce. And so, you know, we notice this when we work with law firms around the country is we have to set up that ADI connection which allows us to feed data right into their system and then a feedback loop that feeds that data back into our system system like Amazon Connect or like Salesforce. These are like canvases, right? Like these do not come. These are not out of the box products like Firevine or Clio is. You need to code these and build them for your company.
- [30:05]
B
Right? This next part, this is like the masterclass in choosing your tech. And here's why it matters. James gets real about when to go with something like, like filevine versus making a huge Salesforce investment. Look, I've been there. Making these tech decisions isn't easy. But he breaks down exactly what you need to think about based on where your firm is at.
- [30:21]
A
I think that you have to be going into a Salesforce or Litify build out with your eyes wide open. Like you have to really be willing to invest hundreds of thousands of dollars between developers, Salesforce admins and building out this tech. And I know that it's going to take a year, but I'm going to come out of it with a customizable system where I can integrate the tools I want and the AI solutions I want and I'm not stuck with someone else's product. For a small or medium sized firm, you know, filevine for example, or any solution that has an out of the box file cabinet with a layer above it that is a CRM layer that plugs into your file cabinet, I think is a great option. I am seeing more firms, especially the ones we work with, that are adding that CRM layer like lead docket on top of filevine. And I will say, like from a basics perspective, that's super important because the only thing that goes into filevine is your actual cases. But you need to be able to measure your data about leads. And so you need a different product ideally that plugs into your case management software that manages your data around leads. And you know, you're tracking, like we talked about earlier, what percentage of leads result in assigned case. Of the ones that are declined, what are the declined reasons? Are they declined for coverage? They decline for liability? Are they declined for no contact? Right. What's your contact rate? Like how many leads out of the ones you get do you actually get a hold of? A lot of people are like, oh yeah, we get a hold of all of them. It's like no, nobody gets a hold of all of them. Right. Like you get a hold of a certain percentage and then of those percentage of, of leads you get a hold of, there's a wanted rate which is the ones you want to sign. Then there's a conversion rate which is out of the ones you want to sign. How many of them do you actually get? And so I think in terms of like sequencing of, of sophistication, the first step is to I think have a CRM at all and measure your conversion rate. Your wanted percentage, your declined reasons can measure different sources and, and what, how many leads and how many cases you're getting from those different sources. I think that's kind of iteration one and then if you feel like you've mastered that, but you really want to get to the next level and you want to be able to build your own tools and not be constrained by the functionality that are in those out of the box solutions. I think that's when you take a leap and you say, okay, I'm going to go into a salesforce or litify build out, eyes wide open. Because I want to be like one of the most tech forward players in the space.
- [33:17]
B
Crystal ball. If you had to like Think like where your sales team and intakes going for the future. You know, if we do another podcast, maybe another 10 or 12 months, like just to see kind of where your theory goes. And then two, I know you have a different model and you're looking for partners all around the country. You know, is there particular markets that you're looking for partners to work with you? Yeah. So those two questions, the crystal ball and then partners. Cool.
- [33:45]
A
So the crystal ball is the big question is how far are we from, you know, autonomous AI agents? I'm not sure, maybe two or three years. I don't think we're that far. I think that there's going to be tools that kind of come in as hybrids. So for example, instead of our intake supervisors answering reps questions on, hey, I have Jane Smith on the line, like they're calling about this. What do I do? It's like you should probably have a chat GPT type solution that has all of your prior call center transcripts. And you're asking like, we could probably build this today. Like we're asking it, hey, like this is what's going on, what do I do? And you get that same feedback that you would get from a supervisor, but instead from an LLM. The other thing that I think is coming very soon, and we've spoke to a bunch of folks about this, is the agents actually not going through the survey and filling out the answers themselves. Imagine a world where your call center agent can just talk and all the pick lists and all the Dropbox are just getting filled in by an AI tool that fills that information in as the agent's talking. If you think about if they could only focus on being empathetic and walking through the prompts and everything else could be automated, that would be an improvement. And I think that's like probably a next 12 months thing. Like we're looking into different options that potentially do this now in terms of the partners. So we're always looking for new partners across every market. Specifically if you're able to do specialty areas like, you know, med mouth, nursing home, birth injury workers, comp, Social Security, those are great. Tons of law firms across the country do auto accidents and we have the privilege of working with a lot of them. And, and we certainly are always testing out new partners. So feel free to, to send me an email@james.helmopdoglaw.com I'd be happy to speak to you and see if we could be a fit. But I love firms that really say like, this is our niche and we're badasses in this one specific case type. And those are kind of the firms that we're optimizing towards.
- [36:10]
B
That wraps up this episode of PIM with James Helm of Top Dog Law. You can learn more about him, grab his contact info and the resources mentioned today in the show. Notes. While you're there, pick up a copy of my new book, Personal Injury Lawyer Marketing from Good to Go. And if you like what you hear, help your boy out. Leave me a five star review on Apple or Spotify. All right, everybody, thanks for hanging out. See you next time I'm out.