James Helm:
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.
Chris Dreyer:
Real numbers and real systems get real results. Stop guessing and learn from one of the fastest growing intake teams, TopDog 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 TopDog does, start with last week's episode with Yani 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.
James Helm:
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 want 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 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.
Chris Dreyer:
Your team's evolved. So now I think today you've even got an outbound team that's really making sure nothing slips through the cracks. How has the team evolved since you started?
James Helm:
Maybe it would be helpful to outline 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 managers that sit atop of them. So we try to keep 7 to 10 agents under one manager, one intake supervisor, and then we have someone at the top that manages the agent side. So it's kind of like a pyramid. So you have 32 agents from the bottom and then you have a handful of 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 an 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, an operations manager, and then we have a workforce specialist which is only in charge of scheduling for all the agents.
Chris Dreyer:
Let's start with the training side. Are they doing a bootcamp? What kind of things are you doing? What's involved there?
James Helm:
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 workday. 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, they're building out TopDog university, TopDog 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 will 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."
Chris Dreyer:
Have you 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 your firm is phenomenal at KPIs. What's some of the main reasons why they just don't work out?
James Helm:
I think 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. 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 probably unrealistic. And so we see that turnover for a couple of different reasons.
First is they're just below their benchmarks on KPIs and like you said, we're trying to have less subjectivity and more objectivity. So an example is missed calls. We try to set a benchmark of 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 going to voicemail. I'm just saying the first agent that the call rang to didn't pick up, we measure that. 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 for your mom's house sometimes. But in this role we just need that controlled. And so to get back to your question, missed calls is probably one factor why an agent wouldn't work out for us.
Another factor is measuring the amount of calls they take that result in signed cases. Obviously there's some type of benchmark there. If you're seeing one agent who's taking 3X the amount of another agent or one of the agent is kind of below the minimum threshold that we set, that's another one.
Another reason might be that their empathy on the phone, it's less about them hitting the missed call or signed case goals and it's more just about 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? 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.
Chris Dreyer:
James walks us through how artificial intelligence is transforming intake quality control. He explains their use of 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.
James Helm:
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, 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, 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, that's challenging.
So there's actually good AI tools that can flag calls. So Amazon has a product called Contact Lens. There's MeetRecord, 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 tone, so hostility. The other thing is erroring out reps. So for us, we're working with partner firms all over the US. 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 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 big iteration we went through when we switched to Amazon Connect. Before it was like our staff had to remember the decision tree of 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 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 a 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 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, 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. Because we don't have a system where leads are scored in terms of quality, all the agents are taking all the leads. But I'd love if when a agent checks catastrophic during the call, someone else's 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, our more kind of seasoned agent could come in and take it over.
Chris Dreyer:
What started as a simple question about web from conversions revealed a game changing insight while inbound calls were converting into 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.
James Helm:
Inbound calls are the easiest calls to take because 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 of your law firm around the country I would guess that your inbound calls signup percentage is higher than your web form signup percentage. That's true of most people.
Chris Dreyer:
Do you have data, what should an inbound, what percentage, just general average they should be signing on an inbound call versus a form?
James Helm:
Yeah. So some of it obviously depends on if your law firm is taking soft tissue cases or if you're NPI and what your kind of threshold is. But what we see for the folks that take soft tissue car accident cases is usually something like one in three, one in three leads is a signup. Now that's using some pre-qualification criteria to filter out a little bit of the junk.
I'll just share our data, I don't mind. On the web form side, we were at something like 25%, whereas on the inbound call side, we were 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 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, it's all about speed to contact. And so we were thinking 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. 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 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 play out the tape on how this affects the overall business performance, we moved from 25% to 29%-
Chris Dreyer:
Wow.
James Helm:
... conversion rate just by building in that outbound dialer. We gained four 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 state.
Chris Dreyer:
That's incredible. That's incredible. And I like how you're taking back control, reengaging so you can do a live phone call transfer as opposed to the form, because who knows if they have the outbound dialing team.
James Helm:
Yeah. I mean, look, I always say for all the folks that are managing litigating law firms, building and operating a call center is a business of itself. It's hard. And I can only imagine if you're 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. It's challenging. And so for us, we want to make it as easy as possible and the people we work with. And so that ops coordinator function is something that came out of failure, which was like we were taking way too long to implement new software changes. When we were making changes there was no measurement of what was happening. And finally we were like, okay, we have a bunch of these new projects where we're trying to improve, let's have one position within the operations function of the call center that's measuring when does this go in? All the agents are trained, they're knowing that this change is happening, and then what's the effect of the change and how do we measure it?
Chris Dreyer:
And then that allows you for new emerging tech, whether it's AI, we know you're already utilizing AI a ton, but something emerging to implement it quickly.
James Helm:
Yeah. well, I'll give you another one. So we just launched, Amazon has a AI IVR called Lex. So, you know when you call the bank or whoever else and you call and they say, "For English, press one. For Spanish, press two. 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, what if somebody gets that in the very beginning and then they just, they're 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.
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 obviously by segmenting it the agents can know what to expect. So there's a lot of positive efficiencies that come out of doing that.
But we finally implemented an AI tool where it actually sounds like a human, where it's a human sounding voice that puts people in the English, Spanish, new client, current client queue as opposed to a robot. So it's hard to tell whether it's a human or not.
Chris Dreyer:
That's incredible. That's incredible. And then you get cost efficiencies there too because not having to just throw additional labor there.
James Helm:
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 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 the more that you can put yourself in their shoes and say, what experience do I actually want? So that's why I'm so big on even with our partner firms, 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? If our agents collected that information, let's not ask people that a second time.
Chris Dreyer:
So funny here, you said the bank thing. Every time I get on the bank, I'm like representative, representative, representative. I just repeat it over and over. So this individual is super... You can't even tell and it's the seamless?
James Helm:
Yeah. It's pretty good. I could show it to you. You ever wonder if they listen to your recordings, their quality assurance listens to their recordings and just hears you screaming about representative? Because we've had a bunch of companies, and I'm super interested in the AI stuff in this space, we've had a bunch of companies approach us about AI doing more of the intake process, and they'll set up these tests and I'll call the number and I'm constantly trying to mess up the AI. I'll be like, "Oh my God, my girlfriend, she just fell in the other room. What do I do?" Try to take it off its script and see how it reacts. And I'm like, oh man, what did they listen to this? And they're like, this guy is such an idiot.
Chris Dreyer:
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If you're seeing a bunch of drop calls or an increase in call volume, your first instinct might be to throw more bodies at the problem. We've all been there. 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.
James Helm:
This is probably out of all the dumb mistakes we've made in building the call center, this is probably 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, so these aren't 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, none of them are available, the system sees, they're all on calls, then it rings right to Smith.ai, the overflow service during business hours. Because the basic idea, we don't want to miss any calls.
Well, we were noticing every day Smith.ai's sending this report that 80 or 100 calls we're going to overflow. And I'm looking at the expenses of the agents and the staffing. I'm like, man, 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, we must just not having enough staffing. So we went and we hired 15 to 20 people to sure up these staffing deficiencies. And then what we realized was, oh no, we actually now are way overstaffed by a half dozen agents, maybe even more, because we made the blunder of thinking that it was an under-staffing 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. Give you an example, like 7:00 AM to 8:00 AM 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 the factory line and the schedules, they're doing it off of a piece of software that actually uses algorithms to tell us exactly how many people we need at each 15 minute interval.
Chris Dreyer:
That's amazing. And listen, I appreciate your candor. But I got to tell you, I wouldn't have thought of that either without experiencing that. Literally yesterday I was talking to Harlan Schillinger. I had this what I thought was a good idea. I'm like, "You know what I'm going to make," and I think I told you this, James, I was like, "I'm going to make this third shift, this night shift so that, hey, we're doing SEO while you sleep, while our competitors sleep." He's like, "Well, why don't they just pay for more on the front end and you could just staff up during your regular hours and deliver it?" So it just made no sense at all for my business model. I got logic back... But I like the value prop and there's these things, like you said, you never know in terms of utilization until you experience it.
James Helm:
How we would've 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've been like 95, 100%. It would've showed, "Hey, when agents are in here, they are 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 for 10, 20 years most law firms, even the ones with an intake center, were doing their scheduling based on spreadsheets or just regular payroll scheduling software and not measuring KPIs, they're not using call center tech. They're kind of just saying, "Oh, we're great at 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."
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're great at intake. We sign all the cases we want." And it's like, "No, you don't. What's your abandon rate?" "Oh, we don't..." The way you measure whether you're picking up calls fast is abandon rate after 10 seconds, 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 feed back your supervisors that data so you can measure it.
Chris Dreyer:
Let me play maybe on the firm side some of the individuals, I consider you very tech-savvy, tech-embracing, and you take something like Salesforce on its own. You've got this integration, 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? What goes into making a decision to go all in? Even on the tech side here,
James Helm:
We 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 200 bucks an hour or 250 bucks an hour, and they weren't bad guys. But 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, I'm not a software engineer. And so I got so frustrated and screaming, I'm like, "These guys, they're just billing me. This is never going to get done." And I had to mentally come to the realization that this isn't ongoing thing. I would pay this consultant, the Salesforce consultant forever. Literally the bills would never end. And so it was like, okay, at some point I need to bring in a tech leader, like a software developer and also bring in a Salesforce admin. Which isn't quite a developer, they don't code, but they're well versed in building what are called flows in Salesforce.
And so we noticed this when we work with law firms around the is we have to set up that API 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 Salesforce, these are like Canvases, these are not out of the box products like Filevine or Clio is. You need to code these and build them for your company,
Chris Dreyer:
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 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.
James Helm:
I think that you have to be going into a Salesforce or Litify build out with your eyes wide open. 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, 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 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'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? Are they declined for liability? Are they declined for no contact? What's your contact rate? 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, nope, nobody gets a hold of all of them. You get a hold of a certain percentage. And then of those percentage 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 sequencing 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 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 one of the most tech forward players in the space.
Chris Dreyer:
Crystal ball, if you had to think where your sales team and intakes going for the future, if we do another podcast, maybe another 10 or 12 months just to see where your theory goes. And then, two, I know you have a different model and you're looking for partners all around the country. 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.
James Helm:
Cool. So the crystal ball, the big question is how far are we from 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. They're calling about this, what do I do?" It's like you should probably have a ChatGPT type solution that has all of your prior call center transcripts and, we could probably build this today, we're asking it, "Hey, 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 themself. Imagine a world where your call center agent can just talk and all the pick lists and all the drop box are just getting filled in by an AI tool that fills that information in as the agent's talking. If you think about it, 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 probably a next 12 months thing. 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 med mal, 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 we certainly are always testing out new partners. So feel free to send me an email at james.helm@topdoglaw.com, I'd be happy to speak to you and see if we could be a fit. But I love firms that really say, "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.
Chris Dreyer:
That wraps up this episode of PIM with James Helm of TopDog 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 GOAT. 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.
