Using AI to Improve and Optimize Client Acquisition

Discover the ways AI is changing how financial advisors identify and connect with prospective clients. Cutting-edge AI tools are now available to help advisors find, qualify, and close more leads. AI tools can help you build lists in minutes, filtering with hundreds of attributes and wealth trigger events. Want to target executives at companies in a specific zip code radius who have had a liquidity event in the last 6 months and attended the same college or university as you? No problem! Then prioritize these leads based on probability to close or on your ability to be introduced by a mutual connection. You can even use it to enrich the information you have on existing clients to enable better segmentation and alerts for trigger events. The possibilities represent an exciting new opportunity for firms looking to grow!


Transcription:

Matt Ackermann (00:10):

All right, well welcome to the next session. We're talking a little about AI and marketing, but more from that perspective of using AI to really improve and optimize the entire picture of client acquisition. It's so great to have everybody here in this room. The pattern of this room is so interesting. We were just saying we feel like we're in a press conference, so it's very Belichick. We're onto the Bengals. Next question, then we're onto the Bengals. But no, no, really excited to have this amazing panel up here with me today. It's going to be really a lot of fun and very engaging. I hope if you guys have questions throughout, raise your hand. We're going to come to you and answer the questions hopefully as they come up with a lot of the kind of real time information going on here. It's so funny, guys.

(00:59):

I was just thinking about this this morning. If I dated back 30 years, it was my first engagement with the internet. It was 1994. I'm a freshman at Seton Hall University. It's my first email address and I was very excited to go into a chat room to learn about who going to be the starting pitchers for the St. Louis Cardinals. They had brothers, Andy and Alan Benni. Anybody else wants to discuss this? We'll get together later. We'll talk about grunge in the nineties as well. It's going to be a lot of fun, but so much, I mean, think about how much has evolved in 30 years where now we're talking about AI. It's been an incredible conference, hasn't it? And we have an amazing panel today. I was just at another conference in California where the conversation with CMOs and it was all about optimizing growth and really it comes down to this idea of lead generation and the CMOs are scared out of their mind right now because they don't know how they're going to keep up with this, how they're going to maintain and manage it, how they're going to afford it.

(02:03):

And I think it's going to be very, very interesting. Oh, I should have introduced myself. I'm Matt Ackermann. I am the Chief Content Officer at Integrated Partners. My seven year old's very impressed with this title. It's the same one that HHH has at the WWE. So I've already won the 7-year-old demographic. I tell everybody I had the fun job any place I go to. Before joining integrated, I was at Investment News where I led all of our multimedia initiatives and before that I actually worked here with financial planning. So I've really been really lucky throughout my career to work and do some really incredible and fun things throughout this. And I'm just going to go down and have Ian and Wilbur introduce themselves. Talk a little bit about what you guys are up to because it is absolutely incredible in mind blowing. So

Ian Karnell (02:46):

Yeah. Hi, my name is Ian Carnell. My twin brother Jeremy Carnell was speaking on the panel yesterday, so I'm wearing almost exactly the same thing.

Matt Ackermann (02:55):

Do you guys do that on purpose?

Ian Karnell (02:57):

No, actually he and I have these conversations. I kid you not before we show up at events, what are you wearing? Because the last thing as an identical twin, you want to show up as looking like identical twins. So anyway,

Matt Ackermann (03:09):

No one wants to do that.

Ian Karnell (03:10):

No one wants to do that. Yeah. My twin brother and I have been entrepreneurial wing men our entire lives. Our very first company was a digital agency in Boston that we scaled to, but we had about 400 employees worldwide, managing about a half billion in media. State Street was our first big investor. It's one of the, this is when David Sina was the CEO. It's the company that launched us down our financial services path and our FinTech path. Up until recently, we sold our last startup two years ago to Investnet. We had built a company by the name of Tru Lytics. It was a practice management tool. We were helping financial advisory firms measure the intrinsic value of their practice across 150 different key performance indicators across a multitude of different real-time pure benchmarks. We had 40,000 advisors on platform when we sold it to in Investnet a little bit less than two years ago.

(04:00):

My brother's still there running data solutions. I left about just under a year ago to launch I think what will be likely my last startup of about a half dozen and a company by the name of VastAssembly.ai, our very first product called Vast advisor.ai, very specifically laser targeted, focusing on solving this front office problem around how do we help firms, how do we help advisory firms build programmatic, repeatable, scalable systems that drive organic growth. While at Tru Lytics, because we were measuring the intrinsic value impact of those firms that had that versus those firms that didn't, we saw a two x increase in their revenue multiple or EBITDA multiple as a result. I mean they were getting the premium multiples. There are a multitude of other factors that drove that, but that had a huge impact on valuation. And so it's an important problem to solve. I know for in investnet it's one of their top three initiatives going into next year. They plan to, they really want to make some investments and solve for how can we help advisors drive organic growth through their practices. And I'm doing that with AI.

Matt Ackermann (05:10):

Wilbur

Wilbur Swan (05:12):

Yeah. Hi everybody. Wilbur Swan. Very similar focus as to what we're up to the United, it'll be a great back and forth in terms of the different ways our companies are approaching this challenge. My background is like Ian, I've been doing entrepreneurship at work for a long time. Sold one of those companies to Thomson Reuters. That particular company was helping companies build their own private version of LinkedIn, and this was back when LinkedIn was in its infancy. I spent about 10 years then at Thomson Reuters working on big data and AI helping the company begin to, similar to the data session earlier, organize its data so it'd be easier to apply artificial intelligence to it. And then got an interesting conversation with the folks at Fidelity about going back to the entrepreneur world, how could we apply some of that to the challenges of advisors?

(06:10):

So like Ian, we saw this wave at Fidelity that growth was going to get increasingly challenging for advisors due to a number of factors I'm sure we'll dive into today and that it would be a really interesting business for Fidelity to take a run at. So our business catch light is part of Fidelity Labs fully incubated within infidelity. The advantage of that hybrid model and pulling down my background is we're doing a lot of work on predictive analytics. And the beauty of doing it within the Fidelity ecosystem is that I think you'll find within all these startups, they really come down to the quality of their data to train their models. So the more data they have and the higher quality of the data, the more predictive their models will be. And that's really what I saw as the advantage of doing that with infidelity. So I'm sure we'll get into all this. It'll be super fun.

Matt Ackermann (06:59):

Absolutely. And that's what we want to do is create something that's engaging. I started by talking about, I had my first email address 30 years ago. Think about how far we've come with AI in a short period of time. I can still remember my first interaction with ai. I was writing a piece of content and I was like, alright, let's test out ChatGPT, take this piece of content and the same information and give it to me in the form of a children's nursery rhyme. Give it to me in the form of a wrap by the wutang clan, give it to me in the form of an Edgar Allen poem. And it was incredible how quickly it could churn this out and it would feel like that. Now I need to know you guys, what was your first interaction with AI?

Ian Karnell (07:43):

Yeah, so I was at Investnet at this time. I was charged with a number of AI based initiatives very early on. Worked with Danny Fava, who's now the chief strategy officer Carson. Her and I stood up the first AI governance committee at investnet and we were working on a number of different AI use cases. One of the big projects I was charged with leading at investnet was an advisor match solution. So from a lead gen perspective, how do we take the 35% of Americans every year? How do we target them? There's 25 to 45 trillion in assets there. How do we match them with the right advisor? Again, it was part of an initiative at investment to help drive organic growth there. And I remember logging into ChatGPT for the very first time. This was my first experience and I began to ask it questions about a match algorithm framework and different variables that we'd want to consider. And I remember getting to this end of this and I was just blown away each answer. And this was the first version of ChatGPT out there. And I remember at the end I'm like, write me the algorithm. I had no idea what it was going to do and it spawned that window and in real time, Python starts to write the code. And at that very moment, I knew I could no longer work for Investnet. I needed to launch my next startup immediately. So that was my first experience. That's awesome.

Matt Ackermann (09:05):

Wilbur, how about you?

Wilbur Swan (09:08):

So this goes back a ways, but when I joined Thomson Reuters as part of that acquisition, I started working with the data scientists there and Thomson Reuters manages petabytes of data and one of the big challenges you get into within our field, which is understanding households and consumers and demographics is this buried challenge under it all of is person A that you're seeing in this dataset the same as person B in this other dataset. And the data scientists had recently gotten a patent, this is probably like 2008 on any disambiguation machine learned model that was actually figuring that out. I just thought that was fascinating back at that point in time. But I will say that gets to the core of, again, all of this is the quality of the data because if it's garbage in, you end up with garbage out, unfortunately.

Ian Karnell (09:57):

so true.

Matt Ackermann (09:59):

Absolutely true. It's so interesting. Like I said, I began the week running a panel talking about that struggle of organic growth and it is a true struggle for financial advisors. I think the data indicates that the average advisor's organic growth is less than 2% and they're like, how do we make this work better? But the idea of leveraging AI to really improve it and optimize it also frightens those CMOs I was talking about in the other think tank. So let's start from there. Why do advisors struggle so much when it comes to optimizing and ultimately getting that organic growth and ultimately, how can AI help to really reshape this story?

Ian Karnell (10:36):

Yeah, I think Michael kind of addressed a part of this morning when he was like, Hey, look, especially smaller firms, solo advisors, not really interested in programmatic growth. I tend to disagree. I think my time as one of the co-founders of Tru Lytics and having worked and with our practice management tool and looking across 40,000 different advisory firms and looking at all of the different KPIs that there, there's a new generation of advisors that are coming in replacing the advisors that are aging out. The first generation of financial advisors with a completely different mindset. They're not thinking, well, look, it's easy to build a hundred billion book. I'm going to build a lifestyle business. They're not thinking that way. I mean, we saw that with the panel, one of the panels yesterday, that young advisor that sat on the panel and he's the profile of the new advisors that are coming in and starting their RIAs and very tech savvy, very data savvy, and looking at how do I systematize the growth of my practice?

(11:40):

How do I benchmark that? How do I leverage tools to help me scale? There are trillions of dollars in assets at play, especially for new advisors who don't have the scale of a multi-billion dollar RIA or PE backed rollup to go out and acquire AUM. They need to be thoughtful and programmatic in the way that they're going to market. And so I think they're thinking differently about it. I think traditionally advisors have been, they see that 2% organic growth rate because they built a lifestyle business and it's word of mouth, it's traditional tactics going to networking events, and they haven't thought about technology or processes or systematizing their practice in a way that can create repeatable, scalable, organic growth. And I just think it's a generational thing. I think the second generation are thinking differently about it. I think advisors kind of in the mid stage of their career are being forced now to begin to think differently about it if they want to remain competitive. So I think that's why.

Matt Ackermann (12:41):

What do you think is that why kind of organic growth advisors can sometimes struggle with it there?

Wilbur Swan (12:49):

Maybe to ask a question of the audience of the folks in the room who are working with advisors under a billion in AUM, so maybe 30%, and then how many are working with larger firms over a billion say about the same? Yeah, so even split. Yeah, I mean I think advisors have had, when we look at it and when Fidelity looks at it, advisors have had a fantastic run the last 10 years. I mean the market's appreciated. The boomers are still at a point of not yet full on decumulation. Some of them have still been accumulating and there's been just a great business you could build on that with almost no effort. I think what's going to happen over the next 10, 15, 20 years is radically different. There's going to be transfer of wealth that we've all been talking about. I think boomers will be decumulating, which will make, even if you were an advisor who has an average client base of maybe age 60, the headwinds to your growth will just be mounting as a result of that. So I think you either decide whether you want to be in a lifestyle business and accept that fact or get better at growth. And I think what we're trying to do with kely is just make those tools easier for advisors to use. Because I think if you looked at the front office over the last 10 years, there weren't many tools available that advisors really, I mean the highest adoption rate according to the T three studies was probably 20, 30% maybe, which is unusual when CRM itself was 80, 90% adoption.

(14:25):

So I think what our approach has been, let's meet advisors where they are. Let's do a lot with integrations. So we're doing a lot with Redtail, a lot with Wealth box, a lot with Salesforce, get that data embedded into their process and then make it easy for advisors to act on it in the environments in which they're comfortable. And then I think advisors are great at a referral based kind of semi-warm sales process. We're trying to think how do we make again, how do we meet them where they are? How do we make all of this so it's like a semi-warm process.

(15:06):

I thought Michael's presentation was perfect though. It really teed up this session. I think ironically, this is the most important session of the whole two days conference. This right here, congratulations, humbly you're here. This is the one that'll go down in the history books. I thought he teed it up really well. The two big opportunities for AI are meeting summarization. So you've seen all the startups here that are focused on it, and then this world of marketing and sales and business development I think is a huge opportunity for ai. I think he was positioning it as maybe only 20% of the smaller advisors are really interested in that. I think that'll increase over time. But I think what is really going on is that the bigger firms that are backed are getting super focused. And this was probably the folks who were at your panel are super focused on marketing and growth and getting very, very organized about it.

(15:55):

And I think those are the larger RIAs, the ones who are doing m and a all the way up to the big shops themselves. Like he was saying, larger firms aren't doing these types of analytics. I will say, Michael, that's not true. I mean we work very closely with Fidelity in terms of how they market and use analytics to market, and this is something that is very embedded in that business. So also he said that advisors don't need to depersonalize. I think that's interesting. I disagree. I think they're great at personalizing when they're engaging with clients, but what they need to be thinking about is how do they personalize when they market? The greatest tragedy is that two to 3% conversion rate on some of the more scaled lead gen programs. And I think when you look at what's happening there, they just don't know the prospect very well. So what they're doing is they're going to a 35-year-old Henry and saying, we're ready to help you retire. And the guy's or the woman's like, I'm not, I'm anywhere near retirement. Why am I trying to market in this way?

Ian Karnell (17:02):

Well, I think the marketing tool set is radically changing. We talked about.

(17:09):

One of the big headlines I think that comes out of at least this year next year with respect to AI and growth in the advisory space is the unit economic of driving growth. I think that's a huge headline. I think when you look at how many advisors here are actually implementing proactive go-to market strategies that are in market today, either utilizing paid traffic campaigns like CPC campaigns to your sites, email outbound, how many are doing that programmatic? How many are measuring cost of acquisition CAC? Have that data? Yeah, some possibly. Okay, great. So when you look at the fully loaded cost of acquiring a customer, you look at some of the averages out there, it's three to $5,000 depending on the type of investor, their AUM, some other factors, and you look at what AI automations are beginning to do to drive that cost through the ground.

(18:14):

I'm talking about like a 30 x reduction in those costs and what that means for advisors for the first time to begin to look at, well, you could be buying smart asset leads for 200 bucks a lead, but it's still going to be a fully loaded conversion cost of 2 to $3,000 per investor who's going to be coming on board with you with their AUM. But now you can implement AI processes that enable you to have almost relationship asymetry as you're going to market, as you're building content, as you're engaging these leads, utilizing GPT powered workflows that have end-to-end memory of every interaction that lead has with your firm from the dwell time that lead spends on different pages of your websites to how many emails. It's open to the chat conversations, the omnichannel chat conversations it's having through your web chat widget, through social, through SMS through voice and understanding very specifically what interests you, where you are at and creating bespoke one-to-one content with real objectives to warm you up, to convert, to qualify at scale.

(19:28):

That's incredible, right? And so now you're looking at that employed, you're looking at a conversion cost of 500 to a $1000 of 35% of Americans every single year looking for a financial advisor. It's 90 million Americans and it's costing you 500 to a thousand dollars to acquire that AUM. Why wouldn't you be in that space? It's been cost prohibitive in the past. When you look at the fully loaded cost, you would need an agency, you would need a series of contractors. Hell, if you have Salesforce, you need three consultants just to get that to work. Love Salesforce. By the way, love Salesforce. We're working to integrate with Salesforce. All of the integrations are important. That's really important, but it's expensive. It's expensive. And so if you can remove those barriers, those friction points and radically reduce those costs, then the game changes entirely. Because the other thing with consolidation, when we look at a market five, 10 years out, there's a massive consolidation going on in this space right now.

(20:28):

PE companies love free cash flow. They're buying up as much AUM as possible. We've witnessed, I've had a front row seat to this trend over the last few years that's not changing anytime soon. So new entrants to the space, new advisors growing RIAs are going to have to be a lot more aggressive with the tools that they have, knowing that they're competing against much bigger firms with much bigger resources. Thankfully, the tools are now available, the costs have radically reduced and you can be smart about utilizing the same tools they have out linking them, being smarter about your strategies and not have to retain a massive agency or consultants to get these things stood up and employed for you.

Matt Ackermann (21:10):

I want to come to you in a word you use and you just use the two and all about kind of this personalization key that this affords you this opportunity. But first I do want to ask all you guys here, and I think it goes back to that question of scalability. How many folks you hear that word scalability and think opportunity, you get excited versus the other side, which is you hear scalability and you're like, gosh, that sounds overwhelming. Is it an opportunity for your business, your scalability? It's an opportunity. Raise your hand. Look at that. See, you see in the right love, you're in the right hand, you're in the right. That's what this is exactly. Because you sit there and there are firms, you do a SWOT analysis with them and they put all this stuff, marketing they put down there, they put scalability down there and threat.

(21:52):

But this whole group is saying, this is an opportunity right now is an opportunity and the personalization's the key to this. I think about that, and I've been a nerd about data and open rates for a while before this, I was really key both at financial planning investment news as we looked at what was the open rate on that email, where did it spike? And when media outlets an open rate of anywhere in that 4 or 5%, you felt like, man, this was a great day. Now as I work at advisory firms, open rates that aren't in the fifties, there's a problem here. But if you can personalize that information and personalize marketing, we can turn this on its ear here. So Wilbur, tell me, talk to me about personalization and AI and ultimately how this is going to change the game when it comes to marketing.

Wilbur Swan (22:40):

Yeah, well, I agree with all the themes have been brought up in terms of the potential of personalization. I think what we are working on is how do you take all this great data that you can have available to you about a prospect and use that to inform and tailor the types of things that you can get out of the large language models. There are a couple of angles that Fidelity Labs and catch later are approaching this on is one, whether it's one-to-one interactions, or could you use these types of solutions to look at all the leads that you have at your disposal and form AI informed segmentation of those leads, understand which clusters are in there. You understand that group of people all have a common interest and a common profile. Can you then use the large managed models to generate content to reach out to them? Can you use some of these models to then tap into, there's a lot of great content that's out there. I mean, some of you might work with FMG Suite, we have a partnership with them. They have a huge content library.

Matt Ackermann (23:46):

Snappy Kraken,

Wilbur Swan (23:47):

Snappy Kraken. We have partnership with them. Amazing. Yeah, I think the key is how do you make it easy for an advisor to think about how does this prospect match to a great piece of content that could send to that person, whether it's large language model generated or pulled from a library, and again, by these matching models so that it becomes a smooth, seamless process and easy to deliver. Again, either one-to-one or at scale so that the sales process becomes kind of fun and engaging rather than laborious. And I've got to sludge through all of this kind of hours by hours of outreach to prospects. So if you can, basically what we're doing back to Ian's point is you're changing a funnel that looks like this to something that looks like this, and you're then increasing the engagement in each step. So you're getting more at the top of the funnel and greater throughput at the bottom of the funnel.

Matt Ackermann (24:35):

More at bats, you get more at bats, you get more hits.

Ian Karnell (24:37):

Well, and we're talking about sales funnel, but let's talk about the lead nurturing funnel. I think another big headline here with AI, with intelligent practical AI automations deployed from a lead nurturing use case is a massive opportunity. Yesterday there were a couple of panels where they were talking about relatively binary outcome that most advisors have when it comes to growth. You're either ready to invest, you're looking for a financial advisor, you're ready to go, yes now or you're not. And how often, how many advisors today have a lead nurturing program automated in market today? A handful. Good for you, a handful, but a small percentage of this audience and lead nurturing meaning, alright, well that person isn't ready, that doesn't mean they're not going to be ready down the road. It doesn't mean that you shouldn't continue to invest, but the gating factor has been the cost of how you could invest in the past in nurturing that lead even through workflows, automated workflows through HubSpot or Salesforce.

(25:42):

There's a cost, there's a fully loaded upfront cost of creating content upfront that you would have to then if you're smart, tailor to different segments and have that implement over time. Now we have AI deployed in a way that can do forever follow-ups with leads through the channels that they prefer with no prescriptive content whatsoever, but content generated off of complete transparency into what they've interacted with, how they've answered questions. Again, content that they've consumed on your site and engagement rates based on SMS outreach, email outreach, social outreach or otherwise. And you can set the cadence of that, you can set the timeframe of that. You can have that run for two years and then watch what happens as those leads grow over time, as they score differently over time and then ultimately reactivate and reengage them. I think there's gold in lead nurturing automated workflows implemented intelligently practically. I think that's a huge opportunity.

Matt Ackermann (26:50):

Implemented intelligently is the important operative word here because if you send out content that doesn't sound and feel like you and it's a wrap by the Wu-Tang client, you are, all of a sudden people are going to be, that doesn't sound like that,

Ian Karnell (27:02):

That I'm going to create a Wu-Tang clan workflow.

Matt Ackermann (27:04):

Please do.

Ian Karnell (27:06):

I hear it done.

Matt Ackermann (27:07):

That's nothing elsewhere. I think it's really important though that it always has. So I have advisors that'll say to us, oh, well I pumped this out this way. And then I was like, but did you read it afterwards? Sometimes it can give you those nice nuggets for the middle, but make sure the lead always founds and feels like you or your attempts at personalization,

Wilbur Swan (27:29):

They're.

Matt Ackermann (27:29):

Going to see right through that. Your clients will see through that. Your prospects are going to see through that too. It was so interesting. I thought Michael today brought up some really good points around advisors still don't quite trust AI and marketing is the first, we all know this. Any marketers in this room know this. Marketing is the first thing that goes suddenly when markets go down and you're not generating the revenue you hoped. How can we bring together lower that fear around AI WIL and at the same time make sure that people are realizing that it's important to keep nurturing your marketing and nurturing these systems, especially when markets go down?

Wilbur Swan (28:05):

Yeah. Well, it'll be interesting to see, I mean, especially as the election plays out, what goes on with the markets, but I mean just in terms of general trends. I mean, I'm just speaking to more and more firms that have been investing about 2% of revenues in marketing and they are saying for them to hit their targets, they want to go from three to six to 8% growth. They're saying we are going to begin to allocate more, six to 7% to marketing. And I've talked to firms who are now beginning to put about 15% of their revenues into marketing.

Matt Ackermann (28:34):

15% of revenues to marketing. Let's all write that down. Let's all spend that much on our marketing.

Wilbur Swan (28:38):

Yeah, I mean it was fascinating and I'm not even sure they're fully counting for all the costs that I would count as marketing in that spend. But then what was the rest of the question?

Matt Ackermann (28:50):

The rest of the question is how do we get folks to continue to really accept AI could be this something and continue to nurture their marketing efforts despite whatever may happen in the marketplace. This is a great intersection here to leverage AI with your marketing no matter what happens in kind of this sphere we're in right now.

Wilbur Swan (29:07):

Yeah, I mean I think it's a challenge on us is to make it easy and engaging to use these systems.

Matt Ackermann (29:12):

To your point earlier, meet them where they are with these referral.

Wilbur Swan (29:14):

Them where they referrals. Yeah, I mean we're doing a ton of work on that front and get more value out of the systems they're already used to. Yeah, I think that's the key thing. But then I think a lot of this conversation is about, feels like the individual advisor. I would say what we're seeing is that the bigger organizations, if folks are here are representing some of those bigger organizations, are really taking these patterns that we're talking about here and applying them in multiple, they'll have 6, 7, 8 different lead sourcing programs they're working on. So it could be everything from their better capture of beneficiaries to better capture of referrals, better capture of things they're doing in the marketing, better capture from their events, better working with their advisors to make sure they're, I mean, simple stuff like that. Their lists of prospects aren't shoved away in some excel file but are actually being captured by a CRM system.

(30:10):

So how do they use these solutions as kind of like a carrot to put your data into Excel and put your data into Salesforce and we can help you get more value out of the list that you have all the way to folks are getting. What I'm seeing out there is folks are getting very creative about partnerships. They're setting up either formal, informal with folks who have access to a lot of households and think about CPA firms, think about anything and everything where they are using these same types of techniques to help them understand, okay, so you do have access to, in some cases tens of thousands of households and we're working with one that has access to millions of households. How do you take that bigger pool of people and understand who in there is actually looking potentially for paid financial advice? So I mean this is just I think playing out at so many different levels, whether it's a small firm, a medium sized firm, or a hundred billion, 200 billion firm.

Matt Ackermann (31:08):

So I guess it goes back to you're talking about spreadsheets, excel files, it comes down to that data question, good data in good data out, bad data in bad outcomes. What can we do in terms of the marketing side to make sure that we're leveraging and getting good data in here? So ultimately we're optimizing better results.

Ian Karnell (31:27):

Yeah, so I mean I think with respect to good data versus bad data to inform marketing tactics campaigns, I mean, part of the challenge that we've had historically when we look at the role of CRM plays with respect to data and informing segmentation and forming, campaign tactics, lead scoring, things like that, it's been inherently flawed because there's so many manual inputs to A CRM to keep it groomed. I think if anyone has sat at the front lines of a Salesforce implementation or HubSpot, there's a lot of excitement at first when you go and spend a lot of money on these licenses. And then the realization sets in very soon that it becomes a very expensive contact database because a lot of that data in there isn't up to date, it's not enriched, it hasn't been groomed in a while, and so you're not really getting any sort of data that's actionable or reliable in any way.

(32:39):

So I think AI plays a role in helping to automate a lot of those processes. We know that advisors spend 20% of their week undertaking manual tasks that AI can now replace, and part of those tasks are grooming A CRM, making sure that they have as much enriched data about the context and the leads that they have in there, UpToDate data and that type of data that can inform outbound email campaigns, inform inbound campaigns, inform lead nurturing campaigns, things like that. So I think that's a part of it is just removing the manual elements that have created the more unreliable data that has historically informed marketing.

Matt Ackermann (33:28):

Wilbur, one of the things that leads to that unreliable data, if you're not grooming it, is the human beings that are the factors in this. Now as you meet folks where there are, take them to where they need to go, and you mentioned that in the referral process, what can we do to better meet people where they are and take them where they need to be to improve their marketing when it comes to AI?

Wilbur Swan (33:50):

I think it's really the first step I would recommend in all of this is unless you're a small shop or you are marketing and sales oriented, we work with some firms who are just naturally wired towards sales and marketing and their advisors are great practitioners and they can do this stuff. They adapt these types of solutions in their sleep and do remarkably well with them. I'd say if you're a larger firm, my suggestion to folks is always think about whether you have that skill and if you don't find somebody, hire somebody that has that skillset to take this on because there's huge upside to it. I mean, I think as we've all been talking about, as Michael Kitts has talked about, the lifetime value of bringing on additional clients is enormous. That role can pay for itself, but if you try to do it and not, this is something that's not in your field of expertise, it's challenging. That's excellent.

Matt Ackermann (34:49):

So we only have about five minutes left and I want to get to your thoughts and questions. I have some more stuff written down here. Believe me, I went very analog with this. I was like, I didn't want to be the guy up here taking questions from my phone. It looks like I'm checking sports scores or something. So if anyone has any questions, raise your hand. We'll get a microphone to you guys right away so we can get to your questions. But I mean, obviously, like I said, I got more on this notepad too. Awesome. They want to get the microphone to you, just so that for recording purposes, we'll hit this gentleman right here in front. Now we're really going to feel like we're in a press conference.

Audience Member 1 (35:21):

Alright. It sounds like AI is going to drive cat costs down. So this isn't quite a marketing question, but do you think that's going to drive advisors valuations in their books and the multiples down because of that?

Ian Karnell (35:35):

No, I think it can appreciate it. I mean, again, what's driving advisor multiples are with respect to organic growth are how well they've implemented programmatic systematic processes that drive repeatable, predictable growth rates over time. That's what drives a premium valuation with respect to that specific KPI growth. Lowered CAC costs means that they can do more lowered cost of acquisitions mean that they can go after a bigger market without having to spend more, they can get greater efficiency and efficacy out of their current marketing campaigns. And so that can power growth. That should accelerate growth and certainly help margin, which is another factor for valuations, right? Your bottom line. So I think it could buoy it if anything.

Audience Member 1 (36:29):

But these clients are moving from somewhere, so very few of them are without advisors. So if the cost to acquire them are dropping, so they're leaving somebody, and I understand that we need to be better at what we do to retain them, but overall, wouldn't that drive the industry?

Ian Karnell (36:43):

Well, yeah, some percentage of them are coming from somewhere. I think a stat I saw recently was like 65% of individuals who have advisors feel like they can have a better advisor relationship. That's a retention issue. I think the, was it the HFP board, Northwestern Mutual, that study, about 35% of Americans are looking for. Those are Americans that are looking who have been self-directed to a certain degree who haven't had those advisory relationship. Those are trillions of dollars in assets. Even if you want to allocate a certain, take half of that and say, well, they have an existing advisory relationship. There's still trillions net new to go out and grab every single year. So yeah, the retention issue is a real issue as well. I think certainly AI can play a role in that. It's not an area that I've, I've stayed away from the mid to back office. I'm exclusively focused on that front office use case of acquisition. But it's a great question.

Matt Ackermann (37:48):

Anyone else? Someone in the back corner over there. Alright, well while we get the microphone over to you, we'll come to you next sir, we're going to go there and then we're going to go here. I love it. Lots of questions. This is terrific. We've all sat in those sessions where no one asks a question and you're like, oh golly, now I'm going to get to a dance routine. Routine plan routine. Nice. Alright,

Audience Member 2 (38:10):

Just a quick question for you guys. You mentioned a percentage more so than a dollar amount of revenue should be allocated to marketing. If you had, and it went as low as two and I think as high as 15, if you had to give a little sweet spot of a percentage, what would you say that would be?

Ian Karnell (38:28):

For me, it's not a set number for me. It's how you're calculating your return on ad spend and it's $1 in generates X number of dollars out at some point. There's a diminishing return to that and until whatever that percentage is to hit that diminishing return should be your allocation. You're acquiring AUM, you're acquiring revenue, you're acquiring profitability ultimately. And so ultimately that could be 30%. I mean, that would be amazing. That would, but the mindset, the budget should be set based off of working into a business model for your marketing investments are generating your marketing investment. X is generating Y return and it should be a positive return and then you should maximize that investment optimally over time until you hit that point of diminishing return.

Matt Ackermann (39:28):

Wil, what do you think? Is there a sweet spot?

Wilbur Swan (39:35):

I had like to come from a totally different angle. It's the end of the day, end of the conference. I mean, I think for advisors, I think there's such a valuable role for the human role in advice. It's the psychology of advice, it's the, you're navigating really touchy topics between families and I think the human role's irreplaceable. So I think the real opportunity for AI is that McKinsey came out with a study that was saying, if you look at what advisors do, could you create 50 to 60% efficiency gains using AI, better marketing, better engagement, better follow up, all assisted by machines, better meeting summarization, better next best steps with each of your prospects, each of your clients. I think that kind of thing is possible. And I think to your point, the first question that was asked, what happens to the industry then? I mean I think you get into this, what was Uber? No VCs like to invest in Uber. They just thought, well, it's taxi cabs and taxi cab industry isn't that large. I think if an average advisor could go from servicing a hundred clients to 200 clients and do it better, it could be a complete change where you could service more of the population with great advice. I mean, wouldn't that be a great thing?

Matt Ackermann (40:50):

So come here for the last question and while we bring the mic over, I'm going to say the answer we give at integrated is always, it depends, and I think so much of it is, it depends on your goal. Okay, we'll get two more questions you get and then, oh no, you go ahead and then we're going to jump to the gentleman in the blue. But it depends and make sure you set your goal first and then help the marketing. Don't back into it with how much you have. Start with where you want to go do first. Alright,

Audience Member 3 (41:17):

So I know you talked about it being kind of you're the front office versus kind of the back office, but in the organize of the firm I work for, we have about 10 billion AUM and our very big focus right now is next gen because not only are advisors going to need talking about who their successor is, it's the family wanting to understand that and then being relevant to that next gen and spending a lot of energy around that and wondering how AI can help assist in that to be more to that point, personal, relevant and in the medium that those individuals want.

Ian Karnell (42:01):

Again, this is a retention use case in many ways, and we know the stats of next gen and it's a relatively low percentage of them sticking with the advisor that their mom and dad had. And so it's a big problem that I think can be solved mostly through relationship building, right? I mean there's still, to your point, I couldn't agree more. The human element is critically, critically important, especially when it gets into the relationship that an advisor has with their client and the trust that has been built and then the trust that needs to be transferred to that second gen. AI can play a role. Certainly it can play a role from a content perspective. In my opinion, that's a relationship play, right? That's a retention play, that's a trust play and AI can be additive to that, but it's a very, very different use case than acquiring a net new customer.

Audience Member 3 (43:05):

I was hoping for a different answer. Yeah,

Ian Karnell (43:06):

I know. I can't give you that.

Matt Ackermann (43:08):

I look at it from the content side and I think no one wants to feel like they're not being spoken to. If you're in a meeting with a husband and wife and all you're doing is talking to the husband, he passes away, you're not going to retain that client. So think about it from your content perspective. You might be creating content around Medicare. There's ways to speak directly to the next generation about it so they feel like they're being spoken to and not spoken around because you're really talking to them. So AI can help with this and helping to bifurcate your client list so that ultimately you're speaking and spanking the right language to both sides. So your one piece of content about Medicare can have two different tops on it, that one that's speaking to generation A and one that's speaking to the next generation. Think about your content and say to yourself, how can I instead speak directly to the right audience here? Okay, there was one more question

Wilbur Swan (44:00):

I'd add to that please. We're doing a lot of work within labs on modeling of next gen investors. A huge focus on that amongst our client base. And the question there is how do you identify the best folks to put your bets on in the next generation? So basically what we're doing is a lot of data science and predictive modeling to say we think a person at this point in their career based on what we know of them, is going to have a great earnings trajectory. And they'd be a great bet for advice versus someone else who might be better for a self-directed type solution. So I think that's kind like the segment and then the segment within the segment.

Matt Ackermann (44:40):

I like that. Did you have one more question? Can you guys give me an example of a client success story? The problem in the outcome in one minute each, just because we're at the end of the time. So

Ian Karnell (44:54):

Yeah, so we have a client in Houston, an RIA, that is leveraging one of our auto blog features on our platform. So where we've implemented, it's really advanced rag, we've fully loaded in all of the SEC and FINRA compliance loaded into the rag, which I think we didn't get into the compliance thing. I really wanted to, I know, and that's a whole different topic. I hope we cover it next year.

(45:26):

But this is a firm that wasn't generating any content, he wasn't amplifying any of that content out to any of his social endpoints, wasn't driving any direct or referral traffic. None of that content had been SEO optimized and we began implementing this two months ago and we've seen a 30% increase in site traffic through direct site traffic. We're seeing a dramatic lift in his SEO results because now there's content that is, we have a module that allows us to track dynamically SEOs for a particular, how we set up the automation. And so it has a huge impact on discoverability, right? Individuals who are out there seeking, obviously typing in those types of keywords to discover his practice. And so it's had a huge impact on that as well. So again, it'll be a great case study that we'll be releasing at the end of the year with real data behind it. But that's one real one.

Wilbur Swan (46:37):

It's more than a minute.

Ian Karnell (46:39):

I was longer than a minute. It was, it was. It's my brother's fault.

Wilbur Swan (46:41):

I'll give you a simple one. So we're going even further up into the funnel. We're doing a lot of work with firms that are acquiring a lot of leads through programs like Smart Asset, Data Line, wiser Zoe, et cetera. You imagine all of you have talked to those types of firms and what we're doing is this type of modeling and focused marketing focused engagement. So they're seeing two X on meeting rates and then two X on conversion rates. How's that? It's under.

Ian Karnell (47:07):

Well done, well done.

Matt Ackermann (47:09):

Well done. Awesome. Well thank you so much. Thank you everyone for joining us. I'm sorry for being a little bit over and thank you all for joining. It's a lot of fun.