Dale Renner: 14:20
Yeah. Two of us. And then we brought on another data guy that had worked with us, you know, big data. He is the epitome of big data. And we brought him on and he worked for me at Accenture. And so the core group was really a lot of us Accenture guys. We brought on our first sales guy probably, I don’t know, six months too early, I suppose. Something like that. 6 or 8 months too early because we didn’t really have a product. But he’s still with me today. And all the years John has, he’s only ever missed his quota one time. And that was because we didn’t have product. So, you know, we just started building the team.
And so we had that first project. And then in August of that year we closed the deal with AIG. So that got us into, and we helped them launch some product and we helped them set all that up in call centers. We actually ended up outsourcing call centers, and we ran the call centers for them too on these products and for that group, and, you know, we had a lot of data, a lot of data processing, etc., and that was really fun. They were wonderful people. And we had those guys, we had those guys from 2006 till I think two years ago. They finally dropped that line of business. And so we were, you know, we had a very long relationship with them. So that was our second client, and we actually sold a piece of software in there that we, that I had done a resell with. I eventually actually acquired that company. And, and that’s how we got that’s how we got that going.
And so it was you know, it. I’ve personally funded the company for the first six years. And it was always about selling. It was always about delivering. It was always about, you know, focused on the customer because that’s really where we had grown up at Accenture. You have that, you know, the client, you know, taking care of the client and, and I’ll pop between customer and client software and call them customers. But in the consulting world you call them clients.
But at any rate. So yeah. So, you know, we just kept building and one thing led to the next. And we never got we we just never we never got ahead of ourselves. Maybe to a fault at some times, you know, but I always opted to focus on selling what I was positive we could deliver. Right. As opposed to trying to sell futures and then disappointing the customer. Because that’s typically what happens when you’re selling futures. Right. So, you know, one thing led to the next.
I think the third deal we did was actually in the UK, because I had run a global business before and with about 5000 people globally in CRM. And so whether we got on a plane and flew to LA or we flew to London, what difference does it make? Right. And so yeah, that’s kind of what we did.
Dr. Jeremy Weisz: 17:31
So talk about the evolution of the services a little bit. So it started off more you know analyzing as a consultant, at what point did you introduce software into the scene?
Dale Renner: 17:43
Well, we introduced software, as I said, when we sold AIG, then we brought product that we didn’t own, but it was a really good product, and I ended up being on that board. And that’s the company that I bought eventually, and those engineers were so good. And in fact, they’re with me still today. And that was in 2012.
So when we started the company, we were just doing a lot of services work. Right. And we were using some third party products, but we never, I guess, you know, we really were driving a lot of services. And then when we resold the data management product, then, you know, we took a fee out of that and then we would support that at the client and we would expand that and we would do things. So, really we always wanted to be a software company. But, you know, we really didn’t have any software developers until two years into the company.
Dr. Jeremy Weisz: 18:43
Well, maybe software growth through acquisition. It sounds like that. At what point did you decide, you know, we should purchase a company as opposed to just keep using them or using third party solutions?
Dale Renner: 18:55
Well, because I thought that, you know, we’re really a data first company. And I thought it was going to be to me, it was going to be hard to be a data first company, but then not have and control the products that we were going to be using to drive that. Right. Because then I control the outcome of that. Someone else can’t decide to make changes that impact my customers, you know, without, you know, telling me about it. Someone can’t decide they’re not going to support something anymore. They can’t, right, after I have made commitments to customers. So I really felt that the data engine was so critical to my business that I had to start with that.
And then we built, you know, automated machine learning, and we built our engagement software. So we built all those products. Right. But the engine, I needed it at the outset of the business because everything we were doing because, you know, really it’s a funny thing and we can debate this endlessly I suppose. But data is really hard. It’s really hard and it’s hard because companies that have a lot of data, it’s expensive, you know, there are a million people who will do or millions of people who will do analytics.
But if the data is not right, it doesn’t matter what you do with the analytics, right? It’s all you do is just get a bad result faster. Maybe that’s all. That’s all it’s going to happen. So my mindset is so married to the idea of working with our clients to give them the absolute best data to drive decisioning and interactions and personalization that I just felt it was critical that we have that.
Dr. Jeremy Weisz: 20:47
Maybe we’ll talk about a couple examples so people can kind of chew on what that looks like. And let’s start with maybe Providence Health and what you did there.
Dale Renner: 20:56
Yeah. Well at Providence Health I mean there are really you know, they’re a very impressive organization. And they’ve got, I don’t know, 35 million patients. And Providence Health is one of those, you know, it was a Catholic, it was started by Catholic nuns way back in the day. Because what they did is they went to underserved communities that tended to be rural communities.
And so when you think about where they are today versus what they started, where they started, it’s so impressive. And they understand, right? What they really understand is patient. They understand they’re patient and that understanding is so critical. It’s data. Right. So if you’re going to do, if you’re going to do meaningful, valuable, high value engagement with patients, you must have the absolute best data, right? Because you are these are life and death kinds of things. Right.
And so it’s very exciting because what we got to be a part of is their strategy on how they think about that and how they think about patient engagement, how they think about their patients. And, you know, they are so attentive and thoughtful about that. So, it all started with the data and and you know, and they got a lot of data that’s coming in. I mean you think about 35 million patients. There’s a lot going on there. Right. And they’ve got all these doctors, you know, these providers across the country, and so driving you know, I can’t reveal. Let’s just say our platform, they drive tens of millions of dollars of revenue through our platform. Right. And so we’re really a, you know, we’re a strategic partner of theirs.
Dr. Jeremy Weisz: 22:47
I’m trying to, what kind of decisions are they making by using the platform? Like you can see here, if anyone’s looking at the video part, we’re just looking through and I can see a lot of use cases from like a healthcare perspective. I mean, it’s so fragmented in general. We’ve all experienced at least, I have going to one practitioner explaining the same thing, going to another one, explaining the same thing. There’s no communication there. How are some of these healthcare companies? What are they? What decisions are they making?
Dale Renner: 23:15
Well, let’s start with their data, where their data comes from. Right. Because it comes in the doctor’s office, but eventually it gets into some kind of electronic medical record. So the next time you go get physical or you go to your doctor’s office and they’re and they’re typing in, you know, and they’re looking at screens, ask them to show you your care gap. Right? Because that’s one of the things that providers want to be aware of. And that care gap could be as simple as when’s the last time you had a tetanus shot or whatever it is. Right.
And if you look at it like if your doctor uses epic, for example, that’s one of the big misses. There are others. But down in the lower left corner of the screen ask them to show you their care gap. And what you’ll see are all the four or 5 or 6 things, or two things, or whatever it is that they can offer you. And that it’s time or something that’s coming up, or it’s been this many years since. And so having that information available at the point of care is extremely important because they need to know where you are in just those kinds of things. What kind of treatments have you had? ET cetera. ET cetera.
But the care gap is interesting because it says, hey, you know, Jeremy, you need to do you you should do this thing. You should take this. You should, we should, you should. You should do that. What is that? Right.
Dr. Jeremy Weisz: 24:36
I have a large care gap. The last time I went, and they’re like, you know, you haven’t been back in seven years. I’m like, you told me not to come back for four years.
Dale Renner: 24:42
But that was because four.
Dr. Jeremy Weisz: 24:45
Four turned into seven. Like, you’re pretty healthy. Whatever. But you’re right. It’s like you haven’t had this blood test in six years, right? I mean, that’s pretty obvious, but, you know, I want to know that just as a patient.
Dale Renner: 24:59
Just think how, you know, when’s the last time you had a colonoscopy. Right. And and you know, those cancers are some of the, you know, easiest to avoid if you have regular, you know, checkups, if you have a polyp in your, in your colonoscopy, well then you’re going to do, you know, it was you’re going to have colonoscopy every ten years. Well, if you have a polyp then they’re going to do it every five years. You know, I can hardly remember yesterday let alone you know, when did I have the last colonoscopy.
So going in for my physical, my annual physical, you know, I want somebody to be telling me, you know, when’s the last time of this? And that is what they take responsibility for is informing you. And that’s where it starts. And, you know, I’m horrible at knowing that stuff. So I’m very appreciative of a doctor telling me those things.
Dr. Jeremy Weisz: 25:44
I know from a customer standpoint it kind of is there any, you know, specific pathway it’s gone through? Obviously I see the first, you know, client, it was more kind of retail e-commerce related and then insurance and healthcare. Was there any thought like I’m just curious internally with the teams like, hey, we really like working with these healthcare clients. We should really focus on that. How do you think about niching within Redpoint?
Dale Renner: 26:16
Yeah, you know, you have your ICP, right? Ideal customer profile. And for us, we like regulated industry a lot. And the reason we like it is because they have a lot of data. So banks, insurance companies, payer providers and healthcare, there’s a lot of regulations. So you know, we are SOC 2 compliant. We’re ISO 27001. You know, we’re HIPAA. We, you know, we’ve got all those certifications and all those all those. Awards if you will, or credits. And so you know we’re built for that. And we really pay attention to the data side of things.
The other thing is, as I mentioned before, we’re built for scale and complexity and performance. And as I said, they’ve got a lot of data and they’ve got a lot of there’s a lot going on in those companies. And probably the third thing is, you know, we have software that can run both as SaaS actually, we have three different deployment models and we have a SaaS model. And that’s the traditional you send the data to us, we have a data in place model where we can run the application, but the data can run, you know, behind your firewall. And we don’t store the data. You got to land it to process it, but you don’t, it doesn’t store.
And then we can also be on premise. So if you look at highly regulated industries, like a number of our clients, they are customers. They will not push their PII data out into a SaaS. They just won’t do it. And you know, everyone is deathly afraid of what could happen to that data, where does it go, etc. And AI now is making that even worse. That bringing that fear even more front and center.
So when you look at us, we’re actually built for that. But our SaaS offering, you know, we actually do a lot of work with retailers, mid-market retailers and so, you know, you can send your data and you can and we can run the applications for you and you can access all that data and do all those things. But regulated industries work really well. Or I should say, we work really well with those because of how we deliver our software.
Dr. Jeremy Weisz: 28:27
So in simple terms, then they’re not going to push their data like a healthcare company is like, we don’t want you having all the data. So do you install it separately onto wherever they’re inside of their system? Is that how it works?
Dale Renner: 28:44
Yeah. Yeah. Exactly. So you know everybody’s going to cloud right in one form or another. You know they’re really private clouds. If you think about it. It could be Google. It could be Azure, it could be AWS, it could be whatever. They all are building their own data ecosystems. It might be inside, it might be the products inside those, those particular cloud providers. Or it could be a snowflake or Databricks or whatever.
And they’re creating their data environments or their data ecosystems inside of let’s say Azure, for example. Right. Well, you know, doing all the data work and building audiences, when people talk about activation, you know, you’re doing you create segments and audiences. And then now you can activate. That activation can be as simple as pushing it into your email provider environment. Let’s just say. But that PII data, it might be you know, it’s an email address and it is a name but it’s not healthcare data. Right. And so there’s that’s where the line gets drawn is of of that data. What am I willing to push out into a SaaS. And the more that I can push out, the more it’ll work for a SaaS. But I also have the issue then with am I replicating that data, the cost of that data, that storage, if I’ve got snowflake in-house, you know, do I really have to push that data out to a SaaS provider?
So all that SaaS stuff is really changing as well. But, you know, putting that aside for a second, it really has to do with data protection, privacy, and most of the companies that we work in those regulated industries, they have a very strong CISO, right? Very strong. They have their information security officers and those folks have zero tolerance to. To move data out and not know where that data is. They do not want that data to be out in the wild.
Dr. Jeremy Weisz: 30:32
Yeah, yeah. You can see here if you know, you’re looking at the RedpointGlobal.com and we’re at the customer case studies. They’re like pharmaceuticals. These are all heavily pharmaceutical heavily regulated healthcare. There’s some retail providers here. There’s also financial services which are huge. Why don’t you talk about American Express a little bit?
Dale Renner: 30:56
Yeah. American Express we work with their merchant services group. It’s about 25 million businesses, I believe. And they use our software. They have if you think about it, they have a lot of credit offerings.
Right. Credit products that they can work with their customers on. And, you know, smaller to larger and moving them through those, those various, you know, products that are an effective product. Right. And so they have very complicated segmentation rules. And and you know, they are of course superb in what they do. And they, you know, the idea of being able to be extremely granular in the targeting of those, of those and what of those customers, of their customers and the offerings that they have?
And if you think about a company like American Express or others, you know, they want you for life, right? And they want to grow with you, and they want to support that growth, and they want to be a partner in that growth. And so the idea that, you know, you you’re you’re this size now and you have this kind of a credit offering and this kind of a credit line or whatever it might be, and then I want to track and I want to and I want to grow with you.
So their customers are constantly changing. So the understanding that changes in what’s happening and maybe it’s transaction buying, maybe it’s, you know, any number of factors that they’re looking at. And then, well, maybe I need to, now, now we should be offering a new product to that business. Right. So that’s how they use our software.
Dr. Jeremy Weisz: 32:31
Yeah. It’s probably because of you I get the American Express Platinum mailers every other month.
Dale Renner: 32:41
I hope so, I hope so. That means that our stuff’s working. Exactly. Open up that. Open up that wallet.
Dr. Jeremy Weisz: 32:46
That’s right. Exactly. And so I want to talk about AI for a second. And just in general, just I don’t know if you’ll talk about some of the things you’re using. It could be on your phone, your computer. What kind of app software, tech are you into now personally? It could be for the business or just personal.
Dale Renner: 33:07
Well, yeah, I think everybody uses the chat stuff, right? You know, we all get a kick out of that. You know, if we take a step back from AI, first of all, you know, AI is scaring the bejesus out of everybody. Right. Because nobody really knows where this is going to go. But, you know, there you know, there was another announcement yesterday in the Wall Street Journal about the, you know, 4000 people being laid off at, at a company. And you know, being, it’s, it’s being pinned on AI. I think that AI itself is, you know, it is just it’s transformative. Everybody knows that.
Dr. Jeremy Weisz: 33:42
Square, I think. Right. Square laid off like 4000 layoffs or 4000 people.
Dale Renner: 33:48
Yeah, yeah. And so, you know, people are anxious. People are anxious about that. And, you know, is it going to replace me? Can I get my, you know, how do I do it? What do I do:? How do I, you know, I got to build skills in it and all that kind of thing. So you have a lot of anxiety with it. And, of course SaaS companies are under attack by AI. You know, the promise from, you know, Anthropic a couple of weeks ago is, you know, all these SaaS applications, I think refer to them as workflow applications, to which Bloomberg had an interesting reaction, right?
Which was, hey, you can you know, if you think about Bloomberg, you’re subscribing to their service. They’re, you know, they have analytics, they have all these things. Yeah, somebody can build that application, but they don’t have my data analytics. And I’m not going to give that to AI. You’re not, you’re not going to get that. So you know it’s what’s your mulch right. Everybody’s talking about the moat. No.
So when I think about AI I see it right now we’re using Claude code coding. And you can’t just use it. And you know, maybe my guys always say, well, you know, if we can get 70 to 80% of it, that’s a lot, right? That’s a big improvement. You still got to know what you’re trying to do. And you got to go back and look at it and you got to fix it. And so I think it’s a ways away before, you know, all programmers go away. In fact, I think Bill Gates said that he didn’t see programmers going away. Right. Because someone needs to understand what you’re trying to do. An AI does not understand, it searches. Right.
If you think about it, that’s even Anthropic. You know, Anthropic is to Google. Right. And Claude is to, you know, search. Right. If you think about you do search inside of Google. Well you’re using Claude you know, Claude coding. So just because you do a search it doesn’t mean that it got you the right information. It doesn’t mean there’s you know, there’s tuning that has to go on. So I think it’s great. I think we’re seeing it as a big productivity gainer for us.
I think that from an engagement from you know, our clients using it and thinking about it I think it’s going to be used to drive. I think it will be used to drive better offers. But when you when you what people don’t I think maybe appreciate yet and I and I talk like I’m an expert on it and I’m not from the I’m talking about an impact here. This is going to be very expensive. AI is going to be very expensive because, you know, they call them large language models for a reason, right? And if you think about it, all the algorithms is really a neural network inside those large language models. Well, those large language models cost a lot. That’s why they’re saying, you know, we’re going to need 30 data centers that are the same to power nuclear power plants. You know, just in the United States over the next ten years. Well, what is that going to cost? And at what point in time are people going to stop burning, you know, 100 million or $200 million a year and have to actually make a profit, right? So and then who’s going to pay for that? And then what kind of lock are you going to be in?
Because right now everybody is worried about vendor lock. You know, wait till you start building a whole bunch of stuff in someone’s AI and then start to think about that lock in and how do you get out of that? You know, so I think this is a long way from being privatized and commoditized and all that stuff. I think there’s a lot there’s a lot of danger. And we see our customers are being very cautious with it. They’re being very thoughtful about it. There’s a lot of experimentation going on. You know, the one thing that I think is causing is inertia. I think that because of the uncertainty around it and no one knows for sure, right, how to use it, how it’s going to impact their business, whatever. I think that everyone has budgets to spend, but then what am I going to do? What am I trying to prove?
And proving out a thing is one is one part, but embracing it as a way of life inside your company that’s another thing. So, you know, there are always pioneers in this, like all things, and we’ll see. But I’m excited about it. I think it has a I think it can really help I think it can help me out a lot.
Dr. Jeremy Weisz: 38:04
Does that help you think selling now, Dale, to these organizations because like as a value prop you’re like, you know, Obviously you’re talking about data, but your solutions use AI to help you know with what they need to do with the data. Is that helping you think on your end?
Dale Renner: 38:22
Yeah, I think I think it is. Well, about 18, 19 months ago, I went to my marketing folks and I said, what I want to do is because everyone had BDRs, right? And you’re, you know, you’re banging the phones and you’re doing stuff. And I said, you know, what we should do is think about how we use AI to drive leads for ourselves. Right? And I really want us to do that. Go figure that out. Yeah. Bring products in. You know, don’t break the bank. And, you know, let’s not do anything too crazy here. But let’s learn, let’s figure this out.
So now we actually use AI products for lead generation for ourselves. So that’s an example of us using it to help sell. Because, you know, if you think about it, any decent marketer is going to talk about account based marketing, right? Particularly when you sell, not the guy that’s selling 100,000 to 100,000 customers, right? That’s really a volume play. But people like us who are selling to enterprises, you know, it’s a lot of work to do. Account based marketing. It’s very expensive. And you’ve got to make a lot of contacts and you’ve got to, you know, you’ve got to get the right messaging and the messaging.
And we actually have two constituents that we sell to. One is going to be that that chief data officer, chief data, chief data, you know, really a chief data officer that the people who are doing all the stuff with the data and then the CMO, the people who are doing the engagement side of things, well, those people buy completely different things, right? And, and and that, you know, marketers don’t buy data solutions. Marketers want good data to use. They rely on their CDOs to create that. Right. Just like CDOs aren’t necessarily worried about which engagement software a marketer wants to use, right? Their job is to provide that data and provide those insights, perhaps around, you know, what the models are doing.
So, you know, when we look at this and if you go back to kind of this idea of selling as a company selling, and you want to do account based marketing, well, you really have to think about all the constituents that you’re trying to sell to because it’s different messaging. And I don’t know, you know, you got to have a flock of marketing people if you’re going to do all that. But AI can help you because AI can go out and figure out who all these people are, and AI can figure out, you know, what are they talking about out there?
And AI can figure out which, you know, what are those companies hiring? What kind of skill sets are they hiring? What are they doing? You know, somebody that’s hiring a bunch of snowflake people probably has snowflake, right? So how do you do that? You know, how do you get that manually? Or how are you going to go out and buy some service that does that. And it’s so dynamic. There’s you know, it’s hopeless to try to keep current with all that. But AI can do that, right? So I see it as a big plus in helping us to sell. And I think that’s you know, I think I’d be surprised if every company out there that we compete against isn’t using some form of AI to help themselves.
Dr. Jeremy Weisz: 41:20
Yeah. I just send them beef jerky. Yeah, that’s all I do. So that’s cheaper. That’s it.
Dale Renner: 41:26
Be more effective.
Dr. Jeremy Weisz: 41:29
But no, first of all, thank you. I just really appreciate you sharing your story, your journey. It’s pretty remarkable. Everyone should check out RedpointGlobal.com to learn more. More episodes of the podcast. And Dale I just want to. Thanks for sharing your lessons with us.
Dale Renner: 41:45
Sure.
Dr. Jeremy Weisz: 41:46
All right. Thanks everyone.
