Episode Transcript
[00:00:24] Speaker A: Welcome, everyone to our latest metricide episode.
I'm Robin Garris, I'm CEO of Metrogy and happy to be here with you today.
I'm going to start off today just by talking about customer engagement and how it's really sort of the top area. It's the top area of increased technology spending for 2023 and our latest technology forecast study. So what we found was 65% of companies plan to increase their spending in this area, customer engagement, by an average of 24%. And that's the most of anybody of any technology, or it's even higher than security, believe it or not.
But not surprisingly, one of the big areas of investment within customer engagement, kind of broadly speaking, centers around AI. And I think we all know, though, that AI is a huge area.
Technology is incorporated into many products and services today, particularly in the customer engagement space. So fortunately, I am joined today by Dan O'Connell, who is chief strategy officer for Dialpadous. He is truly an expert in AI. So we're going to hear from him about Dialpad's focus on AI, both what's available today and hopefully kind of what some of the innovations are that are underway in Dialpad's AI lab. Hopefully Dan will share, maybe give us a little bit of insight there.
So let me just start, Dan, by asking you just to give us a little bit of background on yourself and then your role with Dialpad as well.
[00:01:54] Speaker B: Yeah, so thanks for the illustrious intro. I love it. So, as you mentioned, I'm Dan, I'm a chief strategy officer and I've been a dialpad for four and a half years. For those that don't know, Dialpad's an AI powered cloud communication software. So we do voice, video messaging, contacts center on any device anywhere in the world. And I showed up four and a half years ago. They actually acquired the startup that I was building, which was real time speech recognition NLP startup, which is a fancy way of saying how do we go capture conversations, transcribe them, and then automate workflows and drive insights specifically for sales and support businesses.
And then today at Dialpad, anytime you hear strategy roles, people are always like, well, what exactly do you do? So I oversee our product teams on AI. So anything to do with speech recognition, NLP and the features that we're building out and then oversee corp devs, dev strategic partnerships?
[00:02:47] Speaker A: Yeah, those are huge and really interesting areas right now. Something I've always been looking at in my research as well. So, you know, the way I look at any discussion around customer engagement certainly includes AI. These days. If it doesn't, the company's probably really far behind.
So I wanted to ask you if you could make it real for our viewers and listeners and just tell us how companies are truly using and seeing benefit from AI at Dialcad.
[00:03:15] Speaker B: Yeah, so I think it falls into a couple different areas. You know, I just talked about what I think has been really interesting, literally over even the past, definitely the past decade, but really about the last five years. It's just the rise of conversational intelligence, which is saying, how do we go capture conversations, transcribe them, and once you have something in a text format, you can do all sorts of things with it. So I think you've seen the rise of conversational intelligence, and that's around coaching and driving performance for teams starting to do call reviews, being able to start to automate compliance. But then you also start to get into these areas around. You know, we've had the first iteration of chatbots, and I think what we realized was chatbots are pretty good at remedial questions. How do I go and reset a password?
We have had some challenges in years past when you start to get to things that are a little bit more complex. The nice part is the rise of, as I said, of NLP, which is natural language processing, to say, we can now have chatbots and voice bots and engage with them, and they can start to actually handle some pretty sophisticated requests, processing, refunds, requesting for information. It might be about a new product. So I think you've seen a lot of rise of adoption in terms of chatbots and virtual agents. And then the last piece that. That I get really excited about gets into that we've been working on is really about inferring insights or predictive insights.
[00:04:40] Speaker A: I'm excited about that, too. I'm with you.
[00:04:42] Speaker B: Yeah. And I think it's this shift. We always think about, how do you start to shift seacs away from being reactive, and how do you start to arm people to allow them to be more proactive? And I think we're working on and recently released a feature that we call Aicsat, which is inferred customer satisfaction. And suddenly, you don't have to rely on surveys. There's no lag in waiting for responses. You suddenly have this information around customer satisfaction instantly, and you can better react to it, and you can react to it much faster. And that's going to lead to, ultimately, higher retention, might lead to upsells and renewals, but I think these are the types of things that people are coming to us for, and we get excited on working on.
[00:05:24] Speaker A: Yeah, for sure.
I also see, you know, just as I'm talking to companies, you've got like two different buckets. Some of them are like, yeah, I'm going to start real simple. I'm going to do a basic chatbot and build from there. And then there are other ones who say, I'm going to boil the ocean. And I have found that that first bucket actually has a lot more success. They start very simple and deliberate and just keep building on that success. When we see companies who try and do too much too quickly, I. Anyway, I find that they don't start, they don't really show business success as quickly, ironically enough. Right. As those who, you know, kind of take a more conservative approach and build upon it. Is that, is that kind of what you see?
[00:06:01] Speaker B: Yeah, I think, and I think there's three areas. It's kind of like you gotta pick the problem that you want to solve. And obviously, when you're talking about customer support or contact centers, there's almost infinite problems you can go throw things at. For me, I think there's three really easy areas. One is like, if you're not thinking about digital deflection today, I think there's this rise of look, customers expect to engage with brands 24/7 they expect to do it on any number of channels, whether that's TikTok, Instagram, to voice, to text, you name it. So I think one is like, there's a massive opportunity to go and leverage technology to focus on digital deflection. I think that's a pretty easy defined problem to go and roll out. The next one I love to highlight is conversational analytics, which gets into look, if you're manually reviewing calls and manually doing QA in your contact center or for your sales team, very real applications that can go and tackle that and make it much easier and give you 100% coverage and do some really interesting things. And that's low heating fruit in terms of implementation. It just gets into call recording and then kind of the magic happens.
And then the last one, and sorry that I give these long rambles, gets into things like AicSAT, which is look at for us, there's no change in behavior, there's no new software. It completely removes the need for surveys. And all that happens is you turn it on. People naturally have conversation within their contact center and they get their insights. So it's almost like this perfect feature that shows up. And that's if you talk about the lowest barrier to entry, that's probably the lowest barrier to entry that we have.
[00:07:30] Speaker A: Yeah, and that's the thing I think too, with AI, a lot of people look at it and think it's very complex. It's a complex technology to implement. And you answered my next question. I was going to ask you a little bit about how dialpad removes complexity within AI. I don't know if there's anything else you want to add. You kind of just answered that, really, but I don't know if there's anything else you wanted to add about how you might, you know, remove something that is otherwise complex with AI, which I know people also think is complex, you know, just from a process standpoint maybe.
[00:08:01] Speaker B: Yeah, well, I think, I think about it from any time I'm like building products and I think there's always the story of, look, you can make some complex, you can make some products really, you take any problem and make it.
[00:08:13] Speaker A: Really, really complex to solve.
[00:08:14] Speaker B: It's really overwhelming. And there's a bunch of features that ultimately end up adding tax to building things out of. And I think it really comes down to the way that we approach building products at Dialpad is, look, we want to make it dead simple implement, we want to make it aesthetically pleasing to use because I think we want people to engage this really wonderful experience using software and then it has to solve this problem and it can't have a bunch of add on features that kind of get in the way. So I think some of it comes down to what's the philosophy that the business had in terms of building products and making sure that again, you're really getting to the root cause of the problem and you're having this product instead simple to use. We also then say that, you know, the last thing I would say is, look, if you need help, we have obviously professional services and account teams that can help people through the implementation, but that's not the goal of us, is to go and build software that's easy to deploy.
[00:09:10] Speaker A: You know, when I also, the other thing that kind of comes to my mind when I think of AI's, it's going to solve problems, it's going to maybe take away some of the complexities, but it's also going to automate. You know, I always look at like three a's, you know, AI automation, analytics, like those three all kind of go together. And I see automation as just one of the big benefits of AI. I've talked to you in the past about the AI scorecard.
Maybe you can explain to our listeners and viewers today how this would work. You know, how does AI, scorecard or other functions that you might have help to automate things, automate transactions, automate processes.
[00:09:42] Speaker B: Yeah. So as we started this conversation like that is another big opportunity is, hey, how do you leverage AI to do things for you to drive product? Yeah, if we get into quality assurance. So typically what happens in a contact center today, if you are an agent, your manager might give you a rubric and say, hey, Robin, every time a call comes in, here's five things that you need to go and do. It might be authenticate a user, perhaps. Let's talk about a new feature before they hang up, whatever it might be.
The beauty of this is, look, instead of having managers at the end of the day sit down and go and review the calls to say, hey, did Robin go and ask these questions? Which is what happens today? You can start to leverage AI to say, look, we have the transcript of those conversations. We can then start to use sophisticated NLP natural language processing or natural language understanding models to go and identify whether Robin has done this. And instead of the manager only being able to do this on one or two calls, you then instantly have 100% coverage. 100% of the reviews of every conversation happens.
The purpose of this is not to replace the manager. And I think kind of the next thing that leads into AI is, hey, are you trying to replace people? And you're not. The scoring is never going to be 100% perfect. And I think what's important anytime we roll out features is to say, look, this is a suggestion of the score that we think that happened on the call. We want to provide reasons as to why the AI inferred that decision, or came to that. To say, like, these were the moments that led us to believe that Robin authenticated the user. This is how we came to that decision. And then the third piece is to allow or provide the user or the manager the ability to actually overrule. Overrule might not be the right word, but to make edits or adjustments to things. And again, the whole purpose of this is to speed up the process of the call reviews. It's not to entirely automate it.
[00:11:37] Speaker A: I hear from a lot of people like, oh, all this AI, everything, it's going to just eliminate all these jobs. And I ask about this every year in my customer engagement transformation study. And every year the majority of companies are increasing their number of contact center licenses.
There's a small sliver that are decreasing your single digit percentage and the rest are staying flat. So I don't ever see this concern that people have that AI is going to replace people. It really complements people. It really just kind of helps them to do their jobs better is what I see.
[00:12:07] Speaker B: Yeah. Anything I have learned in my time in this space is that I think anytime you even, and you hear me, kind of get a little bit of tense up when we talk about automation and replacement.
I don't think it's reasonable. And what I mean by that is there's so many one. I think people like to hear empathy and they like to connect with people. So I don't think that's going away. There are always going to be really sophisticated problems that can't be resolved through AI. That's just a reality. And I also think it's going to take us a lot longer than we expect to solve some of these problems. We see it even pop up tangentially in self driving cars. We were told this is going to be kind of easy. We'll have these out in the next five years. Turns out it's a really big problem and we'll be lucky to kind of see it in our lifetime. But I think that also tries that. Also, those problems persist in other areas like contact center. And to have a fully automated agent that has all of the abilities of a human is a really, really challenging task to go and do. So I don't think folks need to be too concerned or worried about that.
[00:13:13] Speaker A: Yeah, absolutely. I agree.
I did another metrosite with your colleague John Finch, and we talked a little bit about some of your acquisitions. And I've been really interested in those because you've been able to develop some new services. Obviously when you were from one of the really cool acquisitions that leverage AI and also, I say, provide predictions. I like the whole predictive nature of things, and so I was hoping maybe you could take a pick. John did talk a bit about AIC staff, but what about things like inferred NP's or churn and revenue prediction? I think that's a big one. That kind of extends beyond just your technical and operational people in the contact center and gets into the sales teams and the marketing teams and purchase intents. I think that's another really cool one. These are some areas I know that you're automating based on the knowledge AI is gaining. So maybe, I guess this is where I'm going to ask you to get into some of the future things you're looking at and what you guys are doing there.
[00:14:09] Speaker B: Yeah. So I think, I hate constantly saying this is the next big opportunity, but as a business for us, we constantly try to figure out? How do we go disrupt industries? How do we go release really innovative features? How do we go and push the market? And to me, I think the whole predictive insights look, if you can go capture every conversation, then what you really want to focus on for businesses, what are the two things they care about? How do we go drive more revenue? And that might be sell new business or it means net retention and reducing churn. So you naturally then get into, look, these conversations happen every day with sales and support teams. We can apply some science to those conversations to identify when somebody is leaning in and might be willing to do a renewal or an upsell or buy. And then there's also ones where, look, this person's called in the past three days, they're becoming increasingly frustrated and we should be able to identify from tone and contextual signals that they're at risk of churning. And you should go take creative action. You shouldn't have to then wait for somebody to call you to say they want to cancel to then figure out roll out the red carpet for them. So I think there's these really immense opportunities once you start gathering this conversational data to then start thinking about how do you help people play better offense. And that to me is a really big market. I think it's really, I'm not saying this stuff is easy, but that to me really changes the fundamentals as we go to market and talk to our customers about using dialpad.
[00:15:39] Speaker A: So is it like, okay, let's say I'm going to do some predictions. Is it as a supervisor, do I get some sort of a dashboard or report or something that's going to show me? Or is it stuff really just popping in my screen in real time saying, hey, so and so, just talk to somebody who really sounds like they're leaving. You might want to get a supervisor on. It's like, how do you envision it?
[00:15:56] Speaker B: Yeah, so these are a couple of things. And we have, you know, we have this notion of like AI labs. I'm fortunate I get to work with our AI research team. And so these are things of like, these are ideas we noodle. So one of the things that we talked about on this is, well, how do you deliver these notifications? So we have one notion and one opportunity that we're mapping out, which is literally a task list every day, which is manager shows up or not even the manager, but the rep shows up and they literally have a task to say, like, look, based on the conversations, these are folks that have expressed more intent. We think there's upsell and cross sell opportunities. They expressed interest in these products. They mentioned these competitors. This is what you should go and focus, and we'll kind of walk you through the conversation. The other opportunities for it, too get into notifications. And so do you start to actually beam notifications, whether it's in app or over sms or in email to the users? The challenge with notifications ultimately becomes like, overload. People then want to be able to customize what they get notifications for. They want to snooze them. If they snooze them, is it like how I sleep in every morning? I hit sluice next time? So I never actually dismiss it. So we're kind of dabbling with different ways to deliver that. And then the third thing that we're also kind of exploring on this is, do you actually take this notion of newsfeed, which we're all used to in a social manner, and apply that to business to actually get. And again, it gets back into all these conversations. Can we start to put in one place the trends and the opportunities that are popping up? And again, I think that gets out of people caring about it just in the sales and support world, but perhaps finance or perhaps revenue operations. Right?
So we're dabbling with all.
Yeah, we're dabbling with all sorts of delivery and ideas on that. You see me kind of smile and laugh. We like to think creatively. Some of those may make it into production, some of them may not. There's obviously plenty of bad ideas that we work on as well, but you got to explore these things.
[00:17:53] Speaker A: Hey, you always learn from the bad ideas as well. You know, bad ideas can turn into good ideas and. But, yeah, I think that's really cool. Like, the, the way that you can maybe take some of this, and it's initially for a customer engagement or a sales opportunity, but it can expand into other areas of the company. And I think so much of the innovation that's happening in CX has other applications to other types of employees.
[00:18:13] Speaker B: Yeah, typically, businesses will do that stuff. You know, they may talk about them as, like, win wires, which is like, anytime there's a bin win, you know, they send out an email. And again, there's ways that you can know that it's happening in real time. You can automate that email because you understand the conversation. And it's a case of like, well, how do you deliver that message? Right? And where do you deliver.
[00:18:35] Speaker A: Well, that's awesome. We're out of time for today's session, and I could go on and talk about this for a long time. I was joined today by Dan O'Connell. For those of you who may have missed out at the beginning, chief strategy officer for Dialpad and had a great discussion today on everything that's going on at Dialpad and all the innovations and the way that you're using. Aih. I really appreciate you taking out the time and sharing that with us today, Dan.
[00:18:58] Speaker B: Yeah, thanks for having me.
[00:19:00] Speaker A: This was awesome, and thanks to all the viewers and listeners, and I hope everybody has a great day.
