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spk01: Good afternoon, ladies and gentlemen. Thank you for standing by. Welcome to LivePerson's first quarter 2023 earnings conference call. My name is John, and I'll be your conference operator today. At this time, all participants are in a listen-only mode. After the prepared remarks, the management team from LivePerson will conduct a question and answer session, and conference participants will be given instructions at that time. To give everyone the opportunity to participate, please limit yourself to one question and one follow-up. As a reminder, this conference is being recorded. And I would now like to turn the conference call over to Mr. Chad Cooper, Senior Vice President of Investor Relations. Thank you. Please go ahead.
spk10: Thank you, John. Good afternoon, everyone, and thank you for joining us today. On the call with me today are Rob Lacascio, five-person founder and CEO, and John Collins, Chief Financial Officer. Please note that during today's call, we will make forward-looking statements with our predictions, projections, and other statements about future results. These statements are based on our current expectations and assumptions as of today and are subject to risks and uncertainties. Actual results may differ materially due to various factors, including those described in today's earnings press release and the comments made during this conference call and in 10-Ks, 10-Qs, and other reports we file from time to time with the SEC. We assume no obligation to update any forward-looking statements. Also during this call, we will discuss non-GAAP financial measures. Reconciliations of GAAP to non-GAAP financial measures are included in today's earnings press release and the supplemental slides where applicable. Both the press release and supplemental slides, which include highlights of the quarter, are available on the investor relations section of LivePerson's website. Finally, I'd like to remind everyone that we are here today to talk about our first quarter of fiscal year 2023. As you may be aware, a shareholder has announced its intent to nominate candidates for election as directors at the company's 23 annual meeting of stockholders. The company intends to file definitive proxy materials related to the 2023 annual meeting in due course. Stockholders of the company are strongly encouraged to read the company's definitive proxy statement, the accompanying proxy card, and all other documents filed with the SEC carefully and in their entirety, as they contain important information. Information regarding the identity of the company's participants and their direct or indirect interests by security holdings or otherwise will be set forth in the definitive proxy statement and other materials filed by the company with the SEC. Stockholders may obtain copies of these documents for free through the company's website or through the SEC's website at sec.gov. We will not comment further on this matter on this call. We appreciate you keeping your questions focused on live persons' performance and results. With that, I will turn the call over to Rob. Rob?
spk03: Thanks, Chad. Good afternoon, and thank you for joining us for our first quarter 2023 earnings call. LivePerson had a really good quarter, generating revenue of $108 million while narrowing our EBITDA loss to $1 million as we continue to execute on our profitability goals. Total revenue was at the high end of the range, and adjusted EBITDA was well ahead of the guidance range. We continue progressing on the business initiatives crucial for our next phase of growth, including a narrowed focus on our B2B core and right-sizing our expenses. We are reaffirming total revenue and adjusted EBITDA guidance for the full year, and John will provide more detail on the financials shortly. For the company, our employees, and our customers, May 2nd was the start of the next leg of our journey with the launch of our new generative AI products and platforms. The changes we implemented over the past five quarters, including removing non-core revenue divesting of our consumer business gives us a solid operating foundation to support our growth and focus on the opportunity we see from the core business. We've always completed, we also completed the consolidation of certain go-to-market functions, which will meaningfully improve our P&L going forward. Our company is at an inflection point, and with the changes we have implemented, we are poised to accelerate profitable growth in the periods ahead. We have set our sights on becoming one of the largest and most effective enterprise AI companies as we have the advantage of our early entrance into AI five years ago. We believe that generative AI will significantly accelerate our existing traction in delivering high-quality automation and business outcomes to the enterprise. Most AI models are trained with tens of thousands of AI-generated conversations labeled by employees or freelancers. Live person hosts billions of conversation with our enterprises and consumer conversations with the input of 350,000 live experts on our platform, coupled with 250,000 API endpoints that enable not only engagements but also transactions, this approach is imperative to enable generative AI in the enterprise. Our generative AI advantages are rooted in our precision data set and 350,000 customer surveyed agents on our platform generating the quality data, our secure guardrails protecting our customers and their data, and integrations into our customers' backend systems, which allows us to do transactions and outcomes. Those of you who joined our product launch event last week saw that LivePerson could customize and tailor responses to suit the situation and reflect the brand's voice. with the largest customer conversational dataset and a very strong platform for handling the data. Additionally, the voice-based acquisition has been a key accelerant to driving the efficacy of our data and allowing it to be prepared to scale with the new AI large language models. LivePerson is a global leader in conversational AI. Hundreds of the world's leading brands, including HSBC, Virgin Media, Chipotle, use our conversational cloud. We power nearly a billion conversation interactions every month, providing a uniquely rich dataset to build connections that reduce costs, increase revenue, and are anything but artificial. We use this dataset and expertise to act as the assembler so that the responses are grounded and the large language models only use these to generate high-quality responses. It can't be overstated how important it is that LivePerson can leverage the humans in the loop on our platform. Over 350,000 skilled humans are using the live person platform, continually training and refining answers to provide the risk mitigation or guardrails necessary to help enterprises safely leverage generative AI. This ensures that all AI conversations are grounded in facts and relevant to our brands, that we reduce what they call hallucinations. And I really feel that one day, if we look at the asset value of the company, our data set alone has such a tremendous value because of its uniqueness in providing high-quality outcomes. One of the most important aspects of our platform is that they combine high-quality conversation using large language models and AI actions that generate sales and service outcomes due to our deep integration to the backend systems. And our tenfold acquisition also supports these integrations as a key pillar. And when we look at working with brands, I've been out with them recently, many of them talking about this. The biggest part they're looking for is the outcome of the action. What we're seeing in most things when it comes to large language models is we see that the conversation is natural and it gives good responses, but we don't see usually an outcome like a sale or service outcome. And that's where we really shine. We have over 250,000 APIs integrated into our system today that provide those outcomes. So as many of you watched on May 2nd, you may have also saw that we have plans to delivering AI in a different way, which we call an EIA framework. And the E indicates our commitment to AI that is equal, enterprise grade, and for everyone. And unlike what we talk about with open AI and just openness as a general term, we think EAI is much more focused on what our customers want in the enterprise. It takes the power of generative AI and large language models, but assembles them with the right data set and training that allows us to deliver outcomes in a safe and responsible way. And with the release now of our voice AI platform, we can integrate all of that into voice platforms like a Genesis or Amazon Connect or Five9. And this will help us accelerate what we set out to do seven years ago. As you know, I fundamentally believe that Traditional voice calls with agents was never the way of the future. And now we will accelerate those conversations to get automated at a very high rate. It's about a $60 billion TAM. And what I could see now is I think we can get to a place where 80% of those conversations can get automated, that we don't need human beings anymore taking those calls. And I think that'll happen over the next five years. So we're really excited about the opportunities. And obviously, all the work we did in the last couple of months is really about restructuring the business to be able to focus on this big opportunity. And obviously, we had to put a lot of effort into that restructuring. But now we can put 100% of our focus into growth. And that's where we are today. When we look at the quarter, we signed 70 new deals in the quarter, including four seven-figure deals, 50 expansions, renewals. 20 new logo deals, and we completed the restructuring of our go-to-market teams in Q1. We did put a focus on more and higher quality logos than we usually do in the mid-market and small business. We're shifting in that area because we see with this technology now, we can do a lot more transformation. So we are focused on that during the quarter, and that'll continue forth into Q2. We did sign a four-year, seven-figure deal with Europe's largest bank and financial services company. Our immediate goal with this brand is to plan a generative AI strategy that puts LP at the core of everything, how they engage with their customers and their employees. And they serve 23 markets today. I think what's interesting about this deal, it's our third, I believe, second or third renewal with them. And even in the face of everything going on with generative AI, they want to put it on a platform that can allow them to do it in a way that generates the outcome in a safe and secure way. And so I think it's just a testament once again of how are we playing in the market with this new shiny object and how do we make it real when it comes to bringing it to the enterprise. We also signed a seven-figure renewal deal with one of the largest multinational telecommunications companies in the world. This brand increased customer adoption of messaging with comprehensive use of our AI suite, like Conversation Builder, Conversational Assist, and Proactive Messaging. We're now going across care, obviously sales, retention complaints, and we're expanding our relationship with them once again as we expand using this new technology. We also landed a seven-figure renewal deal with a multinational financial services company and the largest bank in Canada. This brand doubled its LP investment in the spring of last year, leveraging our automation services. In four months, our automation already powers 35% of all their conversations, which is climbing daily as we optimize the operation with our dedicated automation team. Volume is critical for them, but also the quality of the conversations is what we deliver on a day-by-day basis. In that deal, we beat out Salesforce and Genesis for this engagement and are pleased what we're doing with them on deployment so far. Also important to note that one of our large Fortune 500 health insurance providers set a global goal to shift 50% of their call volume to messaging to achieve further operational efficiencies, providing meaningful upside to our engagement with the client. And this is also with, we're taking that volume out of one of the traditional contact center players. We landed a seven-figure deal with a large healthcare service provider. We'll begin their journey with web messaging and move quickly into IVR deflection and proactive messaging. Finally, a large retailer in the UK has embarked on a five-year transformational plan with digital technology playing a key component. Phase one is to deploy our technology for care, focusing on reducing the contact center costs. And then phase two is to remove one of the ticketing platforms and turn that into an asynchronous integration where we're delivering the large language models and delivering a better consumer experience than traditional ticketing. The final restructuring Q1 enables us to focus on driving profitable growth at a scale that will match the demand now in the market for enterprise AI. Now that we have that you know, restructuring behind us, we can return to focusing on all efforts on engaging the growth engines and bringing our new products and platforms to our brands. We're in a really unique position right now when it comes to generative AI and bringing it to the enterprise because of our history with them and our trust with them. And they've used these tools with us, so now they just want to accelerate the use of these technologies when it comes to scaling their operations, especially in the contact centers. But it's not only limited there. There's already a bunch of customers that are using us for, like, HR use cases and IT use cases. So I think as we see where we want to go with the platform, we will continue to expand into use cases that leverage what we've learned in the contact center to go after other business units. And with that, let me now turn the call over to John, who will discuss the financial results. John?
spk00: Thank you, Rob. The first quarter of 2023 was a transformative one for LivePerson's financial profile and growth strategy. As we committed last quarter, we completed one of the largest restructuring events in the company's history, enabling us to enter the second quarter with a profitable run rate and a focused go-to-market strategy for accelerating growth within the B2B core. Significantly, our restructuring plan did not simply pare back spend for the traditional enterprise sales model. Instead, we eliminated redundancies across sales and customer success and combined those roles with product and engineering talent to ensure the needs of our customers could be efficiently solutioned. By bringing customers closer to code, we reduced the meetings, ticketing, and scoping that were previously necessary. In addition, we sharpened our focus on the B2B core by providing transparency into recurring revenue and winding down non-core business lines, including divesting Kusama, which was the business underlying our consumer segment since 2007. We also strengthened the balance sheet by retiring at a significant discount, 157.5 million in principal amount of the 230 million in convertible notes maturing in the first quarter of 2024. As Rob discussed, our market is evolving rapidly, driven in part by the transformative capabilities of generative AI. The strategy and P&L changes that I just described have also enabled us to reallocate resources in this direction to significantly enhance our broader platform and immediately deliver better business outcomes for our customers. With the generative AI products we launched last week, the rate at which we can automate the consumer experience and reduce costs for our brands in both voice and messaging channels is incredibly exciting. Turning to first quarter and our results, in the first quarter, we generated revenue of $107.7 million, which was within our guidance range of $106 million to $109 million. However, as discussed last quarter and in Rob's remarks, we divested Casamba, the business unit underlying the consumer segment, on March 20, which means we did not recognize a full quarter of revenue for Casamba as contemplated in our prior guidance. Had we recognized the full quarter of Casamba revenue, our total revenue in the first quarter would have been $109 million at the high end of our guidance range. Given the divestiture, we will discuss expectations for the year on a normalized basis. that is, without the impact from CASAMBA. Excluding revenue from CASAMBA, we recognized $100.5 million, consistent with the high end of our normalized guidance range, which would have been $98.4 to $100.4 million. B2B core recurring revenue was approximately 82% of total revenue in the first quarter, and also consistent with the high end of our expectations. The improvement in revenue was primarily due to higher B2B core professional services and certain one-time contributions. Adjusted EBITDA was a loss of $1.3 million, which was better than our expected loss of $8 million to $6 million. In addition to higher B2B revenue, the overperformance in adjusted EBITDA was driven in part by the timing of expenses for sales and marketing and cloud migration, which we do expect to incur in future quarters. It was also driven in part by solid execution of our restructuring plan. Before turning to our standard reporting segments for the first quarter, Note that these segments still reflect declining revenue contributions from non-core business loans. With a B2B core revenue and expense trough in the first quarter and our restructuring plan fully executed, we expect an inflection point in the second quarter and sequential improvement for the B2B core for the remainder of the year. With that said, within total revenue for the first quarter, the B2B core recurring revenue component of hosted declined approximately 4% year over year. Revenue for the total B2B segment declined 17% year-over-year, and revenue from hosted software declined 25%. As discussed last quarter, the primary drivers of these declines are non-core business lines, including COVID-19 testing, gainshare labor, and pandemic-driven gainshare variable revenue. Professional services revenue grew 38% year-over-year, driven in part by the diagnostics project for the JV that we discussed last quarter. Finally, the consumer segment declined 21%. Had we recognized a full quarter of revenue from Casamba, revenue for the consumer segment would have declined 6.8% year-over-year. Given the divestiture, we do not expect to report on the consumer segment in future quarters. Again, we will discuss expectations for the year on a normalized basis without the impact from Casamba in the first quarter. Note that a full reconciliation is provided in the press release.
spk04: From a geographic perspective, U.S. revenue declined U.S.
spk00: revenue declined 21% year-over-year, and international revenue declined 9% year-over-year. Again, the primary drivers for these declines are the non-core business lines that we are winding down. Net revenue retention was below our target range of 105% to 115%, due in part to our focus on restructuring in the first quarter and increased downsells in our SMB and MMB market segments. Again, we expect sequential improvement in the second quarter and going forward. RPO decreased 18%, year-over-year to $368 million, due primarily to the wind down of non-core business lines, including professional services for the JV. Average revenue per customer was $665K, up 3% year-over-year. Note that this metric is based on total revenue, so the sequential decline from last quarter is again attributable to the wind down of non-core business lines, including gameshare labor and professional services for the JV. In terms of guidance, we achieved our expectations for the first quarter. and we remain on target for the year. Given our current visibility into the macro environment, we are reaffirming full-year revenue guidance range. Inclusive of Casamba revenue, the guidance range for the full year is $394 million to $408 million, or a decline of 23% to 21% year-over-year. Note that this growth compares to a full year of Casamba revenue last year. However, normalizing for Casamba in both periods, removing its impact, our revenue guidance range is $387 million to $401 million, or a decline of 19% to 16% year over year. We expect B2B core recurring revenue to be approximately 86% to 87% of total revenue for the full year. For full-year adjusted EBITDA, we are reaffirming our previous guidance range of $15 million to $32 million. As a reminder, part of the overperformance in the first quarter was due to the timing of certain expenses that we expect to recognize later in the year. Additionally, it is not necessary to normalize our adjusted EBITDA range for the impact of KASAMBA because no material contribution was originally expected. As for the second quarter, our guidance range for revenue is $95 million to $99 million, or a decline of 23% to 20% year over year. Note that the recurring revenue component of total revenue in the second quarter is expected to be approximately 87%. This implies a 2% positive growth sequentially from the first quarter. As a reminder, the sequential decline in total revenue from the first quarter is due primarily to professional services revenue for the JV that is not expected to continue, in addition to lower gainshare labor revenue. As for adjusted EBITDA in the second quarter, our guidance range is $3 million to $7 million, or a margin of 3% to 7%. Once again, with the restructuring behind us, we have reached an inflection point in the second quarter and expect sequential improvement in profitability for the remainder of the year. Finally, growth rate in the first quarter was consistent with the expectations we set last quarter for its core revenue to double for the full year of 2023. Before taking questions, I'd like to emphasize several key things. Solid execution of the restructuring plan that we discussed last quarter has enabled us to reach an inflection point for the B2B core revenue and profitability. After troughing in the first quarter, we expect profitable growth in the second quarter and sequential improvement going forward. Our line of sight to profitable growth is a function of three primary factors. First, a narrowed focus on our B2B core, coupled with rapidly growing enterprise demand for AI-driven transformation. Second, a more efficient and capable sales and marketing organization with integrated product and engineering support to deliver hands-on AI expertise to our customers. And third, generative AI enhancements across the platform, including in both voice and messaging channels, with the necessary guardrails and backend integrations to deliver better business outcomes for the enterprise today. And with that, operator, I'll pass it back to you for questions.
spk01: Thank you, sir. At this time, we will be conducting the question and answer session. If you would like to ask a question, please press star 1 on your telephone keypad. A confirmation tone will indicate that your line is in the question queue. You may press star 2 if you would like to remove your question from the queue. For any participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. And as a reminder, in the interest of time, we ask that you please limit yourself to one question and one follow-up. Thank you. And our first question comes from the line of Sidi Panigrahi with Mizuho. Please proceed with your question.
spk08: Hey, this is actually Dan on for Sidi. Can you just provide some additional color on the magnitude of the expense timing impacting Q1 and perhaps what that relates to?
spk00: Yeah, the restructuring event that occurred in the first quarter was the largest over the course of the last 12 months. As you may know, we've been rationalizing our cost structure since we entered 2022, and that culminated really in the first quarter. The key areas of consolidation and expense reduction were in our go-to-market organization and in part our technology organization as it relates to areas of the platform that we no longer need to support. The effective run rate for us in the second quarter, again, as a result of that restructuring, flipped us from a loss to a gain going forward.
spk08: Gotcha. And I guess just on the go-to-markets, consolidation. Is it possible to provide more detail on that, maybe your sales capacity going forward, and if that will allow you to re-accelerate revenue growth beyond this transition period?
spk04: Yeah, I think broadly... Go ahead, Rob.
spk03: No, go ahead, John.
spk00: Broadly, the restructuring allowed us to right-size the organization, and we have come away with a more efficient... sales and marketing organization, coupled with our product and engineering resources that allow us to be more responsive to the demands of our base today. And I think as we look forward, we'll hire according to the rate at which we continue to build pipe and respond to demand. So I think we're well positioned today to be responsive.
spk03: Yeah, we also, because of the nature of where the business is in our focus on the acceleration of AI. Obviously we did messaging then five years ago, we added the automation, but now it's all AI and I can double click on what that really means for us as a company. But we did a heavy restructure around the customer success org. And we ended up creating a new org, it's called LP1, and it's led by product and engineering. And so in the past we had more relationship managers Our customers want experts around AI and automation. So we did this big restructuring and removed a lot of those pieces, and we took product heads that are really key to the company, but now they're running customer-facing operations. Then we're pairing that with client partners that are really instrumental in driving revenue. So I think we're going to have a much better – you know, result in driving usage on the platform. But the bottom line is if you're going to show up as an AI company, you've got to show up with product and engineering folks versus the traditional customer success folks.
spk01: Okay, thank you.
spk04: Thank you.
spk01: And the next question comes from the line of Peter Levine with Evercore ISI. Please proceed with your question.
spk05: Hey, this is Gerard Verdon for Peter Levine. Thanks so much for taking the question. I wanted to ask how you might be thinking about capital allocation for the remainder of the 2024 convertible notes as well as the longer-term notes you have.
spk06: Thanks so much.
spk00: Sure. Again, we retired all but about $73 million of the 2024 notes. We, as we discussed in the prepared remarks, We expect to continue to accelerate profitability going forward and be cash flow positive exiting the year. So the balance of cash that we expect to end the year with will be more than adequate to both satisfy the remaining $73 million in notes and, of course, have ample operating capital to run the business.
spk06: Okay, that's all for me.
spk00: Did you have a follow-up?
spk06: No, thank you so much.
spk01: And the next question comes from the line of Jeff Van Ree with Craig Hallam Capital. Please proceed with your question.
spk09: Great. So a couple questions for me. I guess, Rob, one of the questions I get quite often, I know you're focusing more on the core businesses and trying to get away from distractions. And one of the businesses that I think most people I speak with don't find a tight fit with is Wild Health. So when you look at that business, You know, different end users, different sales model, et cetera. I didn't hear a lot in the prepared script here this quarter, but just talk about your thinking and how that remains a core product, given the differences between that and, say, the core messaging B2B customer care offering.
spk03: Yeah, I mean, we have a large group of healthcare companies in our core. And if you go back to what that is, it's a platform play. And as a matter of fact, they're working on some larger deals with healthcare providers to use that platform to drive scale in healthcare outcomes. So it was always looked at as like, you know, if you want to go into healthcare, there's a lot of expertise you need in that area, especially around regulatory and things, but they built a pretty tremendous platform. And now we've incorporated all the large language models so we can scale, you know, how a doctor or a healthcare coach can service customers at a different scale than normal. So for us, obviously, it's growing very, very large. Healthcare and AI, if you look at any other company out there on the tech side, they've got an investment in healthcare, almost all of them. And it's important as an investment. And I think in the future, we'll see some pretty massive returns with that product. But once again, it's We should look at it as a vertical play today. I think later on in the year, we'll be able to give some perspective on doing deals with these larger healthcare providers, which I think will allow the shareholders to get a better sense of how it plays into our overall strategy.
spk09: Okay. And then on the core business around the core B2B, understanding you're really leaning in on the AI side, But until that takes hold, and as I look at the Q1 performance, talk about the competitive landscape for the core B2B messaging offering. You were early to get there with automations. It looks like the AI slash automation rates were relatively flat this quarter. That, for a while, felt like you had clear sort of best-in-class platform. But the momentum on the booking side, revenue growth, I think you gave the NRR was below the 105 to 115 this quarter. Just talk more in detail about what's going on with that. Are you winning your share? Are you just not getting in enough deals? Why is that business not growing more?
spk03: I think it comes down to our focus. If I can go back and change things, obviously the things our customers got us into and we unwound and the restructurings that we did to get profitable, it's the focus to take out the amount of expenses we took out in 12 months to be here. and the team did a great job at that, and that wasn't easy. Obviously, the focus now is growth again. We're still signing large logos and large banks and all that. We signed renewals with some of the largest banks in the world, even though we're in the middle of generative AI, and it's because they trust us. So I think what we need to just show the world is that we'll get back to growth, but we shouldn't marginalize all the efforts it took to restructure the business over the last 12 months and the focus it took to do that and to execute on that. And so, obviously, the quarters going forward will be the judgment, you know, and how we can execute and grow the company. But I think we're in the right place, and we still have the gold standard of that platform. And now, you know, adding in all that technology we just launched, which is GA, will help us sort of grow. So that's our focus now. That's our one focus. We don't have to worry about restructuring anything anymore. We're done with that. That's behind us.
spk00: Jeff, I just want to add to the NRR comment that while we're below the range, the primary reason for that was increased attrition down market in small business and mid-market segments in particular, as we restructured and focused on the demands of enterprise and, of course, made it through the distraction of the restructuring. And we think going forward that the the down market, that lower end of the market would be better served by the enhanced product usability and platform self-service that you may have seen we launched last week. So we think there's upside there as we move forward. Down market and, of course, within the core of enterprise, it remains strong.
spk09: Given the scale really lies in the enterprises, would you expect the automation rates, the percent of messages being automated to rise, or how should we think about that number going forward?
spk03: Yeah, that's the big thing. There's no more bot building. As of last week, we don't have to build bots anymore, and the ability to automate conversations, especially the long tail, is there. I think I gave an example. Maybe on the last call I didn't, but we looked at all the airlines that we have, and we started to use the large language models to look at conversations that were happening with agents, and believe it or not, there were a bunch of conversations about bringing an iguana in. on a plane. Now, you would never build a bot around the intent iguana. But on our airlines, people are asking, can I bring in iguana? And we can handle that now with the models because it basically is just looking at the data set. So the rate of automation is going to really increase. The second part of that is that the actions that we can do on the platform, the automations are only as good as they do actions. And we've got all these integrations already. So, you know, these should be done at a very high rate, especially on the voice side. I want to finish what we set out to do, which is get rid of traditional voice. And with our voice AI launch, that's what we'll be focused on.
spk09: Okay, and the last one, just, John, I think you mentioned you covered a lot of ground there really quickly, but I think you mentioned there were some one-time items that affected revenues, and I think you were talking about B2B.
spk00: Yeah, in general, those are pretty small. The largest contribution for the first quarter was really core B2B professional services being up. And then in terms of one-time items, there's some catch-ups normal to big enterprise deals that we also recognize in the quarter.
spk04: Got it. Okay. Thanks for taking my question.
spk01: And as a reminder, if you would like to ask a question, please press star 1 on the telephone keypad. A confirmation tone will indicate that your line is in the queue. You may press star 2 to remove any question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. And our next question comes from the line of Zach Cummins with B. Riley. Please proceed with your question.
spk07: Hi, good afternoon. Thanks for taking my questions. John, could you talk a little bit more about the adjusted EBITDA upside here in Q1? It sounds like there were maybe some costs that were delayed versus when you were previously expecting. Sure.
spk00: Hey, Zach. In the first quarter, we had previously expected more marketing expense, for example, which ended up not being necessary for variety of reasons that we fully expect to deploy later in the year. That's a significant component. And then as we continue what is a complex migration to the cloud, there is expense that we expect to hit later in the year as well that did not occur in the first quarter. So those are the two primary drivers.
spk07: Got it. I understood. And Rob, just from your launch event of all your new AI solutions, it sounds like some pretty interesting opportunities if you can expand into HR and IT use cases. It sounds like you have a few customers that have gone down that route. Can you give any sort of early feedback that you've gotten from customers as you expand beyond just customer care with your AI platform?
spk03: Yeah, there's two parts to our platform. One is called Knowledge AI 2K. And the other one is obviously the large language models and the ability to generate the outcomes. But we now have the ability to put in like PDF documents, knowledge base. We've had this previously, but we enhanced it for the models. So you can take in all that data. It could be an employee handbook. It can be all of that. And you can put it into our platform and then instantly it gets prepared for the models. And when you look at all the tooling that you have to do to make generative AI work, it's real tooling. And especially around the data side, if you just put the data in it, the data could be formatted in a way that the model won't understand it. So we built a process for the model to understand that. So it opens up those use cases. And we already have a handful of large customers who use it for that, who have built automations on that. But I think the power, and if you were watching the event last week, the journey to be an AI company from a conversational AI company is one. And the first thing we're going to release in about eight weeks from now is a new interface to the data set. And this will allow anyone in the company to ask questions of the conversational data that we store. So imagine a person in marketing can say, like, tell me why people are not happy with this product today. Tell me, like, what's the best marketing campaign that I could build to sell this type of product? And that access to that data, and then what we're hearing is our customers want to put more data inside there, maybe medallia surveys and other things. This kind of shifts us into a different place when it comes to doing AI in the enterprise, but that could be in the HR side, it could be in the IT help desk side. So obviously we have a focus on continuing down the path of customer engagement, but that data set is important and the ability to put more data into the platform to go other use cases is also important. So that's what they can do today. And that's what's exciting about our strategy and what I think is very different from what people are trying to do out there.
spk07: Understood. Well, thanks for taking my questions and best of luck with the rest of the quarter. Thank you.
spk01: And the next question comes from the line of Arjun Bhatia with William Blair. Please proceed with your question.
spk02: Hi, thanks. This is Chris on for ours. And thanks again for taking the question. The first one for me, I wanted to get your take on the evolution of the competitive landscape going forward with generative AI becoming more and more common. So how to think about a live person's source of competitive advantage as elements make interacting with businesses through chat and natural language more accessible than ever?
spk03: Yeah, so if you look at how I think it's going to play out, take the next couple of months and then years, what the enterprise is looking for right now is safety and security. And so they want to start using this stuff tomorrow, but they need it on platforms that will allow them to adhere to the ideas of data sovereignty and security around that. And we've already provided that. So for us, it's kind of like one click, and we're guaranteeing that using these models are going to be done in a way that adheres to the principles of the enterprise, especially around data. So that's the one part. The second part is, what is an enterprise AI company, and what is it going to look like? And I think that play is interesting, which is that there'll be these desktops in the entire organization, and they're going to use this technology to generate business outcomes. What I believe could win the day, and this is our strategy, is that it starts with the data set. OpenAI gives you the data set of the Internet, and that's there. But the most valuable data set to the enterprise is the customers and the customer conversations. We go to work to understand our customers better. And so what I see in the upcoming years is the data set. And if you want to judge who could potentially win this horse race, it's who's got the best data set to generate a business outcome. And so for us, we're sitting on one of the best data sets. You can ask the customers questions. It's interesting, like in real time, you'd say like, ask the customers, what do you want from me? And I think that has a power to it and it's unique to us. So there's other, you have Salesforce out there now, obviously using it, what they're doing with their data set, which is CRM data. They have a lot of that. They do have some customer care. They have very limited conversational data like we do. There are voice companies out there, and I think they're the most susceptible for change because they have voice data. Some of it's transcripted, but a lot of it just remains in the voice, you know, in voice files. So I think you got to think about the language models become not commoditized, but we'll have our own soon. We're using others. I think the brands will create their own depending on the data set. And then the data sets themselves become the competitive weapon to being pervasive. So I think over the next five years or so, the winners could be these people who have these data sets. And I also think the acquisition model, there may be M&A in the future around data sets. Where do we get our hands on better data sets to generate those business outcomes? And so that's kind of how I see it playing out.
spk00: Yeah, Chris, I just want to underscore a key point that Rob made, which is that today there's billions of dollars spent by our enterprise brands on agents to field voice calls. And that's often the case because the intent, the desire that the consumer has to get resolved with the brand is in the long tail. not easily automated on yesterday's technology. That's no longer the case. And we're very well positioned given our platform that's heavily integrated into the backend systems of the brands today to deploy generative AI, to drive business outcomes today, uh, to, to kind of transform the cost structure that our brands, uh, currently have to run the service centers and, and even, um, to provide support on sales. So the positioning we have at this moment in time, as the data, as Rob said, but also the integrations and the processes that we've been refining for decades to help brands take costs out of their contact centers. And that's something that we can deploy and have deployed already as of last week.
spk04: Got it.
spk02: And then just one other thing I want to touch on, the gen-centered AI topic. Where do you expect that you would see kind of a short-term tailwind show up in the business? I know last quarter you talked a little bit about an uptick in demo volumes, kind of as customer attention is shifted towards things like open AI. Have you seen that translate to increased deal flow or sustained pipeline growth?
spk03: The short-term wins I see is that obviously the one we're turning on immediately is what we call making the agents more efficient so the agents don't have to type anymore. That's actually the easiest, safest way to deploy this technology. We're opening that up. That's on the platform now and every customer can do that. Also, there's summarizations of conversations. Normally, it's a manual process. Now, it automatically happens so that agents spend 45 minutes to an hour a day basically summarizing the conversations they had. And we already have this technology, but it's enhanced with the large language model. So that's the easiest one. The second one is automating the conversations fully. And so that's the next part. And that's also, there's some low-hanging fruit in there. And then I actually think the greatest low-hanging fruit, which will be out in a couple weeks, is this concept that, more than a concept, is the platform we're putting out. We call it Bella for Business, which is, the ability for the organization to ask questions of their data. And that's a safe thing to do. Like you can just ask questions and get outcomes. And a marketer could ask questions of their conversational data to understand how to market better. And that's an easy no-brainer. So I think there's some sort of base hits that we can get. Ultimately, the home run is we automate the contact center, like an 80% volume, and there's only 20% of that's with humans or humans in the loop. And then the other part is we become very pervasive in providing the generative AI platform that every organization can use to do business outcomes like HR and all that. That's what we're playing for right now.
spk01: We have reached the end of our call today, and I will now turn the call back over to Rob Lacascio for any closing remarks.
spk03: Yeah, so, you know, I started the company in 95 and in 97 invented chat. And, you know, obviously it's chat TPT, and everything is around this interface. And the vision of the company has always been around that these conversational interfaces would power commerce, care, and everything else. And we've been singularly focused on it for many years. Our time has sort of come. And I know we're all trying to figure out, I wish we were here without all the restructuring. And that creates a certain noise and uncertainty. But we're here. And we bet to be here. And there's probably a handful of us in the world, when you think about it, there's probably 10 of us in the world that actually can say that they can deliver this technology and this revolution into brands. And Like I said, in one way, I wish we didn't have to do the restructuring. And a lot of companies went through this because it'd be a cleaner story. But we're here. And we're here with one of the best products in the world and platforms. We've always been a leader at that. So right now, when I think about our focus, it's really in two areas. One is we need to finish up what we started. I talked about killing the 800 number and all that. And we need to complete that mission. And we will now with our voice AI products. And the second is, We need to take this platform and use our data set as a way to leverage and apply it to other business areas like marketing and sales, even HR. So that's what we're focused on as a company. The large language models in generative AI just gives us an accelerant, but we always had the vision. We're not chasing something right now. We were one of the pioneers in how this could work. So as shareholders, I'm excited for the next couple of quarters and how our company will get focused back on growth, how we'll get focused on, you know, continuing on our missions of providing conversational AI and then generative AI to the enterprise. And ultimately, I think that leads us to being, you know, the largest enterprise AI company in the world. And that's the bet we're making right now. So thank you for the support and we'll see you next quarter. Thank you, operator.
spk01: Thank you. This concludes today's teleconference. You may disconnect your lines at this time. Thank you for your participation, and have a great day.
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