Greetings, and welcome to Chegg Inc.'s fourth quarter 2023 earnings conference call. At this time, all participants are in a listen-only mode. A question-and-answer session will follow the formal presentation. If anyone should require operator assistance during the conference, please press star zero on your telephone keypad. As a reminder, this conference is being recorded. It is now my pleasure to introduce Tracey Ford, Vice President of Investor Relations and ESG for Chegg. Thank you. You may begin. Good afternoon. Thank you for joining Chegg's fourth quarter 2023 conference call. On today's call are Dan Rosensweig, Co-Chairperson and CEO, and Andy Brown, Chief Financial Officer. A copy of our earnings press release, along with our investor presentation, is available on our investor relations website, investor.chegg.com. A replay of this call will also be available on our website. We routinely post information on our website and intend to make important announcements on our media center website at chegg.com/mediacenter. We encourage you to make use of these resources. Before we begin, I would like to point out that during the course of this call, we will make forward-looking statements regarding future events, including the future financial and operating performance of the company. These forward-looking statements are subject to material risks and uncertainties and could cause actual results to differ materially from those in the forward-looking statements. We caution you to consider the important factors that could cause actual results to differ materially from those in the forward-looking statements. In particular, we refer you to the cautionary language included in today's earnings release and the risk factors described in Chegg's annual report on Form 10-K, filed with the Securities and Exchange Commission on February 21st, 2023, as well as our other filings with the SEC. Any forward-looking statements that we make today are based on assumptions that we believe to be reasonable as of this date. We undertake no obligation to update these statements as a result of new information or future events. During this call, we will present both GAAP and non-GAAP financial measures. Our GAAP results and GAAP to non-GAAP reconciliations can be found in our earnings press release, and the investor slide deck found on our IR website, investor.chegg.com. We also recommend you review the investor data sheet, which is also posted on our IR website. Now, I will turn the call over to Dan. Thank you, Tracey, and welcome everyone to our 2023 Q4 earnings call. To start, I am pleased to announce the appointment of David Longo as our new Chief Financial Officer, effective February twenty-first, as Andy announced on the last call that he will be retiring. David has been our Chief Accounting Officer and Corporate Controller since coming to Chegg in 2021, and we look forward to his continued leadership in this new role. He is joining us on this call today, so welcome, David. Now back to the business at hand. Chegg had a good quarter and exceeded our expectations. The last few years have seen real challenges as we navigate the post-COVID world. Despite those challenges, it's actually an exciting time at Chegg, and I'm proud of the team and how they are navigating the complete reinvention of our company, leveraging the advancements in artificial intelligence and making it core to everything that we do. In less than a year, we redesigned our entire user experience, developed our own large language models, launched automated answering, built proprietary algorithm, algorithms to optimize the quality and accuracy of our exclusive content, and we began to compete more aggressively for new customers around the world. While early, our packaging, pricing, and product strategy are yielding encouraging results for both students and our business. The process of embedding AI into every facet of Chegg's platform is ongoing and iterative as we build a truly personalized learning assistant, a service that anticipates the student needs, adapts to their strengths and weaknesses, and supports them academically, professionally, and personally. There are numerous ways we intend to aggressively market our new product experience, because the data tells us that once a student tries us, they love us. Internationally, we focused our biggest effort on testing promotional pricing to convert the millions of students who have entered the funnel but did not yet subscribe. Additionally, we are building sharing into our service to increase word of mouth, expanding our presence on TikTok, and enhancing our SEO with increased questions from automated answers. Our business model benefits from more students asking more questions as we index those questions into search and other platforms to drive even more customers. Let me provide a little context. Since introducing automated answers in late December, we've seen a significant increase in the number of students asking new questions, as well as the number of questions per student. This is because our new automated service is delivering quality and accuracy almost immediately, which is a huge benefit to students. By building our own language models, along with our algorithms to check for quality, students can feel confident in what they are learning on Chegg and get support in real time. The impact has been immediate and significant. In January, Chegg's automated answers delivered more than 2.2 million solutions to students, which is three times the number of new questions asked and answered at the same time last year. Importantly, as we scale to ensure we meet our standards of accuracy and quality, we expect to launch the rest of our proprietary models by the end of Q1. These models are being trained on Chegg's data, and we are leveraging our 150,000 subject matter experts to optimize their solutions for learning. In education, students cannot afford the illusion of accuracy to learn. They need it to be correct, immediate, and personalized. We believe this is what Chegg can uniquely do for students, and it's a huge competitive advantage over generic AI models. The overall benefit of our new service to students is enormous, and there's also significant benefits to Chegg. As the hype of AI dies down, leaders in their verticals, like Chegg, are taking control of their own destiny by building their own models, which allows for higher quality and lower cost. As an example, the cost to answer a new question using our own AI models is already more than 75% less expensive, and we believe it will continue to decline over time. This means we'll be able to serve more students at a lower cost per student, faster, and in more subjects and languages. We are confident in the value of our new product, and because of that confidence, and to be more competitive, we began testing promotional pricing in international markets in the middle of last year. We believe that if we could introduce our offerings to more global learners, they would find the value and benefit of Chegg and continue to choose us and stay with us. In Q4, we saw year-over-year new customer growth outside the U.S. for the first time in two years. Just as important for our business model, more of these users are taking the Chegg Study Pack, which is our higher price subscription, and remaining paying customers for longer periods of time. We developed this pricing and packaging to be revenue neutral this year while we expand new account growth substantially. While it's still early, we are seeing encouraging results. Given the success of what we've seen internationally, we are now testing promotional pricing for new accounts in the U.S., which began in mid-January. As we have said, online learning support and skills-based learning are a huge market, and they are only getting bigger. AI is still in its infancy, and our product roadmap is ambitious and exciting. Throughout 2024, we are introducing more AI-driven capabilities, such as conversational chat, which continues to layer in personalization and interactivity for our learners. We also plan to integrate personalized learning tools such as practice questions, flashcards, and study guides to our conversational learning experience. Looking beyond 2024, as AI automated translation gets better and cheaper, we plan to expand the localization of our offerings to non-English speaking users. We also plan to build out more AI capabilities within Chegg Skills and integrate pathways for students with assessments and other tools. We are already seeing a reduction in the time it takes to launch new skills programs by approximately 40%, which allows us to offer new courses at greater speeds and will significantly reduce our costs. And the importance of skills-based training has never been more critical. In fact, half of recent graduates are questioning how prepared they are to enter the workforce, given the disruption of artificial intelligence. Employers agree, as 79% say that workers need more training to work with AI more effectively. The opportunity for Chegg Skills has never been greater or more important. There are a number of exciting opportunities ahead of us in 2024, and we remain focused on the following priorities: Returning to new account growth globally, maintaining strong margins and cash flow, rolling out the next phase of Chegg's enhanced AI services, and leveraging our momentum and skills for continued growth. Every decade or so, the pace of technological innovation accelerates and new growth opportunities open up. The history of the internet has shown us that vertical players who know their customer, have reach, proprietary content, and can provide a personalized user experience will win and win big. Given the strength of our brand, with over 90% of our customers reporting they are satisfied with Chegg's service, we believe we are well positioned to do just that in our sector. Before I turn it over to Andy, I want to again thank him for all he has done for Chegg during his 12.5-year tenure. Under his guidance, Chegg grew from a physical textbook rental business to a global online learning platform. When Andy took the job, Chegg was in debt, unprofitable, and we had a single business model, renting textbooks. Andy guided us through our transition to a fully digital business, and in doing so, grew our digital revenue from zero to over $700 million annually. In his final full year as our CFO, Chegg generated $222 million in adjusted EBITDA and $173 million in free cash flow. Thank you isn't enough to acknowledge the impact Andy has had on this company and on me personally. Andy, you leave quite a legacy at Chegg, and you will truly be missed. And with that, I will turn it over to you. Andy? Thanks, Dan, for those kind words, but more importantly, congratulations, David, on a well-deserved promotion, and I look forward to working with you as you transition into your new role over the next few weeks. Today, I will discuss our financial performance for the fourth quarter and full year 2023, as well as our outlook for the first quarter of 2024. As Dan mentioned, we ended the year on a positive note, with total revenue, adjusted EBITDA, and free cash flow all coming in above the high end of our expectations. While the year had its challenges, we executed well on our plan to reinvent the way we help students navigate their learning experience by leveraging AI, and we continue to see strong profitability and cash flows. This, along with the strength of our balance sheet, gave us the confidence to extinguish a significant amount of our debt at a discount and repurchase shares, which we believe have and will continue to enhance shareholder value. Looking more specifically at our 2023 performance, total revenue was $716 million, with subscription services declining 5% to $641 million. Total subscribers were 7.7 million, of which international subscribers were 2 million. Since 2021, international has increased from 11% of total revenue to 14% in 2023, or $100 million. And over time, we expect international to be even more significant. Skills and other revenue of $76 million declined 20% year-over-year. While skills grew 55%, this was offset by the impact of exiting the textbook business in 2022. We continue to take a prudent approach with expense management, and we were very pleased that we were able to deliver adjusted EBITDA margin of 31% or $222 million, and free cash flow margin of 24% or $173 million, which represented 78% of adjusted EBITDA. We expect interest income to contribute less in 2024 from a combination of lower interest rates and a lower cash balance as a result of the aforementioned repurchases. Looking at Q4, total revenue came in above the high end of our guidance at $188 million, which drove better-than-expected adjusted EBITDA of $66 million. Subscription services revenue of $166 million declined 6% year-over-year, driven by a decline in subscribers, which was partially offset by Chegg Study Pack take rate and a continued increase in retention. Skills and other revenue of $22 million declined 22%, as growth in skills was offset by the impact of exiting the textbook business. Looking at the balance sheet, we ended the year with cash and investments of $580 million and net debt of $20 million. This is the result of repurchasing $597 million of outstanding convertible notes during the year at a $92 million discount to par, and initiating an accelerated share repurchase, or ASR, in Q4 of $150 million, which reduces our outstanding shares by approximately 12%. We believe this prudent capital management will enhance shareholder value. We exited the year with 103 million shares outstanding, including the majority of benefit from our most recent ASR. This represents a 90% reduction in shares outstanding versus 2022. We believe our company is undervalued. As such, we will continue to look for opportunities to return value to our shareholders. Our business is somewhat unique, given our subscription model and the life cycle of a student. While we are seeing encouraging signs in the business, it is too early to predict when we will return to revenue and margin growth. The green shoots in engagement, acquisitions, and retention will take time to build our renewal base before we see a positive impact on total subscribers and revenue. In the meantime, we will continue to be prudent with expense management and prioritization while we continue to drive strong profitability and cash flows. With respect to Q1 guidance, we expect total revenue to be between $173 million and $175 million, with subscription services revenue between $155 million and $157 million. Gross margin to be in the range of 73%-74%, and adjusted EBITDA between $43 million and $45 million. In closing, I am proud of what we have accomplished during my 12.5 years at Chegg. This is, by a large measure, the best company I've worked for during my career. The mission, the culture, and especially the team, are second to none, and I want to thank everyone who was with me on this journey. In particular, a special thanks to Dan for your leadership, mentorship, and especially the friendship we have developed. It means more than words can say. Thank you. I can also say with confidence that the future is bright for Chegg, and as a long-term shareholder, I look forward to seeing the many future successes the team accomplishes. And with that, I'll turn the call over to the operator for your questions. Thank you. Ladies and gentlemen, at this time, we will be conducting a question-and-answer session. If you'd like to ask a question, you may press star one on your telephone keypad. A confirmation tone will indicate your line is in the questioning queue. You may press star two if you would like to remove your question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star key. Our first question comes from the line of Jeff Silber with BMO Capital Markets. Please proceed with your question. Thanks so much. Just wanted to confirm something you said in your remarks about rolling out, I think it was the new product experience, to other subscribers. And forgive me if I misheard you. I thought you said Q1, that would happen. Can you just confirm that? And is that included in your guidance, and how so? Yeah, this is Dan. I'm not—yes, we are constantly rolling out the new capabilities that AI presents, but the big one that we wanted for the quarter, we did roll out already, which is automated answers. And what automated answers does is it allows us to almost immediately answer questions that either we used to have to send to a human at a much higher price, or answer questions immediately that students wouldn't ask because they didn't want to have to wait until we actually gave them the answer. So we have seen a significant increase in the number of students asking questions and the number of questions per student. So I think we answered over 2 million additional questions than we got last year at the same time this year. So that was the big move for this semester. The other ones will roll out over the course of the year, but this is the one that we think has the most meaningful impact in the near term, because not only will it improve retention, but it will improve traffic and overall conversion and growth rate. So it's the flywheel that Chegg built itself on, but this is a dramatic acceleration of that. So I think where you may be thinking is when we said we were gonna roll out promotional and pricing in Q1 in the U.S. as a test. That's probably what I was referring to, and that's actually my second question. Can you talk about the order of magnitude of the promotional pricing that you've already rolled out internationally, and give us some framework of what we should be expecting in the U.S.? Yeah. Internationally, we started testing this last June, and our ambition, our belief was that as more students tried Chegg, that they would love it and retain. Because, you know, for the first time, we're competing against a large named competitor, ChatGPT, which has turned out to be less of a competitor than we were concerned with, and that's really good news. That is because they give an illusion of accuracy, but it's not accurate, and students cannot afford to have inaccurate, incorrect information. Plus, they don't go there to learn; they actually come to Chegg to learn. In order to actually master your subject, you have to learn it. We're built specifically for this; they are not. The more students that came to us and tried us, the longer they started to stay. So we rolled out promotional pricing there because we wanted to compete more aggressively for students that have never had a chance to before. That resulted in substantially higher conversion rate of people that were already in the funnel, of which we have millions that come in and register but had yet to convert. So this is beginning to pick up a number of them. Second, on average, they're staying substantially longer than they did before, so they're retaining longer. So all the things that we wanted to see, plus they're taking higher take rate of the more expensive product. So for outside the U.S., we've already returned to new account growth. And we expect to return to revenue growth much faster there because of just the volume of new accounts that we're able to bring in. So that gave us the confidence in the U.S. to want to test something similar to this. Now, the percentage of discounts outside the U.S. are higher than they are in the U.S. The U.S. discounts, that we're testing or promotional pricing, they range from about 25%-35%. And, and we have the opportunity to raise them back to full price whenever we think it's appropriate, if that makes the most sense to do. So we're testing that to a percentage of our new customer audience in the U.S. only. This does not affect any of the existing business, any of the existing revenue. We have ways to block cannibalization. This is a new customer promotion only. And so the tests range from 25%-35%, and it's only been 3 weeks, but the results so far in terms of what's measurable, which is conversion, is up, and take rate is up. The next big metric that we want to look at before we determine which of the tests makes the most sense, because we're running 3 different prices in 5 different variants, because we like to do things and know the answer to it before we roll it out to the full audience. So right now, so far, so good, but we have a couple of weeks more to go to see how retention works in month 1, month 2, month 3. And then, depending on what that yields, we can determine if, when, and how much we want to roll out in new promotional pricing for the second half of the year. But so far, really good result, and outside the U.S., really good result. All right. Thanks so much for the color. Andy, again, thanks for all your help and best of luck. Yeah, thanks, Jeff. Our next question comes from the line of Doug Anmuth with J.P. Morgan. Please proceed with your question. Hey, it's Bryan Smilek on for Doug. Thanks for taking my questions. Just to start on international, can you just talk a bit about more what drove the inflection back to growth there and what the next steps in international are? I guess just on a market-by-market basis, did anything stand out in particular, or was it just broad-based recovery? Yeah. So what drove it there was, what drove it and what's driving it are gonna be a combination of the brand new product experience. So the way our business grew initially and so large. You got to remember, only a few years ago, in 2019, total revenue for our subscription services was in the $200 million range. Now it's close to $700 million range. So we have grown quite substantially. The challenge was we, we grew so much during COVID, and now we're coming back down to the realization of where we, where the base is that we can grow from. And we believe that that's what we're experiencing this year. So outside the U.S., the new pricing promotion allowed people who were nervous about trying Chegg because we're not as well known there, to cross the chasm and then ultimately subscribe. Because the promotional price is lower, they're actually staying on longer, which is exactly what we hope for. On top of that, the long-term flywheel is the way Chegg works: the more customers we have and the more new questions that they ask, not ones that are in their existing database of 100 million already, but new ones that they ask. They then get indexed into search around the world, depending on which country they came from, and then other students search, and they find them, and then they come into Chegg. So we're seeing an improvement in traffic, traffic from new questions, and then holding our conversion rate. So that's those two things together, which is promotional pricing and the ability to rebuild the flywheel, those are driving the new growth, and they're just driving them faster outside the U.S. because it was a smaller base in which to start from. But we are anticipating that we'll see the same kind of success inside the U.S., a combination of the new products. When students are asking, last January, a year ago, January, we had about 500,000 new questions that we were able to answer on behalf of students. All of them went out to humans. This year, we had the same number that went out to humans, but we had another 2 + 2 million that went out that we were able to answer through automated answering, which is our big AI move to start with the high quality, and that's driving more traffic and more conversion to Chegg. So that's a bigger hole that we need to fill, but we're on our way to filling it. Got it. Did any markets stand out in particular, or was it just broad-based recovery? Yeah, no, it's everybody has done a lot better outside the U.S., but we're starting on very different bases. So the larger bases are the English-speaking countries, because everything we initially did was in English, but one of the other real benefits of AI. So AI, AI is moving from a headwind to a tailwind for us because it's allowing us to build a better product, allows students to ask more questions, answer them faster, index them, get more traffic, and convert more traffic. And because our quality is unique and we work with our own large language models rather than external models, the cost of it is substantially less. So as more countries come online and more students can ask in more languages, because translation will really be towards the end of the year and into next year, because AI will allow for automated translation. So, you know, in terms of growth rates, you see countries like India finally taking off for us. But you see the largest countries that Chegg has historically had, like Canada, Australia, and the U.K., those are still our largest countries, and they are also growing again. Great. Thank you. Yep. Our next question comes from the line of Kunal Madhukar with UBS. Please proceed with your question. Hi, thank you for taking my questions. One, on the new product rollout, I thought the new user experience had rolled out in, like, Q3 of last year. So when you're talking about this new rollout in 1Q of this year, what exactly has changed? That's one. And second is, in terms of the promotional pricing, how long is the promotional pricing? So the 25%-35% discount, is it just for the initial month, or is it for a few months? Thank you. Yes, good questions. I'll answer the first one. Let me answer the second one first. Which is outside the U.S., the promotional pricing, we expect to continue for the rest of this year and determine whether or not we want to raise the promotional pricing to the normal pricing and when we want to do that. That's all things that we are testing now. So right now, the promotional pricing is only for new accounts. And it will go on as long as we determine that it makes sense for it to go on. So we don't really have a final answer on that yet. However, outside the U.S., the combination of the number of new accounts that we're getting versus what we were getting before, the higher take rate of the more expensive package and the length of time, means that we expect revenue to grow despite the fact that we're giving new accounts this promotional discount. Inside the U.S., we are really just at the beginning of testing it. We've got about 5 weeks of testing, as I said, in 5 different variants of 3 different price points, and all of them are performing as we would have hoped. And so, you know, we'll be able to determine if we want to roll it out to the full audience, and if so, how long we want to do promotional pricing. Those are all testable things, where the goal, obviously, is to grow as fast as we can from a revenue perspective and new account perspective. So we'll look for that balance, but we have time to figure that out, because it's really early. On the question over product, no, the answer is we did not roll anything out of Q2 last year. We rolled out in the second half of last year, was a very, very small beta test where we tested the new interface, and we tested search and the search results and the quality of those search results. Then we made the determination to expand that from 1% to 10%, 10% to 25%, 25% to 50%, and then at the very beginning of this year, rolled it out to 100% of our audience, the new user interface. But it was not rolled out in Q2. We've tested a bunch of things since the inception. You got to remember, we only really made this decision last February. It's only been a year since we did all of this. So we announced things like our relationship with Scale, that allows us to build our own large language models. And we've moved off of OpenAI so that we can build our own, and it's a lot cheaper and all those things. So a lot has happened between now and then. The big move started really in the testing of automated answers started towards the end of Q4, and then really rolled out in the first quarter of this year, really just in January now. It's just been a spectacular success in terms of utilization of it, the quality of it, and we have a lot more to go. The hope is that, you know, by the end of 2024, the overwhelming majority of questions will go through automated answering rather than humans, and that will continue to substantially lower our cost per question and reduce our overall CapEx over time on an annual basis. Thank you. Our next question comes from the line of Josh Baer with Morgan Stanley. Please proceed with your question. Great. Thanks for the question, and Andy, congrats again on your retirement. Wanted to ask about the trajectory of revenue per subscriber. I was just hoping you could kinda unpack some of the different factors. I mean, we've talked about some of them, but basically, you know, how are you thinking about the trajectory of revenue between, you know, the growing mix of international, the promotional pricing broadly? Is there still runway for the study pack bundle attach? And then, also just thinking about the amount of time that a student has their subscription turned on in a given, you know, year. Thank you. Yeah, all terrific questions, and exactly why we test, so that when we're ready to give an actual answer, we can. What I can tell you is, outside the U.S., where the test has been... Well, it's not a test now, it's run- it's been running now for about seven months. What we look for is, first thing we look for is conversion increase, and that happens or it doesn't happen right away. In this case, it happened. Depending on the rate of discount and the country and where we were priced before, saw different conversion rates, all of them up nicely. It's very hard to make up the promotional pricing discount just on conversion, so that the next variable you look at is take rate, which is also measurable right away. Yes, there's room to grow on the take rate, particularly as we start to differentiate the capabilities inside of Chegg and Chegg Study Pack, more based on AI capabilities, and other kinds of things that we can offer in the more expensive one that has not started yet, and probably will not start the rest of this year. But yes, there's room to move because we still have more than one out of two that don't take it. That's the second variable. The third one that has the greatest amount of impact, because, you know, it starts from your net paying customers, your net subscribers, which have to do with your renewal base. We are seeing a very nice uptick in the length of time that students are staying. So in a perfect world, we would make up the revenue per customer and get as neutral as we could to revenue per customer. And over a multi-year period, we believe that's exactly what's going to happen. But in the short term, particularly outside the U.S., the volume of new customers and those other variables together will generate revenue growth outside the U.S., even though on a per customer basis, it's still not equal yet. But it's very early. We have multiple retention periods to go through, a number of years to go through. And so that's what's been going on outside the U.S., has been really positive. Inside the U.S., the plan—what we are doing is we are testing and the first measurement, so it's not to 100% of the new accounts, it's only to a percentage of them, but it's only to new accounts, so it doesn't affect any of the existing revenue. Then, as I said, there's five variants with three different price points, and that has to do with presentation of it, is why there's five. And then what we do is we narrow down to the ones where we see the desired conversion, the desired take rate, and in a couple of weeks, we'll actually see how it improves retention. Depending on how month one retention improves, and then month two, month three, and month four, all of those hopefully get us closer and closer and closer to a break-even on revenue per customer with a lot more customers. That's the objective. So we have lots of room to grow, lots of optimization to do, and again, the test is now three weeks old, but the first two hurdles are really good, which is driving increased number of overall customers versus what we would have done had we not done it. Because we believe that in a competitive market, we wanna go- we wanna go fight for the market share, because frankly, nobody else is anywhere near as good as we are. And once students realize that, they stay on and they use us more. And then when you launch the new product stuff, which we have, with automated answers, as an example, this is the highest engagement on a per customer level we've ever had. And, if it works as we hope, which is to regenerate the flywheel, more customers, more new questions, more new questions go into search. More students that haven't used us go to search, find it, or TikTok or wherever we put it, drives in customers. All of those things so far have been positively impacted, but the overall objective is get as close as you can to revenue break-even on a per customer basis because you've got those variables. Then in year two, or whenever we choose to get rid of promotional pricing, we raise the rates on those existing customers. So the revenue on those customers goes way up, and that, we'll be testing that to determine cancellation rates and all those things. But the business model is very, very sound, and, but we have to do it one brick at a time, and we've done the first two bricks, which is conversion and take rate. The next one is retention, and then what can you raise it to when you want to come out of promotional pricing for the customers that took it, and how long do you want to keep promotional pricing for new customers? But right now, better to fight for market share and make sure people don't come away with the conclusion that ChatGPT is a better solution than us, 'cause it's not. Great. Thanks, Dan. Okay. Our next question comes from the line of Ryan MacDonald with Needham & Company. Please proceed with your question. Hi, thanks for taking my questions. Andy, best of luck in the future, and, David, congrats on the promotion. Let me just start, Dan. Can you talk about sort of, it sounds like there's some real benefits here on the automated answers in terms of cost savings, and, and how you're answering questions. Can you talk about the mix of, I guess, the overall questions that are being answered today by automated answers, and then perhaps what we need to see that get to as a percentage of the total questions for that to start to translate into some margin expansion, relative to sort of what the first quarter guidance implies? Thanks. Yeah, that's exactly what we're looking at. So what you should be looking for, what we should be talking about, and what we will be talking about over the course of the year, we didn't really know where to start talking because we didn't know how popular our automated answers would be and how quickly it became this popular. But, as we articulated in the prepared remarks, already the cost of answering a new question is 75% less, simply based on the, the tailwinds that we're getting from AI. We call it automated answers, but it's, it's a result of us taking our own large language models and developing our own answers. We have a quality algorithm, so right now, you won't see much in the way of savings in the first part of the year because we haven't fully rolled out all of the different large language models. The expectation is, over the course of this year and by the end of this year, the overwhelming majority of all new questions will go through automated answering, and there'll be fewer and fewer going through human answering. So you should begin to see margin expansion towards the end of the year as a result of... Well, you really see a CapEx reduction first, right? Which is the amount of money that we spent on content has been coming down, but it's gonna come down again this year and then substantially in 2025. So we can answer 10 times as many questions for the cost of 1 question, is a way to think about it. But we have to get all the large language models out so that we can, and the quality at the level that students expect from Chegg, that they don't get from ChatGPT or Bard or anybody else, and that will take the rest of this year to do it. And we're very excited about it because it will be a meaningful improvement in our ability to pay for content and have super high quality and, as I said, also generate the flywheel. The other real benefit is the more questions that get indexed, the more people find us, and we don't have to pay for that traffic, and it comes in. So that's the way Chegg was originally built when we first built expert Q&A. And it's just gonna be a lot faster now because just the volume of questions that we can answer. I don't think we've ever answered 2 million questions in a month. And that's just the month of January, which really doesn't get started till mid-January. Super helpful, I appreciate that, Dan. And then you talked about in 2024, a growth priority is, or one of the priorities is obviously that platform returning back to growth. Sounds like the promotional pricing is gonna obviously help with that. But as you think about the macro, how important is sort of enrollment within colleges and universities to driving that return to growth algorithm for Chegg? And sort of how do you- how are you sort of building that into your sort of assumptions for this year? Yeah, look, of course, it has an, it has an effect. It's just not the biggest one. And I know people think that it is, and I can understand why they do, frankly. But let me just, let me just sort of size to you, just U.S., because outside the U.S., it is just, it's wide open, right? We jumped during COVID, then sort of stopped when things got out of COVID, then ChatGPT launched and had, a beginning of an effect. But the new products and the new automated answers and the new indexing of the questions, the promotional pricing has reversed that course outside the, outside the U.S. So... Yeah, so when you think about enrollment, last year, or on average, in a given year, Chegg will have over 10 million students in the U.S. that will register for Chegg but not convert. And so we have that whole universe to go after that has nothing to do with the roll. So we think the near term, the goal is to get those people to cross the chasm into becoming loyal Chegg customers because our retention rate is so high, because our quality is so good, and now with the immediacy of the responses at high quality, which no one else can give them, we think that's the key to growth.... So enrollment will matter over time, but right now there's a big group of people that are right in front of us. Our next question comes from the line of Brian Peterson with Raymond James. Please proceed with your question. Thanks for taking the question, and a well-deserved congrats to Andy and David. So I wanna follow up on Ryan's question. You've done a lot with the platform this year, and you've done that with R&D dollars actually being down year over year. You know, I see the opportunity for automation, but also mentioned scaling to different languages and time to roll out the LLMs. I'm just curious how we should think about the puts and takes to R&D intensity in 2024, maybe how that arc should look longer term. Thanks, guys. Yeah, really, really good question. So hopefully for those people like you that have been tracking Chegg for a while, you see we try to be very, very efficient with our capital. And so if you take a look at OpEx, OpEx has not grown substantially in the last couple of years, and it's been relatively flat, and we expect it to be relatively flat again for this year. And yet we have 250 people now working on AI, and that is because we have a history of reallocating resources against the things that have a priority, and either stop doing the things that no longer matter as much or where they're at scale and can survive with the number of people that we have on them. Same thing goes through with our sort of capital expenditure, which is the overwhelming amount of capital that we spent was on content. So we're not at, like, there. I think there's some confusion because we said last April that we have a partnership with OpenAI, and so it's easy to have made the conclusion, this is really on us, that, you know, we have big API costs. We don't. We have moved mostly off, and we'll almost be completely off OpenAI shortly because there's now a lot of different alternatives, and they're a lot cheaper. But more importantly, so the real cost is sort of GPU costs and other things like that. It's not... And so the overwhelming cost that Chegg has in CapEx is always gonna be content, and since the cost of content is dropping significantly, it's already down 75% based on automated answers versus human answers. So the next big step is to get off more human answers, which we hope to do mostly by the end of the year. So the way to think about it is you can assume our capital this year will be much better, much more efficiently spent, because AI is allowing us to spend it a lot cheaper on a per-question basis than we ever could before. So we are not holding back investment. It's just, we can get a lot more for our money now, thanks to AI. It's one of the, one of the great benefits of having moved as quickly as we moved. Operator, is there another question? Yes. Our next question comes from the line of Alex Fuhrman with Craig-Hallum. Please proceed with your question. Hey, guys. Thanks for taking my question. Can you talk a little bit about your core customer today versus a few years ago? It sounds like the biggest change, given everything going on with AI, is that maybe some of your more casual users at the margin who might, you know, pop in for a month or two around final or midterm exams have kind of, you know, maybe looking at other AI-powered options. Can you talk about the types of students who have stuck with Chegg? Are there any major call-outs, you know, now versus a few years ago in terms of your core student, in terms of either age or, you know, full-time or part-time status or field of study or two versus four-year schools? Anything like that, you know, you're focusing on a little bit differently versus a couple of years ago? Yeah, it's an awesome question. So, you know, for those who haven't spent as much time as you have on this, the overwhelming percentage of students in the U.S. go to state schools. So, you know, we hear about the, you know, the schools that have, maybe, lost now their prestige. But, you know, that's a couple of hundred thousand people versus 22 million, so they're not a big percentage. The overwhelming number of students in the school go to state schools, and a very large percentage of them go to community colleges. As an example, 10% of all students in this country go to just one community college system, which is California. So over 2 million students go to community college. The average age of a student is about 25 years old, and about 25%-26% of them already have children. The biggest growth areas for where students are going, they are shifting into three or four very large buckets in very big numbers. So one of them is online. And so our focus on making ourselves more visible to online students has been a focus the last few years and one that we want to accelerate, and we really do believe that automated answers will help us with that because we'll be able to have a lot more things that people can be searching for in search. So we're hoping for a boost through that. So I think the largest school in this country that's a not-for-profit is an online school. I think it's Southern New Hampshire University, which Dr. Paul LeBlanc is on our board, so we know a lot of information about that. So they've actually grown their enrollment substantially year over year because more people are not going to get degrees, they're going to get particular courses. The second big growth area that the country is seeing is a real move to giant state schools with incredible sports programs. So students are determining the value of graduating from school A versus school B is not significant in their career path, so they'd rather go to a school where they can enjoy themselves. And that's exactly what they tell us, by the way. So we're not speculating on that. It's what the numbers show, and it's what they have told us. The third big area is, students of color are gravitating, as you might imagine, to HBCUs, and the reason is they finally got funded by the government. And they're very much developing their programs, and they feel more culturally aligned there. So those are three big areas now where we're spending more of our time trying to figure out how to reach them. The other thing is, even though more students every day are taking STEM-B classes, one of the other benefits of AI for us is you can ask a question, increasingly so on Chegg, that is outside of STEM-B. And as we build that out, we'll be able to expand our U.S. TAM, even a little bit more. And then, of course, the giant TAM is outside the U.S., which is not what you asked about, but that is, you know, it's hard to imagine countries that are sort of bigger for growth opportunities than India, the Philippines, Mexico, places like that. We already are seeing really good results as a result of the promotion in those places, and we expect over the next several years to really try to optimize around growing in those countries. So that's, that's what we're focusing on in terms of our messaging and, and where we're putting our, our messages. Hopefully, that helps answer it. Our next question comes from the line of Eric Sheridan with Goldman Sachs. Please proceed with your question. Thanks so much for taking the questions. Maybe two, if I could. On your own LLM, can you talk a little bit about what you're most excited about in terms of how the LLM will evolve and what it means for product and roadmap on a multi-year view, as opposed to just this sort of V1 of the LLM, and sort of how it might get smarter, how it might change, how it might result in different elements of pricing dynamics on the platform? That would be number one. And then in terms of generating the flywheel effect that you talked about and referenced in the slides, can you just go into a little more granularity of what we should be watching for, of where the incremental investments will be made as you see some of those signals as we look out over the next couple of quarters? Thanks so much. Yeah, those are two very substantive questions. Let me take the second one first, 'cause I can remember that one. So what should you be tracking? So as I said, our expectation, and of course, expectations can change, and as we learn more, we always share more. Sometimes we share too much, like our concern that OpenAI would take more customers than it has. So but in this case, we have fought back and we're battling back, and we think we've got the things in place to compete quite effectively. What we look at is how many students are asking questions and how many and what kinds of questions that they are asking, and do those questions resonate with other students that go into search or TikTok, and will they generate more traffic for us? That's the flywheel. It'll be hard for you to look at expenses because they're gonna be relatively flat in CapEx and relatively flat in OpEx because of the efficiency in which we move people into different roles or move our capital expenditure to things that work better than the things that were working before. So it won't be that obvious for there, but I think you'll hear from us a number of students that are asking questions versus the past, number of questions per student, overall number of new questions being asked and answered by automated questions. And the greater percentage that are answered by automated questions, the better it is for our cost structure on CapEx. And then, you know, we expect, as we get more comfortable with the certainty around these things that we're learning, that we'll be able to put out a longer-term forecast, which we can be measured against more readily. We're not there yet because all of these are so new. But as you saw from the last three quarters, we have beaten the expectations we put out there, and that's building more comfort for us. But I think automated answers and the new pricing and packaging, we'll learn a lot more in the first half of this year. So you won't, you won't be able to see it sort of in where the expenditures are, but the expenditures over time should be flat to down. So the question on LLMs improve over time. Yeah, that is, that is an amazing question, and I'm not sure even I understood just how much they can evolve and how quickly they can evolve and how useful they are when they evolve. So the speed in which we can answer a question, the types of questions that we can answer, and the cost to doing it, all of those things, as the LLM learns more, get better. The second thing is the personalization that we can do on a per-student basis. So there's data beyond just the question and the answer. There's data that gets mined. What school are you at? Who is your professor? How does that professor prepare? So we have years of history of when the midterm is, when the final is. So imagine a scenario on a per-student basis. This is over time. This is not this quarter. I don't wanna confuse anybody, but it is what the LLMs will enable us to do and what we're working towards. We'll be able to go like a coach and say to the student: "Hey, we know your midterm's coming up in two weeks. Do you want us to build you a schedule of how to study? Do you want us to build you a unique practice test just for you?"... And we can do it not just based on the subject, but based on the individual and the professor themselves, because we have all the data of what that professor does and when they do it, the kinds of things that they ask, because we have all these years of history already in our data set. Those are the kinds of things that are unique to Chegg that can differentiate. We think those things create value in terms of going back at some point to pricing power and second, retention, and expand out to the kinds of things that we can do. So another example is things like, we know you go to this school, you go to University of Arizona, and we know that students that take these classes major in this, and we know students that major in this generally tend to work for these 10 companies, and these 10 companies are looking for these skills. Would you like us to assess you on whether or not where you are on those skills? And then we can upsell them to, would you like us to teach you those skills so that you can get a certificate that shows that you're actually competent in it? These are things that our own LLMs and datasets will allow us to do that we believe no one else will be able to do. Our next question comes from the line of Brent Thill with Jefferies. Please proceed with your question. Thanks. It's related to the Q1 guide. You're guiding EBITDA down 24% year-on-year, and I think revenues guided down mid- to high-single-digit. I think the question we're getting is, you know, when do you return to health and growth on revenue and EBITDA? Well, I'll answer the second part of that because I'll be here going forward, and Andy is already in retirement. But I think you can answer why the model is what it is in the first quarter. So, we are not prepared today to say when we will return to that. We do feel comfortable in saying we will return to that. And, because of AI going from a potential headwind to a tailwind, we think we'll be going to that sooner than we otherwise would have, because of our ability to have more questions asked, have them indexed, drive more customers, plus promotional pricing. You know, in the next few quarters, we think we'll be more able to articulate when we think that happens, but we're absolutely currently on the path to do that. And, you know, our margins, we think we can return back to where our historical margins were. This is a company that should be able to grow, and starts with the fact that we started with fewer net customers this year than last year because of the people that rolled off and the post-COVID and all the other stuff that we were dealing with. So we have about 9% fewer customers starting this year than we did last year. What you'll be able to track over time, 'cause we report our net customers every quarter, is you'll see that gap, assuming we do our guidance, you'll see that gap continue to close. That's how you'll see and be able to estimate when we'll be able to return to growth, but we're on that path. Our next question comes from the line of Jason Celino with KeyBanc Capital Markets. Please proceed with your question. Great. This is actually Devin on for Jason today. Thanks for taking our question. Just one quick follow-up on, on Ryan's question, also on automated answers. I think in terms of the questions, being answered by automated answers, are these more within the, the STEM and business subjects, or have you seen, automated answers also having the ability to provide quality responses to maybe the non-STEM subjects that I believe is an area that's a little bit, less penetrated for Chegg? Yeah, terrific question. So let me start with the initial questions. There's three parts to that question. The first one is, what are students already asking us? Those are because the people that are already with us are STEM students, they're asking deeper questions that AI allows us to answer, and the next phase is gonna be conversational nature, which will be really fun and helpful for the students 'cause, 'cause we'll be able to ask them questions in addition to them asking us questions. So the first one is they're going deeper into the categories that perhaps might have been really cost inefficient for us to try to answer them because they're deep into subjects. So that's the first thing. The second one is, yes, we absolutely are building it to expand beyond STEM as students ask that. The third part, though, is we have to be comfortable that we can answer with the same quality and accuracy that we can answer other questions, and that's just gonna take the course of this year to get ourselves more comfortable. We're focusing now first on the 26 subjects we have and the 52 LLMs that we're building, for each of those subjects, and then we'll move to, outside of where we currently are. But that is absolutely part of our roadmap. It's just not part of the roadmap today. There are no further questions in the queue. I'd like to hand it back to Dan Rosensweig for closing remarks. Thank you, everybody. Just to repeat, it's been a complex last several years with COVID, then post-COVID, then with AI, other variables. The company is in extremely strong shape despite that, which is we generate a lot of profit, we generate a lot of cash flow, and we are, well, we, we are, you know, moving back to net cash positive on our balance sheet. We've been really efficient with our capital, and we expect to continue to do so. But the real opportunity is rebuilding the flywheel with the new product, new service, new automated answering, and AI moving from potential headwind to absolute tailwind on growth and costs. And so it is a very exciting time. It's not easy. These things are moving very fast, and the speed in which we're moving is faster than we've ever done. And so I just very much look forward to the rest of this year and the future because we've got a lot of good momentum ahead of us. It's just gonna take time, and we have to rebuild the base of net new accounts, and like I said, you'll see that every quarter if we execute well. And of course, I want to welcome David Longo to the role. We brought David in a couple of years ago with the hope and expectation that he would fill Andy's role. Nobody can replace Andy. And to Andy Brown, I say that, I've never had a better partner, a better work friend, and Chegg would not be where it is today had you not joined, had you not made the decisions that you've made and backed the people that we've had and hired the people that we have. So your mark is indelible, and, thank you, my friend. Thanks. And thanks, everybody. Talk to you next quarter. Ladies and gentlemen, this does conclude today's teleconference. Thank you for your participation. You may disconnect your lines at this time, and have a wonderful day.