Dan Rosensweig: Yes. It’s an awesome question. So 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 we hear about the schools that had maybe have lost now their prestige. But 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 stay schools and a very large percent 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 for the last few years and the 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 could 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 at Southern Hampshire University, which Dr. Paul Avancis 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 it. 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 those — and they’re very much developing their programs, and they feel more culturally align 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 benefit 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 — it’s hard to imagine countries that are sort of bigger for growth opportunities in 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 what we’re focusing on in terms of our messaging and where we’re putting our messages.
Hopefully, that helps answer it.
Operator: Our next question comes from the line of Eric Sheridan with Goldman Sachs. Please proceed with your question.
Eric Sheridan: Thanks so much 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 road map on a multiyear 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 or where the incremental investments will be made as you see some of those signals as we look out over the next couple of quarters.
Dan Rosensweig: Yes. Those are two very substantive questions. Let me take the second one first because 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 will be hard for you to look at expenses because they’re going to 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 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 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. Yes, 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 of doing it, all of those things is 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 mind what school are you at? Who is your professor. How does that Professor prepare? So we have years of history of when the mid-term 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 want to 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 mid-terms 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 kind 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, so we know students that major in this generally tend to work for these 10 companies and these 10 companies are looking through these skills. Would you like us to assess you on whether or not where you are on those skills, and then we can upskill them to, would you like 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 data sets will allow us to do that we believe no one else will be able to do.
Operator: Our next question comes from the line of Brent Thill with Jeffries. Please proceed with your question.
Brent Thill: Thanks. As it relates to Q1 guide, you’re guiding EBITDA down 24% year-on-year. And I think revenues guided to down mid- to high single digit. I think the question we’re getting is when do you return to health and growth on revenue and EBITDA?
Dan Rosensweig: 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 index, drive more customers plus promotional pricing. So what — 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 we — 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 because 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. And 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.
Operator: Our next question comes from the line of Jason Celino with KeyBanc Capital Markets. Please proceed with your question.
Unidentified Analyst: Great. This is actually Devon on for Jason today. Just one quick follow-up 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 STEM in 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.
