Andrew Brown: No, Dan, I think you nailed it. I think — and Jeff, you’re aware, obviously, the season start to pick up, like Dan said, in the next couple of weeks. If we continue to see the trends we’ve seen over the last few months, that will certainly give us more confidence, but we need a few more periods before we get to that point.
Jeffrey Silber: Okay, fair enough. Thanks so much.
Operator: Our next question comes from Eric Sheridan with Goldman Sachs. Please proceed with your question.
Eric Sheridan: Thanks so much for asking the — for allow me to ask two questions, if I could, quickly: One would just be the cost question. So when we talked three months ago, you laid out a strategy around CheggMate and OpenAI. With this new strategy, how different is the potential cost or investment implications for this approach versus the prior approach? And how should we sort of bring that back and reflect that in cadence of either margin or needed to invest in the business? And then I’m just a little bit unclear. So the second one will be a follow-up. When people go back to school over the next month, this will be a solution that builds momentum as you get deeper into the year and the solution you’re talking about today would be more implemented towards the end of this calendar year and the beginning of next calendar year? Or will it be deployed over the next one to two months? Just one would be timing and one would be depth of investment. Thank you.
Dan Rosensweig: Yes, I’ll handle the second one first, and then I’m sure Andy is going to want to handle the depth of investment, which I think you’re going to be happy with the answer because we are. But on the second one, consider it just a forever rollout, which is the product is just going to get better every day, let students use it. So Depending on what subjects they use or what they use it, they will see the product evolves. So it really is that way to think about it, which is they’ll start to experience certain aspects of the conversational nature and the generative AI kind of content, depending on the subject matter they’re doing, they’ll start to experience that in the fall. So it’s a little bit like rolling thunder and we expect word of mouth, viral nature of it, all the things that have built Chegg over the years to start to spread over that period of time.
But I think right now, what has spread is the quality of our content and the accuracy of our content, which are essential for people trying to learn. So I’ll let Andy talk about the cost structure and the cost. But I think again, I think you’re going to find them to be constructive and positive.
Andrew Brown: Yes. So when we talked about this on the last call, there was a lot of moving parts. And there still is to some extent, but as we evaluated the multiple options that we had as far as having a fully generative — conversational generative experience for our students. When we evaluated this, the option of partnering with Scale AI became by far a few things: One is it made us get to market sooner and it was the lowest cost versus completely leveraging third-party technology. And so as we look at this, this is by far the least cost-effective way — as soon as we can get — the least cost effective way, yes, the least the most cost effective way and like I said, we’ve said in the past, we think that this will allow us to maintain or even potentially over time, increase margins and we believe over time will allow us to actually deploy less CapEx as we implement these solutions.
So this is — it was really a big win for us. And as it rolls out over the next two semesters.
