Jason, thank you so much for your time. Thank you. We're going to get into it. Jason, when we see the stock trading at these levels, it kind of pops out on the screen as one of the most attractive valuations across the internet sector. Not only within online autos, but all of internet. What do you think has been most misunderstood about the trajectory, whether it be your recent results, guidance, or the broader AI narrative? Thanks for the question, and we'll try and talk over our neighbors here, so hopefully everyone can hear us. It's hard to say what may be misunderstood, but if I take the different elements of what you just talked about. From a results perspective, we're very proud of our growth. Most recently grew 15% in Q1 year-over-year, have had multiple years of double-digit growth now. That's largely through product innovation and product expansion. Our EBITDA is growing just as nicely. We have really strong margins in the 30s. I think maybe actually something that might be missed is just the strength of our EPS growth and free cash flow per share growth over the last several years because we bought back so many of our shares. EPS from 2023 to 2025 grew at a CAGR of north of 50%. On the guide, we guided to, again, double-digit growth in 2026. We also talked about a little bit of margin compression that is really intended to maintain our product innovation velocity, especially as we move into software and data, serving dealer customers with software and data as well as marketplace. That requires significant product builds, that's also helping support our growth of wallet share with our customers. On AI, we think of it, and I'm sure we'll talk more about it today, but we think about it in a few different dimensions. One, we're positioning ourselves really well with the LLM, so we are winning in our category for representing well in the AI piece of the funnel. Two, the trust of our experience. Shopping for a car is a multi-month experience. We have extraordinary proprietary data and integrations which we'll talk more about, but we have the trust of dealers and consumers to go through that multi-month journey, which is important in AI. Lastly, and maybe the most exciting, is that we're building AI native tools ourselves for both consumers and dealers, and AI products that are leading the industry. We're not just sitting idly while AI advances quickly. We're actually, we believe, at the front of that curve. When you think about how AI changes the car buying experience over the next three- to five-year period, where does CarGurus fit into that change, and how does the consumer kind of change their experience? Yeah, we've defined the consumer shopping journey in three segments. There's research, consideration, and then purchase. Research is determining what type of car one might like. Consideration is which of those used cars, typically, could be a new car too, though, which of those cars is best for you. Purchase is your experience with the dealer to actually complete the transaction. We're focused on advancing each of those. There's certainly threads that tie across all of them, but those tend to be three pretty discrete experiences. We're transforming that experience into a full AI modal experience for our consumers. I think the three themes of things that are going to change most with that AI evolution for us is, number one, it's moving from curated information to an expert guide that makes recommendations. That's really powerful and useful to the consumer, and we're seeing them adopt that, and really embrace it, and really engage with it. Number two is it will reduce the human effort. Shopping for a car will still take a couple of months. Today, on average, it takes three to four months. It's still going to take time because consumers need to line things up. They need to do their research. They need to feel confident. The time that they invest during that two or three-month period, we think will be less because agents can do a lot of that work. Agents can do the comparison. Agents can seek out alternative options for cars. Agents can start to engage with dealers in useful ways for both sides. Then the third theme is it will optimize the result for both sides. There's a lot of information asymmetry and a lot of confusion in car shopping. AI and agents can help reduce that so it gets to a better outcome that is a positive outcome for both the dealer and the consumer. I don't think that will necessarily have people buying more cars than they otherwise would, but we do think that it will lead to better outcomes and better deals and transactions that are, in total, better for the car industry. Got it. You have an early ChatGPT app integration. Are there any learnings from that so far? We hear about higher conversion from these types of LLM experiences. Is that something you could speak to or any other learnings initially? Yeah. Just to briefly put it in context, as I said, we're doing well in positioning ourselves with the LLMs. We are the number one traffic destination in the auto category from the LLMs. We are number one in visibility on the LLM search engines in our category. We were the first, as Michael just mentioned, we're the first to have an app in the ChatGPT app marketplace. The traffic that we get from that channel is still about 1% of our total traffic. Just to put that in perspective. It does, though, as you said, convert well. It converts about 2x what our normal traffic does. A lot of that traffic comes into a product we have, which is our AI virtual assistant called Discover. The consumer engagement with Discover, while it's a small percentage of our total audience, their engagement is deep. They have approaching double-digit prompts through a search process and a recommendation process that is now seamless between the research phase and actually recommending cars. The amount of information that they give us is extraordinary. They're not searching for a make, model, trim. They're searching for what their family situation is and the weather and what type of car and how they want it to drive, and we're then recommending the make, model, trim out of that. That's really important because we're then parlaying that information into packaging a better consumer profile for the dealer. When that consumer ends up connecting with the dealer through us and walks into the dealership, if that dealership has been able to get their salespeople to really leverage our platform as much as they can, they tap into something called Shopper Signals. They'll then see that Jason has come in, and he's looking for a particular car. It's because Jason has a family with three kids and a dog and lives in New England and is looking for this type of performance. They can use that to convert those leads much better to sales. Conversion is double through LLMs, which is a big leap. How are dealers reacting to learning about this and changing how they might maybe monetization or just how they're operating their ad spend? I talked about the four dealer pillars, and one of them is conversion, converting leads into sales. We have a number of features and products that we offer to dealers to help them convert better. Shopper Signals, which I just mentioned, is one. Another one is a product called Digital Deal, which allows consumers to do a number of elements of the transaction on our site before they walk into the dealership. They can get a trade-in value. They can put down a deposit. They can set up an appointment. They can buy other F&I products from the dealer. Then when they walk in, they're much further down funnel. Couple that with Shopper Signals, and you are much closer to a sold car and really understanding that customer. The challenge, there's no shortage of data. The challenge is actually behavior at the dealership. It's dealerships facilitating and training their staff, which typically has high turnover, to actually leverage these tools so that they can have a higher conversion rate. We have a group called Dealer Performance Partners, and they go in and work with hundreds of dealers a year for a day or two to make sure that they're getting the most out of our platform. They're using all the data and tools that we have to offer. They're leveraging best practices, and they're understanding their competitive set better than they currently are. It's not uncommon for that group to double the conversion rate of that dealer customer, which is extraordinary. AI is a part of how dealers can do that. There's actually, it's not just AI, it's more around behavior change. We've been hearing, we just had an e-commerce panel where we're hearing about different conversion-related data points and talking through categories, and it seems like the conversational search experience through LLMs lends itself to more complex categories, less consumables, higher velocity, more kind of complex. Would you go so far as to say that autos is probably one of the better use cases for conversational search across categories? Autos is very high consideration, second typically to homes, and it's very complex because literally no two used cars are alike. Make, model, trim, mileage, options, condition, location, et cetera. And hence that's why it's a multi-month process. The much higher upper funnel LLM experience to begin that process, I can definitely understand why that would be a good use case for it. I actually think that there probably comes a point, I haven't thought about it this way, where it becomes so complex that you actually need that period of research. You need that confidence-building exercise that you have to go through. We don't believe that car shopping is going to be a zero-click experience. It just is far too important of a decision. You saw this years ago when Google introduced what are called VLAs, Vehicle Listing Ads. It went from just links to sites to a carousel of cars. That has become a really wonderful marketing channel for us. We perform very well there, and consumers will sometimes select a car from the carousel, but then they come through to us to do the research. We believe that LLMs are similar, that it's hard to imagine that a consumer will gain enough confidence in what has been a multi-month process to make a decision at that superficial level. Furthermore, the LLMs don't have access to all the data that we do. Right. That data advantage, CarGurus being, having the most data out of any platform, online or offline, how does that lend itself in an AI ecosystem? I know there's a lot of questions about data ownership and if there's a intermediation risk there, web scraping and things like that. How do you protect your moat? Yeah. Data is certainly part of the moat answer, but it's not the only part. Data alone is not enough. We do have proprietary data. We, again, just to set some context, there are about 42,000-45,000 dealers in the U.S., about 65,000 dealers total in the three countries in which we operate, U.S., U.K., and Canada. If I talk about the U.S. for a second, 42,000-45,000, we have about 26,000 who are paying us, and we have over 30,000 on our site because we have a freemium model. We have the most dealers, the most inventory, the most paying dealers. We also have the largest consumer audience with by far the most sessions. On any given day, we're collecting about half a billion data points around pricing, inventory, and consumer demand. We also get feeds from all of those dealers, and we are integrated with many systems at those dealers. A lot of those feeds are unstructured data. They will describe a car. We then turn that into an ontology that helps us understand exactly what make, model, trim, options are in that car and allow us to calibrate and compare that to other cars. We do pricing validation. We do deduplication. All of that, plus all of the trends that occur over time, demand trends, a consumer profile that builds over time, those are all things that cannot be gleaned from scraping. That is all data, but it's data over time, some of which is proprietary, and it's what we do with that that makes that a moat. You then build that into a trusted experience, and we think that is the moat actually, is the trusted experience that you need both sides, dealers and consumers, to commit to in order for people to have confidence that that's where they want to transact. Got it. I want to go back to your recent Q1 print. How should investors think about the key drivers behind your Q2 and full-year guidance that was updated? What are the main puts and takes from here? We guided to the year in Q1, or the end of Q4, and we kept that. We didn't change that guide. We've guided to double-digit growth this year again. The underpinnings of that, and I think we may be getting into sort of the elements of two of our important KPIs in what drive our revenue are number of paying dealers, and then a metric called QARSD. QARSD is quarterly average revenue per subscribing dealer, so how much dealers pay us. There are a handful of key drivers in QARSD that have long runways and are really cranking right now nicely. The underpinnings of the revenue guide are double-digit of primarily QARSD, but also rooftop growth. On the margin side, we guided to a little bit of margin compression. That's a temporal, not a structural thing. It is a function of as we move into software and data, and as we want to maintain our product innovation velocity that we've achieved. We've introduced more products in the last 18 months than we probably have in the last three or four years. That velocity and expansion requires investment, and we're really leaning into that. We are definitely getting efficiency, workflow efficiency, a ton of engineering efficiency from AI and agents internally. We're parlaying that or we're focusing that, though, on productivity enhancements rather than on focusing on margin in the near term, because we've seen as that product velocity accelerates, we're getting more engagement from dealers, and it's giving us the license to introduce products in these other pillars. Can you go into some of the specifics of the products that you're investing more heavily into in the second half? Yeah. On the dealer side, we continue to innovate in our marketing category, which has been our bread and butter. One key example there is New Car Exposure, which allows dealers to market specific new cars in more sophisticated ways than they have in the past. That's a very timely product right now because new car inventory is building up on dealers' lots. New car affordability is an issue, is a concern with consumers. Dealers are trying to find ways to move that inventory more. Marketing continues to see innovation. Inventory is a category that we're incredibly excited about. It's a big category. It's between $1 billion and $2 billion of spend for dealers relative to a $3.5 billion U.S. marketplace spend, so it's significant. We had introduced some free products there in the past, and dealers just absolutely devoured them. That gave us the positive signals we wanted to introduce a pricing product. We introduced in Q4 of last year, it's called PriceVantage. We shared that between PriceVantage and New Car Exposure, both of which launched in Q4, we expect those to grow 15X this year and be a $8-figure revenue stream, the two of them. That has hundreds of dealers, and we're seeing really high engagement. On conversion, I talked about Shopper Signals, Digital Deal. There's huge opportunity there. We are still a free standalone commercialized product. Data, what's really nice about data and market intelligence is that makes every other product smarter. Dealers are very competitive. They need to be. It's a competitive arena. We are giving them insights and intelligence around their competition and around the market that they literally just can't get anywhere else. I think of that as sort of an umbrella or a layer over all the other products that we're introducing that help those products become more effective. Got it. Can you unpack the dealer ads portion of your growth and the mix between kind of macro tailwinds versus more execution-driven gains? Where do we stand today in terms of penetration of the overall dealer TAM? As I mentioned, in the three countries in which we operate, there's about 65,000 dealers. We have about 35,000 paying dealers. We're just over 50% penetrated. We're the market leader in the U.S. We are the market share gaining number two in both the U.K. and Canada. Canada is, I believe at a tipping point where we are generating lead quality or lead volume rather, quantity that is in many cases on par with the incumbent, AutoTrader.ca, such that the largest dealer group in Canada called AutoCanada, recently announced that they fully switched from Trader to us. We're a little over 50% penetrated. We're gaining share in all three markets, both in rooftops and in spend. We think that the momentum that we are building by focusing on productivity rather than short-term margin expansion is a winning formula. In all three markets, we're considered the best ROI. That helps us all sleep very well at night. At the core, before we even add any of these other features and products, we know that we're delivering significant value to them. Can you unpack some of your QARSD growth algorithm? Recently, it's been very strong. Are new products contributing to that, and what are the biggest components there? QARSD, as I mentioned, is effectively how much a dealer pays us. Our QARSD in the U.S. is around $7,500 a quarter. The average dealer pays us $2,500 a month. That's the baseline way to think about it. That's been growing at high single-digit, low double-digits for many, many quarters now. The drivers of that, there are two top drivers. One is upselling to higher package tiers, and the other is cross-selling. If you look over the last year, upselling is our number one driver. If you look over the last quarter, cross-selling new products is our number one driver. We love both those drivers because those are a function of our innovation and our product expansion. Upselling is typically now a function of we are adding more and more features and value to higher tiers, and that is causing dealers to upsell into higher package tiers. Cross-selling would be PriceVantage, Sell My Car, New Car Exposure, all of the ones that Digital Deal that we've talked about that are discrete, monetizable, add-on products. Those are the top two. Lead quality and quantity is a driver. We deliver a lot of customers to dealers, and those are in the form of traditional leads, which are email, phone call, text chat. We also are sending a lot of consumers to walk into the dealership. Proxies for that are that we're sending them clicks to their website. We're sending them people who have clicked on the map and directions. A recent very high growth channel is in our app, we have something called Dealership Mode, which gives consumers a ton of value when they're in the dealer. It helps them compare cars. It helps them understand financing. Gives them a lot of information at a particularly anxious part of the process. The number of consumers who are checking in at the dealership in Dealership Mode has grown very quickly recently. The most compelling stat is that about 80% of those who are checking in did not submit a lead. That's showing this is another avenue of value that we're delivering to dealers that we have historically not been getting credit for. The audience quantity that we're delivering and quality is paramount. We do have unit price to pull on. We are considered the highest ROI. For most dealers, when you look at the survey data, we are the highest volume of leads, highest quality leads, and highest ROI. Pricing in this industry is not standard. It depends on where the dealership is, how big the dealership is, the package tier that they're on, a variety of things. There is a unit of currency which is cost per connection or cost per lead. In many cases, we are still below on that metric, our smaller, less innovative competitors. Unit prices have fueled only a couple points of growth for us per year over the last handful of years. We don't want to get greedy. We think it's still there in the long term for us to pull if and when we choose. That's not a focus for us. When you think about Dealership Mode specifically, and you gave a really interesting stat there about the 80% of customers not submitting a lead. I guess, you talk about that trust advantage that you bring for consumers. What are you unlocking for those consumers and is there a path to monetization of that over time or greater monetization? It's a good question. Today, we don't monetize the consumer at all. Well, we don't monetize the consumer at all, and we don't have near-term plans to monetize the consumer. The relationship that we have with the consumer is long-term over the duration of their search. It's increasingly as we build more of these AI features and elements and then pull them together into a more cohesive AI Mode, we really are becoming their expert advisor, soup to nuts, start to finish. Our Discover has memory, for instance, and that memory feeds into their sort order, and that feeds into Dealership Mode, and that feeds into search A, that they have, and search B, that they have with two different dealers. We are really becoming their guide through the whole process, and we don't think that we need to monetize that because if we're their guide for the whole process, then that becomes infinitely valuable to the dealer. If we can win over the consumer, then we will win the dealer, has always been our philosophy. Got it. How do you assess your evolving competitive landscape with AI accelerating development when we think about especially increasing focus online from more traditional offline dealers that are investing there? Is there a specific competitive angle that you're thinking about with that, or competition? I think, when we look at where the consumer will be in three to five years with their shopping journey, I think everyone is investing towards that. How do you feel about your place in that evolution versus competitors? I've said the word a lot today, maybe I'm beating the drum too much, it comes down to trust and confidence. We feel that if we can, by creating the smartest, most efficient, most trustworthy, most data-intensive experience with the most inventory, the most dealers, the most seamless connectivity, that that is increasingly what consumers are expecting. I'm sure we're all reading a lot of the same content that is talking about how when the novelty of AI starts to wear off, the scrutiny of What can I actually trust? starts to set in. We're seeing that with dealers and consumers. With dealers, when we make a recommendation on how they should price a car, increasingly they're starting to ask, Well, why? How did you come to that recommendation? I think consumers are starting to ask those questions as well. By having the ability to start from a position of trust because we have a contractual relationship with the dealer, or all of the dealers, most of the dealers, then reinforcing and substantiating why we're making the recommendations that we are to consumers, we're going to continue to earn that trust. The early adopters of AI are incredibly informative test cases. They are still very early, and it is still very small. For all of the AI features that I've talked about here, and we've seen this at a lot of our e-commerce peers, they're fantastic use cases and there's really deep engagement, but it's on a very small percentage of our total user base. The average user for us is still using the dropdown menus to search for make, model, trim. We're trying to push that because we do think it's a better shopping experience, but it is still the tip of the spear. Are there any questions from the audience for Jason? Want to ask quickly as we wrap up about capital allocation. You've repurchased a large portion of your share base since 2022. How do you think about it from here as we evolve into this more AI-driven ecosystem and just how you allocate whether or not you invest in product development or elsewhere? Our 3-tier approach is always how much should we invest in the business, largely for innovation. We've talked about that a little bit, but I would say we continue to invest intelligently, but we think heavily there, and we're not easing up on that despite all the efficiency gains we're getting in the business. We like how we're expanding into different pillars. We like how we're really evolving or revolutionizing the consumer experience on our site. We're going to stay with our foot on the pedal there. Next is M&A. We have acquired a few companies in our tenure. We hope to acquire more, so that's the second use. The third use is returning capital to shareholders. In the last, I think, three to four years, we've bought back almost 30% of the company, almost $900 million worth of shares. The way we think about it is on a free cash flow yield. When we were at 7% free cash flow yield, we thought that was attractive, and now I think we're closer to 10% free cash flow yield. We think in these times when we might be misunderstood, as you said, or we think we have a long runway of solid, durable growth, and we think it's a good price, then we're going to get more aggressive. In Q1, we bought back $175 million worth of shares. We have a $250 million share repurchase approval for this calendar year. All right. Any other questions for Jason? Who owns the inventory systems? The dealers, do they manage the inventory themselves, or is there one dominant provider that provides an inventory management system? There's not one dominant. There's two layers. There are true inventory management systems. One that skews toward price, which is one of the larger ones, is called vAuto, which is owned by Cox. There are inventory management systems. There are syndication systems that pull from hundreds, literally, of small inventory management systems and then aggregate and syndicate those out. I would say vAuto is probably the largest in that category. There are a dozen or so other sizable ones, and then there's a long tail of a couple hundred. Do you have all of the data for all of the automobile dealers? We interact. Yeah, we have, I believe it's 85% or so of the inventory in the U.S. on our site, which is the largest of anyone. That's by working with virtually all of those hundreds of feeds. The information that comes in from those feeds, as I think I mentioned before, is very unstructured. The way you describe the same car. If you two had the same car, in theory, you would describe them very differently. We take that unstructured information and turn it into something that can then be compared to other cars for the consumer, which drives our deal ratings and our Instant Market Value and all of those things. Are the dealers more willing to deliver that data to you, less willing today than five years ago? Is there any Is there any pushback about them now? That's the underpinning of how they market their cars, and they know that we do a good job reflecting their cars. We give them advice then on how to merchandise them better, how to market them better, how to think about pricing them. We really try to empower them to be as successful as they can with that inventory that we're showing for them. The 15% that you don't have, that is because large automobile dealers do it themselves? No, we have all the large dealers. No, it's probably the opposite. It's the very small ones, or it might be dealers who have a very high-priced strategy because they might be in a rural location and they know they're high-priced. By putting their inventory on our site, we have a deal ratings, and we would say, That's an overpriced car. Their mentality is, Why would I have you say my car is overpriced? I'd rather just not have you say anything about my cars. There's also a segment of buy here, pay here, where we think the price they're showing is not an actual, fair, validated price, and so we don't accept those. There's a few segments like that. Thanks. Thanks. All right. We are out of time. Thank you so much, Jason. Thank you, everyone. We appreciate it.