Autotrader Group Plc

We anticipated trading this year to be tougher as a result of profitability challenges for retailers, a shortage of stock in some age cohorts and fast speed of sales. Retailer profitability was more challenging than we expected due to a combination of new car profitability in part due to the ZEV mandate and cost increases following the government budget last year. This led to intense scrutiny on every cost in their business with many stories of profit declines, redundancies and store portfolio restructures. The pressure on retailer profitability is most acute in November and December, which combined with feedback on our accelerated rollout of DealBuilder. This was amplified across social media, including some factual inaccuracies which were since clarified for customers. Following this period, we have seen higher cancellation levels than in previous years, which has impacted both FY26 and the run rate into FY27. However, despite these challenges, we have continued to grow revenue, profit and earnings per share. Perhaps more importantly, retail numbers, stock and upsells have all been growing since the end of the financial year, so we are past the low points. Furthermore, the core metrics underpinning AutoTrader are in a strong place. Supply shortages will subside, speed of sales has been stable all year, retailers are returning and now years into a janty KI, we're confident that the core of what we do will remain relevant for the future. It's a confidence that is growing as we continue to build, scale and monetise products incorporating AI. In previous technology transitions, including the internet, mobile, native apps, hyperscalers, big data and AI, we have backed the technology and emerged the other side better for car buyers, for retailers, for our people and shareholders too. Now we'll turn to the core foundations of AutoTrader which, as I mentioned, are in very good health. The most important foundation of any marketplace is its buyers. From an already very high base, our share of time spent versus competitors has increased again. There are 11 times more time spent on AutoTrader compared to our nearest competitor, which is actually four brands added together. We're six times greater than all our main competitors combined. and I've seen little change to how buyers use AutoTrader. Munich visitors have been stable at over 9 million a month and 80% have become direct to AutoTrader, 13% through organic search and 4% through paid web traffic. AI chatbots represent less than 1% which isn't changing significantly despite monthly LLM users reaching almost 4 billion globally. Generative chat interfaces and agents are already being used to research goods and services. However, how people use them depends very much on the category. Vehicle transactions are unique because they are pre-owned, complex, high value with a lot of relevant choice for any one buyer and a process that takes around three months travelling both on and offline processes. Our experience has shown that car buying and is improved meaningfully only when the technology is combined with a deep specialised car buying experience, a massive range of real time vehicles and tools that utilise data, integrations and over 50 AI models that only we have and have developed. This is true for car buyers and also for retailers who have an even higher need for trust, performance and accuracy. This is all underpinned by our sustained investment in our public card, delivery, data and AI technology platforms with our 400-person strong product and technology team. Now for Deal Builder. I want to start by saying this remains a big long-term focus for us because we believe it is one of the single most impactful and difficult-to-replicate experiences we can deliver for car buyers and retailers. is indicated by positive feedback over the three years that it's been live. Car buyers like being able to go deeper into the transaction when and where it suits them. They don't want to wait for return phone calls or dealership opening hours. For retailers, they can sell out of hours and get car buyers that are at least twice as likely to convert to sale. Furthermore, over time, there will be the opportunity to get more car buyers part exchanging and using finance, which are good options for car buyers and important for retailer profitability. While we have had to make some product adjustments and taken more time onboarding some cohorts of retailers, penetration has continued to grow throughout the year. We're also updating our capital allocation policy. We've accelerated our buybacks throughout the second half of the year and intend to continue this into the new financial year. We believe this is a rare opportunity to allocate capital effectively at a price that we don't believe reflects the fundamentals of our business. Over FY26 and FY27 combined, we expect to return over £1 billion to shareholders. As I said earlier, we've continued to grow revenue and earnings. Average retailers for the year declined 0.5% to 13,942. We ended the year with 460 less paying retailers than where we exited the first half. Although, as I mentioned earlier, retailer numbers have been growing since the end of the financial year, which we are very focused on continuing. Average revenue per retailer, or ARPA, was 2,995 pounds per month, which was up 5% from the previous year. Group revenue and operating profit were up 4% year on year, and operating profit margins were stable. Averages can be deceiving so it is worth flagging the group revenue growth with 3% in the second half and lower in the final quarter which has impacted our run rate into financial year 2027. Cash generated from operations was up 5% and earnings per share up 8%, higher than operating profit due to our continued share buybacks which as I mentioned we accelerated in the second half of the year. We have reviewed and changed our capital allocation policy, as I mentioned, reflecting our confidence in the business. This year we're also declaring a final dividend of 7.8 pence a share, which makes dividends for the full year up 9% year on year. Now for our cultural KPIs, which are a subset of measures we use to track progress on a number of cultural and organisational priorities. This year our metrics around the representation on our board, leadership and organisation are relatively stable and generally at good levels. Following Catherine's departure our board is now 50-50 men and women and we're continuing to work to improve ethnicity and leadership but it will take time for the work that we've done in early careers to make its way through into leadership positions within the business. We aim to have net zero carbon emissions. across our value chain by 2040 and halve those emissions by 2030. This year, carbon emissions across scopes one, two and three increased 55% to 144.1,000 tonnes, largely as a result of capital expenditure on our new office and vehicles taken on balance sheet through Autorama. Both of these are scope three or supply chain related. Engagement has fallen from 91% last year to 72% this year. It was literally only a year ago when most cultural measures were at all-time highs. As you have heard, this year has been particularly challenging and has impacted our people. Tougher trading, tighter cost control, reorganising some areas of the business, retailer feedback and a tighter approach to working in the office. However, all other internal measures, such as recruitment and retention, remains largely unchanged. It's fair to say the team have performed exceptionally well in tough conditions and I feel privileged to work with such a talented and committed group of people. I'll now hand over to Jamie to talk us through the financials in more detail.

Thanks Aidan and good morning everyone. I'll start by focusing on the core auto trader financials. Total auto trader revenue increased 4% to $585.3 million. Trade revenue also increased by 4%, with the largest component of this being retailer revenue, which also grew by 4%. Within trade revenue, we've seen an increase in home trader pay-as-you-go listings and growth in other trade revenues. Consumer services revenue decreased by 8%, Within this, private revenue generated from individual sellers decreased by 11% due to a lower volume of listing. Motoring services decreased by 4% due to lower revenue from our insurance product. Revenue from manufacturing agency customers increased 14% year-on-year. Much of this increase was due to manufacturers supporting their franchise network with both new and used car advertising. As mentioned, retailer revenue grew 4% year-on-year. The average number of retailer forecourts on our platform decreased by 71 to 13,942, which was half a percent year-on-year decrease. An average revenue per retailer increased by 5% to 2,995 pounds per month, with more detail given on the following slide. The chart on the left shows the components that contribute to the movement in ARPA compared to the prior year. As you can see, ARPA growth was driven by the price and product levers with a negative contribution from stock. We delivered our annual pricing event for all customers on the 1st of April 2025, which included additional products and a like-for-like price increase, which contributed £117 to ARPA growth. Products contributed £72. Most of this growth was from our co-driver product, which was included in retailer advertising packages in April 2025. Prominence, which is largely the movement up and down our package staircase, was not a contributor to the product lever in the year. We continue to review our packages with changes expected in H1 with the aim of returning prominence to long-term growth. The remaining product lever grace was driven by new car, where we increased the number of paying customers over the period. Turning now to stock, you'll see on the right-hand side of the chart that the number of live cars advertised on AutoTrader was broadly flat year-on-year, although there was some positive impact from a stock offer that we ran at the start of the financial year, which did not impact revenues. From November 2025, prompted by the rollout of DealBuilder and reflecting more difficult cost-related trading conditions, a number of retailers reduced the number of vehicles advertised on the platform, contributing to lower paid stock volume. Total costs, Australia costs increased 4% to 181.4 million. People costs increased by 1% to 93.6 million. There was an increase in underlying salary costs, while the average number of employees remained broadly flat, and share-based payments reduced. Marketing spend decreased 11% to $21.9 million, while other costs, which include data services, property-related costs and other overheads, increased by 13%. This year-on-year uplift is mainly driven by higher cloud infrastructure expenditure and increased property costs related to our new head office. Depreciation and amortization increased by 49% to 9.4 million, also due to our new office lease that commenced in July 2025. As a reminder, we fully expense our research and development costs, hence our low levels of capex and depreciation. In addition to our investment in cloud-based services, we have 400 people in product technology who are continuously improving our platform and developing new products for consumers and retailers. Operating profit increased by 4% to $408 million, and operating profit margins remained at 70%. Our share of profit generated by dealer auction, the group's joint venture, increased 14% to $4.1 million. Having covered Autotrader, the main part of the group, we'll briefly cover Autorama results. As a reminder, the Autorama acquisition was and remains part of our strategy to bring attractive new car offers to car buyers on Autotrader and to make new cars a more important part of our proposition. Autorama revenue was 39 million, with vehicle and accessory sales contributing 29.6 million and commission and ancillary revenue of 9.4 million. Vehicle and accessory sales relates to vehicles that flow through the balance sheet, which is not our primary focus. Stable deliveries amounted to 8,056 units, around two-thirds of these being cars, and within this, deliveries from auto trader increased over three times. Average commission and ancillary revenue per unit delivered is 1,167 pounds. The Autorama segment made an operating loss of £2 million. There's a significant reduction on last year through the accelerated integration into the main auto trader business and platform. From financial year 2027, Autorama will operate and be reported as a single operating segment with the rest of the auto trader group. This is due to more than half of all leasing transactions being delivered through the AutoTrader platform in the second half of financial year 2026. In the appendix, you'll find a breakdown of financial year 25 and 26 in this new format, which will be how we report our FY27 half-year results in November. Total group operating profit increased 4% to 392.7 million. and group operating profit margins remained at 63%. As we grow, the strong cash generation of our business leaves us well-placed to return surplus cash to shareholders. Cash generated from operations was up 5% to 418 million. Now to briefly review net bank debt and uses of cash in financial year 2026. During the period, the group drew down 165 million in its revolving credit facility and held cash and cash equivalents of 18.2 million. In the year prompted by the low share price, we accelerated the number of shares we acquired. To put this into context, we acquired three and a half times more shares in H2 than we did in H1, and in aggregate acquired 58.5 million shares 6.6% of issued share capital, for a consideration of £369.1 million. A further £94.1 million was paid in dividends. The Board believes the prevailing share price does not reflect the company's fundamentals or long-term prospects. We're therefore updating our capital allocation policy. We'll continue to focus on investment in the business supporting growth, while continuing to return approximately one-third of net income to shareholders through dividends. We expect to continue the recent acceleration of share buybacks, purchasing around 500 million of shares in the year, and we'll be requesting authority to require up to 15% of issued share capital at our AGM in July. Based on current assumptions, we expect this to increase our debt levels towards one turn of EBITDA. I'll now move on to talk through some of the market dynamics. Moving on to slide 15 and looking at both new car registrations and used car transactions. From a new car perspective, suppliers continue to improve following the impact of the pandemic in 2020 and 21, with five consecutive years of growth. Although the market still remains slightly below the level seen pre-pandemic, and significantly lower than the highs of 2017. The retail market, or new cards sold directly to consumers, continues to remain at lower levels by historic standards. Over the past 12 months, we've seen manufacturers attempt to stimulate private demand with increasing levels of discounts and finance offers, which has had some positive impact, with private retail sales growing for the first time in four years. As seen in the chart on the right, used car transactions have continued their steady recovery, growing at 1% over the last year. Over the past 20 years, the size of the UK car park has grown steadily by just over 300,000 cars per year, reaching 37 million vehicles. We expect this growth to continue over the long term, driven by GDP growth, population growth and stable car ownership trends. We also expect the value of both new and used cars to rise over time. In 2011, the average price of a used car advertised on AutoTrader was £9,000, which has almost doubled since then, reflecting average growth of over 4% a year. This increase is driven by inflation, improved product functionality, and the shift towards more expensive electric vehicles. Over the past decade, gross margin percentages have remained relatively consistent, which means that higher vehicle prices typically lead to higher absolute gross profits for retailers. This trend, combined with the growth in transaction volumes, has resulted in an increased gross profit pool over time. Over the past 12 months, our audience position has remained strong. The number of cross-platform visits continued at record levels at 81.7 million per month. Engagement, which we measure as cross-platform minutes, decreased slightly to 548.3 million on average per month. The chart on the right-hand side shows the total minutes spent across an expanded set of competitors. On average over the year, Comscore estimated that consumers spent 11 times more minutes on AutoTrader than our nearest marketplace competitor. The combination of Gumtree, Motors, eBay and Kazoo, which is an increase versus the prior year. We were 22 times larger than the nearest single brand and six times larger than all of these competitors combined. 67% of our audience was unique to us never visiting these other sites. I'll now hand you back to Nathan to talk through our latest product updates and the outlook.

Thank you Jamie. We wanted to start by providing a timeline including a sample of how our technology has developed over the past decade. There's this sustained investment in the way we deliver software that enables us to deliver at high velocity with stability, to adapt and to scale new technologies quickly and cost effectively without big bang re-platforms which are prone to time and cost overruns. Rather than go through every item on the timeline, there are a few I wanted to point out. Just over 10 years ago, we began building our data science team and supporting technologies. 2017, we started to migrate to the public cloud. by re-architecting and standardising every application so it didn't just work in a cloud environment but was optimised for it. We completed this without pausing development around six years later. Just after 2018, we acquired key resources so we could build our own proprietary vehicle taxonomy for every vehicle on UK roads, something that is even more relevant in a world of AI and requires a team of technologists and people to constantly update and cleanse the data as well as build integrations with manufacturer production systems and other data providers. Our taxonomy underpins pretty much every aspect of AutoTrader. Following the launch of ChatGPT in late 2022, we employed a full-time postdoc from Manchester Met University to work on the LLMs. This capability is now productionised across our data science and engineering team and is made accessible to all our product and technology teams through an AI platform integrated with most foundation models, including hosting, scaling, monitoring and security essentially available to them off the shelf. AI will increasingly surface in our consumer experience, sometimes very obviously and sometimes in the background. We believe the technology is transformative, but not if it is just bolted on the side of existing functionality and tools. As we've built, scaled and monetised AI, we've seen that to be effective in car buying or retailing, the technology needs to be combined with a deep user experience, highly curated real-time vehicle listings, proprietary data, specialised models and distribution to a highly fragmented customer base of car buyers, agents and retailers. We've now built and deployed an MCP server which enabled agents to efficiently interact with AutoTrader. Our initial implementation of this is with a chat GPT app, which you can see in the middle of the slide. However, we've architected it in such a way that it can be used to interact with other agents that arrive either today or in the future. Another example is our new search categories, available under a filter called I'm Looking For on the left-hand side of the screen. On AutoTrader, car buyers had to choose one make or model when searching for vehicles. These filters powered by a specialised AI model enable people to search across makes and models defined by categories in their language such as big boots, all rounders, cheap insurance, cheap to run, birth cars, luxury cars and even an oh my god category. These filters are currently being applied by over 100,000 people every day and will become more and more important given the explosion of new brands selling vehicles in the UK. It's also a very good example of what's required to ensure high quality responses. We could have used a simple LLM to do this task, which would have been less accurate and expensive. Instead we've been machine learning to be much more effective for the task with negligible incremental costs. On the right hand side you can see our current pilot using chat based search, which is integrated with filters. This provides a different entry point to search with even more flexibility in categories. We've experimented with these interfaces using different technologies before and uptake was limited. However, if LLMs become a way in which people want to search for vehicles, then the best such experience for cars will be on AutoTrader. This is because of the specialised models I spoke about earlier that use proprietary consumer and retailer data and an onward experience to navigate enormous choice along with market-leading tools to ensure car buyers get the very best results for all their car buying questions. A CoDriver suite of products will be known to most analysts and investors. For those who are unfamiliar with CoDriver, it is the umbrella brand for a suite of AI products that save retailers time, improve quality and therefore their sales process. The first two products already available optimise the order of a retailer's images and highlight any that are missing using computer vision. The second, which is covered on this slide, writes a description for each unique vehicle, which sounds simple enough but is the perfect example of what it takes to get good results from this technology. If you use the foundational model alone, as is shown at the top of the slide, there will be errors and many of the features of the vehicle will not be known. Furthermore, there will be no data-based understanding of which of those features are the key points of differentiation and of most value to car buyers. You can see how we go around this by utilising both our models, the foundation models, and proprietary data and technology. We've found that every implementation of LLMs to make car buying or selling better has required us to do some version of this. This year we also launched buying signals, which is again powered by AI models. It's been added now to 800,000 inquiries since it's been launched. Buying Signals utilises the model to predict the likelihood of someone buying a car based on signals collected throughout their journey on AutoTrader. If retailers need to prioritise their activity, this gives them the perfect method to do so quickly. It also benefits the ready-to-go car buyer who can be quickly identified, contacted and followed up. Buying Signals also flag whether that buyer is local and their preferences in case the exact vehicle is no longer available. It offers a similar efficiency to DealBuilder with inquiries marked as high intent, typically converting twice as well as an average auto trader inquiry. Now, with over almost 15 million inquiries sent every year to retailers, many of which go unreturned, the benefit to them is reasonably obvious. The new buying journey on AutoTrader, known as DealBuilder, remains a key focus of ours. It delivers a more empowered buying experience whenever people want and inquiries to retailers that convert at least twice as well. For a retailer that's half the work and with almost 50% of deals happening outside of business hours, their stores are essentially now open 24-7 without the staff cost that would normally come with it. We always build products iteratively and with customers, which we have been doing for three years now with DealBuilder. However, as we accelerated the rollout to new cohorts of customers, some were not clear on what we were offering or why. We listened to this, slowed down and made changes to the product, including the ability to choose either full reservations or the ability to request a reservation. The changes were well received and we've continued to roll out the product, retaining the goal of achieving 100% penetration during the course of FY27. You can see from the charts on the slide that penetration has continued to increase throughout the year with more than triple the customer numbers now on DealBuilder and almost triple the number of deals as newer customers tend to be smaller. Now for the outlook for FY27. We remain comfortable with our current levels of investment so we expect group operating excluding vehicle and accessory sales to be at least maintained. In the financial year 2027 we expect group operating profit to be between 395 and 415 million pounds, which with the continued acceleration in buybacks will result in at least high level, high single digit EPS growth. Auto trader revenue was flat year on year in April 2026 due to a lower run rate and package increase. However, retailer forecourts, volume of paid stock and package penetration are now improving and we expect that to flow through to growth in the second half. The contributors to this will be our packaging event, which will grow the price lever within ARPA by £85 to £95. Product growth is expected to contribute £65 to £75. Stock will recover, resulting in improvement from current levels to minus £30 to £40 for the full year. While average retailer forecourts are now growing, we expect the average for the year due to the entry run rate to be down 1% to 2%. Other revenue will be broadly flat and aggregate with a decline in consumer services offset by growth in manufacturer and agency. Our focus in Autorama is on volume growth, however we do expect to make a small profit for the year with commission and ancillary revenue growing 8% to 12% and vehicle and accessory sales of around £40 million. As Jamie mentioned, as the majority of leasing transactions now originate on AutoTrader and due to the extensive integration we've already undertaken, we will move to one reported operating segment in 2027. That's all for the presentation. We'll now take questions from analysts in the room.