YouGov plc (YOU.L) Q4 2026 Earnings Call Transcript

Stephan Shakespeare: Good morning, everybody. Thank you for coming. And it is good to see you. This is my second time of having a last presentation. I think this really will be the last 1. So it has been a good year. We have strengthened pretty much on all fronts. We have got 2% increase in our data products, which while back people were thinking, well, that is all going to be taken over by AI. That will be a theme for me today to say, actually, AI is a big benefit to us and a big opportunity. It is not something that is been holding us back. You can see that in a very difficult market. it is difficult because apart from all the other anxieties, there are particular anxieties around our industry because of AI and will we all be replaced. In that market, we are growing and we are growing where we most want to be growing. We have been strong on controlling costs. You will hear a lot more about the VDP from James. And there are some other interesting things that he will talk about. I will just focus on my role, which has been when I came in 2 years ago, or 1.5 years ago, I said I was going to do 3 things in that interim period, that I had specific objectives. 1 is to stabilize the business. I think you can see our numbers have done that. You some more details about that in a moment. The second is to return to innovation. And the third, of course, is to prepare and deliver the leadership transition. And on the first of those, we have seen accelerating growth in our key areas. With 3% up versus last year in data products as well, we have done particularly well. We have got that cost discipline that referred to. And also, we have made that switch back to focusing on data products from custom. it is not that custom is not important, custom has also become very much more a data product than it used to be. it is less about the customization and more about the richness and fullness of the data. So, even our custom trackers are really very similar to data products. And we have focused. We had a unit that focuses on developing that data set as something that can be partnered with, and a bit more about that. Later as well. Innovation, we have accelerated. We have enhanced the product. There is now an AI agent that can tell you about what is in the data and help you find more. And that will be growing. I mean, everybody has that. Some sort of agent that looks at your data. We have a heck of a lot more data than anybody else. And by an order of magnitude. And to get the most out of that is what we are doing. We are adding MCPs, of course, all of that. But above all, as you will see later on, we are making it a platform that an agent can use directly. We have those are our AI-powered solutions and the platform we have long talked about. Now it is becoming really a full on full on data platform. Again, I will show you later on at the end where that is going. And the third priority was that leadership transition. And I said that we would not make the same emails twice, that we were looking for somebody who is has proven leadership in an adjacent area. Where we can see what they have delivered In Wayne, we think, we have found that somebody who has led teams, grown P&Ls, knows the industry inside out, and also understands the challenges of AI. We have someone that we know is going to do this job well. I also said that instead of just handing over simply we would have a proper transition period in which the new person learns the ropes a bit, and not just not just expected to immediately fit right in because there is a lot We are a complicated company. We are different to many other companies. All other companies in our industry, and it does need a proper transition. So, I am looking forward to that period. I have a very strong relationship with Wayne. And I am very confident. That we are going to be working well together, especially since I have a new role in the post-January period. When I go back to being a Non Executive Director, but overseeing, running, chairing Innovations Committee, which will be very active in helping to direct and guide the things happening that the executives are doing with the system. So handing over for the financial review. To James.

James R. Davies: Everyone, and thank you, Steven. it is now my second results presentation since I have been at YouGov. You may recall my first 1 was at the half-years after just 5 weeks of joining. And the last 6 months have definitely been fulfilling. We have made deep progress on the planning and execution of the value delivery plan. We are investing in areas that matter. We are growing up, now, yet we are keeping the entrepreneurial discipline alongside all of the decisions we make. And alongside all of that as well, we are keeping innovative ideas flowing. They are not just flowing, they are flowing and they are conversing as well. Steven will talk about that in more detail later. So before I get into numbers, I wanted to highlight the key priorities of H2 from my perspective and the wider board's perspective as well. Priority--and there are 7 of these priorities. Priority 1 for a market and investor relations perspective, we want to do what we say we are going to do. I have been in the public markets for a long time, and I know how important that is for employees, for external analysts, and investors. So I commit that is what we are going to do. This obviously included being within the guidance range that we announced in March. Plus delivery on various other areas as well. Priority 2, rebuild trust and improve on clarity where possible. Throughout this presentation, I will refer to things that we committed to at the H1 results and either confirm the action is completed or update on how we are getting on in solving that problem. Going forward, there may be times where we decide an adjustment to previously communicated commitments is required. it is important that our trajectory may change, and it is important that we are agile and we check-in a changing environment. If our direction does change, we commit to explain clearly what that change and why that change has happened. Today, there are no such changes to commitments to disclose. We are bang on track for everything that we have committed to in recent times Priority 3, balance sheet stability. In March, we had a fast approaching maturity date for the debt facility. An extension was therefore critical. This has happened. Priority 4, obtain approval for a share buyback program and start the program. I am delighted to confirm that the buyback starts today, I believe it actually already has started. And over the next 12 months, up to a total amount of £15 million will returned by this route. Priority 5, evidence continued solid execution of the value delivery plan. Wave 1 was executed at pace, before the H1 results, Wave 2 and 3 are well underway. Planning is advanced and execution is happening Priority 6, initiate the wide ranging strategic review of our Shopper division Again, that is ongoing. And priority 7, provide clear guidance going forward, no vagueness or confusion And in the release, you will see very clear guidance in pounds, millions, numbers with no confusion, vagueness, clandestine approach to what we think will happen. And I would like to feel that our results presentation released a few hours ago and our presentation we are giving today provides high conviction that we have achieved these 7 Tier 1 priorities And please do challenge me or Steven either today or later, if you feel we have not achieved those objectives. And I have circled 4 of these points. 1, 2, 5, and 7. These priorities are not for just the last 6 months. These priorities will last indefinitely. that is understandable. We are a young ish tech focused listed business, so we do not have an option. We will make sure that we embrace that in a very growing up and clear way. Before I move on to the segmental operational results, and with priorities 1 and 2 in mind, are you do what we say, we do, and then transparency and clarity, I wanted to cover off how we reconcile between our adjusted and statutory group numbers. We have rightly been criticized for lack of clarity in this area before and I committed in our H1 results in March that the thresholds for items to be classified as separately identified will be higher and also we will be much more transparent on the makeup too. I feel that understanding the makeup of the separately identifiable items is as important as the total quantum itself. Our commitment to priority 2 in particular around transparency and clarity. Due to our history of M&A and restructuring initiatives, we have required the use of separately identifiable items. So how have these reported items been built up in FY 2026? I split them into 3 buckets. Bucket 1, I want to ensure that our balance sheet holding values for assets were thoroughly reviewed as part of my first year end at YouGov. A large chunk of this impairment balance is the write down in the balance sheet value of our DAC business. As a reminder, DAC includes our non shopper German business, but it also includes the Swiss business, including CATI Research. This is a business that runs our computer assisted telephone interviews. The balance sheet valuation needed to be adjusted downwards. Which we did through the numbers at the year end. The remainder of this category includes lease impairments, as we assess simplicity and efficiency of our global office footprint as part of value delivery plan. Along with some impairments, of our software assets, which have been capitalized in recent years. Going forward, a continual firm view will always be applied on balance sheet holding values as our business evolves. Bucket 2, amortization. An accounting rules-led amount which is falling on from our shopper acquisition, relates to 2 items, order backlog and customer list. The order backlog amortization was fully amortized prior to the start of this financial year. And the amount of $5 million from last year from the prior year will not will not continue. That leaves $10 million this year which covers the customer list amortizations. In FY 2027, we expect this aspect to continue with another $10 million amount, for further amortization of the customer lists. This customer list amortization is expected to continue for the foreseeable future at broadly the same amount of this year, However, the order backlog will not come back. Circa £10 million is going to be the number that fills bucket 2 going forward in this category. Moving on to bucket 3, This is the only cash item within this grouping, and arguably the more relevant line item when it comes to assessing underlying value. Buckets 1 and 2 are non cash. In high level terms, bucket 3 covers restructuring costs. These fell from $13 million last year to $5 million this year. As the threshold for inclusion increased, and the vast majority of transitional services agreements for the shopper acquisition have now been completed. Therefore, the cash amount of SIs is more than half year on year, with a reduction of £7.7 million. Going forward in FY 27 and beyond, bucket 3 will continue to be material as we deliver the Value Delivery Plan Bucket 2 will be $10 million as I discussed Bucket 1 will be assessed throughout the year to ensure balance sheet values are appropriate The 33.1 million total explains the difference between adjusted and statutory measures on the face of the results announcement The adjusted EPS at 30p is down 11% which is broadly aligned with the reduction in adjusted operating profit. As a reminder though, as you will have seen from the numbers, H2 adjusted operating profit was marginally up year on year so this EPS downfall related purely to performance in H1 Now, on to the segmental operational results. As Stefan alluded to, each of our 3 divisions delivered headline revenue growth Yes, growth levels were low single digit percentages, Although compared to the majority of our peer group, actual year on year growth position--growth in itself-- positions us towards the top of the pack. On an underlying basis, data products and research grew 3% and there was marginal shrinkage in Shopper FY26 is our 16th unbroken run of Group revenue growth, an achievement that our teams around the world should be very proud of. We expect FY 27 to be our seventeenth year of unbroken revenue growth. We are particularly pleased with the margin uplift in Data Products, where operating leverage continues to kick in. I mentioned in H1 results that our data products margin needs to improve Everything I was seeing in my first few weeks suggested this margin should and can be higher And this is a great step towards achieving the margin this syndicated subscription based product fully deserves. The margin in research was slightly down, This will improve and go back to last year's level and beyond as the value delivery plan delivers. Shoppers margin is materially I do not know whether to use the word different or lower either way, it is lower relative to last year And this is exclusively to do with the game change investment program we discussed at the H1 results. You were to add back this specific investment and targeted investment, the margin would be flat year on year. On to our geographic performance. Very strong performance in Americas Ray and his team in The US had a very encouraging H2 other regions are showing solid resilience in what we all know is a tough market environment The vertical sectors in which we have been growing in the last 6 to 12 months is particularly pleasing There have, however, been some tough sectors as we have discussed before Agencies being 1, and they are weaker and they have declined year on year So is sports Our sports brand name remains very strong. However, there have been some operational challenges and personnel changes, which have led to a drop off. We see no reason why this cannot continue to grow in the future. The academic vertical also down year on year, although this is not a like for like decrease, since FY 2025 included the uptick due to the November 24 US election work. And we are confident this trend will continue in the future. However, as touched on by Steven already, and I am sure he will talk about it in a lot more detail later, we are all particularly pleased with the notable new client wins, from the hottest, most advanced tech businesses who come to us because they want the best data points and they appreciate understand the benefits the best data and insights give you Revenue from the AI labs themselves have shown a nice growth year on year The other vertical which is gaining deep traction financial services We are up nearly 20% year-on-year in this vertical, and we have got some great new blue chip global financial services clients with a very high and deep tech focus. Coming to us in the last 6 or so months. As our H1 results, in March, said that we needed to improve our cash conversion. And I am delighted to say we have increased this to 76% compared to 71% in our prior year and a mid-60s percentage outcome in the half. Not yet comfortable giving a forward looking target externally, but I will give you a commitment this will continue to be a key area of focus in FY 2027 and beyond And CapEx has increased year on year, for 2 main reasons: or 3 main reasons I guess Panel investment as part of the Shopper Investment Programme A big chunk of their investment is in modernizing and improving the depth and strength of their panels. And we have been increasing investment in technology, to enable the next steps in automation and product capabilities. The value delivery plan is not just about efficiencies and savings. it is about investments in the right areas too. We have a strong balance sheet. We are well capitalized with ample liquidity? The answer is a clear yes. As at the end of September, cash was 48 million and we had £8 million of undrawn RCF At the end of June, these numbers were 42 million and £6 million respectively We are generating cash and continue to generate cash. Hence, our confidence of launching the share buyback program today. During the year, we successfully extended the debt facilities, during H2 There was no additional funding no increase in borrower or guarantor obligations no change to pricing, covenants or security. Total commitments remain at €224 million comprising 184 of term and €40 million of RCF The 1 change we did get through with the banking group was to allow us to do a share buyback program. You may recall that at the half year, we could not do 1 because we needed to seek a formal approval. As Stefan has already mentioned, it does say the buyback has started today and will be up to as already disclosed over the next 12 months As guided at the half year, net debt to EBITDA reduced back to 1.7x interest cover over 6x And these covenants will be improving over the following reporting periods. Value delivery plan. Launched this in March. and momentum is building nicely. The transformation plan comprises 3 waves combine automation of key processes, efficiency improvements, simplification, and enhanced ways of working, along with significant transformation enabled by AI Plus, Wave 3 also includes significant new revenue streams as well. As you will recall, Wave 1 completed in March 2026, delivered an annualized $2.5 million reduction in our cost base, which targeted predominantly headcounts other cost reductions in non revenue generating areas. Page 26 includes some benefit from this action already, FY27 will benefit from the full year impact Wave 2 is deep in the detailed planning and implementation phase. It includes a broad range of initiatives. Automation and simplicity are 2 key themes as already disclosed. The combined impact of the first 2 ways is expected to deliver an annualized adjusted operating profit margin uplift of 350 bps over the margin achieved in H1 FY 26 which was 12.3%. We have high levels of conviction, this target will be achieved prior to the end of FY 27, Another example of delivering what we said we would deliver a few months ago. Wave 3 will focus on opening up new revenue streams through development of AI powered products and our data as a product capabilities. Our product development, data science, and technology teams continue to make strides in these initiatives including introducing imputation in our dataset, developing newer products such as YouGov Parallels know Steven will enjoy talking about it and adding more detail on these shortly. Waves 2 and 3 comprise 12 individual work streams each with an executive owner to optimize the speed and certainty of delivery. I was going to name the 12 names, but they are 12 and it will take some time. But everyone's doing a great job. I personally, I know the board is very grateful for the efforts the teams are doing to really push on with this transformation initiative. So final slide for me. Coming back to the priorities I mentioned initially, I want to give more clarity and granularity on trading and outlook. Had an encouraging start to the year bang in line with our expectations and our budgeted numbers. Currently, 49% of FY 2027 revenue expectations are contractually secured. that is not a weak pipeline. That is contractually secured. That is marginally up. On the same period last year. Hence, the confidence I have been earlier about FY 2027 being our 17th year of revenue growth despite the market conditions. We are making a lonely payment this month, the last day of October we will pay back €20 million of the loan. We have disclosed our share buyback already Investment in Shopper will continue in FY 2027 at broadly the same levels as FY 2026 Although, benefits of the investment program expected to start flowing through from a revenue perspective towards the end of FY 2027. Based on the significant progress achieved in planning and executing the Value Delivery Plan, over the last few months, along with continued investment in Shopper, the group expects to deliver adjusted operating profit of between 58 million and 61 million for FY 2027. This is in line with current market expectations. And this represents a year on year growth of around double digit percentage points. I will stop there and try to pass back to Steven, who can talk about the exciting stuff now.

Stephan Shakespeare: Thanks, Thanks, James. And it is called a Strategy Update, which sounds like it is sort of distant prospect. Everything I have ever had in the strategy update becomes reality very quickly. It is not it is actually a roadmap of what we are doing. Not some vague thing of this is what we hope to be doing. This is what we are actually doing. And the story of it is that we are benefiting from AI in 3 ways. It is the opposite of what people expected, AI is very much our future. The first which is very narrow, is--I mean, this whole thing is a new vertical, essentially, for us, AI. In terms of companies. Obviously, 2 new companies, Anthropic and OpenAI are the 2 main ones. They have become big clients of ours. Just very narrowly, we have done 4 million just in traditional reputational work that they use to communicate to understand audiences, but also to communicate Anthropic has made a big deal out of very large surveys that we have done for them, which connect them to their users and to the public in 1 of the ways that is essential to their strategy. So their spending there is already a biggest growing part of a specific bit of our business. And that number does not include lots of other stuff that is adjacent to it. Things that they need to know. Things that are consequence of news items and so on. I am not going to specifically those 2. I am talking about the whole sector. That comes to about SEK 11 million now in sales over the last 12 months. So that is really a big deal for us. They are not They turn to us They do not do it themselves. Of course, need an outside agency. They need to talk to humans. They do that. Mainly through us. Other companies as well. But the idea that human research is replaceable by machines is simply wrong. The machines really need the humans to supply that data. So that is the first bit. The second bit is internal efficiency. We are using AI to make our systems more efficient. I will go to slide on that in a second. And the third area, the most important is the enabled products Really, it is a transformation in products and in how we deploy data. So, that second box, automating research at scale, we are looking to make an end to end automated research flow. That does not mean, by the way, that the humans disappear. I actually think they will even necessarily be reduce. I think that we will grow in scale. And be able to do much more with the people that are there. Because the handling, the helping of clients around these flows, getting the most out of the system, is something that remains very important. So, just say that to ease concerns of people might have at the company that their job is going. Believe that I think we will see growth getting scale out of our systems being the way that we most benefit from the advantages. The advantages are also higher quality in some respects in terms of speed, consistency, accuracy, all of those things, because humans make mistakes. The more of that process that we can automate, the more of it we can streamline before it even gets into the system. Because at the moment, it is typical that people come with their projects and they do them anyway they design them in any way that they want and then we make that happen. And it is highly customized. But the advantages to them, well as to our own efficiency, is to streamline how they think about the work, and how that works its way through the system, and how that helps to reduce error. So the whole process is 1 that benefits all sides. Parallels, our new invention, This time last year, I talked about voices. Voices has become a successful part of our offer. We are now have just launched Parallels, which has also had its first 6-figure client confirmed. Parallels uses synthetic data. It is synthetic data together with human data. You all know what the power effect is. Having 2 eyes means you get 2 views of something that together make a 3-dimensional picture. that is what Parallels means. And that is exactly what we mean here. You get 2 views of the world. 1 is a narrow 1, if I can put it that way, narrow but accurate and deep, which is the human view. We can know, we talk to 1 thousand 2,000, 10 thousand people. That we know well and that we have lots of data for. The data that comes out of that is the most reliable human survey data in the world. And that is the foundation that can yield and that can create twins, synthetic twins, We have a partner, Original-Voices, that helps us with that, that is experienced in that and has operationalized that in various ways. To help get the maximum value out of that data. And that can be whether it is our data, brand index, the cube, all of that, to make the most detailed digital twins you can imagine. Or whether it is somebody comes along, does a survey with us, and then we turn the participants of that survey into digital twins that can answer lots and lots more questions in the future. But just having those 2 things separate, is not what makes the real 3D view. It is not just having either or combining the human view and the synthetic view. Is combining them through verification and validation. So at the same time as you generate questions and answers from the synthetic twins. Parallels allows you to take some of those questions. Let's say you are asking 100 or 200 questions of the twins. It does not matter how many you ask. it is very, very efficient. and very instantaneous, so you have no problem. You can ask as many questions as you like. You take 2 or 3 of those questions and run them against the human version of those same twins, at the same time, you can then use that to calibrate all of the other questions. So it is not only 2 different data sets, it is just the first data set that generated through some synthesis that is calibrated by the human data. That comes after. I do not think anybody else offers this, or can offer this the way that we can. Because we can talk to the same people at the same time as getting the twins because we have high response rates and we have lots of data that we create. So, our twins are constantly updated, they are constantly available, and you get this thing that answers the central problem of today, which is how good is synthetic? Do we have to throw it away and just have human data No. You can actually get the benefit of both in a way that strengthens both. So that is a fundamental change to an operating system. That is a fundamental offer that we make to the industry, which I do not believe anybody else can make. And that will be something that goes through. Somebody previously asked us how much you expect to make from this next year. it is very hard. I am not going to give an answer to that. Question as you already know. But I would say, in this case, because it affects everything else we sell. Every single client can have twins of the work. That we are doing for them in custom. Or in the syndicated part. So that is a big deal for us. That transforms the whole offering. And just to remind you of our ecosystem, it uses all the assets that we already have. I mean, did this a year ago. What are our assets? We have a high reputation with the public as well as with clients that allows us to have the best panel, which produces the best connected data that then allows you to do pretty much anything you like. Because if you start with engaged, live panelists, you can do all sorts of things. You can experiment and you can verify and validate and synthesize everything. So that is the basic offer. You have seen this before. The red stuff is what we have added. The 2 new parts there are voices and Parallels. They are all different entries into our world of data. You can go from 1 to the other, you can add them together. It is a connected system. And that leads to that connected system that leads to a seamless client journey. Throughout the whole world of data. This system is already able to query it using agents. We have MCPs. We have on our site you are able to ask questions of the data. That is at an early stage. I will not say to you that this is--I do say in development. You can, right now, as a client, go on Crunch, ask questions of the CUBE and see what there is. But that is almost table stakes. I said before, everybody else is doing that as well. The difference with us is the sheer quantity of data. But where it becomes exciting, is that the agent can not only say, here's what the data says, but do you need some other data? We can get it for you within 30 minutes. And you can write your own questions, or you can have the LLM, your own LLM,, or ours, or whatever we use in that place. To write the surveys for you from all the knowledge that we have to answer your questions. Then we can use synthetic and Parallels at the same time, In other words, the agents can arrange the entire journey to give you the most full, the most connected, and the most verifiable data there is in the industry. That is our system. And what you see there, all of that exists except for the green circle. The green circle is obviously an advanced AI system. We are not advanced creators of AIs. And we will be looking we have in mind someone like Thomson Reuters, who is made steps in this direction, creating their own domain specific foundation model. that is the area that we are very realistically looking at. Very specific. We are not saying we are going to be a gigantic AI company. that is not at all. We are talking about in our industry focused on how clients of market research use data in their businesses. that is our expertise. that is where we are focused on. And that is where we want to create the most advanced agentic model that there is. Which we can because of all the things that we already have here. And to repeat this model of being able to look at the data we have and instantly verify and add to it from the same people is, I think unique in the industry, certainly at the scale that we can do that. And we do have partners in this. So I know some people have said some of our very good investors who communicate with us, are you doing the Reddit thing? Are you selling lots of your data? That is a very dangerous thing for companies like us to do. If you have vast amounts of unstructured if I may call it dirty data like Reddit, then AIs make value out of that by taking all of it. We cannot possibly give all our data to somebody else to turn into something that people can buy through them. it is our data. We have to jealously guard it. Of course, we can share it through the systems, like MCPs that can be controlled, through agents that can be channeled in the right way to use that data. And that is what we are doing. But we are looking at partnerships here. I mean, we already have it is known to you we have a very strong relationship with Deloitte. Deloitte have upped their level of partnership with us significantly. And for their trust model, this is not a new thing. I think it is it is out there somewhere, but that is a developing an important relationship. And we have other relationships. That we are developing in order to get the value out of that and maybe actually give and take in there as well, that we can gain from their expertise. So, this is the way forward. This is a client journey that I think nobody else can mimic exactly And that is what already. Most of that already exists. So I end by saying we have got a framework for the next phase of YouGov's transformation. First, the new generation panel ecosystem. I have not said anything about that. that is actually my big final task in the next 3 months to make a bunch of changes that we have been making. We have some new methodologies for the panel, and I will tie that up and that will be for somebody else to present. Subsequently. But how we recruit and maintain panel is fundamental, obviously, to everything you have seen here. We are the best at it, but we need to be better because people are changing, young people. Engaging less. We all know that. it is getting harder to engage people into a continuous relationship. And we are doing new things in that area. The second AI powered platform transformation, I have just shown you that in some detail. Third part, I have alluded to before. But it is saying this is a platform company. This has a certain kind, is looking for a certain kind of work, and we have a unit that is focused on those partnerships that has had its first successes. And this goes to all parts of the business. This is not data versus custom. Custom. The difference between custom data custom projects, and data products is not the same anymore. They merge together. I am thinking of 1 piece that I want to mention, that I should have mentioned before, the data products all survive this as well, because they are data as a service. They continue to do really well. And I have said this before, but it is continued that the very, the most sophisticated, biggest companies are increasing the size of their subscriptions here, And probably the most scientific big name company in the world, now has a $1.5 million subscription to Brand Index So far from being becoming irrelevant, it is actually that data is becoming more valuable, not less valuable. And then finally, the operational efficiency and simplification we have talked about. Making all of this automated as possible so that our experts can also give the best possible advice and service. Because different customers need different levels of service. That is what it is all about. that is the end of that bit. We are now going to the Q&A. There is a microphone coming around. And I will take that from the seat. Take them. Thanks.

Analyst: I am Sean Tapp from Canaccord. 3 questions for me. I guess to start off with a big picture question is, sometimes hard to get kind of a client led view on spending. So, you know, across the industry, there is pretty low growth rates. They are pointing out. You know, industry competitors pointing out AI led growth, but there is a lot of AI washing that is going on there. Could you just kind of explain kind of how clients are approaching their research budgets spending areas where you are seeing demand, and maybe where there has been a little bit disruption from AI.

Stephan Shakespeare: Yes. And there has been disruption. I think I said at the beginning that you lose in some areas, but we are gaining in others. And when I look at the growth, it actually represents that loss on the 1 side and the growth on the other. it is a much better growth for the bits that we are obviously most focused on. 2 things, really. Clients are expecting to get more for less. I mean, that is the basic assumption with AI is that we are already benefiting from the magic of it. Obviously, we are not. We are not at the point yet where we have the savings that come in. I think this is true around the whole world in all industries. For most suppliers, they are not yet getting the advantages of the efficiencies which the clients are wanting to bake in. So that is that is 1 pressure. It has not actually hit us badly yet, because we have the other I say 'yet'. We are moving quickly to get those advantages. that is what the automation program is all about. And we hope actually to get uplift from it, because we will be the best suppliers of that automation, and can in fact respond to those demands. But the other area is that the need for human data is growing. So, you are seeing that is why you are seeing a lot of companies wanting more of that, wanting to make more out of it. that is where we are seeing the growth. So, where we are seeing loss is for example, media agencies, they are spending less. Would expect that. Brands, I think, are reasonably stable, and the AI companies are or anybody doing innovation in that area is becoming. Is growing.

Analyst: Maybe coming back on those AI companies is AI labs? Some of the AI labs now are some the biggest companies in the world. From a kind of a research spending perspective, how do they differ from the kind of Mag 7 type companies that you have already got a very big contribution from in your client base? And I guess the slightly cheeky question on top of that is do you expect to be able to capture the same share of wallet as you have done in previous large tech platforms?

Stephan Shakespeare: I mean, 1 of the funny things about it is that those clients come back to you and tell you how you should be doing your business. And they say, well, actually we have looked at how you structure your things, because they sort of a sneaky look, I do not know how, and say, why did not you do it this way? It would be much or much better. So, they can be very demanding in a good way. It forces us to innovate faster, to listen and to see how we want to deal with that. They are much less interested in your advice, in our advice, our consultancy, I think, is going to be assumed to come free. Because actually they do not need it. And they do not often even care how you are packaging up the data. In fact, they tell us we just want it raw, and so, this is changing the demand But for us, this is what we want. Where we make our margin is in quantity of high quality data. The bit that they cannot get from anyone else, is the actual relationship with humans that is a trusted personal relationship, actually. And you need that, I think, in order to create great data.

Analyst: And then a final question for me is just kind of tying together the strategy update with the value delivery program. I guess if we were to take research automation and additional AI revenues, do they map to a certain wave in the value delivery program? Or to ask this different way? Is the 350 bps you are getting from stage 2 dependent on wide scale research automation and or additional AI revenues.

James R. Davies: I think it is the 2 bits together, but Typically, automation is within wave 2. And if we get the full wave of automation, is not expected to happen all in this financial year. It will be a benefit above and beyond the 350 bps for the full automation, but there is a part automation within that number. And the new revenue streams are typically are in Wave 3. There will be no new revenue in wave 2.

Stephan Shakespeare: Thanks.

Lara Simpson: Good morning. it is Lara Simpson from JPMorgan. My first question was just to come back to data products. Obviously, we saw quite strong acceleration in growth in the second half of the year. I know you spoke about the U.S. But could you just talk a bit more around the nature of this client and contract wins and I suppose the sustainability of that if they were more 1-off in nature or a bit more recurring. I suppose follow-up to that is trying to think about the building blocks to growth in FY 2027 and if you think that strong exit rate is sustainable. On the data product side in particular. And then my second question was on shopper. I know you have said the strategic review is ongoing. Wondering if you could give us any indication on when we should expect to get an update on that or otherwise how far in discussions are you, or if the board has at least given an internal timeline on when they would expect a decision to be made. And with that, just interested again on the rationale for continuing to invest in that business. I think, James, you said investments will be similar to 2026. I think the 1 discussion I have is you are obviously investing in a business that might not be with you on a go forward basis. So just trying to understand the rationale for those investments and how you are thinking about yielding the return on those.

Stephan Shakespeare: Well, I think on the on the latter, I am really not going to say anything about the timing it is obvious that I cannot and will not. The other bit of that, though, is that shopper needs to remain strong and yielding growth and that requires investment. So if you wanted to sell something that had gone flat, that would not work either. So that simply fits the plan. It does not say anything about what we think is going to happen. It just has to be.

Lara Simpson: The first question which I think you are saying how are there new clients for our data products? Just trying to understand. I think data products accelerated. I think you did close to 7% growth in data products in the second half of the year. So just trying to understand the drivers of that. Acceleration and performance.

Stephan Shakespeare: Look, it is a really efficient way of understanding something that you can only do with human data. And that is change. 1 of the things I meant to say earlier that is fundamental to understanding our business, and how it is affected by AI, is to know that most of what we do is to measure change. We obviously do some static polls and studies, and so on, but that is not the core of what we do. We measure change day in, day out. By lots of different products and by big custom trackers. All of those things are about understanding how today is different from yesterday. And the 1 thing that AI and synthetics cannot ever do is tell you how things are changing, except retrospectively. If they are to project forward, and I think a lot of synthetic data companies like to tell us they can because they are so brilliant and they know how the weather's going to affect everything and all these other mysterious things. If they could do that, they could only tell anything about the future by continuation of patterns from the past. They might say, if things continue as they look today, it will go this way. that is not why you buy trackers. You buy trackers to see what actually happens. And you are interested in surprises. So this product that we are launching, that tested well, and theoretically should go well, how is it actually going? Will people take it home? And the kids play with it, and the kids' friends play with it. How does that work through? Actual usage? What happens when there is a scandal or a new advertising campaign or some related economic change, If it is as expected, it is priced in. it is not valuable. it is only valuable when you do not know which way it is going, or you need to know when there is a surprise. And you can only do that with live human data. By definition, because of everything else is the continuation of existing patterns. So that stuff is not going to be, in my view, it is not going to be attacked by AI. And that is why I am so confident about synthetic from our point of view, because it is a way of getting extra value. It is hugely valuable. I was not knocking synthetic data as you understand. Just for measuring change. You cannot measure change with it, but you can get lots more value out of the data you have produced. So that does not attack our core business. Indeed, it gets more value out of it. Having said that, I do imagine that some people who are used to having trackers might simply not do them anymore. Or not do them as much or as frequently, because they think actually there are some things that we can get elsewhere. So I do not pretend that there will be no effects And that is why it is important for us to be the best that we can be, so that when you do keep tracking studies going, it is us that do the best job for you. And that is where I think the richness of our data and the smartness of our science is ahead of everybody else. But I cannot say to you, that I can make confident predictions about how all data products will go. I think we are well defended. Our moat is our panel. Nobody can touch that. Nobody can equal it. The entire desire of the synthetic companies is to squeeze out humans. They go and they buy mass polling, and hope that they get this they make their twins and they do not have to talk to them again for another year. And get lots of value out of it. That does not work. They have to have live data. To make a great product. So I think we are in a strong position. Thank you.

James R. Davies: I would not want everyone to model 7% or 10% growth in data products next year on the top line. I think the 2 or 3 encouraging things to add to Steven is even though agencies the overall income we got from agencies this year is lower than last year. But we are still winning some pretty big high profile data products revenue from the agencies. Themselves, which supports Steven's point that our product is still very truly alive. In a vertical sector that is kind of moving against it in some ways. And also, what is encouraging is that the some new technology clients, 1 of which we alluded to with the H1 results, which have no benefit for actual H1. that is come in relatively materially in H2 as well. So technology clients are often more custom trackers and more research based, they are now seeing the benefits of data products. So my focus on data products personally, is very much the margin side. And to ensure that we still get these blue chip new clients coming in. But the margin side is something that the value delivery plan is hitting pretty hard on data products because it is syndicated. it is got amazing operating leverage as we proved in H2. So that is as important as any top line growth a value delivery perspective.

Lara Simpson: Perfect. Thank you.

Stephan Shakespeare: Thank you.

Sean Kelly: Good morning. Sean Kelly from [Inaudible]. Thank you. Morning. Sean Kelly from [Inaudible]. I have got 2 for you, James, and then hopefully 3 for Steven, if that is if that is alright. So apologies for possibly setting a record for a number of questions. First of all, James, you are very clear at the half year that you thought MI and sort of infrastructure inherited was good enough to run the business. I just wanted to get your updated view on what you think now of quality of financial reporting and infrastructure that you are working with. I am particularly noticing you have had a restatement on tax this year and so on.

James R. Davies: For factory reporting, no issues at all. We just had -- I did my first audit. With them and it was a very clean audit, very relatively easy audit The tax issue is I would say, a minor frustration Happy to talk to you 1-on-1 about what the detail is. it is basically to do with the shopper fair value versus cash value when we purchased it. There was an accounting change which was not picked up at the time. We paid -- we paid for the accounting change, it did not give us a credit for the extra payment. So that was a minor sort of acquisition based change, which is annoying and it is not ideal. Does not reflect on anything to do with our systems and our MI. I am feeling that each week I am there, I am getting more comfortable with the commercial MI actually helps people make decisions and the whole thrust of the value delivery plan, there is 1 of the 12 work streams is on systems more generally. And focusing on margin more generally, on time sheets more generally, So all this sort of, you know, know, wiring and sort of a good discipline is key theme, and that is all happening. And, like, for example, now, previously, time sheets were filled in by some cohorts of our team, but not everybody. So you could get misplaced margin on some products, whereas now, 100% timesheet completion. Full stop. Are they all reviewed and everything done properly yet? Not quite. We have already seen the benefits. So in answer to your question, systems from a commercial perspective give me what we need, and I would not read anything into the prior-year adjustment. that is an annoyance as opposed to a systems issue.

Sean Kelly: Perfect. Very clear. Second question, given the ongoing value delivery program, are you able to give us a gentle guide at this point for cash restructuring charge for the coming fiscal year?

James R. Davies: I would rather not give an actual number, but we are the areas we are investing in is in data scientists and engineers. And we are only going to be investing in that area if they are going to deliver a particular feature or product and by definition, that means it will justify going on the balance sheet. So there will be a more structured more tech company focused approach to our capitalization of that type of spend. A bit too early for me to give you an indication of a number. I am happy to be asked that question at the half year when I will have more clarity. Thank you.

Sean Kelly: And then Steven, if I can just rattle through 3. First of all, in terms of Parallels, can you just run me through. I appreciate you have sort of said in the presentation that it is token based pricing. But where are you seeing pricing for that product sort of and I appreciate it is really early stage, but maybe it is more a question of where you are targeting pricing for that product relative to other services that you guys provides. Secondly, respect to the MCP connection, I am just really interested to discover Are you primarily seeing clients pull your data into their own environment? Are they pulling it into an environment created by a third party company? I am just I am hoping to understand is sort of where clients are interacting with your data and so on. And then finally, on the AI labs revenue, both the figures of 4 and 11 that you gave, are you able to just sort of give me a run through of where exactly that sits in divisions and various halves? Of the of the. You are just gone.

Stephan Shakespeare: I started with the last 1 first. Remember the last 1. So the 4 and 11 split this way. The 4 specifically works for AI companies that we were not. That happening before. The other is for investigating and adding to work that we have with other clients. Not with some of them maybe labs. I mean, obviously some of our biggest clients, as you know, are Silicon Valley. So they fall into more than 1 vertical. But there related things about how AI affects them. As well as how using it for AI itself. So the 4 is just specifically for dedicated AI companies. The others are for other effects being measured, but that we would not have done if there had not been that. So you could say that it is a bit blurry whether because there is always something happening that you are investigating. So you might have might have might have had that. But it is. It does present itself to us as a new vertical, as a new thing that people have to think about. They are not only thinking about what the customer's economics or whatever. it is it is it is a new thing they think about. So that is why it is 4, and then rate rises to 11. If you take into account all those other related things. The second 1 was on the MCP connection.

James R. Davies: I am actually not very good on this bit. I am not a technical they do not get to import our data. They pay for data, which they then can use. But I would embarrass myself if I said much more. but I will get somebody to find an answer on that. Just to add to it, yeah, we are very conscious that our General Counsel is, sitting in the back actually, but we are very conscious that if we start giving people to our data, do we get disintermediated? Are we going to lose some control? So we are spending a lot of time on that at the moment with various advisors and helpers, because it is clearly a risk If we get that wrong, that is not good, but we are being very diligent to make sure if we let anybody anywhere near our environment, there is very strong legal protections. And it is a well trodden path in other sectors. So we are getting the best advice to protect ourselves in that area.

Sean Kelly: Anything else, first? Yeah. Thanks for both your answers. The first question was just on pricing for Parallels. Appreciate it is early days.

Stephan Shakespeare: it is actually really hard. We have got a rate card. The synthetic and real bit are 2 different things. And the real bit is priced the same way as any other research that we do. And the synthetic is something we are working out on the fly with our partner. That I mentioned. So, right now everything is individually done and experimented with. It is a completely new area. And these are not definitive answers, I am afraid.

Hai Huynh: it is Hai Huynh from UBS. I have got a couple. In terms of your growth assumptions for next year, could you clarify a little bit of the dynamic that you see versus this year? And is it going to be when you said not 7-10% data products, a bit more normalized than that, but also slight improvements sequentially in shopper the investment you made? Is that what you are seeing? The second 1 is on in terms of the macro impact you are seeing over the next year, obviously, US midterms coming up. How helpful is that to numbers usually? And. But the interest rate environment, on the other hand, and cost inflation coming up, so a general macro view on how that impacts your top line and margins. And then finally, there is been recent news on, you know, a potential acquisition from Salesforce to AI enabled like, ListenLabs, for example, alternatives, which are gaining a lot of traction at least from reporting. Do you see that as a potential threat to some of your business given that their business model is low cost, fast turnaround? And I know, obviously, your answer to that is Parallels, but do you see a potential displacement in the near to medium term, and how do you address that? Thanks.

James R. Davies: I will do the last 1, but you do the other ones Actually, I will do it first. So terms of revenue forecast here. We deliberately have not given a formal revenue forecast. Obviously, if we were not comfortable with what the consensus was, we would let people know. So there will be growth in the core business next year. There will be marginal growth in Shopper is my prediction based on where we are at the moment and in H2. H2, we do expect that the benefits of the previous investment will start to show through. Because with the shopper investment, as many of you will know, you do not invest today and get benefits tomorrow. You invest in a panel over a 12, 18-month period. Then benefits come through at a later date. So there is a time lag, but that time lag ends in H2 next year. So we are not guiding to a 7%, 10% overall revenue growth. But I did allude to the fact that we are focusing on growth next year. Terms of the macro impact, the way that I am personally dealing with it and the company is dealing with it is we will go back to value delivery plan. The value delivery plan is about deep rooted discipline. So if we see something that is not going in the right direction, we will stop it and stop investing in that area. So it is really acting and behaving like a modern tech company where you see trends move, do not be -- yeah. Stop and invest elsewhere. So I think that discipline, if it is to work as it has been in h 2, we should overcome lots of other sort of external challenges to face us because we are being much more agile adapting in where we invest, where we make headcount requests, where we invest in systems and technology as well. So nothing major to report on that. there is obviously some and I alluded to briefly timings of elections. They do impact us somewhat. And we are we have had a great 6 to 12 months in the new sector, the AI world, investing in us where maybe the agencies have been a bit softer. So we are continuing making sure we are relevant to whoever needs our research going forward.

Stephan Shakespeare: You are right to raise those companies. They are very interesting and they are slightly different to us. So ListenLabs as I understand it, does interesting things with people with companies' own data. And that is why it is valuable. I think there is lots of crossovers in some people as well. But principally that they are valuable to Salesforce because of their interface with people. Rather than, I mean, as far as I know, they either have not yet started, or they have hardly done anything with synthetic twins, and I am not sure if they are particularly interested in that. That area. But it is not the same offer. it is not what I have described at all. it is similar to you look at it similarly, simile have a strong partnership with Salesforce. And it is about how they work with Salesforce data. In other words, how they fit into that relationship. So it reminds me more of what Qualtrics does, as something engineered into a company's own customer systems. And then there is ArU, which is different again, but in all 3 cases, they do not develop their own their own human resource, their own panels. Now, that is critical for us. Our special sauce is that. We are not doing the other stuff. We are focusing on what we can do best I do not think they can ever achieve what we are doing there. Partly because of the way that even if they did try to build panels, their relationship to people would be probably a bit spooky. We are very We have a very strong open relationship, transparent relationship with our panelists. They trust us. In a way that they might not trust a pure AI company that does other stuff with their responses. We are very clear about how people's data is used. We give them lots of assurances that we can then follow-up with very ethical behavior. I am not saying that others are unethical, I am saying that they are not able to develop those relationships. Our special sauce is our moat is that relationship with large numbers of humans. Sharing a lot, not just doing a few, surveys, but actually sharing data, sharing even downloaded data, behavioral data.

Operator: Got time for about 2 or 3 questions that have come in online. The first 1 is for you, James. What was the 49% metric of contract secured revenues in the past 3 years? Is that with or without Shopper,

James R. Davies: It includes Shopper. That was a quick answer.

Operator: It was. And then second 1 also for you, why do we not have any new revenue targets given product stroke automation rollout? How much of FY 2026 revenue is under pressure or disappearing as the market shifts to AI stroke synthetic products?

James R. Davies: Well, 1, we did not give revenue guidance because we felt giving bottom line guidance was more helpful. that is the honest answer to that question. But I have alluded to, obviously, growth very publicly a little while ago. So there is going to be growth but we are not giving a clear revenue number at this stage. Terms of revenue under pressure, Stephan and I have alluded to quite a few of the shifts in the vertical sectors that are more in that are growing and shrinking. Do not think there is going to be a material change in anything I think the 1 thing, as I did touch on just now, is even though agency revenue as a whole is down, agency revenue in data products is up. You could argue that trend is potentially beneficial to the value of the business, as opposed to not beneficial. So there is lots of trends that are happening, but I do not see any step change going to think, actually, this is the step change the step change I do think we are going to continue to see is financial services improving. Further. And the AI world investing further and the tech vertical getting stronger and stronger. And some of the less. Could we have to say less modern verticals are willing to maybe accept slightly less good quality data, may somewhat decline, but I think that the growth in the positives will more than outweigh any shrinkage in the negatives. And we are focusing much more on margin and revenue quality now as well than maybe previously. So in terms of value creation, that trend should definitely work in our favor.

Stephan Shakespeare: Yeah. And it is worth mentioning, I think I am allowed to mention that the order book has never been bigger at this time of year. Our history. It is. it is. Yeah. I am not saying it is 20, 30% higher than last year, but it is a good few percentage points higher. And as I said, that is contracted. it is not just a floppy pipeline.

Operator: Thank you. I think we have time for 1 last 1. This is 1 for you, Steven. Can you give more color on refocus on data products? Is the separate sales team structure now in place?

Stephan Shakespeare: So that is a reference to something we said 2 or 3 years ago, when we said that where our strategy had got lost was in merging, saying you can sell everything. And we said, you need to sell data products separately from custom in order to get the most the most sales, because it is a different approach and it requires different skills. And that is why we set up this unit that I mentioned, which is adding this expertise to everybody else's continuing sales, but has its own program of growth. Which is dedicated to its core data partnerships, Some of those--and that itself divides into 2. 1 is basically MCP clients and the other is Deloitte type clients. And that is pushing out solutions, as they say, across all kinds of clients. And the change, which I did allude to earlier today, is that the division between data and data products and custom is changing very much as a consequence. What AI allows you to do. So the contrast you can now customize anything that we do as a data product. Whether that is adding YouGov voices to it, which are then customized to the needs of the client, asking the questions that programmed for the client, or whether it is synthesizing twins that you then validate as add on research There is no longer the clear distinction. But we have changed a little bit of our organizational structure, for a platform team and a research team. They are working together much more than they would have done had I looked at this 3 or 4 years ago. So yes, we are pushing different kinds of sales through different kinds of channels. But also there is much closer cooperation between custom and product.

Operator: Thank you. I think that brings us to the end of questions online, and I am gonna hand back to you Steven, for any closing remarks.

Stephan Shakespeare: Well, just thank you very much. all of you for coming, and Really interesting questions, really interesting discussion. And I think YouGov is in a very strong position right now. I am very happy to have 3 more months as I hand over to an extremely able successor. Who will be here next time. Bye.