Good morning, everybody. Thank you for coming, and it's good to see you. This is my second time of having a last presentation. I think this really will be the last one. It has been a good year. We've strengthened pretty much on all fronts. We've got a 2% increase in our data products, which a while back people were thinking, "Well, that's all going to be taken over by AI." That'll be a theme for me today to say actually, AI is a big benefit to us and a big opportunity. It isn't something that's been holding us back, and you can see that in a very difficult market, and it's 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're growing, and we're growing where we most want to be growing. We've been strong on controlling costs. You'll hear a lot more about the VDP from James. 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 two years ago, or one and a half years ago, I said I was going to do three things in that interim period, that I had specific objectives. One is to stabilize the business. I think you can see our numbers have done that, and I'll give 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.
On the first of those, we've seen accelerating growth in our key areas, with 3% up versus last year. In data products as well, we've done particularly well. We've got that cost discipline that I referred to. Also, we have made that switch back to focusing on data products from custom. It's not that custom isn't important. Custom has also become very much more a data product than it used to be. It's 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. We've 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've enhanced the product.
There is now an AI agent that can tell you about what's in the data and help you find more, and that will be growing. 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. To get the most out of that is what we're doing. We're adding MCPs, of course, all of that. But above all, as you'll see later on, we're making it a platform that an agent can use directly. Those are our AI-powered solutions, and the platform we've long talked about, now it is becoming really a full-on data platform. Again, I'll show you later on at the end where that's going. The third priority was that leadership transition.
I said that we wouldn't make the same errors twice, that we were looking for somebody who has proven leadership in adjacent area, where we can see what they've delivered. In Wayne Levings, we found that. Somebody who has led teams, grown P&Ls, knows the industry inside out, and also understands the challenges of AI. We have somebody 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 expected to immediately fit right in, because there's a lot. We're a complicated company. We're different to all other companies in our industry, and it does need a proper transition. I'm looking forward to that period.
I have a very strong relationship with Wayne, and I'm very confident that we're 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 the 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.
Hello, everyone, and thank you, Stephan. This is now my second results presentation since I've been at YouGov. You may recall my first one was at the half year after just five weeks of joining. The last six months have definitely been fulfilling. We've made deep progress on the planning and execution of the Value Delivery Plan. We're investing in areas that matter. We are grown up now, yet we are keeping the entrepreneurial discipline alongside all of the decisions we make. Alongside all of that as well, we are keeping innovative ideas flowing, and they're not just flowing, they're flowing and they're converting as well, and Stephan will talk about that in more detail later. Before we get into numbers, I wanted to highlight the key priorities of H2 from my perspective and the wider board's perspective as well. There's seven of these priorities.
Priority one, from a market and investor relations perspective, we want to do what we say we're going to do. I've been in the public markets for a long time, and I know how important that is for employees, for external analysts and investors. So we commit that is what we're 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 two, rebuild trust and improve transparency and clarity where possible. Throughout this presentation, I will refer to things that we committed to with the H1 results and either confirm the action is completed or update on how we're 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 in a changing environment. If our direction does change, we commit to explain clearly what that change is 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 three, 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 four, obtain approval for a share buyback program and start the program. I am delighted to confirm that the buyback starts today. I believe actually already it has started. Over the next 12 months, up to a total amount of GBP 15 million will be returned by this route. Priority five, evidence continued solid execution of the Value Delivery Plan.
Wave one was executed at pace before the H1 results. Wave two and three are well underway. Planning is advanced, and execution is happening. Priority six, initiate the wide-ranging strategic review of our Shopper division. Again, that is ongoing. Priority seven, provide clear guidance going forward. No vagueness or confusion. In the release, you will see very clear guidance in pounds, millions, numbers with no confusion, vagueness, or clandestine approach to what we think will happen. 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 seven tier-one priorities. Please do challenge me or Stephan, either today or later, if you feel we have not achieved those objectives. I have circled four of these points: one, two, five, and seven. These priorities are not just for the last six 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, and we make sure that we will embrace that in a very grown-up and clear way. Before I move on to the segmental operational results and with priorities one and two in mind, i.e., do what we say we do, and then transparency and clarity, I wanted to cover off how we reconcile between adjusted and statutory group numbers. We have rightly been criticized for lack of clarity in this area before, and I committed in the 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.
Hence our commitment to priority two, 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 three buckets. Bucket one, I want to ensure that our balance sheet holding values for assets was 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 DACH business. As a reminder, DACH 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 the simplicity and efficiency of our global office footprint as part of Value Delivery Plan. Along with some impairment 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 two, amortization. An accounting rules-led amount, which is following on from our Shopper acquisition. This relates to two items, order backlog and customer list. The order backlog was fully amortized prior to the start of this financial year, and the amount of GBP 5 million from the prior year will not continue. That leaves GBP 10 million this year, which covers the customer list amortizations. In FY 2027, we expect this aspect to continue with another GBP 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 as this year. However, the order backlog will not come back. So circa GBP 10 million is going to be the number that fills bucket two going forward in this category. Moving on to bucket three. This is the only cash item within this grouping, and arguably the more relevant line item when it comes to assessing underlying value. Buckets one and two are non-cash. In high-level terms, bucket three covers restructuring costs. These fell from GBP 13 million last year to GBP 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 SRIs has more than halved year-on-year, with a reduction of GBP 7.7 million.
Going forward in FY 2027 and beyond, bucket three will continue to be material as we deliver the Value Delivery Plan. Bucket two will be GBP 10 million, as I discussed, and bucket one will be assessed throughout the year to ensure all balance sheet values are appropriate. The GBP 33.1 million total explains the difference between adjusted and statutory measures on the face of the results announcement. The adjusted EPS at GBP 0.30 is down 11%, which is broadly in line 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, moving on to the segmental operational results. As Stephan alluded to, each of our three 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 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. FY 2026 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 2027 to be our 17th 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 suggests that 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. Shopper's margin is materially, I don't know whether to use the word different or lower. Either way, it's lower relative to last year, and this is exclusively to do with the game change investment program we discussed at the H1 results. If you were to add back this specific investment and targeted investment, the margin would be flat year-on-year. Moving on to our geographic performance. Very strong performance in Americas. Ray and his team in the U.S. had a very encouraging H2. All 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 6-12 months is particularly pleasing.
There have, however, been some tough sectors, as we have discussed before, agencies being one, and they are weaker and they have declined year-on-year. So is sports. Our sports branding 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 can't continue to grow in the future. The academic vertical is also down year-on-year, although this is not a like-for-like decrease since FY 2025 included the uptick due to the November 2024 U.S. election work, and we're confident this trend will continue in the future.
However, as touched on by Stephan already, and I'm sure he'll 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 and 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 is financial services. We're up nearly 20% year-on-year in this vertical, and we got some great new blue-chip global financial services clients with a very high and deep tech focus coming to us in the last six or so months.
At our H1 results, in March, I said that we needed to improve our cash conversion, and I'm delighted to say that we've increased this to 76% compared to 71% in our prior year and a mid-60 percentage outcome at the half. I'm not yet comfortable giving a forward-looking target externally, but I'll give you a commitment that this will continue to be a key area of focus in FY 2027 and beyond. CapEx has increased year-on-year for two main reasons, or three main reasons, I guess. Panel investment as part of the Shopper investment program. A big chunk of their investment is in modernizing and improving the depth and strength of their panels. 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 investment in the right areas too. We have a strong balance sheet. Are we well capitalized with ample liquidity? The answer is a clear yes. As at the end of September, cash was GBP 48 million, and we had GBP 8 million of undrawn RCF. At the end of June, these numbers were GBP 42 million and GBP 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 EUR 224 million, comprising EUR 184 million of term and EUR 40 million of RCF.
The one change we did get through with the banking group was to allow us to do a share buyback program. You may recall at the half year we could not do one because we needed to seek a formal approval. As Stephan has already mentioned, I would like to say the buyback has started today and will be up to GBP 15 million, as already disclosed, over the next 12 months. As guided at the half year, net debt to EBITDA reduced back to 1.7x, with interest cover over 6x . These covenants will be improving over the following reporting periods. Value Delivery Plan. We launched this in March, and momentum is building nicely. The transformation plan comprises three waves. The waves combine automation of key processes, efficiency improvements, simplification, enhanced ways of working, along with significant transformation enabled by AI.
Wave three also includes significant new revenue streams as well. As you will recall, wave one completed in March 2026. We delivered an annualized GBP 2.5 million reduction in our cost base, which targeted predominantly headcount and other cost reductions in non-revenue generating areas. H2 2026 includes some benefit from this action already. FY 2027 will benefit from the full- year impact. Wave two is deep in the detail planning and implementation phase. It includes a broad range of initiatives. Automation and simplicity are two key themes as already disclosed. The combined impact of the first two waves is expected to deliver an annualized adjusted operating profit margin uplift of 350 basis points over the margin achieved in H1 FY 2026, which was 12.3%. We have high levels of conviction this target will be achieved prior to the end of FY 2027.
Another example of delivering what we said we would deliver a few months ago. Wave three 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 of our data set and developing newer products such as YouGov Parallax. I know Stephan will enjoy talking about it and adding more detail on these shortly. Waves two and three 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 there are 12, and it will take some time.
Everyone's doing a great job, and I personally, I know the Board is very grateful for the efforts the team are doing to really push on with this big transformation initiative. Final slide from me. Coming back to the priorities I mentioned initially, I want to give more clarity and granularity on trading and outlook. We've 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's not a weak pipeline. That is contractually secured. That is marginally up on the same period last year, hence the confidence earlier about FY 2027 being our 17th year of revenue growth despite the market conditions. We're making a loan payment this month. The last day of October, we'll pay back EUR 20 million of the loan. We've disclosed our share buyback already.
Investment in Shopper will continue in FY 2027 at broadly the same levels as FY 2026, although the benefits of the investment program are 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 GBP 58 million and GBP 61 million for FY 2027. This is in line with current market expectations. This represents a year-on-year growth of around double-digit percentage points. I'll stop there and politely pass back to Stephan, who can talk about the exciting stuff now.
Thanks, James. It's called strategy update, which sounds like it's a sort of distant prospect. Everything I've ever had in the strategy update becomes reality very quickly. It's actually a road map of what we're doing. It's not some vague thing of this is what we hope to be doing. This is what we're actually doing. The story of it is that we're benefiting from AI in three ways. It is the opposite of what people expected. AI is very much our future. The first, which is very narrow, is our—t his whole thing is a new vertical, essentially, for us, AI, in terms of companies. Obviously, two new companies, Anthropic and OpenAI are the two main ones. They've become big clients of ours. Just very narrowly, we've done GBP 4 million just in traditional reputational work that they use to understand audiences, but also to communicate.
Anthropic has made a big deal out of very large surveys that we've done for them, which connect them to their users and to the public, in one of the ways that are central to their strategy. Their spending there is already a biggest growing part of a specific bit of our business. That number doesn't include lots of other stuff that is adjacent to it, things that they need to know, things that are a consequence of news items and so on. I'm not talking specifically those two, I'm talking about the whole sector. That comes to about GBP 11 million now in sales over the last 12 months. That is really a big deal for us. They turn to us. They don't do it themselves. Of course, they 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. That is the first bit. The second bit is internal efficiency. We are using AI to make our systems more efficient. I have got a slide on that in a second. The third area, the most important, is the AI-enabled products. Really, it is a transformation in products and in how we deploy data. 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 do not think they will even necessarily 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. I just say that to ease concerns that people might have at the company, that the jobs are going. 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 respect 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 design them in any way that they want, and then we make that happen, and it is highly customized. But the advantages to them, as 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. The whole process is one that benefits all sides. Parallax, our new invention. This time last year, I talked about Voices . Voices has become a successful part of our offer. We now have just launched Parallax, which has also had its first six-figure client confirmed. Parallax uses synthetic data, is synthetic data, together with human data.
You all know what the parallax effect is. Having two eyes means you get two views of something that together make a three-dimensional picture. That is what parallax means. That is exactly what we mean here. You get two views of the world. One is a narrow one, if I can put it that way, narrow but accurate and deep, which is the human view. We talk to 1,000, 2,000, 10,000 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. That is the foundation. That can yield, then that can create twins, synthetic twins. We have a partner, OriginalVoices, that helps us with 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's our data, BrandIndex, 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 two things separate isn't what makes the real 3D view. It isn't just having either or combining the human view and the synthetic view. It is combining them through verification and validation. So at the same time as you generate questions, answers from the synthetic twins, Parallax allows you to take some of those questions. Let's say you're asking 100 or 200 questions of the twins. It doesn't matter how many you ask. It's very, very efficient. It's very instantaneous, so you got no problem.
You can ask as many questions as you like. You take two or three 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's not only two different data sets, it is the first data set that you generated through synthesis that is calibrated by the human data that comes after. I don't 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're 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 don't believe anybody else can make. And that will be something that goes through. Somebody previously asked us, "How much do you expect to make from this next year?" It's very hard. I'm not going to give an answer to that question, as you already know. But I would say, in this case, precisely because it affects everything else we sell. Every single client can have twins of the work that we're doing for them in custom or in the syndicated part. So that is a big deal for us. That transforms the whole offering.
Just to remind you of our ecosystem, it uses all the assets that we already have. We 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, which then allows you to do pretty much anything you'd 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, synthesize everything. So that's the basic offer. You've seen this before. The red stuff is what we've had. The two new parts there are Voices and Parallax. They are all different entries into our world of data. You can go from one to the other. You can add them together. It is a connected system.
That connected system leads to a seamless client journey throughout the whole world of data. This system is already. You are able to query it using agents. We have MCPs. On our site, you are able to ask questions of the data. That is at an early stage. I will not say to you 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. 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 is what the data says, but do you need some other data?
We can get it for you within 30 minutes." You can write your own questions, or you can have 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 Parallax 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 that there is in the industry. That is our system. 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 has 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 what we are saying. 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. Do 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. We do have partners in this.
I know some people have said, some of our very good investors who communicate with us and say, "Are you doing the Reddit thing? Are you selling 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 the 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, and 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.
We already have, it's known to you, 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's out there somewhere. That's an important and developing relationship, and we have other relationships that we're developing in order to get the value out of that, and maybe actually some give and take in there as well, that we can gain from their expertise. This is the way forward. This is a client journey that I think nobody else can mimic exactly, and most of that already exists. I end by saying we've got a framework for the next phase of YouGov's transformation. First, the next- generation panel ecosystem. I haven't said anything about that.
That's actually my big final task in the next three months, to make a bunch of changes that we have been making. We have some new methodologies for panel, and I'll tie that up and that'll be for somebody else to present subsequently. But how we recruit and maintain panel is fundamental, obviously, to everything you've seen here. I think we're the best at it, but we need to be better because people are changing. Young people are engaging less. We all know that. It's getting harder to engage people into a continuous relationship, and we're doing new things in that area. The second, AI-powered platform transformation. I've just shown you that in some detail. The third part, I've alluded to before, but it is saying this is a platform company.
This 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. This goes to all parts of the business. This isn't data versus custom. The difference between custom data, custom projects, and data products isn't the same anymore. They merge together. I'm thinking of one piece that I want to mention, that I should have mentioned before. The data products all survive at this as well because they are data as a service. They continue to do really well, and I've said this before, but it's continued that the most sophisticated, biggest companies are increasing the size of their subscriptions here. Probably the most scientific big-name company in the world now has a $1.5 million subscription to BrandIndex.
So far from becoming irrelevant, it's actually that data is becoming more valuable, not less valuable. Then finally, the operational efficiency and simplification we've talked about, making all of this as 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's all about. That's the end of that bit. We are now going into the Q&A. There is a microphone coming around, and I'll take that from the seat. We will take this.
Thanks. Sean Thapar from Canaccord. Three questions from me. I guess to start off with a big picture question is, it's sometimes hard to get a client-led view on spending. Across the industry, there's pretty low growth rates. Industry competitors pointing out AI-led growth, but there's a lot of AI washing that's going on there. Could you just explain how clients are approaching their research budgets, spending areas where you're seeing demand, and maybe where there has been a little bit of disruption from AI?
Yes. There certainly has been disruption. I think I said at the beginning that you lose in some areas, but we're gaining in others. When I look at the growth, it actually represents that loss on the one side and the growth on the other. It's a much better growth for the bits that we are obviously most focused on. Two things, really. Clients are expecting to get more for less. The basic assumption with AI is that we are already benefiting from the magic of it. Obviously, we're 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're not yet getting the advantages of the efficiencies which the clients are wanting to bake in. So that's one pressure.
It hasn't actually hit us badly yet because we have the other —I say yet. We are moving very quickly to get those advantages. That's what the automation program is all about. 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 that's why you're seeing a lot of companies wanting more of that, wanting to make more out of it, and that's where we're seeing the growth. So where we're seeing loss is, for example, media agencies. They're spending less. You would expect that. Brands, I think, are reasonably stable, and the AI companies are, or anybody doing innovation in that area is growing.
Maybe coming back on those AI companies is, some of the AI labs now are some of the biggest companies in the world. From a research spending perspective, how do they differ to the Mag 7 type companies that you have already got a very big contribution from in your client base? I guess the slightly cheekier 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?
One of the funny things about it is that those clients come back to you and tell you how you should be doing your business. They say, "Well, actually, we've looked at how you structure your things," because they sort of get to sneak a look, I don't know how, and say, "Why don't you do it this way? It would be much faster or much better." So they can be very demanding in a good way. It forces us to innovate faster and to listen and to see how we want to deal with that. They're much less interested in your advice, in our advice. Our consultancy, I think is going to be assumed to come free, because actually they don't need it, and they don't often even care how you're packaging up the data.
In fact, they tell us, "We just want it raw." So yes, 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 can't get from anyone else is the actual relationship with humans, that is a trusted personal relationship, actually. You need that, I think, in order to create great data.
Thanks. Then a final question from me is just kind of tying together the strategy update with the Value Delivery Plan. I guess if we were to take research automation and additional AI revenues, do they map to a certain wave in the Value Delivery Plan? Or to ask this a different way, is the 350 basis points you're getting from stage two dependent on widescale research automation and/or additional AI revenues?
I think it's the two bits together, but—
Yeah. Typically, the automation is within wave two, and if we get the full wave of automation, which is not expected to happen all in this financial year, that will be a benefit above and beyond the 350 basis points for the full automation. But there is a part automation within that number. The new revenue streams particularly are in wave three. There will be no new revenue in wave two.
Thanks. Good morning. It is Lara Simpson from JP Morgan. My first question was just to come back to Data Products. Obviously, we saw quite a 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 those client and contract wins and I suppose the sustainability of that, if they were more one-off in nature or a bit more recurring? I suppose the 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. My second question was on Shopper. I know you have said the strategic review is ongoing.
Just 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. With that, just interested again on the rationale for continuing to invest in that business. I think James said the investments will be similar to 2026. I think the one 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.
Well, I think 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. The first question, which I think you're saying, 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. Just trying to understand the drivers of that acceleration and how strong it is.
Look, it is a really efficient way of understanding something, that you can only do with human data, and that is change. One of the things I meant to say earlier, that is fundamental to understanding our business and how it's 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 isn't 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. The one 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're 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." But that's not why you buy trackers. You buy trackers to see what actually happens. You're interested in surprises. So this product that we're launching that tested well and theoretically should go well, how is it actually going when people take it home, and their kids play with it, and the kid's friends play with it? How does that work through actual usage?
What happens when there's a scandal or a new advertising campaign, or some related economic change? If it's as expected, it's priced in. It's not valuable. It's only valuable when you don't know which way it's going, or you need to know when there's a surprise, and you can only do that with live human data, by definition, because everything else is the continuation of existing patterns. That stuff is not going to, in my view, it's not going to be attacked by AI. That's why I'm so confident about synthetic from our point of view, because it's a way of getting extra value. It is hugely valuable. I wasn't knocking synthetic data, as you understand, just for measuring change. You can't measure change with it, but you can get lots more value out of the data you've produced. 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's some things that we can get elsewhere. I don't pretend that there will be no effects. That's why it's important for us to be the best that we can be, so that when you do keep tracking studies going, it's us that do the best job for you. That's where I think the richness of our data and the smartness of our science is ahead of everybody else. I can't say to you that I can make confident predictions about how all data products will go. I think we're 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, that they make their twins, and they don't ever have to talk to them again for another year and get lots of value out of it. That doesn't work. They have to have live data to make a great product. I think we're in a strong position.
Thank you.
Can I just on Data Products just for you, I wouldn't want everyone to model 7% or 10% growth in Data Products next year on the top line. I think the two or three encouraging things to add to Stephan 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 Stephan's point to that. That product is still very truly alive in a vertical sector that's kind of moving against it in some ways. Also, what's encouraging is that some new technology clients, one of which we alluded to with the H1 results, which had no benefit for actual H1, that's come in relatively materially in H2 as well. So technology clients are often a more custom trackers and more research based.
They're 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's indicated, it's got amazing operating leverage as we proved in H2. So that's as important as any top-line growth from value delivery perspective.
Perfect. Thank you.
Thank you. Morning, Sean Kealy from Panmure Liberum. I've got two for you, James, and then hopefully three for Stephan, if that's all right. So apologies for possibly setting a record for number of questions. First of all, James, you were very clear at the half year that you thought the MI and sort of infrastructure you inherited was good enough to run the business. I just wanted to get your updated view on what you think now of the quality of financial reporting and infrastructure that you're working with, and particularly noticing you've had a bit of a restatement on tax this year, and so on.
For financial reporting, no issues at all. I did my first audit with them, and it was a very clean audit, relatively easy audit. The tax issue is, I'd say, a minor frustration. Happy to talk to you one-on-one about what the detail is. It's basically to do with the Shopper fair value versus cash value. When we purchased it, there was an accounting change, which wasn't picked up at the time. We paid for the accounting change, but we did not give us the credit for the extra payment. So that was a minor sort of acquisition-based change, which is annoying and it's not ideal, but that does not reflect on anything to do with our systems and our MI. I'm feeling that, each week on now, I'm getting more comfortable with the commercial MI that actually helps people make decisions.
The whole thrust of the Value Delivery Plan, there is one 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 wiring and sort of a good discipline is a key theme, and that's all happening. 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% time sheet completion, full stop. Are they all reviewed and everything done properly yet? Not quite, but we're already seeing the benefits. So in answer to your question, systems, from a commercial perspective, give me what we need. I wouldn't read anything into the prior year adjustment. That's an annoyance as opposed to a systems issue.
Perfect. Thank you. Very clear. Second question, given the ongoing Value Delivery Plan, are you able to give us a gentle guide at this point for cash restructuring charge for the coming fiscal year?
I'd rather not give an actual number, but the areas we are investing in is in data scientists and engineers. We're only going to be investing in that area if they're going to deliver a particular feature or product. 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. But a bit too early for me to give you an indication of a number, but happy to be asked that question at the half year when I'll have more clarity.
Perfect. Thank you. Stephan, if I can just rattle through three. First of all, in terms of Parallax, can you just run me through, I appreciate you've said at the presentation that it's token-based pricing, but where are you seeing pricing for that product? I appreciate it's really early stage, but maybe it's more a question of where are you targeting pricing for that product relative to other services that YouGov provides. Secondly, with respect to the MCP connection, I'm 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? What I'm hoping to understand is where clients are interacting with your data and so on.
Finally, on the AI labs revenue, both the figures of four and 11 that you gave, are you able to just give me a run through of where exactly that sits in divisions and various halves of the year just gone?
Okay. I'll start in reverse [inaudible] to remember the last one. The four and 11 splits this way, that the four is specifically work for AI companies that wasn't happening before. The other is for investigating and adding to work that we have with other clients. Some of them may be labs. Obviously some of our biggest clients, as you know, are Silicon Valley, so they fall into more than one vertical. But there are related things about how AI affects them, as well as how using it for AI itself. So the four is just specifically for dedicated AI companies. The others are for other effects being measured, but that we wouldn't have done if there hadn't been that. So you could say that bit's a bit blurry, because there's always something happening that you're investigating, so you might have had that.
But it does present itself to us as a new vertical, as a new thing that people have to think about. They're not only thinking about the customer's economics or whatever. It's a new thing they have to think about. So that's why it's four, and then rises to 11, if you take into account all those other related things. The second one was—
On the MCP connection products.
Yes. 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. I would embarrass myself if I said much more. I will get somebody to find an answer on that.
Just to add to it, we are very conscious that —Will, our General Counsel, is sitting in the back actually. We are very conscious of if we start giving people access 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. We are being very diligent to make sure if we let anybody anywhere near our environment, there is very strong legal protections. It is a well-trodden path in other sectors. So we are getting the best advice to protect ourselves in that area.
Let me think what was the first.
Yeah, thanks to both of you for your answers to that. The first question was just on pricing for Parallax. Appreciate it is early days.
It is actually really hard. We have got a rate card. The synthetic and real bit are two different things, and the real bit is priced the same way as any other research that we do. The synthetic is something we are sort of working out on the fly with our partner that I mentioned. So right now everything is individually done and experimented with. It is completely new area.
These are not definitive answers, I am afraid. Yeah.
Hello, it's Hai from UBS. Thank you for taking my questions. I've 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? Is it going to be, when you said not 7%-10% in Data Products, a bit more normalized than that, but also slight improvements sequentially in Shopper from the investment you made? Is that what you're seeing? The second one is on, in terms of the macro impact you're seeing over the next year. Obviously, U.S. midterms coming up, how helpful is that to numbers usually? But the interest rate environment on the other hand, and cost inflation coming up. So general macro view on how that impacts your top line and margins.
Finally, there's been recent news on a potential acquisition from Salesforce to AI-enabled, like Listen Labs, 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 lower cost, fast turnaround? I know obviously your answer to that is Parallax, but do you see a potential displacement in the near to medium term, and how do you address that? Thank you.
I'll do the last one, but you do the other ones first, James.
Actually, I'll do it first. In terms of our revenue forecast, we deliberately haven't given a formal revenue forecast. But obviously, if we were not comfortable with what the consensus was, we'd 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. In 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 don't invest today and get benefits tomorrow. You invest in a panel over 12-, 18-month period, and then the benefits come through at a later date. So there is a time lag, but that time lag ends in H2 next year. So we're not guiding to a 7%, 10% overall revenue growth.
But I did allude to the fact that we are focusing on growth next year. In terms of the macro impact, the way that I'm personally dealing with it and the company's dealing with it is, we'll go back to the Value Delivery Plan. The Value Delivery Plan is about deep-rooted discipline. So if we see something that's not going in the right direction, we'll stop it and stop investing in that area. So it's really acting and behaving like a modern tech company, where when you see trends move, you stop and invest elsewhere. So I think that discipline, if it continues to work as it has done in H2, we should overcome lots of other sort of external challenges that face us because we're being much more agile and adapting in where we invest, where we make headcount requests, where we invest in systems and technology as well.
Nothing major to report on that. There's obviously some, and I alluded to it briefly, timings of elections, they do impact us somewhat. And we've had a great 6- 12 months in the AI sector, the AI world, investing in us where maybe the agencies have been a bit softer. So we're continually making sure we're relevant to whoever needs our research going forward.
You're right to raise those companies. They're very interesting, and they are slightly different to us. Listen Labs, as I understand it, does interesting things with companies' own data, and that's why it's valuable. I think there's lots of crossovers in some people as well, but principally it is that they are valuable to Salesforce because of their interface with people, rather than, they either have not yet started or they've hardly done anything with synthetic twins, and I'm not sure if they're particularly interested in that area. But it's not the same offer. Well, I've described that. It's similar to, if you look at Simile. Simile have a strong partnership with CVS, and it's about how they work with CVS 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.
Then there's Aaru, which is different again. But in all three cases, they don't develop their own human resource, their own panels. That's critical for us. Our secret sauce is that. We're not doing the other stuff. We are focusing on what we can do best. I don't think they can ever achieve what we're 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 have 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're 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'm not saying the others are unethical.
I'm saying that they're not able to develop those relationships. Our secret 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 behavioral data.
I think we've got time for about two or three questions that have come in online. The first one is for you, James. What was the 49% metric of contractually secured revenues in the past three years? Is that with or without Shopper?
It includes Shopper.
That was a quick answer.
It was.
Then the second one also for you, why do we not have any new revenue targets given product/automation rollout? How much of FY 2026 revenue is under pressure or disappearing as the market shifts to AI/synthetic products?
Well, one, we didn't give revenue guidance because we felt giving bottom-line guidance was more helpful. That's the honest answer to that question. But I have alluded to, obviously, growth very publicly a little while ago. So there's going to be growth, but we're not giving a clear revenue number at this stage. In terms of revenue under pressure, Stephan and I have alluded to quite a few of the shifts in the vertical sectors that are growing and that are shrinking. But I don't think there's going to be a material change in anything. I think the one thing, as I did touch on just now, is even though agency revenue as a whole is down, agency revenue and data products is up. So you could argue that that trend is potentially beneficial to the value of the business as opposed to not beneficial.
There's lots of trends that are happening, but I don't see any step change that's going to think, well, actually this is. The step change I do think we're 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 probably 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're 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.
Yeah. It's worth mentioning, I think I'm allowed to mention, that the order book has never been bigger at this time of year in our history.
It hasn't. And I'm not saying it's 20%, 30% higher than last year, but it's a good few percentage points higher. And as I said, that's contracted. It's not just a floppy pipeline.
Thank you. I think we have time for one last one. This is one for you, Stephan. Can you give more color on refocus on Data Products? Is the separate sales team structure now in place?
That is a reference to something we said two or three years ago when we said that where our strategy had got lost was in merging, you can sell everything. We said you need to sell data products separately from custom in order to get the most sales, because it is a different approach and it requires different skills. 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 in itself divides into two. One is basically MCP clients and the other is Deloitte-type clients. That is pushing out solutions, as they say, across all kinds of clients.
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 of what AI allows you to do. 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 are 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 the research team, but they are working together much more than they would have done had I looked at this three or four years ago. Yes, we are pushing different kinds of sales through different kinds of channels.
But also there is much closer cooperation between custom and product.
Thank you. I think that brings us to the end of the questions online. I am going to hand back to you, Stephan, for any closing remarks.
Well, just thank you very much, all of you for coming, and really interesting questions, really interesting discussion. I think YouGov is in a very strong position right now. I am very happy to have three more months as I hand over to extremely able successor, who will be here next time. Bye-bye.