Yougov (LSE:YOU) Q4 2026 Earnings Call

0:00 Good to see you. This is my second time of having a last presentation. I think this really will be the last one. So 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.

0:50 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, 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 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. And 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 I referred to, and also we have made that switch back to focusing on data products from custom. It's not that custom isn't important.

2:08 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. and 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. I mean, everybody has that. Thank you very much. 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.

3:25 and so on, where that's going. And the third priority was that leadership transition. And I said that we wouldn't make the same errors twice, that we were looking for somebody who has proven leadership in an adjacent area where we can see what they've delivered. In Wayne Leving's 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 is not just expected to immediately fit right in because there's a lot. We're a complicated company.

4:23 We're different to all other companies in our industry and it does need a proper transition. So 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.

5:12 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 years after just five weeks of joining. And the last six months have definitely been fulfilling. We've made deep progress on the planning and execution of the value delivery plan. We've invested 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. 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.

6:05 So 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. Priority, and 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 that is what we're going to do. And 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 HRN results and either confirm the action is completed or update on how we're getting on in solving that problem.

6:58 and going forward, there may be times where we decide an adjustment to previously communicated commitments is required. It's important that our trajectory may change and it's important that we're 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 are 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 programme and start the programme.

7:45 I'm 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 be returned via 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 that is ongoing and priority seven provide clear guidance going forward no vagueness or confusion and in the release you'll see very clear guidance in pounds millions numbers with no no confusion vagueness or clandestine approach to what we think will happen And I'd like to feel that our results presentation released a few hours ago and our presentation we're giving today provides high conviction that we have achieved seven tier one priorities.

8:50 And please do challenge me or Stephan either today or later if you feel we've not achieved those objectives. And I've circled four of these points, one, two, five, and seven. These priorities aren't just the last six months. These priorities will last indefinitely. that's understandable we're a youngish tech focused listed business so we don't have an option and we make sure that we will embrace that in a very growing 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 criticised 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'll be much more transparent on the make-up too.

9:52 I feel that understanding the make-up of the separately identifiable items is as important as the total quantum itself. Hence our commitment to priority too, 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 FY26? 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 DAC business. As a reminder, DAC includes our non-shopper German business, but it also includes the Swiss business including CATI Research.

10:45 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 our value delivery plan. along with some impairment of our software assets which have been capitalised in recent years. Going forward, a continual firm view will always be applied on balance sheet holding values as our business evolves. Bucket two, amortisation. An accounting rules-led amount which is following on from our shopper acquisition. This relates to two items, order backlog and customer list.

11:32 The order backlog was fully amortised prior to the start of this financial year, and the amount of 5 million from the prior year will not continue. That leaves 10 million this year, which covers the customer list amortisations. In FY27, we expect this aspect to continue with another 10 million amount for further amortisation 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. So circa 10 million pounds 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.

12:21 Buckets one and two are non-cash. In high level terms, bucket three 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 SRIs is more than halved year on year, with a reduction of $7.7 million. Going forward in FY27 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, and bucket 1 will be assessed throughout the year to ensure all 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 30 pence is down 11%, which is broadly aligned with the reduction in adjusted operating profit.

13:21 As a reminder, though, as you'll 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. FY26 is our 16th unbroken run of group revenue growth, an achievement that our teams around the world should be very proud of.

14:16 We expect FY2027 to be our 17th year of unbroken revenue growth. We're 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 syndicator 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.

15:14 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 US had a very encouraging H2. All other regions have shown solid resilience in what we all know is a tough market environment. The vertical sectors in which we have been growing in the last six to 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.

15:59 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 light for light decrease since FY25 included the uptick due to the November 24 US 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.

16:44 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've 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. As 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% output outcome at a 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 FY27 and beyond.

17:36 And CapEx has increased year on year for two main reasons. or three main reasons I guess. Panel investment as part of shopper investment program. 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's about investment in the right areas too. We have a strong balance sheet. Are we well capitalised 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 and £6 million respectively.

18:26 We are generating cash and continue to generate cash. Hence our confidence of launching the share buyback programme today. During the year, we successfully extended the debt facilities during H2. There is 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 million of term and €40 million of RCF. The one change we did get through with the banking group was to allow us to do a share buyback programme. You may recall that the half year we couldn't do one because we needed to seek formal approval. As Stephan has already mentioned, as I say, the buyback has started today and will be up to £50 million as already disclosed over the next 12 months.

19:18 As guys at the half year, net debt to EBITDA reduced back to 1.7x with interest cover over six times. And 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. Plus, wave three also includes significant new revenue streams as well. As you will recall, wave one completed in March 26th.

20:05 We delivered an annualised 2.5 million reduction in our cost base, which targeted predominantly headcounts and other cost reductions in non-revenue generating areas. Page 226 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 two key themes as already disclosed. The combined impact of the first two ways is expected to deliver an annualized adjusted operating profit margin uplift of 350 bits over the margin achieved in H1 FY26, which was 12.3%.

20:51 We have high levels of conviction this target will be achieved prior to the end of FY27. Another example of delivering what we said we'd 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 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. Wave 2 and 3 comprise 12 individual work streams, each with an executive owner to optimize the speed and certainty of delivery.

21:36 I was going to name the 12 names, but there are 12 and it will take some time, but 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. 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. We've had an encouraging start to the year, bang in line with our expectations and our budgeted numbers. Currently, 49% of FY27 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.

22:22 Hence the confidence earlier about FY27 being our 17th year of revenue growth despite the market conditions. We're making a loan repayment this month. The last day of October, we'll pay back 20 million euros of the loan. We've disclosed our share buyback already. Investment in Shopper will continue in FY27 at broadly the same levels as FY26, although the benefits of the investment programme are expected to start flowing through from a revenue perspective towards the end of FY27. 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 FY27.

23:16 This is in line with current market expectations. And this represents a year-in-year growth of around double-digit percentage points. I'll stop there and pass back to Stephan, who can talk about the exciting stuff now.

23:31 Thanks. Thanks, James. And 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 roadmap 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 doing. Thank you very much. This whole thing is a new vertical essentially for us, AI, in terms of companies.

24:16 Obviously two new companies, Anthropic and OpenAI are the two main ones. They've become big clients of ours. And just very narrowly, We've done four 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've done for them, which connect them to their users and to the public in general. Thank you very much. Our consequence of news items and so on, and I'm not talking specifically those two, I'm talking about the whole sector, that comes to about 11 million now in sales over the last 12 months. So that is really a big deal for us.

25:20 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 and 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's the first bit. The second bit is internal efficiency. Obviously we're using AI to make our systems more efficient. I've got a slide on that in a second. And the third area, the most important, is the AI enabled products. Really it's a transformation in products and in how we deploy data.

26:08 so that second box automating research at scale we are looking to make an end-to-end automated research flow that doesn't mean by the way that the humans disappear I actually don't think they will Thank you very much. I think we'll 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.

27:07 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's 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's 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 so 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.

27:53 We now have just launched Parallax, which has also had its first six-figure client confirmed. Parallax uses synthetic data, is synthetic data, Thank you very much. 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, and 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.

28:54 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's 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 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...

29:52 Thank you very much. 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. Thank you very much. How good is synthetic?

30:53 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 you know somebody previously asked us how much 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 and just to remind you of our ecosystem it uses all the assets that we already have I mean Thank you very much.

32:11 You can verify, 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. And that leads to... That connected system leads to a seamless client journey throughout the whole world of data. This system is already, you're able to query it using agents. We have MCPs, we have on our site, you're 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.

33:13 But that's 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 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.

34:03 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's made steps in this direction creating their own domain specific foundation model that's the area that we're Very realistically looking at, very specific, we're not saying we're going to be a gigantic AI company, that's not at all what we're saying. We're talking about in our industry, focused on how clients of market research use data in their businesses.

34:48 That's our expertise, that's where we're focused on, and that's 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 developed. I 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. And 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 lots of, are you selling your data? That is a very dangerous thing for companies like us to do.

35:35 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 can't possibly give all our data to somebody else to turn into something that people can buy through them. It's 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're doing. But we are looking at partnerships here. I mean, we already have, it's known to you, a very strong relationship with Deloitte.

36:20 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, but that's as 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. So this is the way forward. This is a client journey that I think nobody else can mimic exactly, and most of that already exists. So I end by saying we've got a framework for the next phase of YouGov's transformation.

37:09 First, the new 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.

37:58 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. And 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. And I'm thinking of one product. Thank you very much. big name company in the world now has a one and a half million dollar subscription to brand index so far from being becoming irrelevant it's actually you know that data is becoming more valuable not less valuable and 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

39:32 service because different customers need different levels of service. That is what it's all about. 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.

39:53 Thanks. Sean Tapper from Canaccord. Three 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's pretty low growth rates. They're pointing out, you know, industry competitors pointing out AI-led growth, but there's a lot of AI washing that's going on there. Could you just kind of explain kind of how clients are approaching that? their research budgets, spending areas where you're seeing demand and maybe where there has been a little bit of disruption from AI.

40:30 Yes, and there certainly has been disruption. I think I said at the beginning that you lose in some areas but we're gaining in others. And 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. and two things really. Clients are expecting to get more for less. I mean, 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. It's for most... 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.

41:27 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. 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 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'd expect that.

42:15 Brands, I think, are reasonably stable, and the AI companies are... or anybody doing innovation in that area is growing.

42:27 Maybe coming back on those AI companies, some of the AI labs now are some of the biggest companies in the world. From a kind of research spending perspective, how do they differ to the kind of Mag7 type companies that you have already got a very big contribution from in your client base? And 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?

42:59 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've looked at how you structure your things because they 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 there is 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.

43:46 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. I mean, 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. And you need that, I think, in order to create great data.

44:19 Thanks. 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 value delivery program or to ask this a different way? Is the 350 bits you're getting from stage two dependent on wide scale research automation and or additional AI revenues?

44:44 I think it's the two bits together. 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 bits for the full automation, but there is a part automation within that number. And the new revenue streams are typically in wave three. There'll be no new revenue in wave two.

45:18 Good morning, it's Laura Simpson from J.P. 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, and I suppose the follow-up to that is trying to think about the building blocks to growth in FY27, and if you think that strong exit rate is sustainable on the data product side in particular. And then my second question was on Shapa. I know you've said that the strategic view 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 and 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're 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're thinking about yielding the return on those

46:32 Well I think on the latter I'm really not going to say anything about the timing. It's obvious that I can't and won't. The other bit of that though is that Chopper needs to remain strong and yielding growth and that requires investment. Tom Fisher, William Ullstein, Laura Robbie, Matthias Gross

47:20 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.

47:30 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 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. And the one thing that AI and synthetics cannot ever do is tell you how things are changing, except retrospectively.

48:17 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. That's not why you buy trackers. You buy trackers to see what actually happens and you're interested in surprises. So this product that we're launching that tested well and theoretically should go well, how's it actually going when people take it home and their kids play with it and their kids' 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?

49:16 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. So that stuff is not going to, in my view, it's not going to be attacked by AI. And 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. So that does not attack our core business.

50:02 Indeed, it gets more value out of it. 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. So I don't pretend that there will be no effects. And that's why it's important for us to be the best that we can be so that you know when you do keep tracking studies going it's us that do the best job for you and that's where I think the richness of our data and the smartness of our science is ahead of everybody else but 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.

50:50 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 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. So I think we're in a strong position.

51:20 Thank you. I wouldn't want everyone to model 7% or 10% growth in data products next year on the top line. But 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 that that product is still very truly alive in a vertical sector that's kind of moving against it in some ways and 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 more custom trackers and more research based.

52:07 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 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 syndicated you know it's got amazing operating leverage as we proved in h2 so that's as important as any top line growth from from value delivery perspective perfect thank you thank you morning Sean Kelly from

52:38 Thank you, morning. Sean Keighley from Pamela. 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 a number of questions. First of all, James, you're very clear at the half year that you thought... and so on. For factory reporting, no issues at all. I did my first audit with them and it was a very clean audit, a relatively easy audit. The tax issue is, I'd say, a minor frustration.

53:25 I'm 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 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. And I'm feeling that each week I'm there, I'm getting more comfortable with the commercial MI that actually helps people make decisions. and 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 timesheets more generally so all this sort of you know you know wiring and sort of um a good discipline is a key theme and that's all happening and like for example now you know in it previously timesheets 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?

54:27 Not quite, but we've already seen the benefits. So in answer to your question, systems from a commercial perspective give me what we need, and I wouldn't read anything into the prior year adjustment. That's an annoyance as opposed to a systems issue.

54:41 Perfect, thank you, very clear. Second question, given the ongoing value delivery programme, 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. and yeah we're only going to be investing in that area if they're 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 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.

55:27 Okay thank you.

55:28 and then 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 sort of said in the presentation that it's token-based pricing, but where are you seeing pricing for that product sort of, 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. 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 year just gone?

56:32 I started in reverse just to remember the last one. So 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. I mean, 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...

57:27 Thank you very much. The second one was... Yes, I'm actually not very good on this bit. I'm not a technical...

58:14 They don't 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 so I can get... We're very conscious that if we start giving people access to our data, do we get disintermediated? Are we going to lose some control? So we're spending a lot of time on that at the moment with various advisors and helpers because it's clearly a risk. If we get that wrong, that's not good. But we are being very diligent to make sure if we let anybody in anywhere near our environment, there's very strong legal protections. And it's a well-trodden path in other sectors. So we are getting the best advice to protect ourselves in that area.

59:06 The first question was just on pricing for Parallax. I appreciate it's early days.

59:11 It's 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. And the synthetic is something we're 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'm afraid. Hello, it's Hai from UBS. Thank you for taking my questions.

59:59 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? And is it going to be, when you said not 7% to 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 in terms of the macro impact you're seeing over the next year. Obviously, US midterms coming up, how helpful is that to numbers usually? But the interest rate environment, on the other hand, and cost inflation coming up.

1:00:46 So general macro view on how that impacts your top line and margins. And then finally, there's been recent news on 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 low cost, fast turnaround? And 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?

1:01:29 I'll do the last one, but you do the other ones first. So 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 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, we do expect that the benefits of the previous investment will start to show through. Because with a shopper investment, as many of you will know, you don't invest today and get benefits tomorrow. You invest in a panel over a 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...

1:02:20 and 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, don't be, yeah, stop and invest elsewhere. So I think that discipline, if it continues to work as it has done in H2, 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. So nothing major to report on that. There's obviously some, and I alluded to briefly, timings of elections, they do impact us somewhat.

1:03:10 And we've had a great six to 12 months in the new 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.

1:03:27 You're right to raise those companies. They're very interesting and they are slightly different to us. So Listen Labs, as I understand it, does interesting things with companies' own data and that's why it's valuable. I mean, I think there's lots of crossovers in some people as well, but... but principally it is that they are valuable to Salesforce because of their interface with people rather than, I mean, 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. It's not an...

1:04:15 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. and then there's Aru which is different again but in all three cases they don't develop their own human resource, their own panels. Now that's critical for us. Our special source is that. We're not doing the other stuff.

1:05:05 We're 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 Thank you very much. You know, surveys, but actually sharing data, sharing even downloaded behavioral data.

1:06:05 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. And then the second one also for you. Why do we not have any new revenue targets given product stroke automation rollout? How much of FY26 revenue is under pressure or disappearing as the market shifts to AI stroke synthetic products?

1:06:55 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, Steph and I have alluded to quite a few of the shifts in the vertical sectors that are more in, that are growing and that are shrinking but I don't think there's going to be a material change in anything and 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 so there's lots of trends that are happening but i don't see any any step change that's going to think well actually this is you know 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 the less 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 favour.

1:08:24 Yeah, and 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. 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 colour on refocus on data products? Is the separate sales team structure now in place?

1:08:55 So 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 and we said you need to sell data products separately from custom in order to get the most Thank you very much. Adding this expertise to everybody else's continuing sales, but has its own program of growth, which is dedicated to its core data partnerships.

1:09:43 Some of those, and that in itself divides into two. One 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 of what AI allows you to do. So the contrast, you can now customize anything that we do as a data product, whether that's adding Yuga voices to it, which are then customized to the needs of the client, asking the questions that are programmed for the client.

1:10:30 or whether it's 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, but they're working together much more than they would have done had I looked at this three or four 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. Thank you. I think that brings us to the end of the questions online and I'm going to hand back to you Stephan for any closing remarks.

1:11:16 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'm very happy to have three more months as I hand over to an extremely able successor who will be here next time. Bye bye.