S4 Capital plc (SFOR) Earnings Call Transcript & Summary

Good morning, everybody. This is the Half 1, the first half of 2026 from S4 Capital. I'm actually in New York, Wes is in Las Vegas at an AI conference, Scott is in London with Radhika, our CFO. So we've got 5 areas to go through. Firstly, the results themselves, which Radhika will just take you through. Secondly, market momentum from Scott. Wes will talk a little bit about artificial intelligence with a demonstration of what we've been doing. And then I'll finally give a brief summary and outlook and we'll go to Q&A. So with that as background, over to you, Radhika.

Thank you, Martin. Good morning, everybody. I will start with the financial headlines for the first half of 2026. Despite global macroeconomic pressures, technology clients and hyperscalers continuing to further prioritize AI investment and ongoing client caution; disciplined cost management has delivered a very strong first half operational EBITDA with a significantly improved EBITDA margin. Liquidity focus has also lowered our net debt. Net revenue was GBP 308 million, down 6.2% reported and 4.7% like-for-like. Operational EBITDA was GBP 38 million compared to GBP 20.8 million in the first half of 2025 with a margin of 12.3%, up 600 basis points reported and 710 basis points like-for-like. Adjusted operating profit was GBP 35.2 million and adjusted basic earnings per share was 2.7p versus 0.2p in the first half of 2025. The Board has approved an inaugural interim dividend of 1.35p per share, 50% of the adjusted basic earnings per share. The company generated GBP 10.4 million in free cash flow and net debt reduced to GBP 66.3 million, which is 0.7x pro forma 12-month operational EBITDA, significantly below the GBP 145.9 million on the 30th of June 2025. The company has now met the reduction of its Term Loan B target, repurchasing a further EUR 40.1 million subject to settlement. This reduces the outstanding Term Loan B to EUR 249.7 million. Moving on to the P&L. Revenue for the period came in at GBP 344 million, which is down 4.6% on a reported basis and 3.2% like-for-like. Net revenue for the period was GBP 308 million, down 6.2% reported and 4.7% like-for-like. This reflects what has been a volatile macroeconomic environment exacerbated by the Middle East conflict in conjunction with technology clients and hyperscalers further prioritizing AI investment. In response to these conditions, we have continued our disciplined approach to cost management and the first half EBITDA performance reflects the annualized impact of the cost actions taken in the second half of 2025, which primarily focused on nonbillable roles and back office efficiencies. Personnel and operating expenses were reduced by 12.6% on a reported basis. The company's aim is to align personnel cost to net revenue ratios more closely to industry averages. As at the half year, this was 72.2% compared to 79.2% for the first half of 2025. At the end of the first half, the total number of Monks fell to approximately 6,150, which was down 11% compared to this time last year and down 3% compared to December 2025. Looking across our 2 practices, Marketing Services and Technology Services, my commentary now is all on a like-for-like basis. Marketing Services delivered net revenue of GBP 281.9 million, a 4.4% decline reflecting ongoing caution among technology clients as they continue to further prioritize and increase AI infrastructure over operational marketing budgets. The practice was further impacted by a scope reduction in BMW, which impacted the EMEA region. Technology Services generated GBP 26.1 million in net revenue, down 7.4%, similarly impacted by broader macroeconomic headwinds and extended sales cycles. From a regional standpoint: the Americas, which represent 80% of our total net revenue, declined 0.8%; EMEA declined 20.3% and represented 14%; and Asia Pacific declined 12.5% representing 5% of our mix. Turning to operational EBITDA by practice. On a like-for-like basis, Marketing Services delivered GBP 44.1 million, an increase of 72.3% compared to the first half of 2025. EBITDA margin strengthened to 15.6%, up 690 basis points reflecting decisive head count actions and continued cost discipline. Technology Services generated GBP 4.4 million, up 214.3% from the first half last year. EBITDA margin strengthened to 16.9% and improved by over 1,000 basis points underlying the effectiveness of our cost control measures. Moving on to the debt and balance sheet slide. We maintained a strong balance sheet throughout the period with strong liquidity and long-dated maturities. Our M&A obligations are now largely complete. Stronger treasury management and a focus on liquidity reduced period-end net debt to GBP 66.3 million. Leverage closed at 0.7x net debt over pro forma 12-month operational EBITDA, below our target of 1x and below our key covenant of 4.5x. The company met the targeted reduction of its Term Loan B, repurchasing a further EUR 40.1 million subject to settlement, reducing the outstanding Term Loan B to EUR 249.7 million. Moving to the cash flow. Free cash flow was GBP 10.4 million in the period compared to GBP 16 million in the first half of 2025. The movement was driven by an expected Q1 2026 working capital outflow. This was primarily due to a combination of stronger year-on-year Q4 2025 collections and lower year-on-year Q4 2025 media billings. As collections normalized and trading strengthened, working capital improved in the second quarter. Capital expenditure in the period was GBP 2.7 million, up just under 30% from the first half of 2025 of GBP 2.1 million due to ongoing investments in AI capabilities. Financing costs reduced meaningfully driven by the reduction in our net debt and the average effective interest rate improving to approximately 5.7%, down from 6.1%. Improved cash management increased interest income to GBP 1.9 million and tax paid in the period was higher at GBP 3.8 million driven by utilization of tax losses in 2025. Restructuring and transformation costs in the period were GBP 5.7 million, primarily GBP 3.9 million due to restructuring costs and GBP 1.4 million related to our finance transformation program. Moving on to the net debt bridge. Net debt at 31st of December was GBP 86.9 million or GBP 79.6 million at closing June 2026 exchange rates. The company generated GBP 10.4 million of free cash flow during the period. The company repurchased EUR 85.2 million of its Term Loan B at a discount of EUR 4.9 million. These movements resulted in a lower closing net debt position of GBP 66.3 million, again representing 0.7x pro forma 12-month operational EBITDA below the targeted leverage of 1x. Our capital allocation priorities are maintained from the year-end. We have established a clear capital allocation priority focusing on delivering shareholder value through first, dividends; second, targeted debt repurchases; and third, share buybacks. The Board has implemented a 50% dividend payout policy out of adjusted basic earnings per share over the medium term subject to financial targets being met. We now move on to guidance. 2026 full year like-for-like net revenue is now expected to be down mid-single digits. Operational EBITDA remains at the current analyst consensus level of GBP 85 million with operational EBITDA margin targeted to increase by 140 basis points. Year-end net debt range has been lowered to GBP 50 million to GBP 80 million. In line with our targeted operational EBITDA, we aim to maintain leverage of under 1x. The company has repurchased a further EUR 40.1 million subject to settlement of the Term Loan B. This reduces the outstanding Term Loan B to EUR 249.7 million. Our forecast net finance expense has been lowered to GBP 19 million to GBP 21 million excluding the one-off gain on the loan repurchase. The effective tax rate is expected to be 28% to 30%. Adjusted basic earnings per share will now be in excess of current analyst consensus. With that, I will hand over to Scott for the market update.

Thank you very much, Radhika. Good morning and thank you, everyone, for joining the meeting today. I'm going to cover some of the dynamics we're seeing in our wider market and then share some specifics on our client relationships before handing over to Wes for an update and a demo on our artificial intelligence product. As you can see, digital marketing spend continues to increase at significant rates whilst overall advertising spend is growing at around 5% meaning analog spend continues to decline. The revenues at the top platforms continue to grow in the high teens, significantly outpacing the market growth. One thing to bear in mind here is that 80% plus of their revenues come from small- and medium-sized businesses and they continue to expand their market share there. So their growth is not necessarily being driven by enterprise client spend. The technology services market continues to have lower growth compared to recent historical double-digit performance. 2025 had just over 5% growth and whilst enterprises continue to invest in areas such as cloud and AI, the outlook for '26 continues to be subdued. The next slide charts the comparison between agency and revenue growth at the main public holding companies and advertising spend and GDP growth. Digital spend now represents around 70% of the total and, as I mentioned on the previous slide, it's growing at high single-digit rates meaning analog is in decline. Agency growth dipped to almost 0% in 2025 and has decoupled from advertising spend and GDP growth. One explanation for this is the continued pressure from clients to maintain their media spend, but to put pressure on what they call nonworking spend, i.e., agency spend. This is particularly the case with technology clients. And the next slide looks at the relationship between CapEx spend and sales and marketing spend at the major tech companies; Amazon, Meta and Alphabet. As you know, historically, almost half our revenue has come from this sector. Prior to 2022, marketing spend at the top platforms regularly grew at 20% annual rates and has now essentially been flat since then. On the other hand, CapEx spend, particularly on AI and infrastructure, has ballooned in the same period growing over 140%. And this trend is expected to continue with the hyperscalers already announcing plans to increase their CapEx spend almost 90% in 2026 and some of them committing to similar increases in 2027 already. The tech companies are unsurprisingly leading the charge on adopting AI in their marketing workflows and leveraging it to achieve more for the same or less. We continue to have a very compelling client list with some of the world's leading and most innovative companies; 8 of them are what we call whoppers and that's revenues of $20 million plus, which continues to be a differentiator for a company of our scale. As you can see, we continue to be skewed towards the tech industry with around 42% of our revenues coming from technology. These are strong relationships that help us attract and retain talent to work on them. Spends per client are slightly down, but essentially stabilizing versus the previous year across our Top 10, 20 and 50 client cohorts and the focus now is very much on returning all of them to growth. With that, I'll hand you over to Wes for an update on our artificial intelligence coverage. Thanks.

Thank you, Scott, and hi, everyone. AI update. The last update we did was very much focused on the work and I'll start with a little bit of work today as well. We had this up and running in Cannes about 1.5 months ago for Google, one of our clients, Google Beach. Very fun use of their Gemini omni video model, which honestly is pretty amazing for this type of personalization. This is not my actual outfit in Vegas. This is all AI related. What I'm going to do today is talk a little bit about our discussions in Cannes. Cannes is one of the 2 big moments we have every year to put a little bit of a stake in the ground. The other one being CES. And if we go to the next slide, our focus really was how does the technology help clients win the race to relevance. I think we showed last time when we showed a bunch of work that efficiency is table stakes, efficiency is mostly down to vision and decision-making. I think what is more interesting is how does the technology help clients generate more demand, capture that demand, grow their business, grow their brand. And to do that well, we have to move away from thinking about an ad and more moving towards what we call system thinking. The system thinking part is something that we've been proving out with clients over the last 6 to 9 months. And if we go to the next slide, we started building it into our go-to-market earlier in the year. I'm not sure if people on the call know AdForum as an organization, global organization that brings pitch consultants together to visit agencies in a specific region. They'll visit 30 to 35 agencies, score those agencies on the relevance; relevance to the market, relevance to their clients, relevance to the RFPs that they see in their pipeline. We did that in May, Monks ended up being scored the #1 most relevant agency. This was I think quite an interesting takeaway quote, meaningfully ahead of our competitive set. We're of course seeing that play out in some of our pipeline already. These are very connected folks that have quite a meaningful impact on pipeline in general. It's also sometimes a little uncomfortable to be ahead. We do believe in the current landscape, it's important to be close to the edge of what's happening because that edge is moving more and more quickly. And I think our ability to stay close to that edge helps us understand how the technology evolves, how it dissipates its marketing and what that means for marketing organizations, which are our clients. So that's a little bit of framing. If we go to the next slide. The way we think about growth is through 2 lenses. One, we need to do work that is loved by humans. That's traditionally how we thought about advertising, marketing, creative. I think the way people currently interact and interface with content is very different to 5 years ago, 10 years ago. People are spending an inordinate amount of time on their phones, I think it's about 13 hours a day, and a lot of that time is spent scrolling. So more and more to be loved by humans, we have to be part of that constrained environment. We have to be part of these micro cycles of attention. And then we need to do work that is preferred by machines. Some of that is about algorithmic media where there's a massive preference for volume variation, variety, velocity; all of the Vs. And of course more and more how do LLMs and agents sort of surface brands within the sort of Agentic ecosystem. So that was our main focus during Cannes. What I'll do now, and I'll spend about 10 minutes on that, is show the environment that we showed our clients 1.5 months ago from Monks.Flow. I think we should be switching screens now, let me know when it's up. So first, a little bit of positioning. Monks.Flow started as an internal project 2.5 years ago. I think we saw early what most large enterprise organizations are now finding out that pilots don't necessarily contribute to P&L impact. It's very difficult to capture the productivity gains if everybody is piloting. So we moved very fixed processes, which allowed us to double down on best practices. That process-heavy movement, we were early when it came to jumping on Agentic workflows. Last year at Cannes, Monks.Flow was the first Agentic marketing platform. And the positioning of Monks.Flow currently I think is really quite unique. It's not bicoded. It's not one-off. It's enterprise-grade, safe, secure, scalable, auditable trails when it comes to everything that happens within the platform and environment across your teams. Lots of high productivity per token, really making sure every token counts. But then we operate at a much higher clip than traditional SaaS products who are stuck in 3-, 6-, 12-month cycles. We launch updates every 2 weeks because our team is fully Agentic enabled and that allows us to do more specific solutions client to client, which I think is quite unique. The way we think about infrastructure from Monks.Flow is 3 levels: intelligence, creation and orchestration; and I'll run through that relatively quickly so you'll get a sense of what we have. It starts with knowledge bases. This is a very easy environment to set up knowledge bases related to clients. In this case, we set this up for one of our clients, Mr Muscle, part of SC Johnson. It has all of the brand information. You can upload anything that you want here, structured, unstructured data. We can connect it to live data feeds. Agents are able to use those context to do really meaningful relevant work. But we're not just creating that level of context. We're also adding agents that are a representation of the audiences. So that means you have a series of audience agents, in this case, the efficient Monk. This is a representation of third-party data. We bring to the table lots of interesting third-party data partnerships. First-party data if it's available. And it means you have the voice of the customer everywhere in your workflow and I'll show what that looks like in a moment. Let's say hi to the efficient Monk for a moment. [Presentation]

You get the drift. Insights on this persona. Where does this persona consume their media? What's the typical brand relationship, et cetera, et cetera, et cetera? You can start conversations with these personas, which can be really useful. They're also part of other tools and this is really where we get the creation piece. We can run focus groups with these personas. For instance, how do you decide to purchase? That's a question and then you can select your personas, run that focus group and what's great about Monks.Flow, my question wasn't great. It wouldn't be good at getting meaningful insights back, but that gets translated to actually meaningful questions that then get run through this Agentic process. All of these personas are now being interviewed. I'll show you what that looks like. This was one done with 4 people. All the interviews are available. But more importantly, it creates additional data sets that we can use in our agentic workflows. I think a huge part of what we're doing here is making sure our agents have lots of context to be high performing. These personas, for instance, which is quite interesting. Look at an example here, which means we can optimize content in a predictive manner that really outperforms some of the traditional algorithmic methods. Just really useful to have these agents available. So that is the intelligence layer starts leaning into some of the tools that we have for creation. The most important one of those tools is what we call opportunities. So if you think about doing work that people love, a lot of that is down to the insight in channel. Can we capture an insight that is of value and how quickly can we translate that insight to an in-channel asset? And because of the speed of social, speed of culture, that time is compressed. And historically, that might have taken weeks, sometimes even months, doesn't really make sense anymore. So a lot of our focus has been how can we do that same day. What you're seeing here is opportunities that are being pre-prepped by agents. So we're capturing data feeds from Reddit, from X, trending topics, news within your category. All of that data is being reviewed close real time by agents that do the job of what used to be a social agency, right; social listening, social strategy. These opportunities are already being vetted by your audiences so you get a sense of who would be interested in what type of messaging. You can get all of the sources. You even get an idea of initial suggested channels and this is ongoing, right? These are continuous. You can turn these into briefs if you want as part of your projects. I'll show how projects work in a moment. Really meaningful, really useful, gives you details on things that need a really fast response, seasonal has a bit more time of course and then behavioral is bigger consumer change, that also helps potentially drive some product development. These are really interesting. If you want, you can start putting additional research against some of these opportunities, we'll call that IQ. A great example here, for instance, is more information on what it means to be Mr. Muscle in Brazil. That also adds information about your competitive set. Agents are looking at what your competitors are doing, their media spend, their messaging. Again, lots of really useful information that also starts helping you define business opportunities. And then, of course, if we have insights and we want to get it in channel, we need a piece of content. I'll show you how that works as well with the few minutes we have left. So part of Monks.Flow is also the end-to-end workflow. Why is that useful? It's useful because it allows teams to work together, client and agency, but also agents to be part of that workflow. And what I'll show here for instance is a working environment that we had running during Cannes. And of course we had the World Cup during Cannes. As a Dutch person, not the best World Cup ever. But we spotted a really interesting opportunity or at least the agents spotted a really interesting opportunity. The Japanese fans went viral because they were cleaning up the stadium before leaving. And then it was actually a little bit of a meme because these were mostly men where the meme was, "Hey, maybe start doing some of that at home as well." So the idea was can we do a little bit of a World Cup sort of cleaning moment. Sorry, we have some sound coming through. So what we'll show here is how we took these briefs and these briefs are auto generated, really best-in-class. You'll get to comment on these briefs again, the sort of collaboration between people and agents is really quite unique. And then you can make content. I'll show a piece of content here. World Cup drama, quick explanation of what happens here. So the moment you take one of these briefs, you can throw it to a studio. Studio looks at the brief, predefines what a great wheel would be. Wheels are really sort of social currency, really key asset at the moment. It also generates initial concepts for you. You can of course collaborate with agents to change these concepts or you can just accept them. If you accept the concept, it then gets translated to best-in-class script for a real IG, TikTok really as the main platforms. And then it generates all of the environments and images, but it does it in a way that's very on brand, very in context, but you can also still edit. So it depends a little on power usage versus people that are just going through the workflow. [Technical Difficulty] And then these ads are on brand safety use and really the whole workflow we just went through from opportunity spotting to working on some of the strategy and creative and then getting to an asset can be done anywhere between 15 minutes and an hour, which of course is a massive, massive sort of change to how these things historically happened. Lots more in here. We were doing these demos in Cannes and took us close to 45 minutes. So really powerful tool. This sort of systemic way of working also means we have more and more interesting solutions that we're launching to clients. I'm sure we'll talk about some of those solutions in our next earnings call. And with that, I'm going to hand it back to Sir Martin.

Thanks, Wes. So finally, a summary and outlook. First half net revenue was down 6.2% reported and 4.7% like-for-like and that reflected the continuing macroeconomic uncertainty heightened by the Middle East conflict and combined with technology clients and the hyperscalers prioritizing AI investment. I think as we said in our release, the Top 4 hyperscalers are spending about $5 trillion on capital investment which they projected to 2025 and 2030. Reported record operational EBITDA of GBP 38 million, up almost 83% reported and 128% like-for-like with a higher proportion of operational EBITDA in the first half compared to previous years based on the 2026 full year target, but a stronger second half is anticipated from a bottom line point of view. EBITDA margin in the first half at 12.3%, up 600 basis points reported and 710 basis points like-for-like. Number of Monks down 3% to around just over 6,000 people compared with 6,350 at December 2025 and 6,900 in June of '25 last year. Half year net debt at just over GBP 66 million, which represents a leverage of 0.7x EBITDA, down from GBP 146 million, which was leverage of 2x, which we reported last year at 30th of June. Full year like-for-like net revenue expected to be down mid-single digits and full year EBITDA remains at current analyst consensus level of GBP 85 million with the margin to increase by 140 basis points. New business wins from LVMH, from Mercado Libre, CapitalOne, Revlon, Square, Seek, Watts and Air India. The targeted net debt range for 2026 has been lowered from GBP 50 million to GBP 80 million -- lowered to GBP 50 million to GBP 80 million from GBP 60 million to GBP 90 million and we aim for leverage to be maintained at under 1x operational EBITDA. The Board's implemented a 50% dividend payout policy out of adjusted basic earnings per share subject to our financial targets being met and will recommend a final dividend for 2026 in line with that policy. The final dividend for 2025 of 1.1p was paid in July and the Board has approved first time an overall interim dividend for 2026 of 1.35p per share. That represents 50% of the adjusted basic earnings per share of 2.7p. The company has met the targeted EUR 125 million reduction of its Term Loan B and it has therefore, reduced the outstanding balance of that Term Loan B to just under EUR 250 million. We continue to see significant opportunities for new business particularly driven by our AI tools and capability, as Wes has just outlined, particularly in relation to the work for SC Johnson. And adopting from existing clients is ramping up as clients driven by existential threats in the automotive category and vertical, in financial services and FMCG, fast-moving consumer goods moved from pilots to fully scaled adoption and our proprietary AI solutions that are at the heart of all of our new business efforts. We remain confident in our talent, in our business model, in our strategy and our scaled client relationships, which position us to deliver sustainable long-term growth. So with that, Laura, as operator, we can turn to Q&A.

[Operator Instructions] We will now take our first question from Andy Renton of Cavendish.

Just a couple from me. First, could you just expand a little on the predicted higher margins now and where those higher margins are going to come from? And then just on the AI side, it would be good to understand what you think AI will be able to do in the future that you didn't think it could do 6 months ago?

Well, so Radhika, do you want to deal with the margin point? And maybe, Wes, you can respond on what AI enables us to do that we couldn't do a few months ago. So Radhika, margins.

So on margins, So the first half, as we said, was driven by really the annualized cost-out impact of what we did at the back end of 2025. So we continue with our cost focus really looking at our cost base in relation to our net revenue. So for the second half as well, that's where we've got that full year impact and that's why we've increased it too by 140 basis points. So it's the full year impact of what we did at the back end of last year and our continued cost management through the year.