S4 Capital plc

in London. Good morning in New York, and welcome to our second presentation on the H1 results for 2024. I'm joined by Mary Basterfield in London, Scott Spirit in London, and Jean Benoit Bertie in London too. I'm in New York. And we've got a presentation, it's on our website, which has seven sections. The results, Mary will run through, and then Scott will run through our market momentum section, client analysis, and artificial intelligence. And then I'll come back with just a brief summary and outlook. There's then time for Q&A. and an appendix which carries some data that Mary has added to explain the numbers. So with that, Mary, can you kick off on the results, please?

Imported net revenue for the half year was down 16% to 376 million, or 14% on a like-for-like basis. Global macroeconomic uncertainty, together with continued high interest rates, resulted in ongoing caution, especially among our large tech clients. Net revenue was also significantly impacted by expected lower transformation activity from one of our larger technology services clients. Given this lower net revenue in technology services, operational EBITDA was 30 million, down 8% like-for-like and 18% reported. We continue to exercise tight cost disciplines. including headcount and discretionary costs. The number of monks has reduced by 1,000, or 12%, compared to this time last year, and is now around 7,550. Operational EBITDA margin was 8%, in line with the first half last year, with significant margin improvements in content and data and digital media, offset by technology services. Adjusted operating profit was 25 million and adjusted earnings per share were 1.2 pence. Net debt at the end of June was 183 million and leverage was 2.2 times. Moving to the income statement, revenue decreased 18% on a reported basis to £423 million and was 16% lower like-for-like in a challenging environment. Reported net revenue of £376 million decreased 16% or 14% like-for-like. Operating expenses of £343 million were down 16% on a reported basis and 14% lower like for like. This is the result of our action to reduce costs last year and during the first half. Operational EBITDA for the six months to June was £30 million, down 18% on a reported basis or 8% like for like. with like-for-like operational EBITDA margin improving by 50 basis points. I have given you a breakdown of adjusting items in the table on the left-hand side. Total adjusting items were 29 million, down from 37 million, due to less cost for share-based payments and lower combination costs. Finally, the net finance expense was lower due to a positive impact from foreign exchange compared to a negative impact in the first half last year. This offset a higher Eurobore rate on the term loan, which provides us with secure long-term financing. Looking next at our three different practice areas, content, data and digital media, and technology services. My comments here are all on a like-for-like basis. Net revenue in content, our largest practice, declined by 9% to £234 million. It was a challenging first half, with some larger tech clients remaining cautious and facing budget constraints. Data and digital media net revenue decreased 8% to £96 million. again reflecting market conditions, with lower activity in the media activation business line, partly offset by growth in media agency of record. Technology services net revenue of £46 million decreased as anticipated and was down 37% against a strong comparator. This was due to lower transformation activity from one key client in North America and longer sales cycles for new business. From a regional perspective, the Americas were impacted by this technology services client as well as lower spend from some tech clients. So net revenue was down 15% despite strong growth in Latin America. The Americas remains our biggest region at 78% of the mix. EMEA declined 8% with lower activity in the Netherlands and the Middle East. And our smallest region, Asia-Pacific, was down 9% with slower demand and less new business in India, offsetting robust growth in China. Moving now to operational EBITDA by practice. Again, my comments are all on a like-for-like basis. We improved operational EBITDA in content from 7 million last year to 16 million this year by taking action to reduce costs. This is also reflected in content's operational EBITDA margin, which grew 450 basis points to 6.9%. We continue to exercise tight cost controls, as the market is expected to remain challenging, and we will reduce costs further in the second half to support EBITDA delivery. Data and digital media also benefited from actions taken in 2023. With operational EBITDA of 18 million, we improved margin by 330 basis points to 18.5%. Technology services operational EBITDA decreased significantly to 6 million as a result of the reduction in net revenue. And central costs were 27% lower at 10 million for the half due to continued cost control. Moving to the next slide, you can see that we continue to maintain a healthy balance sheet with sufficient liquidity and long-dated maturities. Our €375 million term loan matures in August 2028 and our €100 million revolving credit facility, which remains undrawn, matures in August 2026. We have now completed all material payments relating to previous year's M&A and currently have comfortable headroom against the key government. Moving to cash flow on the next slide. CapEx of 4 million is mainly investment in IT infrastructure. Interest paid reflects increased payments on the term loan, driven by the higher Eurobore rate. We incurred 4 million of restructuring costs, mainly related to rationalisation, and spent around 2 million on our ERP programme. We continue to focus on working capital and receivables. There was a working capital inflow in the half year of £4 million. Net, this resulted in a free cash inflow of £3 million, compared to an outflow in the first half last year. This takes net debt to £183 million. Turning now to guidance for the full year. We maintain our full year profit guidance. We still expect overall operational EBITDA to be broadly similar to 2023 on a like-for-like basis as we continue to focus on our cost base. Given the outlook for technology services and wider market uncertainty, we expect overall like-for-like net revenue to be down on last year and to a greater extent than assumed at our last trading update in May. At a practice level, we expect an improvement in contents EBITDA and margin driven by cost reductions and data and digital media to deliver a top-line performance similar to 2023 on a like-for-like basis with some margin improvement. The outlook for technology services remains challenging and we anticipate both lower revenue and EBITDA following the reduction in activity with one key client and longer sales cycles for new business. We continue to maintain a disciplined and active approach to cost management as we right-size the business for current market conditions, together with a focus on utilisation, billing and pricing. We expect the year to be heavily weighted to the second half, supported by further cost savings. We anticipate a net finance cash charge of about £28 million and an effective tax rate between 30% and 32%. Finally, we maintain our full-year net debt guidance of £150 to £190 million. Thank you very much. With that, I will hand over to Scott.

Thank you very much, Mary, and good afternoon, everybody. If you take a look at our two main addressable markets, the digital media market is actually relatively healthy, with a strong end to 2023 and a good start to 2024. Growth is expected to moderate over the course of 2024, but the major platforms will still grow double digits. Obviously, that contrasts with our own performance so far, but our revenues are aligned with their marketing spends rather than their revenue growth, and we're still seeing caution from our clients, particularly technology clients. For example, if you look at Meta's Q2 results, their revenues were up 24%, but their sales and marketing expense was down 16%, and we see similar patterns at the other large tech companies. For technology services, this is a more difficult market, which slowed in 2023 and has actually turned slightly negative in 2024. We actually had a strong 23, so the negative market trends have caught up with us in 2024, and this is primarily driven by a reduced spend with one large financial services client, as Mary mentioned. Thank you. Most of our client categories were stable in Q2, with technology still by far the main category, representing 44% of our revenue. We saw a decline in financial services, and this was largely driven by the decline in spend with one of our clients in the tech services practice. We saw increases in fashion and auto, which saw us gain traction in those two categories, and the recent GM win should boost growth in our auto revenues going forward. The continued softness we're seeing in technology client spend and the specific large financial services client in tech services, which has reduced spend, have had a negative effect on the average revenue size of our top 10, 20 and 50 clients. Whilst we continue to see headwinds with some of our larger clients, this is primarily driven by reduced spending rather than client losses. On the positive side, our progress in new business has helped drive an increase in clients in the £1 to £5 million category. I'm afraid Wes is with clients today, so I'm going to step into his shoes and give you our recurring update on our artificial intelligence progress and positioning. As you know, we were Adweek's inaugural AI agency of the year, and we've since won a series of AI business intelligence awards for our consulting practice, our proprietary technology solution, Monk's Flow, more on that later, and Wes's leadership in the field. Since we last met, we're also one of the few companies to win awards for AI creative work at CAN, some of which you can see on this slide. We were at Cannes again this year to show updates to our clients, but also to show real proof and progress down to our AI technology stack. We also announced our partnership with Adobe, with whom we have a strategic partnership around their Firefly product, which is driving our modeling practice, our team which trains and tunes bespoke models for clients. Of course, you'll hear lots of people in our industry talk about AI, their progress, their partnerships, etc. But the reality is none of it matters if it's not going to change the economics of digital advertising for our clients. And the work we're doing with Google, Meta, and others clearly shows that every global marketing organization needs 10 to 100 times more content than they're currently getting from their content supply chain to get the full value of their media spend. Until now, this has not been economically viable with purely human models. We're changing the economics for some of the world's large brands. You hopefully saw the announcement from GM, who have appointed us as their foundational agency. That means we're working with them to bring simplicity, consistency, scale, and cost savings to how their content supply chain operates across all of their brands. We're doing that through the lens of technology with Adobe, but also with our own platform, Monks Flow, which has been set up for them as GM Flow. Our direct client, Molly Peck, communicated this through their press release announcement, saying we'll bring a modern approach to real-time, efficient content development, and described our partnership as a significant change to the way that we are doing business. We see this as a new model. It orchestrates technology and talent. It moves away from traditional time and materials commercial models. It's about technology making us faster, giving us the ability to create more, and it's about putting the very best talent on our client's business, but still fundamentally lowering their overall headcount, which has a lot of positive cost impact. We're doing that with the use of Monk's Flow, something we officially launched at CES at the beginning of this year and something we've talked about before. We're now fully in market, both internally and for some of our key clients. We have more than 10 applications and a mature product roadmap. But what's more interesting is this is not just point solutions. It allows us to put infinite workflows together through the lens of what we call pathways. It was key to the GM win, and whilst we can't name names, we're also excited that one of the world's largest tech companies has chosen Monxflow as one of their AI transformation platforms. The transformation happens through the lens of what we call the big six. And we've gone back to first principles approach for digital marketing. We think there are six steps needed to create great digital marketing. But the question is, can we collapse the time spent, the manual labor needed, and quite frankly, the cost for our clients? We focus on insights and strategy, which is a part of our data play, and we're using our tool sets to generate deeper insights more quickly and get better understanding of marketing and product strategy and the ability to go to market faster and deliver more profitable growth. In content, we go from high-end creative to scaled adaptation, translation, and transcreation. There's a lot of speed, scale, and spend challenges that we're solving there with our technology stack. And then in media, it's really more about automation and algorithms. How do we deliver that additional wave of content into platforms like Google, Meta, Amazon, TikTok, and others and get the highest amount of performance for our clients? This is best explained by an example. So let's look at what we call the impossible ad. This is a media innovation project we did together with Google. It was presented by Google at Cannes in the Palais, and it was celebrated as one of the hero media generative AI cases. And it shows what using AI in the end-to-end digital advertising process can enable and entail. These are the results, and this is not us marking our own homework. These figures have all been vetted and communicated by Google. This way of working, supercharging creative and media, took down manual labor by 50%. It upped the quality of the work, which you can see through the higher click-through rates and engagement figures. But interestingly, since we were feeding the media algorithm with more content, it also dropped the cost of sale by almost a third. Now, a bit more detail about our Monks Flow stack. If you look at data, we have three products in market, Insights Engine, Persona, and Clarity. Insights Engine helps our clients understand close to real time any trends or threats that are meaningful to their business and brands, and it helps them ideate more quickly. Now, Persona and Clarity I'll go into a little more detail on. Persona is a voice of the customer solution. We've built a series of data partnerships that allow us to build digital twins of any customer segment and allow us to have real-time conversations with those customers, which can replace qualitative and quantitative surveys. We've proven that out statistically. This is not a vanilla LLM skin, although it does work with any of the major frontier models. In fact, if you have these conversations directly with the LLMs, then a lot of the time, the LLM is confidently wrong. Having these conversations with persona gives you statistical relevance. We do that through our partnerships with large data providers like Claritas and GWI, or more niche providers like Motivication. And we can extend these third-party partnerships with first-party data, which is, of course, part of our data practice, which has been helping clients in this area for well over a decade. When we say statistical relevance, we've worked with an external partner, the MMA, a global marketing organization focused on the science of marketing by running tests for a series of clients and pushing existing survey data through Persona. And you can see that we almost perfectly predict the trend line of the answers, and we get 85% to 92% accuracy. which means in insights and strategy, we can now collapse work that usually takes clients three weeks to three months to three prompts. We have similar insights and strategy solution in media called Clarity. Clarity is our close to real-time marketing mix modeling tool, currently up and running for one of the largest beauty businesses in the world across their portfolio of brands. It allows you to do close to real-time marketing mix modeling, a much more granular understanding of the impact on your business depending on your choices, the economy, and what your competitors are doing. Again, all of these are actively being used by both clients and internal teams. In the creation and adaptation space, we'll spend a little less time, as it's the most understandable part of generative AI, as it's about visual output. Most importantly here, we've built one of the strongest creative teams in that space. You can see that from our awards in Cannes. We launched the first AI director roster that we announced earlier this year, and we've been hiring some highly regarded talent that's doing some amazing work for our clients in photography and film. On the slightly less sexy side of the spectrum, we are solving a lot of typical adaptation challenges for clients that sit in translation and transcreation. Our translation tool has been widely tested against other solutions and consistently ranks number one. It has taken down traditional translation work by up to 80%, and almost 90% of translation work for clients is now done by compute rather than human beings. The last part of our end-to-end stack is media, and a lot of this is around automation. A good example, and again one that was shown at Cannes by Meta as their only generative AI case, we showed what it looks like to generate a multitude of content from a content supply chain and feed that into the algorithmic media platform. In Meta's case, that's Advantage+. To create that much content in close to real time, we have Asset Planner. It ingests media plans and other variables and can compress around three weeks of work into three hours. With Meta, we used that to test a hypothesis with our client Forever 21. And the hypothesis here was, let's bake off a traditional digital campaign with Advantage+. a traditional campaign that has smart people thinking about media strategy planning and buying, and usually has around 10 assets per campaign. We baked that off against an Advantage Plus campaign with no human-based media planning or segmentation strategy, and with around 270 creative assets created by Monks Flow. Spoiler alert, there should be no massive surprise, but scaled content with algorithms heavily outperforms the traditional human methods. and we have a video to explain it With that, I'll hand you back over to Martin for the summary.

Okay, thank you, Scott. Thanks, Mary. Just before we go into the Q&A session, 11 observations on our results or summary or conclusions. The first is our H1 profitability was as anticipated at £30.1 million EBITDA at In H1, our net revenue decreased by 13.5% on a like-to-like basis, and that reflected the continuing global macroeconomic uncertainties and high interest rates, which, as we saw yesterday, are starting for the first time to come down significantly, which is good news. Client caution has persisted to date, particularly amongst our technology clients. Some have increased spending, but the majority have cut back, as Scott mentioned, whilst their revenues have been strong, ad revenues have been strong, along with the expected significant lower transformation activity from one of our larger technology services clients in the financial services sector. Third point is improvement in our operational EBITDA margin in content was good news, up 450 basis points. And DDM also, data and digital media, also increased its operational EBITDA margin by 330 basis points. And that was largely due to the cost actions that we took in 2023 and in the first half of 2024. We maintain and continue to maintain a disciplined and active approach to managing our cost base with an increasing focus on driving efficiency across the company as well as utilization and pricing. As a result of this, the number of months is now around 7,500, 7,550 to be precise, and that's down around 12% in line with the net revenue decline in H1 of 2023. Net debt is 183 million, and that's after 10 million of combination payments, which were settled in Q1. We now completed all the material M&A payments for prior combinations, and our targeted range for net debt at the end of the year remains between 150 million and 190 million. We've rebranded to Monks to reflect our simpler structure. And we're streamlining our three current capabilities into two practices, marketing services and technology services. We've achieved B Corp status and continue to make progress in the three areas of our ESG strategy. That's zero impact workspaces, sustainable work, and the area of diversity, equity, and inclusion. We're capitalizing on our prominent AI positioning, as you heard from Scott, and that's been key to recent new business wins, the largest example of which is General Motors. We maintain our profit target for the year, a broadly similar operational EBITDA, to 2023 on a life-like basis. And we're targeting net revenue to be down year on year as before, but to a greater extent than that assumed in May, given the outlook for technology services and continuing global macroeconomic uncertainty. Finally, we remain confident in our strategy, in our business model, and in our talent, together with our scaled direct relationships which position as well for growth in longer term, with an emphasis on deploying free cash flow for shareholder returns. And particularly now that all significant combination payments are well behind us. So with that as a summary and that as a presentation, we're happy, operators, to take questions. We usually don't get many questions, if any, on this call. They're covered and have been covered this morning on the London call. But just in case, operator, can you just check if there are any further questions?

If you would like to ask a question, please press star 1 on your telephone keypad. Please ensure your line is unmuted locally, as you will be advised when to ask your question. And once again, as a reminder, please press star 1 if you'd like to ask a question. We don't have any questions in the queue, so I will hand the call back over to Sir Martin to close.

Thanks very much. Thanks, operator. Much appreciated. Thanks, everybody, for joining the call and those who joined earlier this morning. We'll see you, I think, in November for Q3. Thanks very much. Bye.