Coca-Cola HBC AG (CCH) Earnings Call Transcript & Summary

Good day, ladies and gentlemen, and welcome to the Coca-Cola HBC Bitesize Investor Series. Today's event is data, insights and analytics, translating data into actionable insights. [Operator Instructions] I would like to remind all participants that this call is being recorded. I will now hand over to Joanna Kennedy, Head of Investor Relations.

Good afternoon, and welcome to the first and our series of Bitesize events at CCH. I'm Joanna Kennedy, I'm Head of Investor Relations here. And in a moment, I will introduce you to our speakers. First though, to explain a little bit more about Bitesize. This new series of Bitesize webinars are going to be deep dives into areas of the business that are important drivers of our strategy and investment case, and the ones that you requested to hear more about. We will be introducing you to our subject matter experts and opening up areas that we believe are key differentiators for the business. Today's event is on the -- is the first in that series and it's on one of our key capabilities, data, insights and analytics, D-I-A or DIA. Many of you participated in our DIA breakout session at our Investor Day last year or perhaps you watched the video on our website. We received really positive feedback and also a clear request for more information to build a greater understanding of the capability, how it benefits and differentiate [indiscernible] and what we think it is enabling us to achieve, and that's what we're going to do today. The format today is going to be a presentation from our team, followed by Q&A. We'll be able to take questions live on this call or if you joined in listen-only mode, you can type the questions, which I will put to the team. So now, let me introduce you to the team today. I'm really pleased that we're joined by our COO, Naya Kalogeraki, who will share some thoughts on the strategic relevance of DIA. Naya will then hand over to Ruchika Sachdeva, our Head of DIA, who will take us through a presentation. And after that, we'll all join back for Q&A with the combined team. As you know, we are in close period ahead of our Q3 results, so please bear that in mind on your thinking of your questions. And I'd also remind you that this presentation and meeting may contain various forward-looking statements, which will be considered along with our cautionary statements at the end of this release. With that, I'll pass the call over to Naya.

Thank you, Jo, and hello, everyone. I'm really pleased to be back with you again and also excited for us to share the considerable progress we've made on DIA. Let me explain a little bit about why this is one of the areas that our Board and leadership are particularly excited about. The essence of DIA is the importance of understanding our customer and consumers, so we can serve them better. Many of you will have seen this slide before. It gives an overview of our bespoke capabilities, which underpin our growth ambitions. Our bespoke capabilities are critical for us to better understand the real and changing needs of our customers and consumers, drive profitable revenue growth and anticipate or react to new challenges faster and smarter than our competition. Put simply, by accelerating our core capabilities, we drive our growth algorithm. DIA works across every part of our business as one of these bespoke capabilities acting as a connector and an accelerator of our other key capabilities. Through DIA, we are driving a better understanding of our markets, our customers and end consumers at a wider scale and at faster speed than we could achieve before. All of this is allowing us to better personalize our execution for every single outlet to be more agile as we go into the market and to uncover opportunities that might not have been visible before. Ultimately, this is all -- this all drives our growth algorithm, ensuring that we remain highly adaptive to the environment and stay ahead of the competition. It is one of the reasons CCH has delivered a resilient result even in challenging markets. And what's really exciting is that each layer of additional data allows us to go to the next level of understanding and personalization, which, in turn, drives better relationships with our customers and revenue growth opportunities. We have been very busy since the Investor Day and have made great progress. But this is just the beginning. There are some things that we're working on, which we will be able to share at a later date. But for now, I will hand over to Ruchika, our Head of Data, Insights and Analytics, to open up this topic in more detail. And I'm looking forward to join you after the presentation to answer any questions.

Good afternoon, everyone, and hello also from my side. I'm excited to be here today with you and share our progress on DIA. Since I last spoke to many of you at our Investors Day in May '23, we have continued to collect more data and further evolve our analytics and AI capabilities to continue finding growth opportunities. Let's start with a quick recap on what DIA is. The capability that translates information into actionable business insights, leveraging statistics, machine learning and artificial intelligence is called data and analytics. This capability is relevant to all parts of our business. But the way data enhances our understanding of each customer is particularly important for Hellenic. Given we serve over 2 million customers in 29 markets, in wide range of channels and offer the breadth of 24x7 multi-category portfolio, that's why we are investing in this capability. And while there are many opportunities for leveraging DIA across the business value chain, the focus of today's discussion is on its application within the commercial part of our business. Data intelligence enabled by AI algorithms powers our other bespoke capabilities, revenue growth management and route-to-market. RGM defines what we offer to our customers and RTM defines how we serve them. Data and algorithms allow us to proactively understand the customers and their shoppers needs. So we can pivot more precisely and offer personalized services through segmented execution. This allows us to treat every customer as an individual segment. Let me tell you more about it. What do we mean by segmented execution? Segmented execution is all about segmenting customers as one size does not fit all. Our customers have different needs. So to be truly relevant, we first must understand our customers and have a holistic view from an internal and an external perspective. Data enables this, with a 360-degree view of the customer and AI algorithms help generate outlet-specific insights for personalization and customer-centric actions. We start by segmenting our customers and predicting their revenue potential. Then, we identify the right assortment to offer from our 24/7 portfolio. Proactively offering the right portfolio to the right customer in the right pack size for the right occasion. We personalize in-store execution with customized displays and relevant in-store marketing. And we make sure that every customer interaction irrespective of the channel is relevant and personalized. We also guide profitable promotions and investment with our customers, deciding where to place the cooler, or a coffee machine or how best to promote our products. Today, data and AI-enabled insights power our 2 million active customers across 29 markets, personalizing our 24x7 assortment and execution approach. This supported by our partner network, the Coca-Cola Company, Monster, Brown-Forman, Costa Coffee and Caffe Vergnano gives us a distinct competitive advantage. In the last 3 years, we have invested significantly in purchasing a lot of external data and combined this with our internal data to develop this 360-degree view of every customer we serve. We have wealth of internal data. We know the sales of our customer, their location, address, number of coolers in the outlet, number of times the coolers are open among several others. We complemented this data with location intelligence of our customers about who is around these outlets. The profile of shoppers, information about the neighborhood, purchasing power of people living nearby, traffic around the outlet and many more. We went a step further and got even more specifics within the outlet, specifically in HoReCa channel, collecting information on traffic within the outlet, peak hours, popularity of the outlet, reviews of the customers, consumers, offering and occasion served. The power of combining all this internal and external information makes that holistic understanding of our customers possible and allows us to use data as a competitive advantage. The picture that you see here will continue to be enhanced, as we are continuously scouting for more data that enriches this understanding of our customers, helping us generate insights that allow us to be more precise, targeted in our personalization approach. So how do we leverage these insights and make them usable for our markets and teams. We support our marketing, sales and business developers in the market with these data-driven insights to personalize actions for every -- each and every outlet. And let's bring this to life today for you through some of the cases and show how this is enabling 3 important objectives for the business: firstly, meeting consumer demand for both affordability and premiumization; secondly, driving growth in HoReCa channel by leveraging our full 24x7 portfolio; and finally, seizing our vast growth opportunities in Africa, while navigating the complexity and scale of these markets. Let's talk about the first one. We have a vary portfolio to tackle consumer demand for both premiumization and affordability. Affordability is always relevant, particularly so in these times and last few years of significant price inflation. Leveraging our RGM capabilities, we are continuously evaluating new packs that can add value, ensuring we focus on areas with real opportunities. With data-driven segmental execution, we enable better targeting of consumers and customers that could benefit from affordable packs. Premiumization is equally important for certain consumers and customers. Here again, a data-driven segmented execution approach allows us to target premium products to the most relevant customers. We'll also use promotions across the portfolio as a way of managing affordability, encouraging newer customers to join the category. With DIA algorithms, giving us now the ability to measure promotion effectiveness, we invest where it pays off most, improving returns for both us and the customer. Let's see how we do this. The first step to enabling segmented execution is all about segmenting customers. AI algorithms analyze all the external data that we have for every single outlet and categorize outlets into distinct clusters, which we call micro segments. Here, you see an example for Bulgaria, where we serve 54,000 outlets. Each of these outlets differ in terms of location, traffic, point of interest, purchasing power and so many more other dimensions. The algorithms work with this data to better understand specificities of each outlet and classifies each outlet into 1 of these 6 micro segments, allowing us to understand distinct characteristics and making this extremely relevant for our marketing and sales team that can then drive targeted portfolio and execution priorities. Micro segments gave a phase to our outlets, allowing us to drive targeted actions with a segmented approach at scale. For example, knowing the outlets that are highly urban with high traffic, high purchasing power. These characteristics allow our teams to activate Schweppes better and drive other premiumization activities. And we are glad to share that this capability of micro segmentation is live in every one of our markets. And each market has a custom-build segmentation based on market specificities, and, of course, the availability of data they have. So let's move forward and show you how these micro segments are used and how they connect to affordable and premiumization proposition. Here, you can see how we use DIA for the launch of 300 ml PET in Bulgaria. You've heard us talk about this in the past about the launch of this pack in Bulgaria and for a good reason. This was a new pack specifically designed to hit an affordable price point to target out-of-pocket spend for young consumers in Bulgaria. With our segmented execution, outlet intelligence, we were able to select the best 1,700 outlets that would benefit most from this pack. This is how we did it. Firstly, micro segments helped us identify rural and towns outlet with low to medium purchasing power, low food and beverage spend and also low urbanicity. All of them making them pretty relevant from an affordability standpoint. Then, we selected styles of consumers. In this case, young and middle class. We then selected purchasing power per capita. In this case, low and average level. We further selected outlets having minimum 2 cooler doors to ensure there is enough chilled space for this innovation. Finally, we selected priority channels as local and traditional to focus on smaller basket sizes, 4 to 5 items and on-the-go drinking occasion. So from a market of 54,000 outlets, DIA enabled us to select 1,700 most relevant outlets for the launch of a specific affordable pack. This is a good example of how our bespoke capabilities work together in executing a new launch. RGM guides the pack and price choices. DIA segmented execution intelligence identifies the target outlets based on specific criteria and route-to-market allows us to execute the plan in the targeted outlets. Combining all these bespoke capabilities, we executed a customer-centric plan, and the results were very encouraging. Nearly 100% of the targeted 1,700 outlets agreed to the distribution versus a historic market average of 50%, demonstrating the relevance of our segmented approach. Cannibalization of other packs was significantly lower than what would usually be the case. Ensuring the sales from the new pack were truly incremental to the business. And perhaps most exciting was that we saw a 35% increase in completely new shoppers in this category. This is really important because the purpose of this pack was to recruit new shoppers, and that's exactly what we did. So let's move forward and now take another example this time from Poland and focus on premiumization. How we drive premiumization with Kinley. As part of Kinley relaunch, we wanted to increase the distribution of single-serve packs, including new flavors. DIA allowed us to quickly identify the outlets suiting not fully -- not only for Kinley relaunch, but also for potential of single-serve packs. And this is how we enabled it. Firstly, we selected highly urban micro segmented outlets, meaning outlets with high traffic, high population density, lots of points of interest. Then we looked at the outlets already having high sales of Kinley, we called them gold. Third, we used AI algorithms that predicted revenue potential for this category, and we selected outlets with high probability of Kinley sales. Finally, we selected outlets having enough space to accommodate a large range of this innovation. So we went for large format modern trade outlets. Through this approach, we identified targeted 930 outlets from 181,000 total outlets based on the segmented execution intelligence, and the results were encouraging here as well. For the 500 ml pack, we achieved 80% distribution in selected outlets versus a country average of 45%. For the 250-milliliter cans, we saw 55% selected outlet listing of this pack versus country average of 30%. And finally, 70% of the selected outlets listed new Kinley flavor versus 37% of the market average. With both the Bulgarian and Polish cases, we emphasized the relevance of our segmented execution approach enabled by data and AI-enabled outlet intelligence. And now, let's continue our journey forward and talk about promotions. Promotions are a key tool in our RGM framework, allowing us to drive joint value with customers, while meeting demand for affordability from consumers. We now use advanced analytics algorithms to provide our modern trade customers with promotion effectiveness insights by brand, pack, promotion type and depth of discount. We can decompose the sales and quantify the real contribution from promotions, netting out the impact of weather, seasonality, holidays, cannibalization that happens because of our own promotions or competition promotions. We calculate ROI per customer, brand, pack, type of promotion and depth of discount. The example you see here is for a particular customer where we decompose weekly sales for last 3 years. We are able to see contribution from promotion peaks highlighted in yellow. We understand the impact of seasonality, weather and the loss or the cannibalization that happens, when our packs steal volume from each other, or we have a competition promotion that is happening. This is allowing us to have insights for joint value margin improvement, emphasizing when to promote, how often to promote, how much to promote, and how to promote? Let's take an example from Italy, where we have rolled out this promo optimization tool. We involved our customer management team to use insights from this tool to amend promo plans of a large modern trade customer. As a result of these insights, we took following actions. We increased promotion slots on the 300 ml can, over 600 ml PET, as it showed a 10% higher ROI and 24% higher volume uplift than the other packs. We increased promotion slots for purchasing multiple packs of Powerade, as ROI and volume seemed stable even with deeper promotions. And we launched new promotions for Monster, identifying the optimal discount range that we could play in this case, between 20% to 30%. These actions helped us drive joint value creation with customers, driving profitable growth, while navigating the affordability challenge for our consumers. This capability that you saw for promo is already live in 11 markets of CCH, primarily for sparkling category, and we look to expand this to our coffee and premium spirits business. We have been progressing adding more customers to this capability. As of now, 75% of our promotion spend with modern trade retailers is already analyzed by algorithms, which is an increase from the 50% that we shared with you on the Investor Day 16 months ago. So we continue making progress and a lot more to come. Now, moving on to the second example for today, driving growth in HoReCa channel by leveraging our 24/7 portfolio. Let's show you how we are enhancing opportunities in this important channel by leveraging the power of data and insights. We see 2 main areas to enhance revenue growth in HoReCa. First, by recruiting more outlets, we call them leads. We want to recruit the right leads prioritizing our effort on the outlets that have highest potential for the categories we offer. Secondly, we want to maximize potential within the existing customers for additional products and categories they could buy, we call these opportunities. Let's see how DIA supports these strategic priorities within the HoReCa channel. We show you an example here from Greece, one of the biggest markets for us in HoReCa. To enable the priorities I talked about before, there are 2 things that are needed. Visibility of total universe of HoReCa outlets in the market today and prioritization of this universe, so that we focus on right leads and opportunities. In the past, universe information was collected manually and maintained in Excel databases, making it infrequent and static, often an issue for HoReCa where the turnover our outlet can be quite traffic. We had hunters manually scanning in the market every now and then with making this as a very extremely costly exercise. Today, we have AI algorithms, scanning external sources every week and giving us this information in an automated way at the click of a button. I just see with the map on the left, our route-to-market team gets full visibility of the HoReCa universe of Greece, and they can understand which outlets we serve and those that we do not serve, the potential leads. Next, we prioritize the right leads to focus for each category and the right customers within our existing customer base to pursue for additional categories. This prioritization is enabled by 2 dimensions: one, category-specific segmentation on each outlet. An algorithm-enabled estimation of potential revenue we can make on every outlet for every category. For example, a platinum outlet for sparkling may not have the same value for coffee, which is why it's critical to assess each category individually. In this case, let's take the example of spirits. We have set characteristics from the data that the algorithms evaluate when deciding that it's a gold outlet for spirits. We look at the type of outlets, bar, restaurants, pub. Each channel offers different potential for spirit sales, then operational factors like open and closing hours of the outlet. Outlet traffic is a critical factor, particularly when we can analyze traffic distribution by hour. We further assess the presence of dedicated bar, professional bartender, which serves as a strong indicator that the outlet can actually promote premium spirits. We leverage algorithms to analyze customer reviews, consumer feedback, which allows us to understand mentions of cocktails, spirits, bartenders and the sentiment of consumer behind this. A high level of positive sentiment specifically for these categories, further validates outlet potential in the category we are looking for. Now imagine the algorithms are analyzing this data in a holistic perspective and able to give a data-driven outlet segmentation for every single category. The more closely an outlet aligns to the criteria we are seeking for every category, the higher the segment it will be placed in. And this capability is now allowing us to classify HoReCa outlet into platinum, gold and silver for every single category we offer. And having this supported by the estimation of potential revenue we can make allows us to focus on right portfolio, right outlets, activate right occasions, differentiate our offering and allocate right resources, so we maximize it 24/7 portfolio opportunities in both new and existing customers. Now this map, this capability hopefully have given you a sense of the scale we are talking about. But the power comes from the granularity of the data, which is feeding the 360-degree view and the algorithms that have been built behind it. You can see here an example from a bar in Athens, highly urban, dense, high traffic area, highly popular, having high consumer sentiments. Our algorithms show it's relevant for all categories with best incremental opportunity for coffee followed by adult sparkling and premium spirits. Let's take a closer look at how these tools are working. As you see in this slide, at the click of a button, the sales team is seeing 48,000 HoReCa outlets in Greece, which we currently don't serve [indiscernible]. We are also able to have an estimate of the potential as I said before. But resources are not unlimited. So we will not go after all these outlets. We will prioritize based on the segmentation and the potential. At the click of a button, we can understand of these 48,000 outlets. We have 1,480 outlets that are platinum or gold for all our categories, making this a right choice for 24/7 portfolio activation. We quickly identified these relevant outlets and put the right effort behind conversion -- converting this. And this shows how with clarity and precision our sales teams can now effectively focus on adding new HoReCa outlets to improve our revenue potential within this critical channel. And what about the existing outlets? Today in Greece, we work with over 70,000 HoReCa customers, but that doesn't mean that we are maximizing the potential revenue from each of these outlets. Here, you can see another example of estimation of potential revenue and how we are able to execute in the marketplace and get to a very focused approach even for our existing customers to ultimately drive profitable business growth. We are happy to share this HoReCa intelligence that I just explained to you for Greece exists already in 15 markets established this year. And to show you how the business developers are interacting with these capabilities, let us show you a short video. [Presentation]

Hope you enjoyed that video. And finally, to our third focus for today, Africa. CCH is excited about long-term growth opportunities in Africa. But we also know that these markets face challenges and greater volatility than our other markets. We have to navigate these short-term challenges, while remaining focused on long-term growth opportunities. Along with all our bespoke capabilities, DIA support this. Our 2 Africa markets are at very different stages in their CCH journey. We have operated in Nigeria for over 73 years. It's well-developed, also with our bespoke capabilities, including DIA, whereas in Egypt, our recent acquisition only in January 2022. We are still on a journey to embed our capabilities and bring the best practices from Nigeria and also across other markets of CCH. So let's move forward and first talk about Nigeria. Nigeria is a critical part of our long-term success and also for us to grow in the market, it's critical to drive recruitment, which in turn will help us continue expanding the per capita consumption expansion within Nigeria. To help achieve this goal, we have been collaborating with the Coca-Cola Company to link consumer and customer data sets. It's all about knowing who we need to recruit and where we can find these consumers around our outlets, so we drive personalized execution for targeted recruitment. Coca-Cola Company has detailed consumer insight studies. And this allows us to create and understand better these consumer profiles, understand the relevant occasions. This helps answer the who we are looking for. In case of Nigeria, we have identified 6 consumer profiles. We then work to match these identified profiles with our data-driven outlet intelligence. When we understand the consumers, we can specifically identify the outlets, they are most likely to shop at. We address the portfolio for the relevant occasion and activate the outlets with relevant messaging. This way, we are able to identify the priority outlets for each of the consumer profiles and drive targeted activation at scale. This linkage of who to where is one of the first type ever done in the Coke system. The initial results from this innovative data-driven approach shows that average sales per shopper from our initial pilot was 40% higher in the outlets we targeted compared to the control outlets. Importantly, sales actually remained harder in these outlets even after the pilot, and this is a great example in many ways of how we are collaborating with the Coca-Cola Company, and our teams are driving common objectives of recruitment together in Nigeria. As I said before, this case is particularly exciting because this collaboration is one of its first time happening within the system in sharing data and insights. We continue to raise the bar when it comes to how we use DIA in Nigeria, and we've got many more initiatives already underway jointly with the Coca-Cola Company. Now let's turn the directions to Egypt, where we have rapidly rolled out DIA capabilities, much of this already being embedded in the market ahead of the target. When we ended the Egyptian market outlet segmentation was very basic, existed only by regions. We rapidly bought in our micro segmentation capability and other levers of segmented execution I explained before. Algorithms was set up to predict the revenue potential of the outlet and we leverage this intelligence to inform cooler placements and resource allocation. Further, we step up the capability to analyze cooler pictures from the outlet on a daily basis, giving us insights to improve occupancy and usage of existing and new assets within the outlets. Enabled by these insights, we are driving, understanding of more than 200,000 outlets in Egypt through data rather than the manual processes that existed before. We refresh this outlet segmentation even more frequently at a 6-month basis, giving us ability to check the market direction, which is very particular in a -- particularly important in a market like Egypt where outlets or a whole area can transition from being less to more affluent in a very short period of time. All of this is providing insights to segment our portfolio of a differentiated brand and pack options and match this to the different level of affluency. Our sales force is also prioritizing high potential outlets supported by targeted competitive recommendations. And let me give you a practical example of how these capabilities are driving a segmented approach in Egypt. Earlier this year, we used data to prioritize investments in Cairo and Giza to drive higher visibility of our brands to improve execution and sales. This included investments in terms of branded signs, marketing materials, placement of branded coolers. We call this initiative own the street, and it was a fully data-driven approach. Outlet segmentation informed who we go after. We went after outlets with high traffic, high estimated revenue potential in sparkling as suggested by the algorithms. Identifying 11,000 kiosks in grocery stores to activate and play coolers. We leverage algorithms to monitor cooler pictures taken by the sales force on a daily basis. Analyzing these pictures and the cooler door opening helped us identify gaps in time, so we could improve merchandising standards, ensure coolers are stocked with our product and placed in the right position in the outlet. Further, we suggested specific in-store activation recommendations to our sales force. Results? We saw a 33% increase in sales from the outlets we activated compared to the benchmark outlets not activated. Strong results with efficient resource allocation. We are now looking to scale this approach to more outlets in Egypt in 2025. We hope with these examples, we have helped you understand how we translate data, insights and analytics to actionable insights and targeted actions for our business. I'm coming to the end of my presentation, but before we move to the Q&A, let me also take a few minutes to explain and to help you understand the investments we are making behind the team and the internal talent and how we're developing a capability, which is best-in-class now and for the future. Algorithms and data is important, but it's our people and the talent that truly makes a difference. Over the last 4 years at Hellenic, we have developed a best-in-class expert team of more than 50 people, including data and AI scientists, business analysts and data quality experts who are building these solutions at scale. We invest behind this talent so that they are skilled with the latest and the greatest capabilities. Also, we are focusing on upskilling the rest of the organization that needs to leverage these insights from DIA. We already have a data and analytics online learning platform, open to all employees and we have more than 2,000 people now, investing time in learning. This is helping us build data and AI literacy, which is critical to support usage of these solutions and drive data-driven actions on a daily basis. As I look forward, I'm super excited about the journey ahead. Let me highlight for you a few forward-looking areas that we are already working on. We continue to gather more data to allow us to go deeper in our customer segmentation. And our ambition is to move from micro to nano segments. We are expanding the HoReCa intelligence to the rest of the out-of-home channels including At Work and Vending. We are working to enhance execution in high-potential new categories. For example, for Powerade, we will identify nontraditional ways to prioritize outlets, focusing on areas with younger population, outlets closer to the parks, gyms, sports centers. And we are strengthening the collaboration with the Coca-Cola Company to drive hyper-personalized marketing, also including generative AI for high revenue potential outlets where we can really combine forces of bringing segmented consumer marketing with segmented execution, this time to drive customer transactions. And having this 360-degree view of the outlets help the Coca-Cola Company to drive hyper-personalized marketing around the right outlets. Finally, as I said, we are already working with generative AI, unique opportunity and we will continue to improve our current algorithms and bring in semi-structured and unstructured data like outlet images, consumer feedback, customer feedback, comments and all of this will further amplify the 360-degree approach and improve all the decision-making we are already embedding with the prioritized use cases. So these are some of the exciting cases that we are working on already and happy to bring this forward as we continue our sessions. With that, I will conclude my presentation on DIA, and I thank you for your time and attention today. But before we close, let me bring it back all to our bespoke capabilities. As Naya shared at the start of our presentation, the progress we are making on each of our capabilities, and particularly the way they interact together is allowing us to better understand the real needs of our customers and consumers, drive profitable revenue growth and anticipate and react to new challenges faster and smarter than our competition. Overall, this interconnection is driving personalized execution for every outlet, allowing us to continue to win in the marketplace.

Thank you very much, Naya and Ruchika for the presentation. We will now start with Q&A. [Operator Instructions] As I mentioned at the start, we're currently in close period ahead of Q3. So please bear that in mind when you are thinking of your questions. And can I ask if you stick to one question and one follow-up. While we're assembling a list of live questions, let me take first question from the webcast. And it's a question for Ruchika. So Ruchika, can we ask a question about scaling this capability. How scalable are the tools in terms of being able to roll them out swiftly across countries and categories?

Thank you for the question, Jo. Let me start by saying scaling has 2 dimensions. There's first aspect of building the tools and rolling this out in the market and second is getting people to use them in their daily decision-making. As I shared before, with the best-in-class capability and the prioritization that we are doing behind this capability, the examples of promo, segmented execution, HoReCa multi-category, they are already available in many of our markets, demonstrating our ability to scale and grow these capabilities out. We continue to invest behind the second pillar, which is increasing the usage of these tools and continuous effort to build capabilities and changing the behavior of the users that can benefit from these insights. And that's the second part of scalability that we are continuously working on.

Thanks, Ruchika. And it now looks like we have a question on the Zoom call. So let me pass back to the operator to moderate this part of the Q&A.

We'll take our first question from Edward Mundy from Jefferies.

Can you hear me?

Yes. We can hear you, Ed.

Great. Thanks for the presentation. So now the first question is perhaps for you. This is a huge differentiator for you. Are you able to sort of talk to what are you doing better than peers either in terms of your capabilities or any particular parts of execution? And I guess as part of that same question, I mean, how important has data, insight and analytics being in your ability to drive that big step-up in revenue per case that we've seen over the last couple of years, would that much impact on volumes? That's my first question.

So the first view here when it comes to your question is why it's different overall, and why we call it bespoke? It's mainly because of 4 elements. One, we are achieving local relevance while having overall group framework. So there is a discipline at a group level, but at the same time, we're trying to commercialize this in the most local relevant manner. The second thing is what Ruchika mentioned, we're working together with the Coca-Cola Company in complementary partnerships. There is a third part, which has to do with delivering fast results when it comes to method and segmentation. So we go as targeted as possible, taking into consideration all the different dynamics from consumers, from shoppers, from customers. And last but not least, there is an element of obviously investment when it comes to that, both in resources as well as tools. So this is a little bit how it's working. And it goes without saying that all this work together in order to deliver better quality when it comes to the growth.

And I guess part of that same question, I mean, I spent one way to ask the same question is you managed to get through quite a big step up in revenue per case. Would that much volume impact over the last couple of years, unlike a lot of your CPG peers? I mean if you didn't have some of these tools, do you think you would be able to sort of execute in quite that same manner?

These tools are really provide -- are making us more well informed to ensure that our choices are done in a way where we prioritize them towards the right sort of play-to-win, if I would say. So yes to your question.

Okay. And then my follow-up question for Ruchika. Thanks for presentation. Clearly, the insights and analytics are really as good as the data that goes into them. I mean, how do you ensure data, which then drives the algos is up to date? And perhaps you could give an example when you saw consumer sentiment soften a bit in Bulgaria and you've started to launch the 300 ml PET pack. I mean, what were the inputs into that data that then allowed you to mobilize that quickly?

Absolutely. And you rightly said, I mean, the algorithms are as good as the data that goes into it. So that's why when we were even establishing the capabilities, we have a specific team that's working on the learnings of data. So we make sure that we do thorough validation, especially on the external data that we are purchasing in the market before we start rolling out these capabilities. So to your example on Bulgaria case, which used extensively the external data I talked about. Before these capabilities were created, we actually did extensive validation within the market, going to sample areas, sample customers, validating what the data was showing us and that gave us confidence to move forward at scale. And that's where across all pillars that I talked about, we invest in validating the information we use. The second thing that we do, which is a big call out to our technology teams is we make sure data remains secure. And we have the best privacy controls around this. We allow access from an access management to only people that can see the data at the right level. And the third thing really from that perspective is how we drive usage of these insights in the interpretation. And that's the third thing that we work on. I would also like to call out the partnerships that we have established with a lot of these external providers, which are key in the sourcing we are doing, and having worked with them over the last few years, we have established a way in which we are validating the data upfront with them, and then scaling this out in the market. So I think this whole ecosystem approach is allowing us to go faster and maintaining the quality of the data. And probably one more thing I would call out, which is very important. We always have human in the loop. No algorithms, no quality of data allows us to localize the part that Naya mentioned, unless the relevant people standing in front of the outlet have a say and can give us input back. And that's the last critical driver that we absolutely amplify in any of these solutions.

Our next question comes from Mandeep Sangha from Barclays.