 Ladies and gentlemen, allow me to move on to our next panel session for today. The topic for this panel session is advanced metrics in mobile marketing, the right way to practice it. There will be three key highlight points being discussed on this panel. One, best practices of mobile marketing. Two, building effective dashboards to understand metrics that matter. Three, dynamics at play for next phase of mobile marketing metrics. Allow me to welcome the session chair for this panel, Mr. Kousal Maladi, Vice President of Madison World. The speakers for the panel allow me to welcome the same Mr. Ajay Dhyani, Head Marketing and Econ, Timex Group. Mr. Siddharth, Tahbade, MD and of MIQ India and SAR, MIQ Digital Commercial Private Limited. Pravalita Bora, Head of Marketing 91 Mobile. Juhi Singh, Head of Digital Center of Excellence, India and International, Mariko. Krithiman Kohli, Digital Marketing and CRM Lead at Rekit Venkansar. Welcome to all the speakers and our session chair and I hope I ununciated all your names correctly if I haven't pleased to point it out. Over to you. The floor is all yours. Thank you. Thank you so much. Hello everyone. Welcome. So, since we've had a very quick introduction and we have got half an hour of session, I'll quickly jump into the topic. So the discussion is about measurement metrics in mobile marketing. It's very interesting. I remember a time 10, 12 years ago when we used to talk about digital marketing and numbers. We used to get really excited. We used to track the com score numbers month on month and we would say, you know, there are 20 million users per month on digital today. There are 25 million. I remember this one time when we got really excited when we hit a number of 40, 45 million. Today we probably had 450 to 500 million and that's the truth today, right? At that point of time, we had internet marketing, which is pretty much what we did on desktops and we had mobile marketing, which was that one thing that you did through SMS, OBD, and so on and so forth. Of course, things have changed and as a great man, Uncle Ben once told Spider-Man with great power comes great responsibility and that's where we are today. Mobile marketing, digital marketing gives us so much data to play with and with so much data, we just don't know what to do. There are two challenges with data. One, what do I do with the data? How do I analyze the data and make sense of it? And two, what about privacy? Where do we stand on privacy today? So with that, I'd like to just open the floor and I'll address the first question to Ketiman, taking a step back again. As I said, we had digital marketing, which was internet marketing and mobile marketing. What is mobile marketing today? How would you define it? So as in the last session I was mentioned, almost 85% of all media consumption on the internet is happening over mobile. So almost all digital marketing right now is mobile marketing or mobile first marketing, which triggers us marketers to think in that direction and there is a big paradigm shift for us as well, because earlier we used to look at our screens where we're looking at assets, we're looking at our tech stops while approving assets. We'll have to look at each asset in each communication to see that if does it fit well in a 16 screen or not? Or does it fare well? Does the consumer get the message in a 16 screen or not? It's something which is paramount as a marketer now. So just a small tip, and I've been using this the past few months, is every time I approve an asset or review an asset I'm sure that the team sends it on my phone rather than on the desktop. So that actually helps. Yeah, it's very interesting to say this because I remember this back in 2014, we were creating this website, it was a really fancy website which was opening by QR code at that point of time and lots of things. And we had created it for a desktop and we had optimized it for the mobile screen, but the client was constantly complaining that it wasn't opening properly, it was opening on all our phones properly, but it wasn't opening the clients properly. Then we figured that the client was still using a four inch screen while the rest of us had five, five and a half, six inch. So the size is interesting. That does not work, of course. Yeah, thanks for that. So I just like a slightly different perspective now. I'll move on to Prajavita who essentially sells markets to people who buy mobiles, which gives us all the data that we have today, right? So how would you define mobile marketing? Thanks, Kursal. So well, my views largely resonate with what Kirtiman has already sort of highlighted. We can't think of mobile marketing as a channel anymore. And I mean, and in the smartphone space, marketing is essentially mobile today. So we have to adopt a mobile first outlook. So whether it's the creative, the ad creative or the ad, the length of your ad film or your brand film, the format, the sound, we have to make sure that they're optimized for mobile. So that applies, of course, to our space as well. The other thing in the smartphone and tech space is whom are we distributing our ads to, right? If I'll give an example. For a smartphone brand today, any of us is a potential consumer, right? But how many of us are looking to buy a new smartphone immediately? Not a lot, like the number will be very few. In fact, in a given month, only 10 to 10 million, 10 to 12 million smartphones are being sold. So and in laptops and tablets and appliance and other categories, the numbers will be even smaller. So while your TG may be in careers, the in market high intent audience would only be a few lacks. So when you have to advertise, it makes sense to disproportionately go after this audience. And there are ways to identify them. For example, of course, on gadget sites like 91 mobiles and further segment them based on their search behavior and customize your ads for greater impact. So that's something that we sort of follow very closely adopting a scientific way to marketing. The other thing that I want to sort of touch upon and it applies to all categories, not just tech, I would say, is that in mobile marketing, like people are looking for immediacy, they are looking for compelling. And if you don't deliver it in an easy to consume format, they'll just walk away, right? So I think as marketers, we have to make sure that you're delivering content and getting to the key value proposition immediately. And I think the fourth thing that I sort of would like to quickly touch upon is the fact that there's a whole proliferation of channels today. And it's very important to pick the right channels. Of course, it will vary based on your campaign objective, etc. But if you're creating ads for Facebook, you have an app, you have email marketing, you're doing mitro, you're probably going to clubhouse, you're leveraging influencers, it's definitely difficult to maintain brand consistency. So it's very important to sort of figure where your consumers are spending the most time learning and discovering about new brands and making sure you're available in those platforms in the best possible manner. So yeah, those are like a few highlights about how we sort of adopt marketing here at 91Mobiles. Yeah, I mean, it's very interesting because in fact, we can probably dig into this a little deeper. I mean, at 91Mobiles, you obviously have, I mean, because of what the platform is, you know exactly what the consumers are coming here on the platform for, right? How do you actually start creating codes of users outside of your platform when they're not looking for mobile exactly, looking to buy mobile products, but understand that they are consumers of mobile, that will be something that will be interesting to look for. And it will obviously apply for a lot of other brands because, I mean, the website is not meant for that purpose, right? So that would be interesting. And another thing that you mentioned, which I thought was very interesting was they are probably not looking to buy the phone immediately. They're doing some research. So, and I think it's a fantastic way, it's a fantastic reason. I'd probably want to ask the question to Joey because if you're talking about the attribution here, right? I mean, if I'm searching for something on 91Mobiles, I'm probably not looking to do that. So there is a certain look back window. So today, if I look at what Facebook would say, Facebook would probably give a look back window of rating anywhere between one day to seven days, depending on the category. And there is a different look back for each platform and attribution is always a big challenge. So it would probably be fantastic to know how you handle this attribution challenge at Marico. And also, how do you use data to make decisions on which platforms to be present on to drive more sales? Yeah, thanks, Parcel. So like you mentioned, it's very, very easy in case when we have a DTC brand, where in, let's say the sales is also happening on the website and then the direct attribution is possible, because we are having some tags, etc. to know that which of the channel actually converted. It becomes difficult when somebody enters a black box like Amazon and Flipkart. While to an extent, if we land them on brand store, etc., we get that data. But what happens is that most of the time on brand store, they are still exploring and they go on the PDP later on and convert. So what we did at Marico is that we try and gather everyday sales data for all our brands from, let's say, Amazon, which is the largest partner for us. And then of course, we get all the digital marketing data. We run a multi-channel attribution model, which actually helps us to derive ROI for each of the platform at a brand level, which in turn, which we have built a spend optimizer tool internally, which helps a brand manager to play around with. And they can make a choice to go by the model, which is predicting the ROI or apply their own intelligence, because maybe they have a better asset this time or a better cohort defined on certain platform and they feel that it will give a better outcome. So the model predicts the expected, let's say max or optimum sale as well, if the spend attribution is made as per model. We keep tracking that and we keep improving the model as well. And one number that we track very actively for the senior leadership and at each brand level is ROAS, which is essentially opposite of ACOS. And it's a very simple yet very effective matrix because it can be applied at a company level, geography level, business unit level, even at a category, brand, time period and campaign level. So what we have done is we have arrived at certain benchmark at each of these level and we keep evaluating whether we are performing better than that or not so good and then keep improving henceforth. So I think that's the way we do it. Okay, interesting. So just a follow up question. Would you also, while obviously you are able to track the ROAS for an online sale probability, is there any modeling you are looking to do to track the offline sales because a large part of Marico products obviously still sell offline. And for the e-commerce sales or e-commerce marketing spends to grow, I'm sure there is a huge impact that will have on the offline sale as well. Like for example, I see a product online but I don't necessarily order, I mean if it's an oil I probably don't order online. But what I see on an Amazon makes a huge difference. So is there any impact there? Yeah, so like the multi-touch attribution model is of course much more frequent because we have the data at that level. So it can be let's say a quarterly level model to predict the ROI and make changes. But for large brands and where offline data is there and there is a, you know, data which is coming late to us through the store audits etc. Of course the data cannot be collated and the model cannot be run immediately. Also a lot of factors come into picture, right? Because there is store, let's say general trade visibility and, you know, there are promos running and all of that. And data accuracy is also a problem. So there we apply a multi-MMM model, right? And what we do is that we do it by annual and then we keep refreshing it as we go. However, having said that the accuracy of that model is also getting impacted by let's say conditions like COVID etc. Which was not unprecedented, right? So that ways we attribute for the offline sales. Okay. Okay. Thanks, Julie. So just taking the e-commerce conversation forward, we have Ajay from Timex. So I'm just curious to see if the e-commerce journey for CPG versus e-commerce for Timex wouldn't be very different the way you look at it. Right. So in Timex group, we have also seen unprecedented growth in our e-commerce and especially on the digital platform. Especially, you know, talking about the last lockdown at that point in time when our stores were closed and physical stores, there were no walk-ins. And that point in time, I mean, I mean, it was complete lockdown in from e-commerce point of view. But even after that, you know, the kind of growth and kind of response we have seen on digital platform that has been phenomenal. And we have taken a lot of initiatives to further grow this journey. And those initiatives are backed by data. I mean, one is our D2Z initiative where we sell our watches directly from the brand website. And I would say that, you know, the performance of the brand website also started growing significantly just after the lockdown period. And that is again backed by a lot of data. We say first party data and third party data and doing marketing activities and, you know, planning all sort of marketing strategies, top of the funnel strategies and bottom of the funnel strategies to to leverage from that and optimize your sales performance. Second, I would say that on e-commerce platforms like Amazon Flipkart, again, the growth, I would say the significant factor behind this growth would be data. I mean, working closely with e-commerce platforms and then, you know, getting those valuable data from the partners. I would say not only, I mean, consumer data, of course, not available, but other product data. I mean, that product insights data really help us to improve performance, be it, you know, for example, looking at, you know, what consumers are preferring to buy online space and then we match it with our offline data. We get, you know, CRM data from our stores and then we have DMS data from our distribution channel and then website data. And we try to analyze this data so closely to find and to make the cohorts of the consumers and try to optimize. And then there are various factors which are involved, like, for example, you know, if there are certain issues where you can really improve to lower the return rates and to improve the product performance by, you know, making, by, you know, doing contextual targeting and also improving our product presence on the e-commerce platform. So again, I would say on and all e-commerce, journey e-commerce growth has been a phenomenon in the last couple of years. And I would say that data played a very, very important role, helping us to optimize and helping us to achieve these significant numbers. Thank you. Thank you, Ajay. So essentially, when we talk so much about data, we cannot run away from the question of privacy rate. And that's something that's been on top of a lot of people's minds. So addresses to Siddharth, considering programmatic as a platform has always been about transparency. It's been about consolidation. It's been about having more control on your campaigns. With all the conversation around privacy coming in with restrictions coming in about how data gets captured, so on and so forth, has it really affected programmatic advertising in large way and will it going forward? How do you see this? Yeah, yeah. So I think, you know, just to take a step back on this, you know, because this is a very interesting and fundamental question which you asked. And thanks a lot for that. So let's look at the evolution of digital marketing and digital in India, right? So, you know, it started with Google, Facebook, and then, you know, there are e-commerce platforms like Amazon, Flipkart, they have, they are growing now. So we are going through a journey in India, right? And what we also see in this decade is that probably TV is going to change. TV, traditional TV is going to morph into OTT and connected TV and so on, right? It's the digitalization of TV which will happen. And of course, you know, as we go more and more into this decade, we will see that all the news is being consumed on digital and, you know, so it's basically a lot more other channels coming in. Connected TV has spoke about digital lot of home. 5G can bring in a lot of other form factors as well and, you know, get you in a very advanced way in terms of where you want to target the consumers. So in this, definitely data privacy is an important factor and consumer privacy is something which is very, very critical. And what we see as a trend which is emerging because of this is that, you know, there are a lot of form factors coming in. There are a lot of new channels coming in. The biggest need of the hour is that how do you bring it all together? And within that, you have ward gardens and you have open internet system. But ultimately, you need a place where everything is coming together. And programmatic is probably one of the first good step which, you know, clients can take, you know, the brands can take to look at all the different channels. Like, you know, you have display, you have video, you have OTT, you have connected TV, digital lot of home, other form factors which will be coming in. All these things, how you can have it together have measured measurement in single panel so that if you are, for example, doing a campaign where you want to maximize your reach in a particular TG, you would want to do that in a single screen and you would also still be able to manage an ideal frequency. If I want to have an ideal frequency of 8, I should be able to do that and manage it, right, and maximize my reach on all these form factors. So that is where programmatic comes into place. And what we are seeing is that is one of the big reason why programmatic is growing very rapidly because it also creates a lot of financial savings. You are able to have all these channels together and you are able to optimize across all these channels together. So that creates a huge amount of financial savings. Then the other innovation which programmatic brings in is you can also overlay data on top of it. So you can have, as Ajay was also saying, first-party data, third-party data, second-party data which is coming from campaign. And you can make your campaign very data-rich and you can first look at what is the right cohort, you know, and then from there actually activate the right cohort for yourself. And that's where the question of data privacy comes in. And so, for example, at MIQ, we have 700 million consumers' data in India. We have an extensive data lake. Globally, we have 500 plus data partnerships, all data coming into a single data lake. And then what we are doing there is every new data partnership we have, we connect the data at a primary key which is cookie ID and a device ID level. And of course, cookie is going to go away. Device ID is going to remain for some time. But definitely one is cookie because cookie is going to go away. We are also collecting a lot of contextual signals and switching this data together so that, you know, at a cohort level, we are still having signals, both online and offline signals. And it is a non-personally identifiable information which is completely GDPR compliant. So that way, you know, we are completely taking care of the privacy. But at the same time, we are able to leverage the good parts of problematic and data and help the brands with the insights as well as very strong data-driven marketing, which you can leverage. And what I also feel is that cookie-less paradigm is a good thing. It is coming in and it is going to keep growing. And that's where, you know, you would want to look at your authenticated data, which is basically the data, which is the consumer data, which you are getting. Because when consumers are coming onto your website or app, they are logging in. And obviously on purpose, they are, you know, consent, they are giving you the information and accordingly you can use that information to target these consumers. But obviously in a smart way, in a privacy compliant way still, right? Because even if they have given the permission, it doesn't mean that, you know, you are going to take advantage of that. So that's very, very important. And then the emergence of the anonymous data where I was talking about contextual signals and a lot of other signals which are there, you know, where you are able to leverage that data at a cohort level and still maintain the efficacy of the advertising, but also managing the data privacy in a very, very good way. Got it. Thanks. Thanks so much for that. Just actually, it's a very interesting point you brought out, right? About how you're actually looking at cross-screen planning. So I want to get a perspective of a brand marketer. So, Keith, within Rekid, do you think that you have mobile marketing? You have TV, digital overall, but we still call it mobile because today we are in this forum. Is there a challenge in driving cross-screen planning? I mean, there are multiple conversations and I've been a part of so many conversations where there is a team that says that TV is a big screen. Mobile is a very small screen versus another audience which says that but mobile is more personalized. TV, you don't know whether the person is actually seeing or not. How do you address these challenges? Cross-screen planning here to stay and how do you actually create a single data point to track them? So it's certainly here to stay, like you said. See, even if there are multiple screens, it's the same consumer, it's a single consumer. So rather than looking at mobile or TV in silos, it's very important to have some sort of a screen neutral planning there. And obviously, that's an ideal scenario to have. We are still very nascent when it comes to screen neutral planning and we as a group would like to evolve a lot where there are other markets globally where you could plan TV and your mobile campaigns together through programmatic. So we're still nascent there as India as a market but we would want to move into that direction. But one thing that we can do is rather than looking at TV and mobile as different platforms in silos, it will be very necessary to understand that we need to look at it more from a business objective sense rather than going to a platform. So we need to look at the funnel where we need to say we've got an objective for awareness or consideration and according to that, we need to overlay our platform or platforms so that we can achieve our business results. So if, and for example, you get that query a lot in digital, just because you have data, you get exploited a lot there. But vis-a-vis TV, you don't get data and still the requirement suffices. It's very important to look at each platform at the business objective level. So for example, if you're planning an awareness campaign on both TV and digital, it's very important to look at the awareness brand metrics only and rather than looking at converging which a mobile video or notity could provide. So it's very important to look at each platform and each campaign towards the business objective. So if you're going for an awareness campaign, look at your reach metrics, look at your brand metrics, look at your BLSS. If you're going for a consultation, you should have your KPIs set, your expectations set behind each platform and then look at the results. Otherwise, you'll just keep hopping around objectives which won't make sense. Okay. Thanks for that. I actually just want to understand one thing. If we look at each platform, and this is a challenge that we face, right? And as you rightly pointed out, I mean the measurability of digital is sometimes what actually restricts the usage of digital because people always want results, right? But for example, on TV, there are certain parameters that have been said. I mean, you say that if you don't do 150, 120 GRPs per week, don't activate a TV plan and so on and so forth. On digital, Google and Facebook have been trying for the log this time to say that you need to do, I don't know, 50% reach at an average frequency of five a month to be this one. But nothing's really, I mean, while there is an attempt, is it possible to really compare the two mediums? I mean, that's my question. If you look at each medium in silos, while it's good to have different parameters, comparing the two mediums, what would the right parameter be? I'm assuming it probably be reach, right? But how do you scale one medium over another and how do you take calls if you do not operate them together? So it's important to look at the advantages of each medium. So if the expectation is to go to a wider audience where you can carpet bomb a lot of people for a lot of great impact, you could look at a TV. But let's say if you want certain micro cohorts, you would want to target with personalized communication to move towards more of a digital format. Or you would want to target only a set of consumers that are from let's say an H&I group or from a certain section. You'll have to look at the platform as per the business objective that you have. So you'll have to look at the strengths of each platform and create an amalgamation when it comes to planning. That makes sense. Thank you so much. And Siddharth, considering you are doing the cross-screen planning, which are the categories that have really picked up cross-screen planning? I mean Google obviously has been trying to create its own reach planner between TV and video data. Every agency has its own cross-screen planning tool. BARC has been trying to do this for the longest time with ACUM. So which are the industries that are catching up here? So actually all the industries, it can be tech, it can be FMCG, it can be consumer durables, it can be even BFSI as well. And basically the innovation which you brought in here and this is something where it's about data. So basically the richer data you have for the market, what you would want to do is you would want to basically understand the consumer profiles first. Who are the different cohorts which you have? So that's what we do. We create a very deep profile of the consumers for a particular brand and they can be online signals, offline signals. And also we have the signals for their media behavior, online behavior as well as offline TV watching behavior as well. So kind of connect the consumer profile with their media behavior as well and then kind of create the planning structure where you are saying that these are your most important consumers and if you are looking at doing an online video campaign for example, in a single panel you want to do OTTs, YouTube, connected TV and possibly digital lot of home as well, then the planning will tell us that these are the right OTTs for you. If it is IPL time it doesn't mean that everyone is watching only IPL. So who is your particular consumer and where are they in the OTTs and which are the right channels on YouTube also and what are the locations for digital lot of home where these consumers are present. And that's how then you plan it so that your first step when you start the campaign itself is very well informed. And then once you start the campaign then obviously as you get more data you can refine it further. But the planning process becomes very important and that's where then you are able to bring in a lot of inefficiencies to be eliminated even before you start the campaign. Perfect. Thanks. And a lot of, and I'm assuming and you can correct me if I'm wrong, a lot of what you're doing between cross grid planning is on the back of probabilistic data, right? No, so it's, you know, a lot bases the device ID data which we have, because as Kirti Manu also talking about that 80% of the ad delivery or the consumption of internet is on mobile in India, right? And also what device ID helps us with is the location data as well because you carry the device with you all the time and that's why the device is intelligent to tell about your location as well. And then of course it is all non-personally identifiable information, but then with the screen, mobile screen which you are, you know, spending the most time with and also with the location data as a combination that creates that synergy which I was talking about as an example between online video and digital auto form. And then of course now depending on the platform, depending on the DSP, you can also have the synergy between connected TV online video and digital auto form as well. Thanks, thanks so much. So speaking of data and non-personally identifiable data, Ajay, what sort of role does data play for time? I mean you mentioned initially in short that you lose data, you will go and so on and so forth. So I really want to understand what sort of, let's dig a little deeper into this, understand what role data is playing and what role do you see DMPs and CDPs playing in this journey? Right. So in my view, I think data is, I would say in our digital marketing strategy, data would be the most important piece of all the various digital marketing activities which we plan. Like for example, first party data which is actually a kind of gold mine for the marketeers to use it in a way to really, really flourish. I mean, not only flourish, but also to understand your consumers and plan strategies trends and all. Like Siddharth also mentioned in a post cookie era where this data would not be freely available. The cost of digital marketing, cost of acquisition will go up and marketeers who would have this first party data will have the benefit. So from time experspective, we know that consumers who buy watches generally try to do a repeat purchase on certain occasions, be it wedding or be it birthdays or other festivals. So I mean, we like to retain our customers and make sure that not only they but their family members also stick to the brand and we use that data in a way that we are able to create that personalized experience for them and stay connected with our consumers. So I would say, all in all, data is absolutely critical. I think mobile phone is one device. I think it's the device where the first time product discovery happens. Consumers searching for the product or maybe experiencing your products be it through apps or app downloads for smart watches. I think mobile phone is the first way of connecting with the brand and product discovery and all. So using mobile phone as a medium, creative-wise and all, even the brief with the creative agency starts with the mobile first approach. So on and all, data is absolutely important to create that kind of experience and to leverage from that data. Especially in today's time where digital marketing is absolutely critical. So I would say data for us is absolutely important. Perfect. So Prajlata, we've spoken a lot about data. You also mentioned initially that you leverage influencers in the tech space. I mean, I know there's a lot of attempt to get data about influencers, which market are they from, what are they interested in and so on and so forth. But we also know that there are so many influencers who are fashion influencers today, tech influencers tomorrow and something else the day after. And they're also probably promoting a Samsung today, they're probably promoting an Apple tomorrow and so on and so forth. So how exactly do you actually create a data-led strategy when there is very little data available? I'm especially talking about influencer marketing actually. Very correctly put actually, Kausal. It's not as clear-cut in the influencer space because it's still evolving. And in the tech space, influencer marketing like key influencers can really make or break a product in a certain sense because top influencers and it makes sense. Smartphones, tablets, laptops are highly considered purchases and top influencers would experience the product, use it, test it and then give a verdict. And they have massive following base and based on their verdict, their followers would sort of have a certain affinity towards the product or not. So some of the things that you talked about, right? It doesn't make sense. So it's very important when you're adopting influencer marketing strategy, it's very important to consider the influencers that you're onboarding. Do they, for a particular campaign, do their audience space resonate with what you're trying to sell? It doesn't make sense to ask a fashion blogger to promote a gaming laptop, for example, obviously. And there are a few other such checks that you should do. For example, how often does an influencer produce content? So there are a few qualitative and quantitative checks that you must do to ensure that your influencer marketing program actually works. So how often does he publish content? How often does it do his followers engage with his content? How often does the influencer interact with the content? These are some basic qualitative checks. There are of course the standard quantitative numbers that you would check, you know, that what is his total subscriber base? Where is he most active? When he does a branded content, what is the typical engagement you get? All of those. But yeah, I think broadly it's about making sure that you sort of, you analyze the audience space and choose the right influencers for the right programs. That's very important in the influencer space. And as it evolves, I think we'll have better metrics in place to track efficacy. Thank you so much. Just before wrapping, just one last question. So, Juhi, with all the data that's there for us, how do you put it together and make sense of the data? We have about, we're actually short on time. So if we can just get a little bit here. So I think it's a very relevant question. And one quote, which I keep hearing is that data, data everywhere, not a drop to think. But most of the organizations are actually struggling with the same thing because gone are those days when Tom was an indicator that your marketing has delivered effectively. And especially when you look at digital space. So at Mariko, we have developed a custom framework which we call digital quotient where we look at 90 plus matrix and we attach a weightage to the matrix which are most highly correlated with business. And then we look at about 130 plus brands where in 20 are Mariko brands, etc. And we do with some product. So you get an index score out of it with the weightage as well as the performance of each of the brand. Looking at this whole framework, then each of the brand knows that how good or how bad am I, and at each of the matrix, how should I improve. So I think that's the way we have done it at strategic level and of course that there are weekly, monthly, daily dashboards available to track these matrix. So I would say digital quotient has really helped us to focus. Thank you. Thank you so much. Before we sign off, a quick show of hands. I have two questions with all that are this one about data privacy. How many of us here hands on our heart? Don't mind sharing the data with the world so that we can get personalized communication. Quick show of hands. Okay, fantastic. So that's two. And secondly, how many of us and there is a saying, right? If you torture data hard enough, it will tell you what you want to hear. So do you really trust the data that you get today or do you? How many really trust the data that we're getting today? Fantastic. Thank you so much. And just one word from each of you. What do you think is a trend that will come up in the future for mobile marketing? One future trend, just one word. Juhi. I think owning your own data is the most important and data is the oil. So I think that's the oil. Perfect. Kintima. Yeah, dude. Like he said, owning data and then having a platform that can tell you how to leverage that data in the right way that you can target the right consumer is extremely effective. So platform. Perfect. Thank you. Ajay. Yeah, I think it's related to first party data, right? Mobile, you know. First party. Yeah, yeah. A lot of material data and consumers are, you know, kind of, you can basically target without infringing on the privacy in the right way. Perfect. So first party data. Ajay, one word. Right, I think content creativity and the experience using technology will be absolutely interesting to watch out for. And I expect that, you know, technology will play a very crucial role enhancing customer experience through creative content. I think video and images are there, but still I think there are a lot of scope. Yeah. So future is great. Perfect. Taking a little bit from Ajay, like as there's proliferation of more mobile first formats, vertically oriented videos, stories, et cetera, figuring out the right metrics to measure impact as you run campaigns on the newer formats. Perfect. Thank you. Thank you so much. We are out of time. We know fantastic. Thank you. Thank you. Thank you, everyone. Thank you so much. Thank you. Thanks, everyone.