 Ladies and gentlemen, with this, we will now move on to our next panel discussion. That is, of course, an interesting one because it is on the topic of data and creativity. And how data and creativity can work together, where our panelists are going to tell you how creativity can become data-driven and personalized, and how can data fuel and enhance creativity. So how they are related to each other and how they can sort of support each other, these two elements. Please welcome on stage our session chair for this panel discussion. We have Punit Avasthi, Director, Specialist, Businesses, Insights Division, Kantar joining us on stage. Welcome, Punit. Ladies and gentlemen, a round of applause. And now I would like to introduce our panelists to all of you. We have Prasoon Kumar, CMO for Just Style. Please give it up for Tabrez Alam, Chief Data and Strategy Officer, Bobble AI. Sumeli Chatterjee, Head Integrated Marketing Experiences, India and Southwest Asia, the Coca-Cola Company. Please give it up for Ruchika Gupta, CMO, Luminous Power Technologies. And lastly, Udit Malhotra, Head of Marketing, MG Motor India. Ladies and gentlemen, that is all our panelists here on stage. And now I would request Punit Avasthi to lead the talk and let's set the ball rolling. Thank you. Thanks a lot. Are we audible to everybody right in the rear? Audible? So it's a very interesting topic that we're going to be discussing here. We are now living in a world where there is so much data that is being created through all our interactions with, our transactions, whether they are on social media, whether they are on Google search or e-commerce, all of that data as such. And of course there's a lot of first party data as well that businesses, marketers have. How is it that they are using this data for a multitude of purposes as such? But the important question here that we're going to be addressing ourselves to is whether this data and particularly this world of data driven decision making is in any manner relevant for creative development. And if so, how is it being used as such by marketers? And we've got a very panel as such which are people representing very different industries. We've got Udith here from MG Motors. We've got Ruchika from Luminus. We've got Sumeli from Coke. We've got Tabrez from Bobble and Prasoon from Just Dial. So it's a very varied set of panelists as such. People with very different experiences given the kind of categories that they're handling and the kind of requirements that they have in terms of being able to respond to consumer requirements on a day to day basis and communicate with them in the right moment as such at the right time when the consumer is likely to be purchasing a particular product. And there are multiple nudges that are possible as such. It's not just about having a great creative as such, which is 30 second television commercial. But it's also about being able to give the consumer the right nudge at the right moment because the data world actually provides that information 24-7. So without any further ado, let's try and understand this entire ecosystem and how it is playing out in the space of creative. And in fact, what I'll do is I'll start with first really putting the elephant here in the room across to everybody. And I would want everyone to respond to it as such, which is do you believe that data and creativity as such are mutually exclusive? And the other question is, it might be currently or may not be, should it be exclusive at all as such? Or do they need to interact? Do they need to talk to one another? Would you want to go first? Good afternoon, everyone. So I think the straightforward answer to this is they should complement each other and they should not be mutually exclusive. When we talk about data in particular, generally it's only thought from a function perspective of how would, let's say, marketing derive it. But the bigger question is that as marketeers or as businesses, do we have a data mindset? Do we have our audience first mindset? And that is what can power your creative for now and the future? So it is a complementing exercise. It's not mutually exclusive. They are inclusive and complementing to each other. And that's how I see it going. But there is one fact that data can enable creativity. It's not there to demolish creativity or take control over creativity. So that's my perspective. I think from my point of view, the simple simile or metaphor I can draw is that data for me is the ingredients and creativity is the recipe. You need the right ingredients and the right recipe to come together to deliver a great dish. It's as simple as that, whether it means in terms of developing the actual campaign, whether it means actually the media usage that you put out there. And I know we were having a lot of discussions in the panel room. And I don't think there is a scenario in which you can have only one of them because then you will be either shooting in the dark without any data and relying only on your creative gut or instinct or whatever that may be. Or you may be so lost in data that it may lead you to, I guess, the discovery of America rather than coming on your route to India. So that's where I stand. Interesting. OK, so for me, the one word that beautifully sums up what data or creativity means is actually clouded as creative and as analytical as it can get. So literally, like when I would talk to my kid and I have to say cloud the one which is up at the sky. Because for him, possibly, the cloud, which actually makes more sense is which has the data which goes back into whatever he's doing on computer. So to me, it's not about data and creativity. It's how much data and how much creativity. And I also think that that depends on what life stage the brand is, what audience you're talking to. There is no one formula. And that's amazing because that's why possibly we are all in our jobs and we're getting paid because there is no formula. But that's that. I mean, I don't think there's a right or wrong answer. Couple of years back, we were talking about traditional media and new age media. Now we've stopped talking about it, right? So I think in coming years, we'll stop talking about treating them differently because data gives you insights which builds creativity, creative, drive conversation, actions, behavior, which drive data. So it's like, it's a circular economy in a way. And as the sooner that we adopt that data mindset, and that's a very difficult journey. It's not very easy, I think. Even for people who understand data, it's still not very easy to convince others who don't understand data. So it's like a very happy conversation sometimes in the room. And I'm sure all of us are going through that. But the sooner these two come together and start residing in one dashboard, that's where I think we'll all be very happy and that's the utopia right now, yes. Yes. David. Puneet, what I feel is I'm going to stand on what Udhis said, right? Data and creativity complement each other, but they should not be exclusive. So taking Udhis example again, right? Data is like an engine in a car. It is required. But how beautiful the car has been crafted from the outlook is what creativity is. So it's like they're complementing each other. So either of the two, if they're disconnected, right? You will have a lot of no's rather than yes in terms of people going for that particular car. So I think this is far more important and the marketers needs to understand that data fuels the right audiences so that you reach to the right people. But the message is from a creative. That message has to be crafted beautifully. Even if I take you to the right audiences, but your message is not crafted beautifully in the form of creative, right? Then you're losing the game because you're not generating the interest because we all believe that, you know, data is going to create the instant conversion, no. Because it totally depends on how do you resonate your product to them, right? And I see there's still a total disconnect in terms of connecting data to programmatic where dynamic creative optimization has been used, right? A same creative shown to a user again and again probably might not create an impact. Anti-analyst, you know, where Someli was talking about integrating our CDPs or customer data, first-party data, then, you know, building that bank of emotions and understanding, you know, what is critical. It's almost like, you know, I'm sitting in front of YouTube and I'm seeing a like me ad. It doesn't affect me at all, right? How beautiful the creative was, I'm not the right audience, yeah? So this is where I feel that, you know, they complement each other, but they're not exclusive. Yes, but they're both essential for any campaign. Well, I think the answer is both affirmative and negative. See, saying data and creativity are mutually exclusive is, in today's context, it's like saying, is technology, are technology and life separable? You know, the point is one necessarily governs and, you know, the other necessarily drives things, right? I think data governs everything that you do, including the creative process to a large extent today. But the actual process of creativity does have those rooms where they are not driven by data only, you know, where probably the right-brain takes over and, you know, takes it to a different level altogether. But, you know, the point remains as market-y as the biggest challenge is what is the purpose of creativity? What are you creating what for, right? And when you're looking at businesses and across categories, you do realize that the ROI-driven mindset ultimately makes you look at data as be all and end all of everything. And that starts driving then, you know, a whole lot of processes from there. So it's not an easy answer to find, you know, to be very frank. But to say that creativity as a process can exist in a silo, no, that's not possible anymore because everything is data-governed. But that brings me to the other point, which is that whilst there is complementarity and data in a sense, there is an interplay between data and creative and creative, leading to more data being created in terms of what do people respond to better and therefore, you know, how best to communicate with them further from their own birds. But there is another element to it, which is that, and Ruchika, you touched upon it, which is if you have too much data at times, it becomes very difficult to distill the, you know, the essence as such. And sometimes data in itself kind of, you know, could potentially stifle, you know, creativity or the instinct that one has. So sometimes, you know, data can kind of, you know, at times be at variance with the instinct. Have you come across such instances and what in your view, in your experiences, are the ways whereby, which can be, you know, or processes that can be used to kind of, you know, avoid the pitfalls of, you know, completely missing the, you know, the essence of what the dealer is saying. So, you know, so I don't have an immediate example to give you where at least I've personally gone through this one, but yes, overload of data is something that pretty much every marketer would put a hand up on saying that there is too much data. I mean, we were discussing this in the, you know, meeting as well on saying that the number of dashboards and none of them talking to each other itself is one of the biggest pain points of any marketer's life. I think what I have used at least, and this is only something I can share from my personal experiences, I have believed in the fact that data helps me hone my creativity. It helps me hone my gut, but that data needs to be backed up with pretty solid, you know, test control or some amount of testing because that is what has helped me in my, you know, journey as a marketer a lot. So when I, for example, use data to develop a new solar campaign that we just recently launched, we went through an extensive amount of data crunching on it, including the decision journeys, the, you know, the profile of consumers who are buying the early adopters because it's still a nascent category. We don't have established habits, you know, to kind of look at and everything. The data could have led us to a direction where it pointed us to only reason A. However, what helped us tremendously was that the team felt very strongly that every interaction that we were doing ourselves with, you know, individual consumers or users of that journey. While that X factor was important, but there was also the Y and Z, which was, you know, maybe not a stated verbally as strong a reason or a barrier and everything else. So what we decided to do was that we took a call on it to say that we will not develop one main creative. We actually developed three different creatives, addressing all three of them. And today, you know, thankfully media allows you to target and I'm not going into what TV does or what radio does or what digital does. It is just media, right? So today it is something that allows you to actually contextually place the relevant message for the audiences and that has helped us a lot. It has, you know, kind of bone fruit. It's just been a month or so, but the kind of leads and direct leads. So this is again not counting on any other data point, but you know, traffic on our website and leads that we're getting, that's kind of paid heat. It's reaffirmed the fact that all three were equally actually important to the end user. It's great that we've got three marketers from very different spaces as such altogether. So Sumeli, in your view, how would you avoid such pitfalls of over-reading the data at times and kind of missing out on the instinct that a person has? Okay, so I'll take two examples because it's always easier to talk through examples and these are the brands that you know. So one case is of Thamsa Palade, which is more strong on storytelling backed by data, but the data is obviously doing a secondary role over there, creative is what is in the driving seat. The second brand is Pride, where data is in the lead seat and creative is enabling data. So it's literally DCO, it's creative for different data. So I'll just give you a base of why we were very clear what's the role of data, what's the role of creative and therefore obviously there would be obviously heated arguments across the table, but since we are very clear what's the role of data and what's the role of creative, it's a easier journey so to speak and that's the way I try and navigate it. For Thamsa Palade, it was very clear we were coming with a new, I wouldn't say new, but a repurposed positioning which is Thamsa down to Ney said, which was coming from the core of Thamsa, then therefore Palade was the story that we wanted to see. How data helped is to figure out what story to say, who to use to tell the story, what story needs to be told where, but what was at the driving seat is the creative to tell the storytelling because it was a part of creative that got amplified by data. So we are very clear on that. Sprite on the other end, when we repurposed again, I'm not calling it reposition, it's repurposed to saying that there is heat that happens, heat as in mental heat where you are fried and you're very, very heated up in your head because of the situations that are around you and that situation can happen anything, from anything, it could be exams, it could be traffic, it could be meetings, it could be anything and everything, right? And therefore the Sprite comes as a, as a contrarian thing to the voice of heat. For this, in fact, we did work together with Boba Liay and to do a fantastic campaign together and with multiple other partners. It was very clear the signals were very important, where heat is happening and once we had identified those signals, whether it's traffic, whether it's integrating with the API, whether it's integrating through conversations and the conversation, especially when we work together on what exactly was the conversation happening and therefore push that message over there and push that content over there. So that was completely data at the driving seat and the creative then following the leader of data. So I think once we're very clear on these two, this couldn't have happened in case of thumbs up and storytelling couldn't have happened in case of Sprite because then it would have been a broadcast and nobody would have been like, both of these brands had fantastic results because H1, I think, we over-delivered. Obviously, it's not because we did great advertising. There's a lot of other factors to it, but my point is that the brand love scores clearly say that the message has reached to the right audiences and I totally agree with you that data gives a purpose to creativity. Otherwise, why are we creating, right? So I'll just kind of give an example from one of my previous assignments. This was at Magic Bricks, which is India's largest property portal. And while you have tons of examples of where data actually enables creativity and helps you in better narratives, but there are times when you really go against data as well. At times, you do take those calls for different reasons. So at Magic Bricks, in real estate, the primary audience, the target audience, always has been the man, right? It's always presumed that it's the male of the house who's going to look for property or do the purchase decisions and so on and so forth. It has always been a very masculine category to say so. And if you would see a majority of the imagery that is propagated by all the brands, you would have the man of the house and then you would have family in the background. There's a little child there, somewhere, et cetera, et cetera and so on and so forth. But the man is always a decision maker and that's how it's always presented. This was way back in 17, 18 when we were looking at our next campaign. The data would have suggested to go the same route, right? Because the data was no different. You still had 65, 70% of the searches happening from the male gender and there were other cuts of that data as well. But the creative idea on the table was one where you were putting both man and woman of the house, the couple, as the protagonist and the decision makers. So women were equal partners in taking that decision of investing in a dream home. Now, data may not have led you there, but it's the creative thought that was on the table. Collaborated with data to really see whether it's gonna make sense or you're gonna absolutely off the track and not going to be acceptable. And the decision therefore we took was to go ahead with the creative idea at that point of time, not look at the data and what data was saying and to really start that narrative in the category where you are presenting both the genders as equal partners in decision making per se, right? And so there are times when you really go beyond data or to an extent not look at what data is also telling you and look at the power of the creative idea and take that forward and execute. I think your question was precisely in terms of having lots of data and how do we manage that data, right? So what I see, there's a problem, right? Because the more touch points are required, it is not the ample amount of data. More than that, I think it is all about recency of the data as well. So, I mean, if you go to an aggregated model, for instance, you know, you have a lot of service provider who basically aggregate data from multiple third parties and they sell it to advertisers and marketers. You need to understand that, you know, too much of data is hard to analyze, yeah? And you need to look at the collection process of the data as well, because if, let's say if I go to Cart Deco once, I may not be a potential auto lover, right? This could be one of the instance where I landed up, right? But what is more important is that, you know, the aggregation model has disadvantages. Why? Because you don't have too many touch points. You only have personas which has been created with the intention of visits. And that is what's been sold into the market. What advertisers and marketers has to look at is in terms of effective CPM, not the carpet bombing on a data, right? So, internet lover, right? I think everybody nowadays is an internet lover, right? So, it can't be a global segment, right? Internet lover. Yeah, so, we are all internet lovers, right? So, I mean, the selection of the wrong data. B is the source of the data. Third is, you need to cut down and understand, you know, how these data points are basically tabloid, right? With the different touch points. My interaction, if I'm targeting somebody, let's say somebody wants to target somebody who loves food because, you know, probably that is going to come with the coke bottle, right? Because he's going to order that, right? So, he needs to look at delivery options, right? Probably a 10 minutes delivery or Zemato's or Swiggy's of the world and understand people who are consuming a lot spicy food, right? If they are ordering, let's say Tandoori, they're going to compliment that with coke as well, right? So, that is where we need to look at. So, it's not about having more because, you know, obviously, whenever I tell agencies that, you know, I have only one million co-hurt of this particular segment, they say it's too less, right? So, I'm saying that, you know, okay, you want to spend, you know, 30 rupees, right? For a CPM of 8 million data, I'm saying just spend 60 million on just 1 million data. So, that effectiveness comes out with reading the touch points on the data. So, yes, it's a problem that too much of data creates a lot of confusion and waste of budgets as well. Very well said. And therefore, the important, and that really leads me to the next aspect that we want to cover, which is, then is there a kind of a process, you know, which is in place to allow marketers to be able to dovetail data better with the creative output as such? And if there is a process, would you want to expand on it? So, I'll start with you, you know, how does data kind of, you know, feed into or inform the creative process? Firstly, I'll start with the previous question. I think there's too much to measure. But what to measure and when to measure, like, you know, even directionally is the bigger question. You know, there has been, there have been areas of last touch, first touch, CPM, CTRs, but does that really matter in the overall journey of what's happening on ground? These are indicative data sets or directive data sets. So, when it comes to measurability, what are we measuring more than the dashboards makes a ton of a difference? Now, coming back to how does data enable creativity, like you said, or how do we go through the iterative process? I'll just cite an example. In fact, before that, is there a process? Is there a process to it, or is that in itself something that is horses for courses? It kind of, you know, varies depending on the use case. So, there is no, I would say log book or there is no guide that can say this is how you measure. Where, like, you know, Sumeli said where your brand is, what your brand wants to achieve, the strategy is devised, basis that. I'll just give you an example when we were planning the Hector launch. There was nothing considered to be as an internet car. There was no internet car back in 2019. Now, if I had to analyze data and if I had gone by the industry status quo, there was no need of an internet car. Everything was still happening. Everything was partly connected. There were voice assistants, but there were no voice assistants inside the car. That was our product truth that essentially we used, you know, so that is one example where category never experienced, let's say, something that had internet and voice-enabled stuff in it. So, where would you find data for it? How would you do the product validation for it? So, that's where, you know, second-party data or category data actually helped. That in that segment in which Hector was operating, it was all masculinity. There was no humanization of technology and that's the data set that we used to enable the campaign. Actually, I don't know if you guys remember, Benedict was our brand ambassador when we launched it. It said, MG Hector, it's a human thing. So, we didn't focus on the fact that this is a masculine car, it's a power A, it's a fuel efficiency A. This is what it'll deliver. We said, this is a car that can listen to you, respond to you, talk to you like a normal human being. So, it entirely shifted how cars are perceived to be in the connected world today. They are collecting data. And now that data, I'm again, telling you the stage where the data is coming from, is enabling us, okay, which are the next set of apps that we need to choose, you know, that customers are using. Let's say Ghana inside our car is the most used app even before the maps. So, broadcast or audio is something that we are gungo about finding new partners. And that's how we even changed it in our next car, which was Aster, we had Geo7. We said, why don't give customers the choice for music? So, again, there is no method to this madness, but there may be cases where data will exist already. There may be, you know, where you are defined data to see how will it turn around. And we actually took that leap of trust in certain scenarios. So, there is no guide or there is no thumb rule that will happen. There's nothing like it. I think it is an experimentive and iterative process. You win some battles and you lose some as well. Thanks. Sumeli, what would be your take on this? Yes, I'll tell you how we work. And I think all of the companies work very differently because we are also in different life stages as a company in terms of, you know, what we are doing and what we try to achieve and the kind of data we have. So, for us, we have a lot of data. So, we do a very deep dive on social listening, social metrics, digital metrics. We run a lot of panel with you, Kanthar. So, we get a lot of data, but I think the point is not getting the data. The point is the story that you kind of tell, the patterns that you see, because for us, the insights have to be very, very deep. Every brand that we have in the portfolio is a brand that you either connect with or you don't. As simple as that. It's not just being visible. It's about the entire funnel of it, obviously, which is now no longer a funnel. It's like a jigsaw puzzle with the awareness purchase, sorry, consideration and purchase, but the point is that we try and look for patterns. So, while we do post-campaign analysis, but they're only post-campaign analysis. Brand analysis largely looks at patterns that are changing, so which is not done at a very short interval of time, because that's very important for us. We rarely do moment marketing. I mean, it may or may not happen, but it's not a big part of our existence. Viral, if it happens, great, but I think what needs to happen is it needs to move the brand metrics. So the data that kind of moves the brand metrics, and obviously it's a nice theory to give right now. It's not a very easy thing to actually do and look at that, but that is what we try and do, because internally, also, it's the same thing. It's almost like a pitch process, right? Because every company has a particular budget assigned to it at a portfolio level, and everybody who is internally there and doesn't matter whether you're in category, in media or whatever, you're literally trying to build a story to figure out how much budget your brand, your activity, your campaign can have. So it's about looking the right metrics and seeing the right patterns, and therefore, are you able to build that story? I think that's more important to me, and that's the way we kind of operate, rather than saying that, okay, let's just do an analysis and see what happens. And I believe that's how largely all of us operate. I'm just trying to simplify it, but patterns over just data analysis is the way we kind of go with. A blip is great. We should notify it, and we should bank it, but maybe not take a decision-based. That's how we try and operate. Great. Ruchika, your views on this? I actually completely agree with what Sumeli is talking about. I've been a researcher before being a marketer. I am a very, very strong proponent of the fact that blips are not the decision points, unless and until you see it becoming a part of the main data trend itself. But trending is by far the biggest learning and biggest thing to cash in on, and that only comes with a constant eye on data, rather than just a one in this thing. So what even we try and do is that when we are coming up with a new campaign or a new initiative that is being undertaken, that is the time to sit and pause and just look at the trends and look at the data points that you have so far and then take calls on basis of that. But other than that, having a set process around it, not really. The praise, Prasoon. I think, yes, we need to understand the current ecosystem as well, to compliment the two processes of data versus creativity. The way we operate right now, it is brand decides what message they need to send. So you can't have audiences in hand before to send that message. So first the brand decide, like so many of you said that, sprites and animals too, let's say for instance, heat or anything. So after that, once that message has been decided by the brand, then we look out for those areas or geographies where you have a lot of heat and probably this is where we need to push. That is where the data is going to come in. We are far away changing those sort of processes where because TV, we're not talking about here because TV, if you have to rotate a lot of creativity, it's a lot of money. When you talk about digital, it's possible. Because once you, the biggest problem is, we need to understand all these things are in silos. You have a market research company which brings the sentiments to you. The second thing is that basis that the creative agency creates a product because they have a brand message to convey to the consumers. Then you look out for agencies who can basically send that message to the right people. The time, this is all been, this all can be done within one roof. Then I think even this is going to be possible. Which is, you have a research analytics available, you have the audience available and you have a right message going out. That is where you can think about in fact, evangelizing on creatives as well. I think just building a little bit on Tabriz's point and expanding this a little bit. See, there are, and he was right, there are zillions of data points and there are different sources of data. And for a marketer to look at all those sources and all those data points coming and then putting all of this together and then making sense of it and then letting it govern the creative process, et cetera, et cetera, is, I think it's a tough ask to begin with, right? And so, I mean, let's take the example of Just Dial. We have about 700,000 unique users on a daily basis on the platform. That itself is humongous data, right? Then you have social media. Then you have third-party data. Then you have, there are multiple data points that you're looking at and then you're trying to find a common thread across all of this to really be able to take a decision. I think we also need to work and I think this is work in progress pretty much and I think people like Barbal and all are helping a lot in the sense that you got to bringing all these data points together and you have to have that one linear kind of a method of looking at all of them, removing duplications out of this and really looking at what is it that you can really read as a trend. Because as she rightly said, mostly you end up reading trend because the amount of data is so vast that getting into every small segment of that may or may not be fruitful as well at the end of the day, right? So broad trends coming out of all of this but this remains a challenge and we have to wait through this challenge and therefore I think some part of creativity process. Some part of creativity process also kind of is not as influenced by data because of all these problems that are there, right? That you think of a message fast then you start working backwards and so on and so forth, the point that he was making. Though things are changing and there's a lot more and more data now starting to govern the kind of campaigns you would wish to do or the narratives that you would want to have or the messages that you want to give. A lot of this is now data driven but then I don't think it's very coherent. I think we need to have that correction process pre and post-campaign, right? Because if we don't, I mean, taking about we're just discussing offline, right? If you don't have a correct measurement process you can't measure it. Very true. If you don't have a correct sentiment collection process you can't send the right message. Absolutely. So those are really very probabilistic or panel based analysis right now if you go to market research companies to understand they collect a sample data set. We need to move to the real customers, right? And that is where the collaboration of first-party data versus second-party data rather than going out of the wall gardens or data aggregators, that has to evolve from the marketer perspective. They should be ready to, so maybe we'll have one information, people buying Sprite or Coke, right? But what are their intents? What are their behaviors? Where they're spending time, right? I mean, it's going to solve even the problem of campaign allocation as well, right? Where do I reach my customer? Which platform should I choose? You know, the budget allocation becomes a very easy process then that, you know, my sort of people are available, let's say, on Facebook. That should be the medium where I should spend. Rather than Facebook putting a compulsion saying that, you know, you should spend more with me. Right. So I think this pre and post campaign analysis on a real deterministic first-party data set is what is required. Absolutely. I agree. And there is another element to it, which is, you know, when we are looking at either an effectiveness measurement of the campaign or, you know, developing the campaign and informing it basis data by deciphering patterns that are really defining that particular consumer cohort. That has a human element clearly that seems to be kind of, you know, coming out. But at the same time, we are also in a world where companies like bubble AI are interpreting patterns and behaviors in themselves. And how do you see the future as such as this kind of, you know, evolves this new world of, you know, trained supervised learning or unsupervised learning gradually and the algorithms that are being created, which are kind of, you know, able to decipher patterns. What is your view as such and whether that in itself is something that is going to start having a play in the creative development process or more than the creative development process, I would also say the messages that need to be delivered to the customer at, you know, at various stages of his or her journey. How do you see that, Tabrez? Well, it's like I said that, you know, the data touch points today cannot be a cohort which is created on a request, right? It should be more predictive. Backed up by AI and ML to understand that, you know, this is what the right audience for you. We are still not moved from those ready-made cohorts or customized cohort where, you know, we combine, we filter, then we, you know, give it to you guys to, you know, advertise upon and then we are happy to see a 0.5% CTR or 1% CTR, right? I mean, Udett has very good example that, you know, they've been able to, you know, launch cars without running TV commercials. Yeah? So the point is this, you know, is something where, you know, they have a trust on data because they've been adapting technology to measure that data probably, you know, through Adobe's or, you know, different cloud management. So similarly, what we feel is that, you know, understanding patterns of the users is quite critical, right? It's not that difficult because now they broadcast patterns, right? They show intense. And the bubble AI being a conversation platform, see, we need to even push right creative to the right conversation or context as well. That is where, you know, the success of the keyboard is. So if I'm saying that I'm happy and I'm giving a very good creative or emoticon of, you know, probably an happy person or that particular emoji or a big emoji because this is how I do my prediction, right? Rather than suggesting a word, I'm suggesting a creative over there, right? And Gen Zs and millennials, they are far more expressive in terms of using a thumbs up. Instead of writing, I'm all right, right? So by virtue of which, we understand a lot of things from the consumer that, you know, hey, this is where they're interested. This is what they're going to buy. They broadcast a lot of intent, you know, going out for coffee, buying a phone or anything. So we basically take this entire information to our CDP. We create different touch points of the users. We understand their patterns not by just one visit. We'll see there's a user which is constantly on, let's say, a food tech site or application. We see that constantly, whenever he goes over there, he's only ordering South Indian food. Then I build the affinity. Then probably it helps me in terms of, you know, giving him the right content because I know my customer very well. Now, this information on a secured way, right, can be given to an advertiser as well. Who can utilize it? I mean, even Google does it, everybody does it because this is all consented data. What I see and that is where, you know, brands are integrating with us to reach through a very different creative medium is what we call like CMM or Conversation Media Marketing. Somalia has done that, you know, where we can have a surprise sort of creative which can be created and tag certain words to it. So if somebody says thirsty, cold drink or anything, I can recommend a brand sticker over there that, you know, you can push that. I mean, this was not possible. You can't advertise on WhatsApp or Facebook Messenger, but you know, your brand can be pushed to multiple people at a given point of time and the sort of sharing we have seen is huge. So I think this is where everybody needs to change where, you know, we had to move out of the aggregation model and combine more data sets so that, you know, the creativity, data, all things combined, we are able to read the customer journey and then curate our campaign accordingly. So do you see a future where the emotional intelligence of human beings and their ability to interpret data and connect with it from a human story standpoint will, in a sense, get added to or, you know, subtracted by machine learning? Yeah, absolutely. Absolutely, that's what... Absolutely, I mean, we do it. We have another product which is called CTS where, you know, we've been integrating, you know, our creatives within the conversation not chatbots as well. You know, just to give more emotional impact to the conversation. You know, chatbot writing, I'll be back and there's a photograph of customer service rep or, you know, there's caricatures and a very interesting, I'll be back, right? Or something like that. You know, the customer feel that he's been listened, right? So, yes, you can change the emotions as well. The MI, AI, I mean, ML and AI has this entire fantastic understanding of people's emotions and predicted, it's been used everywhere. Scary. So, we are at four minutes, just got four minutes left. So, any final comments on this particular aspect? Otherwise, maybe we can also take in a few audience questions as well? I just wanted to make one small point. You know, a contrarier point to the next, you know, towards the way you're saying. See, yes, data, you know, if you ask any CMO, any market here, which is the religion you follow, everyone will say we follow data. You know, that's the only religion we have. But at the same point of time, you know, you would ask data is fine when it comes to, you know, understanding consumers, understanding what works, what doesn't work, et cetera, et cetera. He said it's gonna give you content, right? But content as information versus content as narrative or two different things altogether, right? That's one point. Content and context. Okay. The second point is, you know, just ask. You know, Amul comes to you every week. With a new story, right? What data are they looking at? While, you know, kind of crafting that, right? And they're connecting with you at some level. At emotional level as well, right? You know, when probably PD-Lite did, you know, that famous campaign, right? What data they were looking at, right? So at some point of time, at some level, you know, creativity as a process does become kind of independent of data. But yes, you cannot deny the importance of data. But in future, if you say data is going to make everything and do everything, then that's a little scary. Thanks. I'm gonna just add a provocation over here. So you do have, I mean, right now I'm saying it's today. I don't know what will happen tomorrow. None of us can predict. But today you do have successful AI newsreader, but you don't have a successful AI comedian. So that's the status today. I don't know what will happen tomorrow. Maybe you'll have. Very well summarized, actually. So thanks a lot for putting it that way. Can we open this up for audience questions? And there are quite a few hands that are going up, as I see. So is there someone who can pass the mics around, gentlemen there? We will allow just one question. I think in the interest of time, we are running slightly off the schedule. Can I add one more provocation? Okay, we're talking in terms of marketing, the ultimate objective of any marketer is branding and performance. For an agency who's communicating, their challenge is positioning and creativity. We have on the other hand data, which helps you in terms of identifying the need gaps, identifying the segment, targeting the specific segments, and then talking in terms of what are the communication needs. Having identified the communication needs, you're talking about rational, emotional, which brings in neuroscience as well as behavioral economics. And then we are, let's talk about complications which arise in the US market, where they have no credibility as far as advertising is concerned. People don't believe it. It's only used as a reminder media. And third thing is the attention span within seven seconds. Can we put everything together and put a process in place? That is the holy grail, isn't it? I will, I will, that was my response to my mission. So, anyone, any thoughts on this? My view on this is that, and as it has been said by multiple panel members, is that there are no silver bullets here. It depends on the situation, depends on the brand, its context, and therefore what is it that is most apt for the brand at the, you know, and there could be varying situations also. You're looking to build the brand. You're looking to kind of, you know, get quick sales. So, those situations are the ones that you're kind of tapping into it. I'll add IMC to that. Sorry? Multiple audiences, multiple requirements, multiple communication. Absolutely. IMC into it. Yeah. So, and then they're being done at scale in 24-7. So, that's, yeah. And country-wise preferences, cross-cultural preferences. It is possible. And sir, you know, I mean, you made a point about decreasing attention spans, right? And so, for a consumer who has only got five seconds to take a decision, right? You know, how much of creativity you want to really push to the consumer, right? So, you have to also take all those things into account. So, yes, data also will play a very, very critical role, but today's topic was very interesting. Yeah. Sorry? Data does not give you creativity. It doesn't. It doesn't. It doesn't. It doesn't. That's something that is established. It is, it's something that informs. So, thanks a lot. It's been a very wonderful discussion. Thank you very much. All of you. Thank you.