 Well, ladies and gentlemen, now with this, it is time for me to move on to our next session. A cluttered ecosystem, a deluge of data, multiple touch points, are few of the challenges for a marketer for today. Well, in this scenario, how can the data be leveraged to build the brand trust? Well, joining us now, we have with us Deepak Khurana, co-founder and CEO we serve in conversation with Rohel Amin, the Senior Editor, Exchange for Media Group in a fireside chat on the topic, data moves the needle from mass advertising to mass personalization. But with this, I'm going to pass on the live bait into our gentlemen out here and also to all the ones who are viewing us. Please do drop it in your questions in the chat box. We will take it up at the end of the session if time allows. So, Rohel, a mammoth task ahead of you, we've got Deepak with us, so I leave the stage screen to both of you. Thank you and welcome. Thank you, Bhavana. And it's been a great conversation so far, a great power packed speaker lineup we have. And thank you, Mr. Khurana, for joining us on this important fireside chat, where the focus is data. I mean, so much is written and spoken about data that it needs no further introduction. In fact, it won't be wrong to say that this is the data economy we are living in. And founders and co-founders, the new businesses, they're not driven, they are definitely data driven. So which brings me to this first question. So we have heard and spoken about how data helps businesses reach the mass scale. But here the question is also, how do you make it personalized on a mass level when the personalization is a one-on-one experience so far traditionally spoken. So give me a sense of how can data become a mass personalized, you know, an effective tool that businesses can use, marketers can use. Okay. First of all, thanks to the A4M team and thanks Rohel for having me for this discussion. Coming to your point about how data helps with mass personalization, so largely, if you probably try to think at it, look at this piece from a marketer's objective, and if you were to probably dial back a few years, you would say that look, from a marketing perspective, we've gone through a phase where it was about mass advertising. And obviously, you know, at that point of time, TV print delivered that objective, correct? Increasingly and now what has happened is with the way digital has participated in our life or we've participating in the digital age, okay? What is happening is that consumers are developing different tastes. Consumers are, you could probably, you know, probably say that listen an automobile car manufacturer like Maruti could get away with two or three models back in 2000, okay? Fast-tracked that to 2022, you know, I don't even know the count of models they have, yeah? So and when you go into, you know, similarly, when you go into an apparel store, you go into any particular area, the amount of choices we have is empty, correct? So what does all of this really mean? It basically means that I think by and large, we recognize that consumers are different, okay? There are variety of consumers. Consumers have taken to a variety of different tastes and like, you know, fondness. So if the consumers are creating something, which I would say that there are many micro clusters of consumers today, you can't really probably say that, you know, what there is one type of customer, okay? There are so many, so many different customer types. Now, if there are so many different customer types, okay, as marketers and that's indication, you know, you know, clearly marketers themselves have produced products which cater to different target groups, right? Okay? So in many ways, businesses are thinking about mass personalization, they're thinking about not a single product, but thinking about multi-products for consumers. In the same manner, marketing is also now moving in that direction and really talking about saying that, listen, you know, let's do mass personalization or let's identify commonality between certain groups of customers, which are relevant for this product of the brand and then try to weave a marketing strategy around that cluster. So I would say that when you're thinking personalization and when you're trying to say personalization, does personalization mean only one-to-one personalization, okay? Not necessarily, you know, in a context where I, as a consumer, I am on the brand's website and I am personally engaging on the brand store. Maybe there is an opportunity to do personalization there, okay? But the moment when I'm not in a brand's personal environment and I'm probably on Facebook or I'm probably on Hotstar or I'm probably on any other app, right? Okay, at that point, brand is looking at saying that, look, I don't need to know this person, but can I probably find a cluster of people who are similar, okay? And data helps me identify certain clusters so that I can make my marketing efficient. Absolutely, I think finding those clusters becomes the core point of all this targeting. Absolutely. So Mr. Karana, we have also seen that content marketing has become crucial for all brands over the years especially. Give me a sense of how can brands ensure mass personalization effectively in the context of creative and content. Also, I want to request you to share a few examples of we so how they have helped brand tell this story with the content and the creative part of it entirely. Got it. So let me break, let me answer the first part out here that you spoke about content marketing and you spoke about personalization since the topic started about, the whole discussion started about mass personalization. Obviously, we are talking about content marketing, influencer marketing, which has really taken off, okay? Now, the other commonality and the interesting part about influencer marketing or content marketing is today what has happened is that what are influencers? Influencers are nothing but a set of people or a particular individual who resonates with a certain cluster of people, correct? Okay. So potentially, say assume I follow millions someone's insta page, okay? And probably, I'm enthusiastic and I'm fond of fitness so probably that is the reason I follow it. So in many ways, here is an example where there is a persona out there which has a following of some form which is having a commonality of interest, correct? So if a brand believes that look, they want to drive a message to people who are enthusiastic about fitness and they want to do some content marketing around them, who is the best anchor, okay? Or who is the best anchor to take that narrative to the customers out there? So they would probably go ahead and choose a particular influencer of that form which resonates with that purpose itself and try to convey the story via that anchor, right? So now, when you're thinking about these influencers, there are so many different influencers which are enabling content marketing today, right? And you take any topic, whether it is food, whether it is finance, whether it is travel, whether it is gadgets, you name it or whether it is beauty, you have different anchors. It's no more one celebrity or two celebrity giving out your narrative, okay? But now today, you're also living in a world where there are enough people who can take your story out or there are enough content creators who now have their own own own followings, which people can leverage or brands can leverage. Right. While we're on this topic of data, there's another part, one is effective targeting and one is delivering and getting that ROI and reducing that spillage. How can market use that issue? Yes, how can market use that issue? Got it. I got your... How can you ensure, yeah. Yeah, I probably wanted to even address the second question, the follow-up point about some examples, how we serve as Ghana and help certain brands do data-driven marketing, okay? And your other point, which last point was about really that how can brands really benefit or how is marketing become efficient for them leveraging data? Right. So I'll answer that for you. So basically, we serve as a platform where we have deterministic audience data and we leverage that deterministic audience data to create audience clusters for brands, yeah? And we cater to various sectors, whether it is FMCG, whether it is BFSI, retail, e-commerce, auto, consumer durables, you name it. We've created different kinds of audience packages, which can resonate for these industry verticals, okay? I'll give you a couple of examples out here to kind of probably make a much sharper sense out of it, yeah? We recently ran a campaign for a leading brand like PhonePay and PhonePay was clearly looking at general insurance. So they were really looking out for consumers who would be interested in general insurance, yeah? They were looking out for people who are likely to go in for auto insurance, you know, whether it is a two-wheeler or a four-wheeler per se. So they really wanted to reach out to people who are possible car owners or two-wheeler owners, right? So that is the problem statement out here. Now, what V-Serve did was V-Serve has deterministic data on consumers where we are able to profile users that these are salaried employees above a particular income level. These are people who have taken a car loan. We have an understanding that, okay, this is the value of their car loan, okay? And this is the recency of their car loan, okay? So when we tie in all this together, we are able to create an audience cluster, okay? And then we are able to create this audience cluster and help the brand reach out to these customers on any platform, okay? So a brand could come and say that, look, we want to target this audience cluster on Facebook or we want to target this audience cluster on YouTube or we want to target this audience cluster on any app which the consumer is browsing, you know? So that's really how we bring together audience and platforms so that advertisers are able to reach their target audience. Now, this is a case where I took an example of a brand, you know, a fintech brand, a leading fintech brand like PhonePay. Similarly, I'll give you another example from a category like FMCG, okay? So Epigamia, you know, was really looking out for people who are having interest, who are conscious when it comes to food habits and also have a significant amount of interest when it comes to fitness, you know? Their research guided them that, look, this is the kind of TG which resonates with Epigamia. So Visa, again, leveraged the authentic audience data platform which it has and from the platform we called out users, you know, who are into fitness, okay, who go ahead and buy food online, buy grocery online and this is how we ended up creating a relevant audience cluster for them and then this audience cluster again was leveraged on the preferred media channel of the brand. So that's really how we try to achieve, you know, a superior targeting for them. In another example, another example which is because when it comes to audience data, we are able to leverage audience data whether it is for a brand campaign or whether it is a performance campaign, you know? In a performance marketing campaign, MaxLife Insurance came to us with a problem statement that, look, they really wanted people who would be interested in life insurance products and their biggest problem statement was the leads which they were generating, okay? For them, a quality lead means someone who has an income of 5 lakh plus, okay, and is also a graduate. These are two essential criterias for them. So using similarly our audience cohorts, we were able to do significant amount of lead generation for them, okay? And out of the 100 leads we were giving them, 42% of them qualified as quality leads and the brand had a KPI that, look, whatever leads we generate, whatever is the customer acquisition cost, our minimum threshold should be at least 40% of quality leads, you know? So this is how we were able to then, you know, prove to the brand that leveraging data, we are pouring in quality leads to them. Quality leads to them means, see, if there is junk data going to them, it means it puts a load on the call center, it adds up to the cost of reaching out to the customer, it's an overhead to manage, right? You know? So through the process, we were able to give them quality leads and hence, their subsequent costs were also in check. Yeah, these are some of the ways, yeah, go ahead. So while you're talking about building those effective data clusters, you know, it's also reducing spillage of course, the cost, but give me a sense of traditionally how far is the adoption of these clusters in the market, give me a sense of that also, also what goes on for a lot of getting questions already, you know, on this conversation. Someone asking that, how do you ensure that these effective clusters are built? What goes into it? A little bit of that, you know, how is research approach different from the rest of the players in the same domain? No, interesting. So basically, you know, so if you look at, let's say that, you know, from when you're talking about data-driven marketing, okay, you know, when you're talking about data-driven marketing, today, if you look at the digital landscape, okay, in the first phase, and I want to probably just say this, that data-driven marketing is not a new phenomena, okay, because digital is about data right from the very beginning. It's just, and obviously in the first wave, you know, large players like Google and Facebook, okay, because, you know, if you look at the whole digital adoption, yeah, the way things have evolved in the advertising world or even in the consumer space world, okay, you had large platforms, you had few platforms who had the reach, consumers were spending significant amount of time with those platforms, and hence those platforms had the advantage of consumer insights or consumer data, fair enough, yeah. Overtime what has happened is that this, you and I are not just on a Google or a Facebook, correct? Okay, we are going and spending time on OTT platforms today, if we want to take a personal loan, we are on a personal loan app, right, tomorrow if we are looking at, you know, buying food from Swiggy, so we are on another app, so in many ways, the consumer is leaving breadcrumbs, okay, of their deterministic data at multiple places, fair enough, are you getting the flow there? What V-Serve does is that the V-Serve DMP, you know, goes ahead and partners with such organizations, okay, where we have deterministic understanding of consumers, these are platforms who have their first party data, partner with us, and we are able to then build profiles, okay, from a variety of partners, which we call deterministic audience profiles, and that's how we are able to create a cross-tab, okay, of a relevant audience cluster, all right, okay, and then leverage it from a marketing perspective. Absolutely, absolutely, I think, so right, I think you hop on from one platform to another and you leave your digital footprint, of course, and that's how today's, you know, audiences, you know, there's also this discussion of AI, a big massive thing happening in that space. If I point out to an recent industry report that has said that customer experience and innovation in the AI is putting market years under pressure. Now, how far is this true? I mean, you tell, what are your thoughts on it? Is it happening? Is the AI conversation becoming so big that stressing out market years? No, I don't think, I don't think anyone is getting stressed out there. I feel that it's a great time for a marketer, for people like us, for the entire ecosystem because what is happening is that we are all pushing boundaries and trying to bring in more and more technology and efficiencies into every part of our lives, right? Okay, and obviously these are tools. When we spoke about cloud computing or when we are speaking about AI, when we are speaking about data, okay, these are nothing but tools or tools which are available to the marketer, whether it is the marketer themselves building it out or whether there are partners like us who provide an end to end stack to them. So I don't in the first place believe that someone needs to stress out there. Yes, it's a great time where the whole ecosystem is participating very actively and such efficiency when it is brought together and executed well, okay? Finally goes ahead and says that all of this put together is helping a marketer or a business generator, business outcome. So I think that there is a need, I would just probably say that the good part is that today maybe some people are under an artificial pressure to do things very quickly, okay? But I would out of time and obviously we are also in an ecosystem where quality talent is limited, okay? So when you're trying to manage your resources and capital is also a finite thing finally for every organization. So there are those levers which have to all fall in place. Some organizations may have the capital but not the resources, some organizations may have the know how but not the resources to really scale things up. Absolutely, absolutely. So here's another part of it, I mean we all most of us have been touching this conversation that how data ensures a better customer engagement across platforms. Much has been again written and spoken on this but given that you are very, the skin in the game is more deeper here. If we look at the recent couple of years and how customers are behaving, looking at data, how marketers are looking at data, what are your insights that you have gathered which you could share with our listeners here? See, I think if I got your question right, A, in the first place I think businesses, I would probably say that like from a visa perspective, today our experience in the journey has been that marketers have been working with us to exploit the opportunity of alternate data which can be leveraged for targeting. So that's, in many ways we are like a category creator for alternate data in the Indian market. So we've basically, we've seen across categories how the kind of FAQs we receive from marketers are things about okay, tell us how the segments are created, tell us the authenticity of these segments, tell us how you will deploy it, tell us how we can measure the business outcome once we go ahead and leverage these segments. And then a variety of our partners are able to experience the campaign outcomes for them to really see proof in the pudding. So that's one use case out there. Talking about data from a customer engagement perspective, there again marketers, what is happening is that marketers themselves are gradually building first party data at their end. And obviously for businesses which are pure digital, those businesses from day zero have customer data and customer is going to their online store, putting things in the cart, making a purchase, returning the order, responding to an offer. So all those events marketers are capturing in order to build a better understanding of the consumer. So all of that understanding as they gradually develop and they are able to then run internal campaigns on their own customers okay, which in turn provides them a guidance of what is working, what is not working. Yeah, so they themselves, so every organization is going through that learning curve and many organizations, I would say that you could say there are some organizations who've gotten the scale, who've gotten the understanding and who've gotten the whole piece right. But obviously, I would still say that it's still very early, very early, there is still because businesses are evolving, consumers are evolving. So I think, but in that evolution, the good news is that marketers and platforms like us have started to understand how to leverage data. Right. So I have two more questions before I take up some audience questions as well. You know, digital is growing in a very big way, the recent report that we also released, you know, that AVEX is expected to grow over 30% this year. So I want to get your thoughts on digital overtaking print as the second largest ad spend category and eventually taking over TV. Your thoughts on this, how do you see this happening again? I think that, you know, I think the way I look at it personally is that, you know, the consumer is spending more time on those digital platforms. Okay. So in many ways, the ecosystem is doing a catch up. Okay, we all, you know, at the end of the day, we all follow the consumer. Right. And if the data is giving us a guidance that consumers are spending this proportionate amount of their media consumption time, okay, on digital, you know, hence for those reasons, you know, the ad dollars are going to shift towards digital. Okay. So I think, you know, as far as India is concerned, you know, we would look at India holistically and we would say India is Bharat 1, Bharat 2 or Bharat 3. Correct. And all these trends would, when it comes to digital adoption over print TV or TV adoption over digital, you know, all of this is like a fairly heterogeneous and operates at, you know, different scale in different parts of the country. Right. So if, you know, so I don't think, I think the good part is, I would say that clearly the good news is that digital at least is now at scale, significant amount of scale. Okay, whether it is video consumption, whether it is content consumption. Okay. It's at a massive scale right now. And obviously, if people want to capitalize on that, clearly, you know, people are finding ways in which how digital can deliver to their marketing objectives. TV will continue to have, I would say that, you know, TV continues to play a good role, an important role and will continue to play an important role. I think from a media perspective, I just probably feel that, you know, TV will be a strong participant in the ad dollars and obviously TV and digital would probably be, you know, going head to head when it comes to split of ad dollars. Absolutely. So which also, you know, while there is a lot of growth and we know that digital is growing and gonna grow further, but the next level of growth is what will fuel that growth in your view, you know, what are the particular trends that would fuel that growth? See, I think, see, already there are a lot of existing trends at play, you know, so when you look at digital, obviously, the way the payment ecosystem, the digital payment ecosystem has expanded in the country, the content consumption, the smartphone devices, there are lots of macro trends right now at play, lots and lots of macro trends at play. Okay, so all of this cumulatively, you know, is a driving force. So I think already we, it's a very, you know, when you're looking at consumer habits three, four years back to, you know, when you compare the consumer habits three, four years back to 2022, you know, we already talking like significant amount of shifts, right? You know, you're talking about OTT consumption, you know, when it comes to long format content consumption, that's gone through the roof, you know, when you look at even sectors like education, that option of education online, again, is a huge shift in the consumer behavior, right? Okay, so there are, there are many such examples out there, you know, where we are talking that many of the, many of the essential discretionary or entertainment-led needs of customers or shopping, you know, are gradually moving in the digital world. So as all these macro trends are at play, okay, I think we are now at a place where what do you say that we are in a very, very hyper growth stage. Right, right, great. So I won't bring in a couple of audience questions, I'm getting a lot of requests. The first one is from Nitin T and he's asking how much of this growth is fueled by a small town and challenges when targeting this audience, the Bharat 1, Bharat 2 audience? See, I think if I could understand the, you know, understand the point, I think what the question is really about that, is there a challenge reaching to Bharat 1, Bharat 2? Is that the question? How much of that is fueling the already in the setup? How much of that Bharat is fueling the growth of the next phase? I think clearly, clearly when you talk about digital adoption, we are talking about digital adoption, like whether it is the metros or Bharat 1, Bharat 2, Bharat 3 everywhere, right? Okay, there is massive digital adoption happening out there. We ourselves, as a platform, have profiles for over 550 million users, you know, so a large part of our user base is representing Bharat 2 and Bharat 3. Yeah, so I don't think like when you look at even payment adoption in the country, yeah, we are really talking about, you know, payment adoption happening across India, right? Or when you're looking at e-commerce adoption, when you talk about, you know, D2C businesses, okay, who are selling things to consumers, whether they are in the fashion space, beauty space, or whether it's an e-commerce portal, all of them are getting that both because finally, see, digital is a big equalizer. Let's see that, right? Digital is a big equalizer. And obviously, you know, you could probably say that, you know, when you're talking about the population in India, there is still a handful of people who live in metros. So clearly, the growth is going to come from where the numbers are. Okay, great. Well, I have one final question, which is, you know, the name is not given, you know, each, you know, you witness data trends, data is so fluid, you know, the trends are also fluid. What is the shelf life of a data point, you know, in terms of capitalizing on that trend, according to you, is there something like that in your view? I think you would classify data into different types of data. There could be data points which are perishable, highly perishable. There could be certain data points which could have a much longer shelf life. Okay. So you would say that, okay, fine, you know, you know, finally, from a marketer perspective, someone looks at the demographic profile of a user, someone looks at the life stage of that user, and then someone looks at their shopping behavior, correct? Okay. So there are some of these pieces out there. Yeah. So when you're looking at if I'm, let's put it this way, if I'm an insurance company, and I want to target people who are graduates with an income of 5 lakh about, correct? So anyone who's in that bracket is relevant to me, right? Okay. So anyone which is an ed tech player, if Bayjus is an ed tech player, and they want to target parents, so then they're really looking at a mix of demo profile, then they want the right affluence profile, and they also want to know whether, you know, these people, this person out there is digitally savvy to make online transactions or not. Right. So I would say that whenever we try to look at data, we just have to look at the context and say that, you know, whether I'm leveraging perishable data or whether I'm leveraging some data points, which have a longer shelf life. Right. Absolutely. I think there's a lot that lies, you know, in this conversation. But however, we are short on time. So I have to really thank you for taking out time and sharing those deep insights. And of course, the small screen is the place where the big data is coming from, and it will come keep coming. But thank you so much for joining us on this fireside chat. Thank you, Mr. Koran. Thank you so much. Yeah. Thank you. And thank you. Thank you for having me. Yeah. Bye.