 of the stage, Mr. Natharaj Krishnamurti, Chief of Strategy and Anarchicals Officer of Madison Media, who is going to be talking about the new perspectives in media planning. Let's give a huge round of applause as Mr. Krishnamurti joined us on the stage. Okay, good. First of all, it's a privilege for me to be addressing such a new audience. What we'll be talking about today is how, together, we'll be addressing a 180-trillion dollar opportunity that exists in front of us and how we can be a part of it. So what's the privilege that I'm talking about? Actually, that's a private consumption that happens in India. So collectively, in marketing, consumers are spending 180-trillion rupees every year. And that has actually grown up quite significantly. Over the last 10 years, it has grown up by 2.2 million times. It has grown thus. Collectively, what we can do is we'll be able to address this opportunity. And that's what the bulk of my presentation is all about. So I mean consumption in India on an average is around 1.6 lakhs. And now it has grown up to 3.76 lakhs on an average per household, per year. And that's because our total private consumption in India is 180-trillion and we have 319-million households, that's what the numbers are. Apart from that such a huge size of consumption that we all participate in, we also need to understand that we are one of the largest numbers in terms of the number of households. We are twice as big as the largest economy, which is USA. Now, another big opportunity we have as marketers is most of the product categories in India are underrated-rated. So I've just given a representation of categories here, but most of them are underrated-rated. And that means there's a huge room for us to own. Now, all this is very gross here. It's a huge opportunity. You also need to understand the challenge that you're facing. Well, I'm one of the biggest challenge for us is inequality. So while India is growing in its appearance, there's also a huge amount of inequality. By inequality, what I mean is this is a data released by the World Bank. What it says is the top 1% of the population do twice the rate of the overall average. So the overall average due at 150%, the top 1%, the likes of companies and other companies, we have 200% in terms of their income. Unfortunately, the bottom 40% they can only get from each side. So what this means is our appearance on an average is going up very high, but it is fairly unequal. But overall as a society we have made some improvement. That's not a problem for marketers only to address, except that when we increase the overall consumption, I'm sure, you know, with that when the night goes up all boats rise and therefore all of us hopefully they grow up. And India will become a much better society. But as we proceed with, that's the biggest problem that we have. Now what that means is that it is still very skewed consumption. What is the skewed consumption? I'm talking about, okay, I said that 390 million households as per estimates, 3% of the households actually continue to 13% of the total consumption that happens. So just 3% is 13%. And unfortunately there's no problem also that nearly a quarter of the households, they contribute only to 10% of the total consumption that's for the struggles. So basically this is a BCG model where we have a life of credit as far as next billion and struggles or as co-hosts basically on their income and their consumption profile. And this clearly shows we have such a skewed consumption. Not only most economists' consumption will be skewed, but not to the extent that we see in India. So what we at Madison we did is we took this consumption for votes and we moved the struggles because struggles are those who are technically below the poverty line and therefore they will not be participating much in the consumption and we pocketed into 3 buckets. So you have other income who are roughly 3% of the households which is 2.5 million. They contribute 40 trillion of consumption. Then you have mid income who are 65 million households which is 25% and finally we have no income, not 44 households which is 60% of the total. So these are important amounts. So 15% who are up and income and then we have 25% from mid income and 60% who actually what we are making as the low income and we have to get the struggles out for these other assets. What is the use of all of this is when you are planning your marketing strategy this could be one clear path to write your marketing strategy for example. What we use in those category in which the integration exists. 60% basically is a game of share game and you will be talking to a mid-term low income and that's why we fought. There are those where you need to type in it or where for example if 2 with us is already 43% penetrated. So the best way of growth will happen when they target the low income people and then you have certain categories where the penetration is only less than 10% in which you have a huge room to grow within the upper income category. This is one way to look at how we can use it on board. The other one is within the branch what you need to do is if you calculate the average this has just put some set of so branch and I have calculated the price for branch and then you can see some branch and the average price per gram of this selected sample is 0.4. Some of them are operating at a price which is much lower than the category and some are operating above the category. So those who operate within the category branch will be taking the those who are operating lower than the category will be going after the lower income and this is one way to use the cohorts. So till now it was all very easy and we would say that cohort targeting by income group makes a lot of sense but that was the academic right now because we do not have a right mechanism for targeting consumption by cohorts. And why do I say that one example that we can talk of is in terms of NCCS classification. We all know NCCS classification is a cross tab of the of the rural and the education level of the chief waiter and let me just illustrate that. So here is Akhen and Ramesh. This occupation is a shopkeeper. He owns around 25 to 30 thousand per month. So by income that cohort that I discussed in terms of consumption he will be your next billion. Up towards the lower end of the consumption cohort. But when I do that in my NCCS classification he is SSC fast and he has since Europe. So not many of these people are not on the portal and a shopkeeper would be having it. He becomes NCCS-A which is at the higher and not the straight up. So here is a person if I go by consumption cohort he is at the lower end. I am not saying he is not going to consume. He is not a traveler. He will be consuming. But when I look at it from the NCCS-A point of view he is at the higher end of the social strata that we define. That is not going to be of much help to marketers. So what we did is we devised how to be agile. So this is more not segmentation from an attitude and point of view. It is more from how to be agile better in media and we devised three roots to it. One is of frames. And again I am making action over pricing how we can use of frames from the media absorption itself. Then it is high stage and third is micro geographies. These are the ways we can target in media for the top funnel. So we have to understand that India is basically because of the huge bedroom that is there in terms of the penetration that we can grow for in most strategies. Much of the challenge lies in top funnel and we need to find a way in which we can improve the top funnel and targeting and these are the three roots that we will be discussing now. Now let's say the first one was what I said was of frames. The way you consume video in the past was restricted primarily to people. Creators got various favors so it starts with let's say the population is 43 crores. Those people who access TV is roughly 99 crores. Then you have a whole set of newsflips, OTV that includes YouTube, Facebook, video on your Vivo allow all the options. That comes to around 47 million or 47 crores. Then you also have a set of people who access video through HD and ask 16 crore people and then finally you have an independent TV which is around 2 crore people as we speak today. And all of them will agree that there is a certain amount of income differentiation that naturally exists and let's explore that. Now what we set up first is if you analyze the view in detail you can actually differentiate people by the heavy light and medium amount of consumers and this is what we just ran recently. So if you see in 2019 and this is where we were and I did also where we had some averages and coming to some constitutions, 2019 you had 7% of the people who were not watching TV and let's just focus on that set for the time being. That's because they were on vacation and it happens. You know if you take any year in the past you will always find certain people in any given month or whatever is your time period by variation, some of them will not be switching on TV. Today that percentage is 1 to 11% and you will be feeling those serious value when you are treating the data that's because you know people migrated from upper areas to crude oil or the head back home grounds and that was COVID thing. But if I just take the last 8-bit average it looks like around 11 and though it's early days to say that it has stabilized we can broadly say possibly 4% people have become caught fighters that is they have moved out towards connected TV and this analysis also brings the number to 35 million and there are various other estimates which my colleague Bushan will be teaching in the future that also sort of caught fighters. So what we have to understand is 4% of the TV audience are only helping could be possibly caught fighters in India. You see how do they access TV that's 96% of the people who are that how do they access TV then basically you have 4 ways you access media TV one is cable which is the biggest chunk 50% 100 million households access it through cable then you have 30% of people accessing through DTH and then you have 10% accessing it through DTH and that's sort of moving up and DTHK is coming out that could again get entirely going but this is probably the landscape what is more important is not the way they access it the more important is one of the estimates we have for SD and HD phones Sam in one of this recommendations he said HD channels are highly highly underutilized by marketers and this bears it out so we need an estimate this is the data that we have from VAR and we have from the DRI and also from other DTH operators the 43 million households who subscribe to HD channels and if we would presume in the other in the group that I spoke about which is basically the 3% of households consuming 30% of consumption because it sort of mirrors where the most of the consumption happens it is hiding over in extra mega cities it is again in extra larger cities so far this is the first thing that we do get a way of addressing the upper end of the segments is HD homes and the product address which I estimated at 4% which Vishal would be taking proof in the near future then also you will find that the underutilization of the HD homes if you have to analyze it separately versus what it is in SD homes it is very very dramatically different but what we normally in media we do is we do not take care of this representation and we just go ahead and just use the HD channels on our standard normal plan the first recommendation is to actually plan for HD homes because their view of shit is different especially if we are targeting if we are targeting those who are taking this weather penetration is lower we are going up to the high intervals so first point that I am saying let's answer it is mainly under reported because a lot of people in the sample design the mode of access of TV is not considered at all so they are perfectly right in not having a specific way of getting HD homes so that results in a push under reporting another thing we need to understand is there is an optically poor rating of HD channels so in the previous slide for example I showed that the rating was 0.3 the simplistic application is 20% of homes are HD homes and if I am only interested in the upper end of the same point then I have to multiply like that by 5 and that would be the actual rating of the program within the HD homes and then it actually becomes very effective and efficient so if I am going up to the top 10 of the consumers for example I clear on HDs only for a person so all that I identify after the upper end of the consumption where the consumption percentage per capita consumption is high then it makes a lot of sense the second thing that I would talk about is at the extremely other end of the spectrum which is low income and here we can see giving free dishes and giving free dishes is great after all that's great and that's because many people are moving away from cable to free dish and especially in certain industries which what we would call as the in the hotline here again if you see and here actually you can evaluate on HD homes I mean on FTA homes you will see that if you take me you will see channels only on this big market so there are a lot of friends of whom that's a cold market and when you do that analysis on the total homes in future on 800 Japanese for the same thing if you evaluate only on FTA homes it dramatically shoots up to 2,642 it's the same plan but it's just that the base where we obviously we won't expect when I advertise on a FTA channel I expect a guy who doesn't have a FTA channel to watch it and therefore what it also does is like I said the bulk of the consumers are in also I mean the size of each of the signals are very important but here is a very actionable insight if your plan is after the lower end consumers especially in the hotline first of all in the small budget of 6 crores in an actually median very high level of activity across the years and also cricket and really does make sense and a lot of people are moving on towards the FTA channel so there are two points that I have made with regard to the actual so one was if you go up to the high end consumers then you have a better marketing option in Hshti homes and if you are going at the other end of the spectrum you can use the FTA channels next I'll go to live stage so what do you mean by live stage let me just explain so what we did is we took all the ad-ex and we don't have very reliable data but digital outside of digital we took for all the ad-ex that happens in the last 3 years and across each category there appear all the high-specified categories which have been listed we sort of gave each category to a specified audience for example if it's a kitchen or a home category then it's me and the home maker soft range and even digital persons who market it as you and the remaining like for example BFS side and OTC we put it as all others and the others would be business and others called other categories which does not come into the shop and we checked what is the advertising expenditure that typically happens and this is outside of digital the 38% goes to home maker 27 to 21% goes to all others let's just go to these 3 segments and let's just understand first we start with the housewives one thing that we need to understand again is the participation of women in labor participation that is who are employed is the lowest of the second or third lowest anywhere in the world and that's actually quite a shocking data so if you see right now is that around 17% in USA of 25% of women who are over 82 years they do go for an employment whereas in India only 23% of women are actually employed so this sort of gives an insight that we cannot be actually mirroring what is happening in the other parts of the world it was our demographics as far as our things are quite mini too India and probably this is one of the reasons why Exxon Australia and all other countries the 30% is much lower but in India it's still higher because of this particular problem this is one inside it sort of tells why in India it's still quite good and also if you just back calculate this with ILS data you also find that 68% of women who are over 82 are not working in Australia therefore we can consider them to be homemakers now it's well known and the data also shows that women by and large are heavy consumers of TV so if your brand is actually targeted at homemakers then TV still remains to be a highly potent media and might be unique to India because you know compared to our South Asian neighbors our participation of women in the labor market is much lower in India so TV still remains for data as long as we are targeting only the women and that's because it is a high reach and obviously the CTM is low that does not mean that we are saying it has to be completely innocent we should actually also in social and digital want to reach the hard to reach women as well as to our member race brand and in our switch currently on a grocery it's only 3% will be expected to grow further so this is how you could actually hang it within your media by going by the income covered and also in particular about whom you are targeting here very sharply for women now let me talk to you and this is very interesting I think again India is very different from all other markets because in most markets at least the most advanced markets they have an ageing problem we are actually the cover of you because 65% of Indians are under the age of 35 and that means we have a immense potential and there is a lot of trends which can be evident to you and we need to see how we can harness that potential first observation is so this is a very interesting fact so we did by age cohort what is a media consumption and the first thing that stands out is the older you are less types of media you consume so for example the silent generation which are basically the senior citizens you have 41% of them can be accessed by using only one medium as you go down millions and densities which are actually the age cohort they are more comfortable they might be spending less time per medium but they are actually consuming more media and therefore by default whenever your brand is youth suffering you need to be multimedia we are just too inshallah to reach that second most important observation again compared to different from other cases we are assembled in the homes and that means so certain and interesting in their specific observations let us take OBE OBE means people with whom you are watching a TV program so this is a great where on the access here you come here 0 to 2 means main person with whom you see OBE what is very interesting is if you go to yesterday to on 30 actually the bulk of his OBE he is watching much of his TV along with his mother who is in the age of 50 and that goes up when he is at 30-40 so then you can also see that he is also OBE with his partner because that is 29% but actually most of the time he is OBE with his mother on his mother's law because the percentage goes up very high and this sort of shocks you if you actually see you are a youth brand you want to target to youth in his or her specific relevance but most of the time if you use TV you are actually ending up in an environment where he is sharing a viewing behavior with his mother or his mother in law is that actually the co-voting with the specific partners actually increases in the prime time so most marketers that I speak to they say what is the percentage that actually are getting youth what this clearly shows is the more you go to youth which the advertisers go to youth and the more you go to youth in the prime time actually you are only going behind the ratings not much of relevance assuming co-being will be much more attention when he is solo-speed in our analytics of this analytics over across various studies in France cricket and off-prime spots they actually do well for example in Christianity I was just doing an analysis of Spotify they have used all sorts of tablets in the non-prime time and there seems to be doing quite well and cricket we go why there is such a huge thing e2dv all digital course plans and with central France understand this on the page on cricket is so high for example you know certain brands use a certain mix of tyrants do it the same it does not work because you have to be doing everything else but at large like cricket doesn't work I also said that when you are going to youth we need to have multiple tyrants as if assuming in the top corner much of that will be on video e2dv actually you can combine a linearity which gives you a high bridge like I told you there are still people who watch TV's quite high on two basis one is called CPIR that is gospel incremental bridge and the other is economics so on a gospel incremental bridge what you do and like you did it was the same it becomes a lot to make money so you have a campaign but let's say a focus on algorithm is created in the spawn chance let's say of four backs each as one chain and you first go on buy which of the three options let's say Facebook, YouTube, just to give an example and it's in one I'd like to be fighting over and helping something that requires which is adding an incremental bridge we know in India we don't have a single parameter but there are very robust probabilistic methods in which you can add an incremental bridge and then in one keeping and doing it here and finally you will get the maximum bridge for the given budget and that's what is called as a CPIR now there are advantages, advantages basically are reaching not more people for the given budget but you are also getting yourself an advantage which is digital which is happening and also you are comparing CPIR and digital in one grid the advantage on TV like I showed you before being is actually it means multiple audiences are the spillover is very high on TV and there is no spillover on digital so for example if you have a fork actually you will be surprised that a lot of fork users actually come from the older age group and if you are very demanding on digital on YouTube you will be losing out on that opportunity in CPIR where it won't be as good both are even we go and that's what makes lot but otherwise and that's what reaches me that's why sir the other way to do it is through econometrics in econometrics we model for outcome so the econometrics should be very well advanced so if we get the data by the outcome and we have the data on news fans and digital fans and capturing certain other variables we will be able to build what is called what is called as multiplicating models I don't want to get too technical what it means is the interaction between on medium and on the other medium is great in mathematics and that must be built on orbit and simulated and we will be able to find out what is the best rate show in digital simulation apples together so that will take care of all the other things including co-viewing and TV target and making digital and in the subject to miss or run up against the other and typically if I do like this across various models that we build and this keeps changing so the 7030s are called today for most few grants that we have done it's about 1730 and more and more change as the digital reach goes higher and also it depends on each market the spectra conditions then the third point that I wanted to discuss was is about micro cover why do I say micro cover it is so if you take what I have done the first step is for ceiling fan where the penetration is very high about 90 and you can see under each dot represents a state so for example there is a dot bacteria, there is a dot Maharashtra and each of that is the state you see you will see that in a heavy you can see fan the operation dispersion and the category it says Maharashtra are in line but then let us take other category which is bridge which is at around 34% penetration the line is not so consistent so there are some states which are over index and many other states where the operation is high it is under index and if you take cost which is given less than in a bridge the difference is because events are so what the point here is some of the western models assume the cost is equal which might be true but here we also have various conditions because of which each state are between a state for example if we take beauty which has a huge population not all of the beauty have the same cost as in August and maybe in general has a higher cost as it was and it is to be real so how do I compare all of this in general in that week it takes three parameters for example ability which includes variables from RBL and the per capita bank deposit by every district also this is done at every district per capita bank deposit, per capita bank and also the employment structure like I said the employment structure is a very good process for consumption and you have awareness including the reach of internet and then you also have a good ability where we can this is an attitude that we have for example consumer level, house ownership vehicle ownership is a general standard that we take at every district so if I do this then what I get for example is that roughly around 740 districts today and we have 8 opposes for the districts in our system we will be able to identify 1292 districts where the consumption power is much higher in average and actually it opposes 70% of consumption on an average if I take those standard parameters and what we normally suggest to marketers is these districts you need to do a specific local target actually this approach is quite well recognized in fact if you when you see the pointless India special edition there is a mention of this framework that we have come up with I mentioned about management power but we hope for again like what it does is it assesses market space's potential and also media homogeneity like I said India is 800 kilometers and it changes so that homogeneity is also going into the system and then in the system we also have our brains and tools so that we can go ahead and activate the local media escape so for example some of the tools come with information for example if you surprise that in several parts of the question will be the YouTube integration is much higher than TV and typically if you were to build a plan TV would saturate in certain markets of TV and you will end up spending a lot more money but if you were to use the way of video planning where you consider TV and digital media must run YouTube will do better also you know that in certain markets especially the small amount of the short-com videos do well and also why platform video do well what are the short-com videos that do well actually the language is quite important in certain markets so we also have every edition available which for each of the district which editions we need to buy so for example we sort of buy all of the editions and actually buy specific editions if the potential of those markets are high and what this eventually plus for the marketer is we get a lot more hyper local escape into those districts which we have shortest so this is I wanted to discuss today so let me just go back and sort of summarize what I spoke of in India actually the thing that all marketers need to understand is there is a high amount of disparity and at the same time the influence of this is quite high to actually target in India we need to do it on free access one is on more of free access as I showed you we have looking at it for example whom housewives and your need of digital may be lesser there because they give you a higher reach and then I also said if you are operating in a category which has no penetration then you are going up there the house of the society then actually we need to use options like HD which deliver much higher reach than your digital and those houses which we have 33% consumption that's a very good choice then we came to adapting by the life stage so youth in India will be the biggest consumption protection because they are not only the youth to consume more we are fortunate enough to have 30% of Indians are actually they are under 30 and such a huge consumption power when you come and try to accomplish not having the same end rate but we most must think about some of the learnings that we have the effectiveness is very high on cricket and offline especially certain donors and more importantly we need to add digital labor some of these will be we can go ahead then I said in some what we need to look at you can not see cybers, digital and media and the two models as we were saying which is basically the CTIR we can choose you know even from half days the product then from the CTIR we do well then probably a common model should be used and if you are only trying to be shared that means you need to have more CTIR so probably you can go for CTIR models what you need to do and third on the last part is we need to understand that our size is so huge that you actually we need to see in India not as one but as many in India and we have a business in which we will be able to do like a local CTIR and that's something that should be demonstrated which is what matters so that's what I want to discuss about today how there is an opportunity in which we as marketers in this room can harness with better timing that's what we have there you go