 I thought we'll do a quick temperature check in the room. Following up, Dr. Batra is always a tough ask. How many people really think they're going to take away something from this session? Show of hands is good. Excellent. Because by the time I walked from that door, right to this corner, there were about six people who told me all the best. I was wondering, why should I be the only one taking pressure? So, great. We'll start out by actually a simple pop quiz, right? It's the simplest thing to do. Let's actually figure out how many people here, how many people actually pay attention to their data, and how many people genuinely going to walk away with something more meaningful than the first slide itself. What is India's rate of inflation? Any guesses? Actually, how does it even matter? Because you could argue it was about 7.9 the last month. It went up to 7.04 in May. The quarter likely estimated at a 7.5. But what do these numbers even mean to us? And that's the problem with data. We keep confusing ourselves with numbers being data. And that's not the reality. When you look at this graph, you will suddenly realize the moment you start contextualizing timelines, trends, relatives to how data is moving, they will start throwing directional insights at us. And I'm not saying this means a thing to this session. All I'm saying is that there is a lot of people in this room who may feel. We use data very data-centric. And so we thought when we started out noise. But that is not the reality. And that is what we'll explore. Because invariably what we think is data is nothing more than anecdotal evidence, what we keep terming as gut feel, intuition, and quite frankly, nothing but opinions. We keep using data to substantiate what we think our hypothesis should yield and keep hiding behind the fact that we are very data-centric. At least we were when we started out. And there are a few reasons to it. But let's understand were we the only ones that felt this way. Because PWC did a recent study where in the midst of the biggest crisis that the world went through, 91% CEOs in the US felt their businesses will organically grow this year. Of course, something that the key takeaway there is that they were US CEOs. But the fact is that they still all feel that this will happen. I also feel I'm absolutely sure I will lose weight this year. But these are all statistics used to substantiate what we think is data. Warren Buffett, another such specimen, basically said, I have checked all electoral tables. The lowest death rate is in six-year-olds. Therefore, I chose to eat like six-year-olds. Data suits convenience. Of course, it was a joke. But this is what happens with all data, that we make it suit what we think works for us in businesses. Because constantly, what we are grappling with is this. These are just not amoebic shapes. This was the best attempt at what I thought were brain and the gut. There is this conflict. There is a constant dilemma for intuition and reason. And this is something that we all go through. And I'm not saying one is right, and therefore there is a purest way of running a business. You need all of it. In fact, the most successful entrepreneurs start out with maverick ideas and great gut. They're blessed with incentives, why they do well. You'll always find arguments. So the one extreme is Napoleon, who said 90% of war is won on intelligence. And on the other end of the spectrum is Steve Jobs, who basically said, past is past. Future has to be built on what you think you can rely on. It could be intuition. It could be karma. It could be luck. You can figure out whatever works for you. But it is only directional. The past only tells you what the future may hold for you. Absolutely true. Therefore, what is the relevance of data? How and why is data so important for all of us? And that's the question that we'll keep asking ourselves. Why does this predicament even exist in the room? This predicament exists for a simple reason that most founders start with great visions. They have big ideas, and unfortunately, very small teams. So when noise started out, we started out with a six-people team that believed, we'll do this. Of course, the ideas change. There are people who buy into that vision. The vision changes. The fact is, those six become 16. And you are at all points in time counting on the maverick of these individuals. It is people who are more important than there are systems, processes, or data. And you're relying on their ability to pull magic for you. And what are people best at? Gut. Most opinions, actually. And that's how businesses are formed. That's how all startups take shape. The easiest thing is, let's marginalize cost. There is some people in the room who will relate with this. All text apps, all solutions start out with what's the easiest plug-and-play, a conversation that played out on this very stage 10 minutes ago, that you have Shopify, Shiprocket. Come on, let's e-commerce. But are we looking at data? Are we really looking at what is it that I need to do? Or I will be another me too in this space. And because speed and agility are important, we decide that bias for action takes precedence over everything else. Who will sit to study data? Data is not relevant. We are very young. We don't have history. All of those things play out. Most importantly, the environment is such where a bit of risk works. There are people saying, kuch karlo, data figure out karleenge. Let's go with what I believe in. This is a vision. I have a great idea. Magic will happen. And magic does happen. And I'm not discounting that. Therefore, in this whole situation, again, back to the macro question, why is data even important? Data is important because if you look at hard facts, hard statistics. Less than half the company is world over invest in big data. In India, this number is a paltry small. And when you talk about small Indian businesses, it's a scary sight. We're not investing in big data. Do we see the merit in it? Maybe yes. Why are we not committing to it, therefore? Because that conflict of the gut continues to be our obsession. We are so obsessed with the idea that my idea is perfect. We will hit home and let's go for it. The other way of looking at it, and let me start building reason here with this group. Are we willing to hedge our business on gut? How many people here have a pension for mathematics? Quick show of hands, one is good. Two is even better. Let's just say about five people have a pension. Simple question. What is the probability of hitting success if you are taking decisions on gut? Statistical probability, mathematical probability. 1%, 50. Statistical probabilities, success, failure, one out of two, 50%. Agreed. The advantage that I'd like to give myself is that if I start adding a little bit of data, chances are I can push it north of 50. And who doesn't like a little extra credit? The bigger problem to deal with it is that when you are starting out businesses, things will go wrong just because they can go wrong. The Murphy's law is not that things will happen contrary to what you believe they will. Things will happen because they will happen. So you've got this. You've got the fact that chances of success on gut are 50%. You also got to account for variable change, the biggest variable that plays time and it's changing every day. So we were just informed that we had three product launches. You have to account for the fact that there are 13 more that somebody else would have been planning to do. Therefore, speed and agility are important. But most importantly, as you become larger, your risk of wrong decisions is larger. So cut yourself some slack, rely on some data that can potentially reduce the risk of those decisions. And for me, that enough is reason to believe that let's follow data. And that's what happened for us. The reason I'm saying this is that ironically, it's not an either or decision. Let's evaluate. In the current given scheme of things, we I'm sure safe to believe that lion's share of the business is digital or growing digitally. We've had disagreements or agreements on this, but for convenience sake, we know for a fact that there is massive growth coming from that sector. We know for a fact that customers are more dynamic than they ever were. Getting a grip on who the customer is and therefore predicting likely behavior is becoming more and more difficult for marketers. We know that customer experience is more important than ever. People are going to stores for experience, but that experience is still relevant for us. That's the only differentiator. We also know that personalization, retention, a lot of this is becoming important. Acquisitions are more expensive. And we know that cookies will be a thing of the past. And if all of this is true, where do we stand on the ability to read data and therefore leverage it? And whilst it may seem that I have spent a lot of time setting context, the reality is what my first slide said, that data is in your DNA. You either are data-centric or you're not. Keep telling yourself that as an organization, we believe in data, but there are various stages of how organizations use data. So sometimes asking yourself these hard questions is important. Are we really data-centric? Is there a cultural emphasis on collecting data to start with? Are we an organization that believes we should correct data? Are we an organization that actually makes investments in hiring or upscaling people for data manipulation and calculation and analysis and all of that? Are we an organization that is willing to commit across verticals that decision-making will be centered to what the data tells us and not what five people or gray hair in the room say? Are we willing to let go of decisions that are contrary to what the data says? And I'm saying this out of having gone through these labor pains when we were building noise up because there are times where data will tell you that there is X likelihood of success of a product. And you can choose to go ahead with it or not. And sometimes it is the passion, belief or opinion that takes precedence. And if we do that, we're making two mistakes. We're making the mistake of letting go of a viable idea and the opportunity to make this one successful. And therefore, building a DNA culture, building a culture or DNA or data in the system becomes imperative. You'll realize that it all starts with data denial. We all start data. We know. There is also a case of data indifference. And these are two stages that most organizations are very happy being in and still calling themselves data-centric. The other two that I've highlighted are the ones that will have the lion's share. Most people in this room will be a part of organizations that are data-aware and data-informed, but not necessarily taking decisions based on what the data has to say. It is only the last step where you can truly call yourself data-driven. And I'm not going to comment on this because this is self-evaluation. And this should tell you if you really are data-driven as an organization or not. Therefore, when I keep saying data culture, la, la, la, la, la, what is it that worked for us and what did not? There were some first principles that were drilled deep in who we are as a business. In our business DNA, we basically said that the business model is geared towards data, which means what? Which means we are one of those rare brands and a lot of you may not know that started out by our own website. We had our own brand store before we even dreamt of going to marketplaces. Contrary to popular belief, that's how you start understanding, connecting with your consumers, your own consumer insight, and you build the brand basis those insights. It's fast, it's efficient, but that's the only way it works. Second bit, we realize that there is a large degree of products where we are not being able to capture the life cycle of the consumer because FMEG, a lot of times people will come buy a headphone, go away, relationship is transactional, you don't know who the customer is, bought somewhere in Roper, I don't know where he bought from, took home, chose never to speak to noise again. No social listening, no tools, nothing came in handy. What do you do? You activate their warranty and bring them back. You build an app where the experience of a watch is built on that app. You build a firmware upgrade that allows the customer to come back. Of course it may seem like cheat codes, but these are not cheat codes. This is how we geared from bringing out the first truly wireless product in the country with a hard pivot to saying that we'll do connected devices but we'll focus on watches because that's an ecosystem that we understand and that's an ecosystem that will allow us to understand the customer better. So it was a part of the DNA, it is not a mistake. It had to make those hard pivots. Of course, a lot of you would say, it's very simple, right? Big data, this, that, do you realize how much those tools cost? Of course, we're a bootstrap business. We have zero external capital. We have to fund every decision that we take. It's a black ball with our own money. ROI is more important than anything else and imagine the ROI for this. Imagine sitting in a room having to explain somebody the ROI of this. What did we do? We went to old school. We said, we will speak to our customers every week. If it requires a Zoom call, we'll get on a Zoom call and cometh lockdown, bliss. People were at home, they're saying, okay, we'll talk to you and we'll tell you everything that we have to tell you on the brand. Imagine the power of those 200 Zoom calls that you have almost 3,000 people on who are willing to let the brand grow, co-create with the brand and imagine the richness and anybody who's a call, research scholar here will tell you a sample size of 3,000 is gold mine. We put a 3I model in place. We said for all products that we'll do, we'll have products that are iterative, which is how all technology products are done. We will do products that are innovations, which is basically saying, I know what's next best, gut and gumption. But more importantly, we'll do products that are based on insight. If customers come and tell us lockdown, we don't actually get to figure out when to take the hand wash break or how frequently to do that, we put a reminder. We have a watch where you actually have a hand wash reminder. People in lockdown said my use case has changed on TWS. Now I need it for much longer duration, but I want the battery to last. I want the weight to be less so it doesn't stay in the air. We came up with the solution. And I'm just saying this is insight and insight driving design, product development, the core of a business. And this is what data can do. This is not numbers. This is not statistics. This is hard data speaking to you. Most important, and to my mind, the most important line in the entire deck, be open to failure. Data can throw you off. And we've often heard paralysis by analysis. Sometimes we are so absorbed in actually just studying and going over data again and again and again that we don't realize that it's lost relevance. And we just go chasing an insight. Be fast to learn. But most importantly, be tried to pivot. Because if a data insight is contrary to what you've been doing, it's directionally telling you that you might hit roadblocks. It doesn't mean that, okay, let's stop the project, let's do something else. But be prepared to look at what it might entail. Course correct. And most importantly, what data should we look at? Should we look at our own data, competitors, industry, world? What data should we look at? Because some analysts will get source-espaired data, they'll have a cut for everything. The reality is, you are a different business than your competition. We keep letting us, why do you compete like this? The fact is if I start reading their data to apply it to my competencies and resources, we will end up with failure. Important, what was the measurable impact? We got a fuller, richer picture of the consumer, and I told you how. We got our pricing decisions right. To understand what is that right sweet spot, and we're in a business where pricing is everything. When you take the overarching mission of saying, I will democratize technology for India, where price is everything, then getting a price right is the first step. We identified some new trends. Real green shoots, and that's how you get to doing smart glasses. For you to figure out that there is a real use case, there are people who don't like the idea of things sticking in their ears. How can I use guided audio, fit it in a form factor that works and present it to the world? We improved forecasting, it helped us manage our inventory better, nothing better than this in a bootstrap business. And we improve customer service. This is really a differentiator, because if you're not listening to your consumer, we, the strap line for the brand by the way, and this is the height of irony, is Suno Dilkashore, which is listening to your inner noise. But when it comes to taking decisions, we've been listening to that consumer noise. And if you're not listening to consumer noise, you get nowhere. We adjusted for a lot of decisions, right down to a stage where we had to pull out products because we realized that the data was telling us we'll head for failure. And that was the best money we ever saved. What did it get us to? And since we're talking data, let's look at some hard data. We became the number one smart watch brand eight times in a row. Yeah, it is worth celebrating. You know what's worth celebrating more? We were the number two TWS brand. And we climbed up to this spot from ninth position, having beaten Samsung now. The app is rated number two on the Play Store. We are behind Aroge Setu. Do the math. In the global arena, we are the number three basic smart watch brand. And the best part, we became India's number one bootstrap D2C brand. And that's our story. Data got us here. I'm sure it can for you. Thank you so much. I'll just leave you with this thought. I saw some cameras rise up. People taking pictures. If it's really meaningful to you, if you really want to take away something, this is a slide. Please take a picture. But what it tells you is make a commitment. Figure out what your DNA is. And I'm sure if we can, you can. I'm open for questions. Happy to take them. I think we've got time for two of them. Yes, we'll take about a question. One question probably. Yes. So data gives you direction and you have this gut feeling that crunches your experience over the years, right? That's also kind of a data. How do you decide which way to go in such a situation? So the problem is too prompt. The problem is when you set it up like, I have strong experience and insight, it is essentially discarding the fact that data could counter that intuition. And I'm, like I said, that there is no substitute for either. But the only mirror that you could have for your instant going wrong is to triangulate that, look at data and figure out, are you likely to succeed or not? This is like a coin toss. Right before the coin lands, you know exactly what you want. That's your heart or the gut. But if you're looking at data and you're willing to spin that coin thrice over, then I think we're making a mistake, right? Yes. Let's take just one more question. One more question, that's all. Just one more question, one last question please. Let's quickly circulate the microphone in the interest of time. Let's just keep it very. Make round of applause, ladies and gentlemen. I had spent much more time in business world. Operationally, I don't spend any time. I come to the events and we had our, which was the one in Bombay, which was a jury meet in Bombay at the JW Marriott, pitch 30 under 30. Yeah, okay. Ruel and me were at the jury meet and I was going one day before that, I get a call from another player in this segment, large player, possibly the largest, I won't give you the name, but they have something to do with water and rain and so on. We only have one aquatic friend that is larger than us. Yes, that's it. That's the one I'm talking of. I haven't given its name. And he said, oh, one of my colleagues is applied, but there is somebody from the competition. So maybe my colleague won't want, and I have had this issue in BW Legal World, a lawyer called me saying he has his ex-partner who will not let anyone win. By the way, that ex-partner voted for five of that guys. So I must tell you, I was sitting in the jury meet and I have only one vote, so I can, but Utsav made sure, because he believed in that guy, he championed in the jury and that guy won by unanimous, because sometimes we have these notions about other people that they will not do this, they will not. So I just want to compliment Utsav and I said this to Utsav and after the jury meet that Utsav, you're very kind and gracious that you let, he said, this guy is so good, he should have won. So I want you to give a big round of applause to Utsav. Okay. And now your question. So Utsav, my question is around the metaverse and we know AR, VR, XR, the biggest challenge is the headset or the glasses. So what's your view and again, how we talk about data, that will be the ultimate data collection engine in the future, so how that can be monetized? So first on the device part and second on the data part. So I think being a bootstrap business through Galilee comes to you naturally, right? The biggest virtue to take away is timing. You have to learn to prioritize and you're absolutely right, the Oculus is the future, where we want to lead experiences in the third dimension. There are three problems. The first problem is knowing when to trigger off the hardware for mass adoption. And are you in the business? So for us, we are very clear that we want to be players that speak to the bottom, the mid and the aspiration, but we are not in the business to solve the problem for three people. Right now that is a problem for three people. As for the second part with regards to the data collection, I think the data that you will get will probably be the richest. The bigger issue is what do you do with that data? And how do you draw intelligent insights to be able to make meaningful solutions for those customers out of that? A lot of times you realize that people are willing to leave and this is a statistical number of 67% apparently, I'm guessing it's a rounded off number, but 67% people are willing to leave their data behind with brands if it enhances the experience for them. And if people leave this data behind for you, which is a peak into their lives, it becomes the responsibility of brands that operate in that segment to drive the highest experience for them and be judicious with what they are doing on that data. Personally, we feel it's about a few months out there. It will to start with not be data about the individual, it'll be data about the life of that individual. So you've got to be cognizant of how you're saving it and how you're using it, but I think we are living in times where people are more than happy putting their lives on social media, let alone share data. So I'm not exactly sure if it serves the purpose to something, but I'm absolutely certain that that is directionally putting us at a level where people are willing to put their lives for third dimension experiences that could be customized by brands around them. So, exciting times ahead. Thank you.