Good evening, everyone. Welcome back to the MarTech Fridays by Exchange for Media, a platform specially curated by Exchange for Media for marketing and digital professionals, whereby we discuss marketing and technologies that are kind of coming around. Today's agenda is about maximizing data ROI, aligning data and business strategy to drive growth and profitability. Pretty, pretty interesting. We have an eclectic mix of panel represented very well by brands, marketplaces, research consulting firms, and a marketing automation platform. So welcome to the panel. And I will introduce the panel to you, starting with Hitu Chawla, CMO Microsoft. Hitu is spearheading the marketing efforts at Microsoft in India. She drives the curation of engaging customer experiences, deepening the intersection of marketing and sales to deliver tangible business outcomes. A firm believer of modern marketing, she leverages data to make a wider impact, driving growth of the business and the brand. In her previous role, she served at Microsoft US as senior director of the partner go-to-market vertical, McKenzie and Company, and three common there. Hitu has drawn different hats from strategy, consulting, business, and channel management. She's led brand marketing and go-to-market initiators in India and the US. Passionate about mentoring the new generation of business and marketing leaders, she's a strong advocate of women driving impact and senior leadership roles. In a free time, Hitu enjoys dancing, adventure sports, and hiking. Welcome on board, Hitu. Thank you so much, Oniya. Next on board, we have Sagar Bokeh, shopper and customer marketing Tata consumer products, accomplished CPG marketer with experience across food and personal care brands. He's been instrumental in creation, scale-up, and rejuvenation on many iconic brands like Tata Salt, Tata Sampan, Dalda, Goldbridge Number One. Sagar is a marketer with a very key near to the ground. This comes with his experience in sales and P&L management. Sagar is a great believer in digital and has taken significant initiatives in building data management platforms, content platforms, and imaginative and effective use of Matic. He enjoys challenges that involve setting up businesses and business turnaround. Highly passionate professional with clarity of thought and direction. Welcome, Sagar. Thank you. Nice to be here. Oh, great. Next that I will introduce is Isha Nagar, managing director, Nipah India. Isha Nagar leads the country hat for Nipah India. Nipah is a stock home headquartered leading consumer science firm working on the crossroads of tech, consulting, and research. Isha has been with Nipah for the last three years. Her prior stints have been with Cantor and Nielson, where she led the West region media and digital practices amongst her many roles. Her work cuts across multiple verticals like consumer retail panels, digital focus solutions, path to purchase understanding, and media effectiveness. All things around content, campaigns, and marketing come from a very special passion space for Isha, coupled with her command on deciphering consumer sentiments. Welcome on board, Isha. Thank you, Sonia. Hello, everyone. Next on board, another woman leader in marketing and digital, we have Anika Agarwal, CMO, Max Bhoopa Health. Anika is a digital and a marketing leader who joined Max Bhoopa in the year 2011. With over 15 years of experience, Anika has a wealth of marketing experience across India, Middle East, and African markets. Prior to joining Max Bhoopa, Anika spent more than six years in Nokia India and Nokia Corporation. And a very brief stint at the Indian Cellular Association. As the head of marketing function at Max Bhoopa, she's responsible for the overall brand strategy and marketing communication. She leads brand planning, communication, digital, and social media, consumer insights, loyalty, and CRM. That's quite a handful for you, Anika. Hi, everyone. Nice to be here. Anika has an extensive portfolio of digital brand building, online sales and lead generation. Under her leadership, Max Bhoopa has won several accolades, including the coveted E.T. Best Brands and Super Brands Award. Welcome on board, Anika. Next on our panel is Sushant Mishra, head of digital marketing, Grofus, a fellow agency person, colleague, who's now moved to the client side. In his current role, he's heading the digital marketing strategy at Grofus and is responsible for business growth, for driving acquisition and managing retention. And that is not an easy task. Before Grofus, he worked with renowned companies such as the Puglises Group, DDB Worldwide, and within that, Tribal DDB India. With an extensive experience of more than 15 years in the overall marketing space, Sushant has spent 12 years primarily in the digital marketing domain, leading campaigns for many reputed brands across the country. In his capacity at various organizations, he's implemented multiple martech solutions to steer the business, innovation, optimize consumer journeys, and increase operational efficiencies. A very warm welcome, Sushant. Thank you, Nivya. And the last person on the panel, actually the second last, a poor soothed vice president of global business development and partnerships at Web Engage. Web Engage is a SaaS company headquartered in Mumbai, vocal for local, everyone. It is a cross-channel marketing cloud for consumer businesses with clients in close to 52 countries across the globe, fantastic. He comes from software, SaaS, and digital advertising background with expertise in revenue expansion and go-to-market strategy. He's both visionary and practical with high levels of analytic horsepower and has the ability to turn analysis into insights and actions. He has keen understanding of market conditions, product requirement, demand for products and resource requirements, thereby creating value for his customers. He enjoys nature and all kind of outdoor activities like mountaineering, scuba diving, running and backpacking. So welcome on board as well, Apur. And finally me. I'm actually a serial entrepreneur and my second stint right now is with an agency that I've launched which is called Pumelo Digital. I basically come with two decades of experience in marketing and digital. The two pillars that we offer at Pumelo is employer branding and digital marketing. I'm also on board of a new tech startup in fashion which will be launching soon. If I wasn't here, I'd actually be a mountain goat trotting my way up the mountains. So great to have you guys on the panel and we will move on to our questions. And I'll call out each one of you as I put across the question. So this is really, you know, to all the brand leaders that are here, how are you leveraging data to drive business strategy? What is the tipping point for you to activate data-driven insights into business objectives? And I would like your perspective because each one of you either come from a B2B, B2C and B2C background. I'll start with Hitu. Hitu, why don't you take this question and give us some insights from a B2B perspective. Happy to. So Sonya, I believe marketing sits at the intersection of data, business acumen and creativity for it to truly work its magic. And I'll share that with a couple of examples where we saw it being stress tested in the last six months. First and importantly, I think the use of smart data actually helped us improve our response time across all facets of go-to-market starting from, because in the current circumstances, I guess all of us had to, none of us were prepared, none of us knew what was hitting us. There wasn't like a playbook. Everything is off the playbook is how we've executed. So I think the fact that we turn to data, like I said, help us improve on all facets of go-to-market starting from demand forecasting to product enhancement to real-time offer adjustments. Microsoft Teams is a great example because we saw a surge of almost about 12 million users in a single week back in March and we could adjust our supply elasticity literally like within days. And while we have since then we have been innovating in-flight with ongoing feature add-ons like virtual meeting rooms, whiteboards, et cetera. And all of that is possible only when you are leaning in on what's the actual customer reality. What is it that they're looking for to enhance your product? Well, what is the potential demand and how much do you scale up in terms of to be able to fulfill that? Second, I would say virtual events, which all of us will relate to. We are painfully aware of the virtual events fatigue, be it your first-party engines or third-party. I think the best form of targeting most are able to do is which accounts to go after and probably the specific titles and personas within those accounts. But there's no way to intelligently predict how many will register or how many of them will really show up. But most mature automation tools have AI-infused predictive audience capability. And at Microsoft, we use Marketo. And as an example, there is a feature called Adobe Sensei. I think that's how the particular capability is labeled, which builds an audience list using predictive filters like likelihood to register and likelihood to attend. And it'll give you alerts when a goal is predicted to be missed along with intelligence recommendations, et cetera. So the fact, again, that you are leaning on technology to be able to make more intelligent, informed calls in your business strategy, in your marketing strategy. So it really sits at the center of everything that we do. And the last I would call out is, it also allows, in our function specifically, it allows you to eliminate the marketing waste with that whole hidden trial approach, which in the current context, I think none of us really have the time in luxury for. Because when the lockdown first hit us, I remember as a team, we had so many questions like, and given the wide portfolio of products we have at Microsoft, we had questions like, which products do we prioritize to take into market? What messaging do we lead with? Which is whether the existing audience segmentation and high-prepensity data models that you have, whether they'll work or not. And the answer, and we turn to data because it helped us not just answer these questions, but also be more nimble in going to market with messaging and being more pertinent and really being hyper-targeted. So in netting it out, data sits truly at the center of all aspects of business marketing or how we live today, I would say. So what is the threshold of data that you're looking at before you make a decision based on that? Just some insights there. Talk to me a little more when you say, what is the threshold? In terms of sizable amount of data that's showing you, that you believe in, and then you kind of move forward on that. So I'm not sure if there will be a straight-jacketed answer to that because it's contextual to what situation are you trying to solve for. And hence in that context, you'll see what volume of data will help you infer meaningful insights or not. So I think it's probably more contextual. We're comparing on objective to objective, actually. So great. I think I get a sense of how Microsoft is kind of leveraging data and kind of making decisions more from a marketing standpoint. I'll move this question now to Sagar. Sagar, you come from an FMCG background and data has been something that you have to build on now because FMCG is really about your small retailers, modern retailers and things like that. You never had the data. So give us in terms of how are you leveraging data from a business objective? So I think there are various use cases of data in the FMCG context, as you rightly said. And I will restrict myself to marketing and sales environment. I think first from the marketing environment, the first use case for data is to building efficiency and affinity of the consumer that you are targeting. So the whole data management platform and creating the whole data lake, I think the whole idea behind it is that how do you ensure there is no duplication when you are targeting? How do you ensure that the data that you are targeting is authentic and how do you ensure that the data that you are targeting has high affinity to the kind of customer that you are wanting to target? I think that's one major use case. The second use case is essentially the FMCG industry pursue a significant amount of investment that happens both on ATL and BTL. And there always has been this classical fight between sales and marketing when sales wants to spend money on below the initiative promotions and marketing wants to spend money on ATL. I think data really helps to solve it because essentially you have the data for the last thing for years and you can exactly predict with the data as to what input has really helped you grow sales. I will give an example on TataSold which is obviously one of the large brands in the FMCG industry that we have. We used to spend around 65% of money on below the line promotions. And when we get brought into marketing analytics, we realize that the effectiveness of that was much lower as compared to the ATL investment. And we cut back the money by around 35-40% over a couple of years and it has actually helped us in increasing the sales. Not only in terms of reducing the total amount of money because while there has been a reduction in the ATL investment there has been a bit of an increase in ATL investment. So I think it solves for an argument that I think data is the right point which will really clear a lot of arguments that happens in the bottom. The third use space is to really predict how the consumer is going to behave. So we have been using social listening very extensively to really spot the trends. Like one of the trends, couple of trends that we really picked was this whole thing after the pandemic about the spices and health. We realized that the searches for the spices and turmeric had really gone up and significant amount of marketing money on TataSold as a brand we put there and it gives tremendous results. So I think people are looking at source. So we got a range of sorts like Himalayan rock salt. We are also coming up with a sea salt which comes from the coast of Poramandal. I think those are the insights ahead of the time you are really picking from the internet. I think that's a great example of how you can use data. And the fourth use case in consumer research. Actually what happens in consumer research never tells you what he or she really means. People tell the answers which are actually wide answers to really, basically consumers tell you the right things to say they will never tell you what they actually feel. We have been extensively using the neural research because while your voice can lie but your mind can never lie. So we have all our attesting, packaging research or retail panoramic we have been using data there. Neural research really and that has not only has saved a lot of time and also the results have been perfect. And the fourth use case in go-to-market because what happens in go-to-market in FM city since you are spending significant amount of money in non-performance marketing or awareness. So what happens because of that while your cost of acquisition is lower there is significant leakage that happens within the entire funnel. So how do you look to build an entire value chain from the factory till the end retailer you are ensuring that the supply losses are minimized. I think there are significant use of data which really helps you to do that. So I would say among various things these are the four or five things which between sales and marketing significantly helped us to build a robust business growth. Great. I think you've been leveraging data in all facets from social listening to actually looking at your spend in a way of BTL, ATL prioritizing that. I'll take this question now to Apul. Yes. So, yeah. Super. So I think yeah, so what I have kind of, you know, in a way notice per se overall is catching up from Sagar when the lockdown started certainly I think the only category that was selling was groceries. I saw certainly businesses actually trying to become grocers and actually every business from a travel to everybody else wanted to survive and started selling groceries overall. So the good news overall all of that pieces that you know why grocery was the largest selling category and actually is by the global supermarkets the largest category selling online today from a business standpoint what has interestingly happened is how the percentage of online purchase behavior has changed, right? For example earlier total online sales versus you know your sales which was totally versus online sales you will see a bracket of 8 to 15% or globally, right? Now suddenly this is jumped from anywhere between 22% to 25, 26% which is a dump like within last couple of 5 to 6 months, right? So that's great one. The overall strength of this whole segment retail e-commerce is right now at about 3.53 trillion globally, right? That's immense amount of you know traction online.  If you're not online, I don't think in the near terms you're going to be relevant because today with pandemic one thing that it's shown us is that you know probably physical real estate is important but digital real estate is even more important. Now we are bringing services to people rather than you know we have the services but if we don't take them to people I don't think we'll be able to survive and scale and overall what I've also seen what I've seen is you know like the mobile growth has also increased you know the way people are using mobile you know today 51% of the entire traffic globally is mobile so if you don't have an app or you don't have a mobile sensitive website and you're not engaging with users you're not talking to them proactively across platforms, across channels whether in terms of a brand conversation or whether in terms of a purchase conversation or whether in terms of an advocacy or a feedback conversation. I don't think you'll be relevant in the present times. So the good news overall is that yes there is buying which has come back from a certain null of no buying happening online platforms like us which is web engaged and a lot of other products have become more important. What I feel I think the struggle going forward per se on a data side would be I think people yet as rightly mentioned by Sagar the data lake right we yet don't know how to sync together the entire 360 degree user profile with all right nuances underneath because if you don't have that I don't think we can see data in the right way we want to in terms of analytics and trends and so on and the trends we need to make realities right if what is the point of a trend which is not actionable right so if I see you know like a bounce rate is about 40-50% I need to do something about it that's the game right. So I think three key pieces that I feel one making sure that we have the right data in the right format at the right place in a degree fashion as a form of a data lake both online and offline together because you have the same customer with online and omni channel experiences it's not two different users. Number two is how do we see those trends across you know the funnel or whatever you want to call and three is how do we leverage that data or insights to make them actionable to you know you know convert the user and then repurchase and promote advocacy brand and so on support so that's my kind of take on what it looks like today. Right. We will come back to you with the follow-up question but I'll take this and move this to Anika now wherein again you know we are seeing as in health you know and health insurance what is it that you are doing you're sitting on a landmine of data you have a lot of data what is changing for you now in terms of data-driven strategies So you know COVID hasn't really changed anything frankly if you were in that business before you've sort of just expedited your journeys So Sagar spoke about the data lake Abur spoke about the data lake I think the single biggest thing that we've done in the last 12 months or so is to get a unified view of our customer data and when we say that we are sitting on a mine of information about our customers that's actually true because when we onboard a customer we have a lot of personal and demographic information along with that we have a lot of health customers and as customers stay with us for longer we actually accumulate a lot of data about them so what we've done as first steps actually is having a unified data lake in place with all these variables thrown in I would not go in a lot of detail Sonya on a lot of use cases because everyone's covered but from a digital business and use case point of view we take a 3-pronged approach we build use cases for customer acquisition we build use cases for customer experience and we build use cases for efficiency so whether it is growing the funnel or whether it is improving cost efficiencies on that funnel or driving up experience and hence improving conversions I think that's the 3-pronged use cases that we speak about and execute in the business I just have one question when is this going to be a reality where since you gather a lot of information in terms of health it could be customized plans coming to you do you see that happening sooner or later now that you have a unified view so in the next couple of years a large part of the challenge also is the way insurance pricing is done Sonya so you pool for a risk right and in that risk pool you've got millions of people with varied risks coming in and you know one offsets the other having said that with a lot of data coming in and the usage of IOT data also coming in at least at base level you know pooling of customers and segments of customer getting similar pricing should be a reality soon one on one hyper personalized plans I would say are still a few years away even if you have the data fantastic great to know that there is some we have something coming up soon I'll move this question to Sushant Rohfers and again another company that is sitting on a lot of data of how are you looking at data and data driven marketing and strategies and especially post the pandemic what is changing for you Sonya we are an e-grosy platform and data sits at the center of the business at the heart of the business data helps us to understand our consumers better the behavior on the platform better and this also helps us to kind of write customization and better platform experience so that retention on the platform is stable or goes up very recent example pandemic where data made a change or made us change our business strategy or marketing strategy when the lockdown started I mean we were on the fortunate side we experienced a massive surge of traffic on our platform everyone wanted to stock up and buy groceries because things were very unsure so over a period of time when we analyzed the data we realized that the entire consumer behavior on the platform has changed drastically we observed few data points like people who were aware non-priors came back to the platform people who had lapsed out came back and started engaging with us again the cart composition changed people started spending more on necessities and less on indulgence cart sizes grew so the number of items in the cart went up because the in-home consumption increased the other part of these are data signals that you get the other part of data is through insights when you directly having one-to-one conversations with your consumers across cohorts we figured out that particular time, safety and value for money was the primary anxiety of these consumers so all our marketing communications were also customized as for those anxieties as we speak things are getting normalized and this is changing so data is very critical for us it is not only important from a marketing standpoint but at an overall organization level because it does impact your supply, your inventory your category, tech for product innovations so yes, you can't escape data and it definitely drives your business strategy thank you my next question is basically that data gives us numbers, proof points to make rational business decisions how do you balance rational versus emotional decision making something that you really feel from your gut and I will open this up to Isha how do you look at balancing data and your emotional gut, what's happening there thank you Sonia for that question I think as you know everyone just spoke in the group for us definitely there has never been a tipping point on data driven business decisions given that we are in the business of selling data driven decisions so for as if I had to choose I will always choose data over gut but having said that I think we are currently in a situation where most of the organizations and even situations we have been talking about pandemic we are looking at gut being either data plus or data solving being the situation of being gut plus I would say that you really cannot pick one out of the other because if you talk about numbers they give you a great jumping off point but ultimately we are in the business of consumers ultimately we are talking about purchase patterns, we are talking about consumer journeys they have a certain human element attached to them so yes data is super crucial it will be more about if I have to talk about strategy then as bad as false data or the wrong source of data equally bad could be the stubbornness on gut so thus the emotional side of it and the gut size of it it needs to be fairly balanced with data and what we have seen at NEPA after working on case on case and different studies and Sagar talked about this situation of consumers never telling us what they really want and the journey for us has moved from say claim data to now more neuroscience techniques and more passive data and behavioral data captures but they have been trickering themes when you talk about data and gut in particular like there is no magic formula in terms of proportions but if I have to talk about guidelines that we propagate to a lot of our client partners I am just speaking agency voice but the first one is that we are trying new things something that we saw during covid so creativity that is exactly where the marketing dividend was irrespective of what data was saying or gut was saying creativity really helped so the first thing is trying out new things when you are in the debacle of choosing data versus gut the second would be do not blindly trusting either like data could be a great trust multiplier it could be a great gut multiplier versus gut when it's really telling you what to do and you have the data which is just not speaking as your intuition is so do not just going by what the pivot tables are really talking to the numbers if I have to give a very simple example of again pandemic because that's the most recent where we can align both of them could we imagine we believe by gut or by data that a very nice looking decadent moist cake is something that is going to attract a consumer it completely failed like people really wanted everything to be health they wanted to know what's inside it they wanted to know what is the ingredient inside it because every business suddenly became health business right from food and working out to even something that is not even remotely related to health so that's a very simple example of where the gut and data sort of completely failed us the debate sort of failed us the third guideline that I have been at least noting down for myself given that we often come at situations where they are asked this and know this is what the marketing budgets are this is what the creative team is saying this is what the content is at but your data is not speaking in line so the third is that you know gut definitely improves with age and experience the gut definitely improves with more and more use cases so more as we go along gut and data definitely start talking at least remotely talking badly to each other and the last one you know coming back to what Apple quoted to what even Sagar quoted and Annika quoted about you know the whole you know the side of things of technology that we have but realizing that we are dealing with humans keeping the business still human and then taking that you know that rational divide of data and gut is where I leave it at not choosing really between the two but seeing how one is helping the other so I think the take out for me is definitely data first but don't ignore your gut as long as you're experienced yes yes okay I will actually take this up to Hitu what is your experience being a data plus you know is it emotional is it rational what is it that you guys are doing at Microsoft so let me just start by saying there's no arguing with the saying that data is the new currency I think we heard it across all the examples that we've said it is practically driving everything from business decisions innovations to literally our everyday living but I would say what is equally important is that you balance that data with human touch because yes in a marketing context data is critical to our marketing efforts because it helps you identify audiences boost your creatives create demand even before it exists all of that goodness that we just spoke about but using data can be tricky because it often misses the context lean on it too much and your your messaging could become emotionless or worse tone deaf to what's happening in the world and don't use enough of it and you'll lose precious insights into your audience so I'll say two examples where I would say that it is both a for or a friend there's I'll use a recent example there was a post which has been doing which was doing the rounds on LinkedIn very recently which was highlighting the flip side of leaning too much on an automated model I think it was a cosmetics brand from the US and suddenly they started serving ads for the black for black beauty products to non black communities because they were interacting with a number of posts on social media themed around racial injustice now the algorithm that the company had built was clearly using rules to bucketize people based on keywords volume of engagement but the algorithm was missing or could not understand was the developing situation in the world that provided the context of why these non black people were interacting with those posts so in netting it out I would say you want to let the data inform but not dictate your actual message or your creative or the approach that you're taking but at the same time let me take another example and there are multiple such instances where data or advanced technologies like AI and ML they are playing a big supportive role in the world of marketing but in creation too I'll take an example of Disney one of our customers and they're currently using AI to tell greater stories so they have AI based auto encoders to actually understand how audiences respond in real time to their films the technology actually uses a night vision camera in movie halls to conduct sentiment analysis on our facial expressions you know to detect emotions like fear or surprise so here you're using the data or the technology essentially to be a co-creator with your content it is influencing or it is telling you the content that you created or the storytelling that you're doing whether it is effective or not so in netting it out to me data is a guide post not the end game to keep your decisions and messaging real so it's a blend of the two both of them so I would say still human intervention is very very important in terms of making data driven decisions also pure play automation is something that one needs to be kind of very about I'll move on to the next question and this is essentially addressing a lot of brands today are wanting to go D2C and also from a perspective of that not all of them can leverage an automation stack or a platform because of the efficiencies you're talking about a million transactions you know and if there's a brand that's just making a headway into the DTC kind of space when do you think should the brand launch in terms of making the investments and what should be the key takeouts for them when they're doing that right so I'll open this question again to Sagar because we are talking FMCG and FMCG is not typically people who collect organizations that collect data so Sagar over to you please on this one I think that's a very valid question Sonia during the pandemic one of the things that you know everyone wanted to buy from the companies directly and you know the whole buzz in the FMCG circles was that you know we have really missed the bus you know we never tried to do D2C but I think one of the major points that we really missed that time is that let's not confuse an exigency for a business trend and you know many companies have tried and we realize after 5-6 months into the pandemic that it's not really panning out the way it does so my advice to anyone who really wants to go D2C is to really first look at the business model because I think we shouldn't put the card before the horse it should actually be the other way round so fundamentally if you are looking at an FMCG company just in offline universe you are selling through like millions of retailers you are selling through an offline modern rate you know retailers like Adi Mart or Big Bazaar or Reliance similarly I think it's exactly the same way it will also pan out in the online space primarily because of the economics and the aggregation of it having said that as a company you need to be very clear as to why you are wanting to go D2C and while I would believe that there are no right or wrong answers to this I will tell you the way we are looking at it because you know I think there is a thought and there is thinking that is behind it we believe that the D2C should really allow us to build quality audience because what really happens on most of the platform people who are coming today on e-commerce platforms like a Grofus or a big basket or an Amazon there are light consumers who keep shifting between platforms and they keep shifting between brands I think what as a brand you are missing is the depth and the quality of the consumer who is going to buy your brand consistently so and you can use those consumers who could be lesser in number but you can use those consumers as micro influencer for a brand for a company like ours which essentially all are offering based on nutrition it makes a lot of a lot of economic sense so the way we look at it is that you know as long as the D2C model is operationally profit neutral and the cost of mentoring the platform is what we consider the marketing investment and we are building say a 10,000 customer hypothetically but they are buying at least 5 or 6 ranges of my products regularly I think they are doing the purpose that we want they are serving the purpose that we want and you know then the same consumer you can use for market is that the same consumer you can use tomorrow as micro influencers you know so there are a lot of the use cases that you can have but can I have like 5% or 10% of my business coming from D2C operations I think more from the cost and the time point of view it doesn't make sense so I would urge everyone who is wanting to take the D2C plan to essentially first look at the business logic for it and then really start looking at the tools like automation or creating a plan UIUS which is great that's the way I would look at it So another follow up question in terms of do you see this trend that people are buying online because they really not getting into retail stores is just a trend and short lift or you really feel that this is going to happen because at the end of the day we are talking to the younger audiences and the future family makers and all of them are very very comfortable with digital so from a long term perspective what's your thoughts on that well I think the jury is still out and I will share what I think will happen I personally believe that this as a trend is here to screen I think the I mean once you are you are basically once you are addressing the first barrier to online purchasing people and understand how easy and convenient it is to really buy online consumers would want to spend more time on things which are more meaningful as we are looking at the audiences which are younger we are talking about the JNZ and we are talking about the millennials right we believe that they are wanting to seek more experiences and buying grocery going to the shop and buying grocery that's not an experience that really counts I think for that audience so I believe that the audience which has really come to the online platform I don't foresee that audience really restraining significantly in the near term that's what my opinion would be I think only time will tell how it will Okay great I will move this question now to Sushant what are your thoughts in terms of D2C and when do you think companies should actually take it on what is the kind of size that we are looking at from sales perspective that makes merit I mean there is no right or wrong answer here I get this question a lot many times that what is the size of the base that you should look at you know for data automation and you know see it's any and every company which is into the consumer space and is looking at the kind of competition the clutter that is growing in each of the category you need to put data very very look at it very seriously secondly you need to invest or build into that a plunge into that ecosystem it also depends on the objectives and the growth trajectory of the company or the vision of the company initially you might not kind of invest heavily into building that ecosystem but then it is important for you to understand your consumers better so that you can have that business growth so therefore investing in a data automation data ecosystem is very critical to understand your business and your consumers better sure so you're saying that primarily it's just not about sales but to understand your consumer behaviour is also another big take away when you look at automation tools and marketing automation yes I think you have to at some point in time build that ecosystem because otherwise it will be very difficult to kind of gather that intelligence of consumer and because see at the end of the day today it is all about customization I mean each consumer on the platforms behaves very differently so from an offering perspective from a communication perspective you have to drive that customization for better experience fair enough I'll move this to a poor now what is the minimal threshold if you want to be light in terms of an automation platform a marketing automation platform we've got views here Sagar essentially is spoken about it has to be in terms of a long term view before you get into it and we have Sushant also saying that for us to better understand and to target it kind of works so what is the minimum threshold if you were to look at the marketing automation stack what would you recommend thank you for the question Sanya I think what I'm hearing across the panel is that you know we have data and we have context to that data and no decision can be taken without seeing data in a context of sorts I think that's the larger message that I kind of read and that's fairly correct as well like for example nothing please absolute right for someone 100 could be large enough for someone 100 could be very small and it changes with time it's a multi-dimensional sort of a scenario so my take on this per se this is my perspective from what I see across domains that we deal in I think there are two sides of the funnel for any business I think one is called acquisition which is getting a customer onboard to actually be aware and be familiar with the product category brand and second is retention which is basically getting to purchase and then there's loyalty and so on that's how I break up I think the way to take a decision whether you want to deploy a marketing automation system or not is basis where do you stand in terms of the impact on the funnel if you're yet figuring out very early and you're a small business again context changes right I'm assuming someone who's yet not figured out the acquisition model is very early in its own business whether we do to see or not or we to see businesses then they need to focus on first actually enabling some sort of awareness and familiarity about them making sure whether you know if there's a real estate shop then get customers inside that shop if there is an online shop then we're selling a product or service then making sure there's some awareness and familiarity and people are getting onto your website checking things out, playing around get that part fixed first if that is fixed first and you see some bit of trend of buying happening right which basically is customers saying hey you know I read about your product or service it makes some sense and you know a few of them end up buying and you see that trend growing going right and before that I think you have a lot of analytics to catch up because you're looking at trends and so on and optimizing for the total funnel to get people in I think till then I would always suggest anybody should use very easy and free products very easy light very very analytical very data driven products and optimize on the top of the funnel now once you're in and you see some buying happening now first again as I said I would say for someone you know 100 purchases be something like for example a grocery business right 100 purchasing might not need anything but for a real estate business 100 business might just be everything that they wanted in a quarter or in a financial year so you know depending on the product category whichever you fall into if you feel that there is some traction and trends being seen and people are buying I think that's from that place I think it's a very contextual thing that you figure out a way that if someone's buying how do I make sure that he comes and buys again from me because depending on the product that you have whether you're buying an insurance right you will either renew it or purchase somewhere else the next year that you're buying grocery if you bought it let's say let's say you bought diapers which has a certain pricing size you're going to replenish it right so you're going to either buy from this platform product at same business or you're going to buy it from somewhere so once you have some buying purchase happening you need to figure out how do you enhance cross sell upsell sort of use cases your loyalty and you go into you know this funnel buying funnel and I think that's when you actually start leveraging a marketing automation or an engagement or any of that sort of platform till then I would always advise keep it simple focus on your core practices core values look at more data and trends and use as much free products it is enough free online you don't always have to pay that's the beauty of SAS and what we're building globally right great of course so primarily look at your funnel and essentially invest as you go forward when you say see traction I have a follow up question very quickly and that's really about building data your first party data right and I will actually take this up to Sagar what is it that you're doing in terms of building your first party data and Anika since you have a lot of data any advice for us Sagar yeah so Sonia as you as you would know for the most of the FMCG companies you don't have first party data because the actual transaction is happening at the retailer place and large part of the retail universities in moment box stores where anyways you don't have the data so one of the things that we are doing for building our first party data is we have created a content destination for the start of the corner where we have we have created content which really essentially is created around the theme of importance of Indian nutrition in everyday life and we believe that psychographically that's a big trend that many people believe eat local, eat seasonal is globally a very very big trend and if you are looking at from the Indian context people always believe that Gharaka Khan and the wisdom that was passed from our grandmothers I think there was something very valuable about it and this platform essentially you know doles out content on this we have been working with big influences like you put you know and you know we keep having various content ideas around this particular thing we had doing something called as Haridin Haldi we had around around 300 content creators who created innovative ways of using Haldi in everyday simple data I think what this is doing is we are getting a sort of audience on this platform who is psychographically and behaviorally homogenous I think what if you have to build your data strategy fundamentally building a demographically homogenous audience is very easy you can just go to any third party data provider and you will get that but building a behaviorally and you know psychographically homogenous audience where you believe that they will have higher affinity for your brand I don't think there is any solution that really exists and that is a fundamental starting point for us we have been on the journey for close to now and we believe that it has paid us hugely we get around a million of audience every single month on that platform out of which at least 20% of the audience is organic and understanding that audience regularly time and again and building lookalike audiences from there what it is really helping us is improving both the efficiency and effectiveness of marketing campaigns and that's the way we look at data actually pass this on to Isha Isha what are your thoughts in terms of collecting first party data I have almost a similar opinion already cited in terms of the homogeneity of data that we are talking about but I would echo strongly the point that Sagar just talked about which is the psychographic side of it and the problem that we are struggling with I mean we are talking about clickstream data a lot of third party data and secondly psychographic because the social cultural nuances in the country are so vivid that if we just have to depend upon third party data which is existing looking at that ROI is going to be like a like that's not the best ideology you know the actionability based on just the data which is existing by different sources is not the best ideology so one source which is a challenge there is definitely not an answer but carefully deriving the algorithm of answering two questions which is where to play and how to win which is which exactly are the course that you are playing with and what are then the touch points and only channels the different channels that you are using to really crack them up is the way to go so one source and psychographic is definitely where my heart is in terms of answering your point on first party data right and what are the great touch points you can gather that kind of data is it by way of surveys I mean how do you get this data in that specific yeah so so multiple ways of gathering it of course there is primary data which is by the virtue of doing surveys by interventions etc etc you have to carefully invest in them not necessarily existing also very important you know something that we have been seeing that everyone you know one request that keeps on coming to us which is yes we want to do something in digital and we want digital data and we want the online data but a lot of times not really like you know not really knowing that where in the whole you know the funnel that we are talking about digital really sits is digital really impacting the top funnel is digital really impacting the bottom funnel is making the product look more Instagrammable really going to lead to a purchase is you know investing into a YouTube vlog video really going into a purchase so that at least to the second point which is primary data is definitely not enough because there is a face the enemy of what the person is claiming versus what they are actually feeling secondly click stream data which is widely available in app data that is you know a lot used in terms of fusing the data to the responses but if you look at you know multiple sources that we are discussing one point that doesn't changes quantifying the ROI which is how powerful each touch point is in the journey how powerful each touch point is in that only channel path is I think the question because the sources are like a plenty today like the brands agencies we all have a lot of data and the second is the efficacy which is quantification of the power and secondly what is the effectiveness of that data in the whole part to purchase or even the part to viewership now because content is what we are consuming like we were purchasing so so you know it's actually both part to purchase and part to viewership because we used to talk about ropo and then we used to talk about ropa now it's like it's the new term is are you know people are researching anywhere and purchasing anywhere the whole part to purchase is broken so so vividly that quantification and efficacy is super crucial okay great so I'll actually be running out of time and we have some questions here so we have to drop the fifth question that we plan so I'll read the question and then you guys can decide who's going to take this this is Akash Singh and he says organizations have built multiple sources of data how can they avoid the trap of data silos for example different data might be related but the teams may not find the trend because of lack of experience I'll leave it to the panel to kind of take this on Anika would you like to take that on sure so I think we all spoke about the fact that you may have a lot of data but it's all broken and fragmented and we did speak about getting it all together into a data lake I think that's the first point and then we also spoke about you know how different teams will use data I think the objectives for each will be different and if you can define the objective that your team carries it's much easier to then create use cases so for example a very simple objective could be let's look at the customer lifetime value and see which are the data points out of the data sets available in our data lake which impact that the most and then hence a communication team will you know use it for channel orchestration and acquisition team will probably use it for creating local likes and adding third party and psychographic data to you know to increase and improve conversions and somebody else may use it to drive up profitability so I think two three key things one have the data in one source have the larger organization objective and your teams objective very clear keep always a profitability and a lifetime value lens and then build your use cases on that data fantastic and this is coming from someone who has a unified you know like a look of the data that's available Anika you spoke about it initially yeah I have another question by GK and that goes he says do you have a view on social dilemma the movie that was on Netflix you need stronger regulations for social media yes we do but and that's where we get all our data what is a point of view there Hiddu would you like to take that who won't have a point of view on it is yeah and I think there is enough out there in terms of the movie itself the documentary itself says I think the important thing is when you're talking about technology as I mentioned earlier it can be a for it can be a friend what is and when these companies have started and the documentary says it I don't think anyone was intently there wasn't malintention in terms of collecting that data or using it for the purposes that they work but given if there isn't governance and if there isn't someone who's for lack of a better word using policing there has to be certain industry norms of how we are using data and that is very critical and you are seeing that you're seeing that with the GDPRs and various others across countries but how how effective is it for each company and for us as customers to actually invite by them use them and make it real and not as a concept I think that's something which is evolving and we have to wait and see okay so we have to have policing for sure but when I saw the movie I actually went off Facebook and Instagram instantaneously and I said well I'm not using it because at the end of the day what you're discussing is also getting displayed and relayed as ads so it is kind of a bit scary you know just conversations converting to ads but I think just to kind of sum up today's conversation thank you guys you were a fantastic audience and I think the key take out for us has been that it's going to be a data driven world as we move forward we need to balance ourselves in terms of definitely be data plus and gut plus, gut plus more from your experience and what you feel is right move towards to what Anika said that you look at a unified view of data coming more from what is it that you want out of data, Sagar primarily talking more about does it mean make a business case a poor augmenting it by primarily talking about a lot of free tools wait it before you kind of deep dive into it see some traction before it goes and obviously Sushant also had a lot of great recommendations for us from someone who was coming from Grofers which is really a great marketplace and you know they sit on a lot of data so great Friday to you guys and everybody who came in and watched this episode of Martek thank you exchange for media for getting us all here thank you Priyanka you were great and you got us all together thank you and goodbye good bye everyone have a good evening thank you


Where are we actually? Okay, glad you asked, because I did think a little bit further than you, since you've started driving and you've no idea where you're going. I thought since we went to the boozer in England, we could this time continue the trend but go to a vineyard. Ooh, that's a... Keep it classy. See now, look at this, right? I kind of feel like, yeah, all right, like we did the pub before back in England. But I do think this is a slightly better view. How qualified do you feel? Not at all. I know you're going through this. I know it's red or it's clearish kind of colour. It's nice and it's not nice. It's one of those, very binary with my wine tasting. And I have an upper limit of about five pounds or eight dollars. And if it's more than that, it's probably not worth it. Anyway, right. So since we're here, we tend to talk about the web and today I think is no different. I want to talk about libraries and frameworks. Ah, yes. Because you're not big on the frameworks, are you? No, and neither are you. On the other hand, I am not big on the frameworks. Yes, I don't think there's going to be much of an argument, but I do want to talk about it because it bothers me that I seem... I perceive that the default state of developers is, I've got a blank page here. How am I going to fill it out? Ah, I need a framework. Which one do I use? That is a problem I have for frameworks that they have way of starting projects. There's a kind of expectation to use them from the offset. And I think if you're thinking what combination of frameworks should I use to render this blank page, then I think something has gone wrong. Yeah. For me, it's entirely from a performance point of view. Well, no, it's not actually, but okay. Step one, performance. If your page has to load a ton of JavaScript in order to make a request for the actual data it's going to display, you've lost performance. And you can sort of say, oh, but next time it's going to be cached, it might not be. You might have changed code, busted the cache. And it's an assumption that somebody's going to come back again. Right? Well, it's your goal, I would say. It's your goal, but you don't know that somebody's going to.  That's true. No, it's true. You might not. Yeah. And stuff falls out of the cache all the time. Yeah, exactly. So not the service worker cache, though. Oh, human service worker. Here we go again. Service worker. One trick pony, Jake Archibald. Come on, but it's got the cache. You can rely on it. All right. Okay. Performance that notwithstanding. I think for me, it's about code ownership somehow. It's about a level of trust that I don't necessarily feel. And what I want to do is I want to be able to feel like my application code is the thing that's running, that I'm not running through something else, that I don't necessarily understand. Running through something else is fine, because that's what a library is, right? That you've got hold of both ends, and you're running through bits of library that you don't understand. But that's fine. Because if one of them starts misbehaving, rip it out, either code it yourself or find a replaceable library. But when you're going through something else, to kind of get something else, I think, with the framework, and the framework will then do little bits of, it'll give you scraps, and then you do something. Please, sir, can I have some more? I'd like to work with this application. Can you please send this data up in it? Get out. But then the frameworks, you're kind of, you're sat in a tiny bubble of the overall application with the framework. And I feel like to get the most out of the framework, you need to understand how the framework is built. And these frameworks are huge. So it's really good to do that. I actually feel maybe, and maybe this is wrong, but it feels to me like it's a kind of, the decision is an ergonomics one. Like a developer is saying, my ergonomics trumps the user's requirements.  And my whole approach is very much the other way. I'd rather go the extra mile and all my users benefit than my life is a bit easier, and I'll take some of the bad performance or the tax of using that framework. So I don't think that frameworks are inherently evil and to be avoided, but I think you want to be able to transition to one and say, yeah, now it feels like we're getting to the point where we're going to reinvent that. And I think you can only do that when you've got to a certain point with the build. So for you, it's start lights, start with libraries as when you need them, and then make the jump to frameworks only if you have to. Agreed.


Hi everybody. How you doing this morning? Good. All right. It's actually really special for me to be here because my whole beginning of my life essentially in social entrepreneurship began with SoCAP. It actually began with Good Capital and Kevin Jones. He hired me, thankfully to be an intern for a couple months. And so it's actually really cool to kind of be back in the world and be speaking up here today. So I'm excited to talk to you today about about social funding. A lot of people call it crowdfunding. I actually think it's a terrible word for the industry, but we can talk about that later. But what I want to talk about today is how we're actually changing finance for good. And this is both permanently and for the better. Double entendre, totally intended. But to give you some background, you know, many of you guys have heard and you go go, we're now at it. We're like old news, you know, we're in every country. We're distributing millions of dollars every single week. To every industry, entrepreneurs, artists, causes, you name it. If you have an idea, you can use IndieGoGo to raise money. And where IndieGoGo came from was this place of wanting to democratize access to capital. My co-founders and I saw ideas going unborn every single day, not for lack of heart and hustle, not even for lack of an audience, but simply because they didn't know the right people. And so we wanted to blow that model up and make you not have to be dependent on knowing the right people. And that's why we created IndieGoGo. And what actually IndieGoGo became in the early days was this incredible alternative form of finance. I would actually like to say that when the credit crisis hit back in 2008 and 2009, that actually helped IndieGoGo. Because it forced people to look outside of banks, look outside of VCs, look outside of the traditional financial systems to see where else can I get money to get my ideas off the ground. But then when the crisis subsided, I actually started to get a little worried. Are we a counter-cyclical company? Are we going to die when the economy comes back? And actually the exact opposite happened. That's when really things started to flourish. And the reason is, is that IndieGoGo isn't just addressing the most obvious risk, which is financing risk, when you're an entrepreneur, a social entrepreneur trying to get your idea off the ground. What we've actually found is that IndieGoGo also addresses the two other major risks that you face when you're trying to birth an idea. And that's market risk and execution risk. And it's exciting because this is why I think IndieGoGo is here to stay. And why social funding is going to be part of the entire fabric of finance and actually make finance a lot more sustainable. So what do I mean by market risk? What am I actually saying? So a great example of this is gravity light. There's a light that these designers out of London had actually created a light where 30 seconds of lifting creates 30 minutes of energy. They saw it as an alternative to kerosene in the developing world. A lot safer and a lot cheaper. They couldn't get a venture capitalist to call them back. So what did they do? They did an IndieGoGo campaign and they raised $300,000 and in the process basically validated that they had a market. Kitepatch, same thing. What they did is they actually had raised some money, but they used IndieGoGo not just to launch the product but actually to build a brand. They ended up raising over $500,000. It's a kitepatch that if you put on your arm it emits the signal, it makes you invisible to mosquitoes. Much better than mosquito nets. But they used IndieGoGo not just to launch a product and raise the money but actually to build that brand to reduce that market risk. Same thing with Kinoma Create. This actually was an idea which is a JavaScript toolbox where it was created by Marvell, which is a $5 billion company. But they used IndieGoGo as a way to kind of build a community around the product before they actually launched. So thereby creating that market before they launched. Same thing for Lavame, a mobile shower for the homeless. When they launched their IndieGoGo campaign they actually proved that this was something that could stick. And a whole bunch of cities started calling them saying, when can you come? When can you bring your mobile showers to my city? And Solar Roadways. A lot of people have heard of this one. Too young, too young, yes, young. People in the middle of their life, inventors out of Idaho, were passionate about saving the world. They believed that if we could actually make all the roads across the world solar powered and cover them with solar panels, we could actually reduce the carbon emissions by 85%. And make the roads a lot safer at the same time. So they ended up using IndieGoGo. No, it's going to cost trillion. No, it's not going to. They used IndieGoGo to raise $2 million and no, it's not going to just cost $2 million to change all roads across America and the world. But it was basically the beginning and it actually put their idea on the map and actually earned them the respect. From the press, from the media, from partners, from people who are actually now focusing on trying to make this idea happen. So those are examples of how these campaigns have used IndieGoGo, not just to raise the money, some of them didn't actually even need the money, but actually to build, to create that market and thereby reduce the market risk, prove that they have an idea that is worth coming to life in the world. On the execution risk side, sorry for the blue line here, we have plenty of people who are now using IndieGoGo, again they have the money or maybe they don't have the money, but what they're doing is they're using it as a way to get smarter faster, to really test all of their assumptions and therefore refine their product market fit before they actually launch their idea. Skybell here is a perfect example, it's a smart doorbell, video doorbell. This guy had a whole road map of the features he wanted to launch and based on his IndieGoGo campaign and based on the feedback from his funders, he completely switched a lot of the prioritization of which features he needed to launch. Same thing with Cooley Cooley, which is a super food snack, these young girls discover Moringa, which is a very special element that can actually, it's very healthy and cheap. They were launching these new bars, they used IndieGoGo to raise the $52,000, but they actually in the process learned who their early adopter segments were, it was yoga moms shopping at Whole Foods, which was an hypothesis, but their campaign actually confirmed it. Same thing with Nick's underwear, this is high tech underwear out of Canada, women come ask me what that means later, it's awesome. This woman was super excited about launching her underwear line and she had three versions of her underwear and she was convinced one was going to be a best seller, but she threw in a third just because she thought it was cool and sexy, guess which one became the most funded perk on her campaign? It was the third one that she thought of as an afterthought. So she actually completely discovered who her customers were and actually the customer mix and she reshuffled her whole production schedule based on the demand proven in her IndieGoGo campaign. Same thing with Jibo, this is the world's first family robot, they've raised almost $2 million. Dr. Cynthia Brazil out of MIT launched the IndieGoGo campaign simply because she wanted to learn who her customers are and what they wanted to use this family robot for. In her mind she thought it would be like the personal assistant for the whole family, what she learned is actually most of her funders are dudes and most of them don't know how to cook. And so they're going to use this robot to learn how to cook and that's why, and they wanted someone to talk to them and tell them what to do, how to follow the recipes. She had no concept that that was going to be the use case, but she learned that all through launching this idea, letting people fund it and tell her what they wanted to do. Same thing with Misfit Shine, these guys are actually here from the Bay Area, they launched an activity tracker and the whole point of it was to have an elegant solution to tracking your calories and your workouts and all this kind of stuff. So it was going to hide in your clothes and totally be hidden. In the process he actually learned when he launched his IndieGoGo campaign he actually offered his shine in different colors and actually learned that people were willing to fund the black version way more than the silver version, actually willing to pay $50 more for the black than the silver, he learned this all by swapping perks in and out and seeing what people funded and what they didn't. And also in the process his funder said, you know, he said, what else would you guys like? And he said, we really want bracelets and necklaces. And he started to fight with them saying, well the whole point of this is to hide in your clothes, why would you want to wear it? And then he realized he was fighting with his customers, which as an entrepreneur, you know, that's a very bad thing. So he said, okay, I'm going to get humble for a second, let's prove it. And so he threw up a perk mid campaign of bracelets and necklaces and it got claimed overnight. And he completely unlocked a whole new revenue stream and accessory line, et cetera, that he never knew existed. All because he ran this campaign in a matter of weeks. So he likes to say, Indiegogo made me so much smarter, faster. No matter how much money I raise, I'm always going to do an Indiegogo campaign to launch a product. And this is one of my favorites. This is Miss Possible. This is a recent campaign actually out of two young entrepreneurs just graduated college. They totally believe that like dolls are awesome, but we need more options than just Barbie. And if we want to get more girls into STEM, why don't we make dolls that look like Marie Curie or Jane Goodall or Rosalind Franklin. And so they've launched an Indiegogo campaign. They raise money to launch their first doll, which is modeled after Marie Curie. But they've turned to their funders to decide what's next, who are the future products. So all of us are now voting, voting with our dollar on which dolls are coming next. It's a great way to market test. So as you can see, when you create a campaign and you invite the world to be part of the ideation and creation process and you allow them to vote with their dollar, literally what products, what features, what colors, at what price. You don't just raise money and reduce financing risk, which is incredibly important and valuable. You actually reduce the market risk, which is the risk that you're making something that nobody cares about or not enough people care about. And you're also reducing execution risk, which is maybe you're solving a real problem in the right way. You're just not getting the product market fit right. You're charging too much. You're including too many features. What have you? And so Indiegogo has become this really flexible and open and quick and easy and fun and intense way to learn all of this in just a matter of weeks. And so what are the benefits of this then? It's more than just, you know, what are the benefits of having less risk in the system? Clearly that's a positive. So what we're seeing now is we're seeing these campaigns actually using Indiegogo as a way to attract investment capital. When you reduce your marketing execution risk, you actually make yourself look better to the venture capitalists, to the banks of the world. Gravity Light and this possible both got an investor interest out of their Indiegogo campaigns. Lava May got a $100,000 grant from Google and Scannadu actually, which I haven't talked about, which is like this doctor in your pocket medical tricorder, which is literally from Star Trek days, but they made it a reality. They used Indiegogo to raise $1.6 million and right after that they actually were able to close a $10.3 million series A route. But it's also being used not just to attract a traditional capital, but actually to close the capital. So I actually met Tinkerbots, which is a robots for kids in Germany. And the guys behind that were actually able to close a million dollar venture round because they had written Indiegogo into their roadmap. And the venture investors were not willing to put the money into their company unless they knew they were going to do an Indiegogo campaign to product test before they launched. Same thing with Jibo. Their investment was partially contingent as well. So attract investment capital, close investment capital. The third is actually to make you spend your investment capital more wisely. So like I said with Kitepatch, they had raised money from the Gates Foundation. Misfit Shine had raised money from actually a venture capital, $7 million venture capital. And Konoma Crate came from a $5 billion semiconductor company. They used Indiegogo to really understand what products they need to build, what features they need to build, what pricing they need to do. So they actually are spending whatever capital they already have in a much more efficient and smart manner. And lastly, I'm running off out of time here, is it's also a way to stay independent. So we're now actually starting to see people completely bypass the traditional financial system. We have NYX that went right, got picked up for distribution out of her campaign in Hudson Bay, which is like the North Streams of Canada. This was a first time entrepreneur maker.  Cooley Cooley got right into Whole Foods, and Sky about completely passed the venture role completely. Apple came calling to them saying, we want you in our home get store when we launch. So the question is, does this mean traditional financiers are going away? What's their role? Is this their future?  No, I don't think so, and this is why. I'll hold you in suspense for a little bit longer. What's happened is what Indiegogo is actually proving is that cash is becoming a commodity. So whether you can get cash from the crowd or from an investor, cash is cash. It doesn't really matter. And so what matters then is what else can the sources of cash bring you? So clearly the crowd can lower your execution and your market risk. So what must the traditional financier bring? And they do bring relationships. They bring expertise. Indiegogo took traditional venture capital. I know it is definitely beneficial. So the key is what we see is the two types of capital, whether it's the crowd capital or traditional capital, actually working hand in hand together. And the way we see that doing is in two ways.  What I mean by incubation platform is that what we're seeing is because traditional venture investors, governments, et cetera, are looking at Indiegogo to try to find ideas that are market validated, they're bubbling up to the top, and they're actually using Indiegogo as a sourcing and a discovery platform. So that's why Indiegogo is literally in a merit-based fashion bubbling up ideas to traditional capital so that they can have better ideas to actually invest in. And the same thing on the market testing platform. We're now seeing companies, like I said, venture capitalists requiring that when they make the investment that their portfolio company actually run an Indiegogo campaign before they launch, that they're actually launching a product. The world wants, not just a product, they think the world wants. So the new role for traditional financiers then is one of amplifiers. So we used to like to say that traditional finance and finance is broken because it's inefficient, and it's inefficient because it's riddled with gatekeepers, and gatekeepers are just inefficient ways of allocating capital. But what we're doing now is we're actually turning traditional financiers into amplifiers. So when they're discovering ideas and putting money into them off of ideas that have already been community validated, they're bringing them out to the world. And they're, what I like to say, they used to have two jobs. One is to bet right, and one is to amplify. It's the betting part that makes their job really risky, and it's the betting part that makes them want to say no more than they say yes. And so because we reduce a lot of the risk from the equation, we get to allow them to say yes more than they say no, and then they actually get to do the job which they probably wanted. The amplification job is the job that is the thing that probably attracted them to become an investor from the beginning, as they want to say yes, they want to help companies launch and thrive and grow. So overall what's happening is we're creating a more healthier financial ecosystem because we're getting more ideas going. We're enabling faster failure, which is actually, we all know is a very good thing. If you can't raise money within a few weeks, if you can't prove that there's a demand for your idea, if you can't, your product market fit right, then maybe you're not ready, or maybe that idea isn't something the world actually wants, and so you can move on to the next thing and not waste the next few years of your life, and all your life savings on something that was never going to see the light of day. And then the ones that get through, the ones that the world is actually funding, are the ideas that the world wants. The ideas are better that are coming to life, and the way they're coming up, the way they're bubbling up is in a much more merit-based fashion. It's based on true market needs. It's not based on what a few people, traditional investors or gatekeepers, think the world wants. It's actually based on what the world wants because the world is actually involved in voting. And as a result, then we're going to have less waste because a lot of on the physical side, the products that are coming out are the ones that are actually wanted. And when you do an integrated campaign, you completely mitigate the risk of overproduction and underproduction. So you actually produce exactly the amount that people want. So in the end, this is how I think Indiegogo is changing finance for good. It's both permanently making it more sustainable by reducing risk and for the better, which is allowing more ideas in a merit-based fashion to bubble up to the top and exist. And that's all I got for you. Thank you.


Good afternoon everyone. This is Melissa with the stockswish.com and welcome. Welcome to Apple. I thought I would do an earnings preview on Apple. It has earnings out tonight at four o'clock. So let's go over it. What do I think Apple's gonna do? Well, it's anybody's guess, but I will tell you what it needs to do. I will tell you that if it does this, if it does that, if it does this, it does that.  Apple is still in a downtrend. I'm sure I'm the only one that sees it that way, but that's the correct reign. Okay? Apple is not in an uptrend. It's made a series of higher highs and higher lows and it doesn't have any meaning. Apple is not back in an uptrend. And no one should be an Apple long unless they've been in it for like the last 10 years. No one should be an Apple long for a short-term long trade. It's not gonna buy for a year, year and a half for a while. Unless they're in this as a core trade for years, like as an investment or something. But as a regular trader, as a swing trade, no one should be an Apple long. Okay? But I'm sure people are. Anyways, Apple has one of two things that it's going to do tonight. Well, one of three things actually. What Apple needs to do tonight, if it's going to go back in an uptrend, it needs to do it on the earnings tonight. And that I know. Okay? So, Apple really didn't do anything on the last earnings. It didn't. It was a nothing gap. It wasn't a play. It was still in a downtrend and held the downtrend. And it really wasn't a gap that was playable in either direction on the day of the gap in the earnings the last time out in October. So, Apple needs to correct itself back in an uptrend tonight if it really is going to, which means Apple needs to get up up to 600. Apple needs to gap right up to 600 tonight. And if Apple does that, it's an immediate buy. It will hold in the sky and rallying you highs this year. Apple's too close to correction now to not correct itself. That's why I know it must if it's going to recover. So, what does that mean? That means if Apple gaps down anywhere, anywhere at all, or is a nothing gap, the overall trend of Apple will stay intact in a downtrend and it will stay intact and it will be in a downtrend. It will continue down and it is in a downtrend and it will continue in that downtrend and be a continuation gap. If it does not gap up to 600 tonight, that's what it must do. There is some article in Yahoo Finance today actually about Apple being more bearish than bullish. It was the first thing I saw in public genre, besides what I'm saying, that that Apple, you know, is not going to recover. Now again, I'm leaving it out there because Apple could do it tonight, but it must. It must, it must, it must, it must, it must do it tonight. This is it. Okay? We're in a bullish market despite the fact we traded on the last few days. Okay? Apple didn't perform last year with the market, which did, both in the queues and the spies. Apple's been in a downtrend ever since the first gap and Apple must correct itself. It's too close to the number now here not to do it tonight at 4 o'clock. Apple must gap up to $600 and hold, and if it doesn't, if it gaps down, if it is a nothing gap, if it doesn't gap up to $600, if it doesn't do what it's supposed to do, it's going to continue in the trend that it's in, which is down. So it'll be very interesting to see what's going to happen. Very interesting. I'll know as soon as I see it. As soon as I see it, I'll know. Okay? Because the trend of Apple is still down, down. Okay? It doesn't matter that the 200-pery moving average here has made a little scoop. It doesn't matter the 50s up or the 20 or the 80. It does not matter. There's so much more to look into charts. So much more than pivots and moving averages. So much more information. So it'd be really, really interesting to see. And the Apple needs to do it if it's going to do it. And if it does, fine. I mean, I'm not invested in this. I'm not sure that I'm going to have nothing in it. But Apple's a buy. You want to buy Apple? If it gaps right up here, it's a buy. $600. And if it doesn't, then my overall call in Apple, the longer-term call in Apple that I have, the overall call in Apple is still intact. To the downside, targets everything. Everything I've been going over, everything I've been saying, still intact. Because it really has to do it tonight. And there's no more chances for it here now. So that, I know. We'll see what Apple does tonight at 4 o'clock. I'll be watching it to see even though I'm not in it because I love reading charts. I'm very good at reading charts and I want to see what it does. You know? Apple will make new highs this year if it corrects itself tonight back up to enough trend. And if it doesn't, Apple will be in the downtrend and break and break again and again and again and again and again and again and again. And my overall longer-term targets in Apple are all still in play and are in play right now. You know? We'll just have to see what Apple does tonight in the earnings. But it must make the correction tonight if it's going to. And if it doesn't, then anything it does is bearish, basically. So this is Melissa with the stockswish.com. If you'd like to learn how to read gaps, bullish, bearish. If you'd like to learn how to read charts, understand price, technical analysis, candlesticks, all of these things that really affect how you trade in your ability to make money because you won't profit in the market if you don't know how to read charts right. I know it's fun to read fundamentals and stuff on TV and talk to friends and everything else, but you've got to know how to read prices.  It tells you what to do and when to do it and when to get in and when to get out and when to do what you need to do. And what's going on? And remember, trends and things don't stay all the time forever and ever in a certain trend. Apple wasn't going to sustain an uptrend forever, okay? And it didn't. It broke. Now, if it's going to correct itself, it will very quickly here not tonight. So just like anything else, Apple was in a downtrend for the last year and a half. It could correct itself back in its uptrend here. Again, things don't last forever, but you do have to know how to read them in real time. It helps you take positions on and take positions off. Timing is important in trading when you trade. It's so important because it has to do with when and how you're making money. This is Melissa with stockswish.com. If you'd like more information on the next Golden Gap course, it's February 8th and 9th. Email me at Melissa at stockswish.com. We'll look at Apple tomorrow after Gaps Up Tonight and after Trades and we'll see what it does. Thanks, everybody. Have a great day.


Recently, I've made videos showing you guys the power of command line utilities like AUK and SID. Today I want to continue along with that journey. Today I want to show you two very powerful command line utilities. They are CUT and TR. So I'm going to switch over to my terminal and I'm going to show you guys the CUT command. What is the CUT command? What does it do? Well, it removes sections from each line of a file. That's essentially what it does. And when I say each line of a file, it could also be each line of some input that you direct into CUT. So you could pipe something into CUT. So let me show you a basic example of CUT. So I'm just going to echo something and pipe it into CUT. Let's echo, this is a line of text, exclamation point. And then I'm going to pipe that into CUT. And the most basic way that you use CUT is cut space dash C for characters and then one through 10. What this is going to do is it's going to go and grab the first 10 characters from each line of the input. Now, there's only one line of text in this case, but it goes and grabs the first 10 characters, including the spaces. If you wanted to see this on something that's multi-lined, I could cut dash C. One through 10 again, the first 10 characters from each line of, I don't know, how about my dot bash or C file? And that's how that would work. Let me clear the screen. So another thing you could do is instead of grabbing like the first set of characters here, one through 10, you can give it a character number such as 11 and then give it a dash, meaning grab every character starting at character number 11 to the end of each line. And that's how that would work. So the first command I did on bash or C, it grabbed one through 10 from each line and that second command grabbed characters 11 through whatever else was remaining on the line. One of the cool things that the cut command can do is it can go and grab certain fields from a line of text, similar to the way Alk does it. But this cut is kind of a poor man's Alk, really. It's not nearly as powerful, but some of the basic stuff you can do with the cut command as far as grabbing a certain field. Let me paste this line into the terminal. I'm going to echo, this is a line of text and then I'm going to pipe it into cut and I'm going to give it the dash D flag for delimiter. What is the field separator? What is the delimiter that separates each field? I'm going to say it's a space. So I have a space inside the single quotes. And then dash F for field number five, dash F five. I'm saying go and grab the fifth field based on spaces. So what would be the fifth field in this word? It would be the fifth word. It would be, this is a line of, of would be, of course, the fifth field. And of course, that field separator, that delimiter can be anything. It could be commas. If you were working with a file that was using a comma separated values, it could be a colon, which is something useful. For example, if I did a cat on my slash etsy slash pass WD file, you know, everything in this is actually separated by colons. There's no spaces. So what you would do for something like that is I would, I could cat that into cut, but I actually don't need to even cat into cut. Cut can take a file name.  I'm going to put the colon for the delimiter. And then I'm going to tell it, grab the second field. And when I do that, the second field is all x's. And if I cat that again, you can actually see that x is actually the second field for every single line in this file. Now let me clear the screen. And one thing I should briefly mention is what is the difference between using cut, you know, as far as grabbing fields of text from lines compared to using something like awk. You got to understand cut really it takes a single character in dash D for the delimiter, meaning it takes a space, a single space as the delimiter or a single colon by default. If you don't tell cut what to use as a delimiter, it does a single tab as the delimiter. Now, awk is much more flexible because an awk, what you do is you give it a FS variable field separator variable and that can be anything. It doesn't, it's not limited to a single character. It can be an empty string. It could be a single character. It could be a regular expression, you know, whatever it is you want to use as that field separator. Another thing is awk also, it suppresses leading white space by default. So depending on whether that's something you want or don't want, that could affect your choice and whether you use cut or awk in some circumstances. Let me show you what I mean by that leading white space. So let me echo and let's do echo ABC space D E F. And then I'm going to pipe that into cut dash F2. Let's grab the second field and then dash D for delimiter and we'll just make a single space as the delimiter. And that works as expected. The second field of course is D E F. Now where things break down a little bit with cut or how they differ from awk is what if instead of ABC space D E F. I had ABC space space space D E F. Now, what is the second field? Well the second field is a space because it only treats one space as the delimiter and then the next space is actually the field. Now awk, this wouldn't trip up awk at all because if I did awk and then inside single quotes inside the braces, print, dollar sign two for the second field, it's going to give me D E F as expected. So that's just one tiny difference between cut and awk again. I'm just putting that out there so you don't get any unexpected consequences especially if you're scripting and you're using the cut command and you have leading white spaces and by leading white spaces also mean white spaces at the beginning of the line. If instead of the spaces being in the middle of the line, I had a situation where I had a space at the beginning here and I want to go grab the second field. The second field now becomes ABC because it actually treats that first space as a separator where if I did this with awk and added a leading white space, awk still gives me what you would expect which is D E F as the second field. Now let me clear the screen and let's go ahead and cover the TR command. What is TR? What does that actually stand for? Well, TR, a lot of people think it stands for trim because you can trim extra white space and things like that with it. Some people think TR stands for transform, like transform text. TR actually stands for translate. If I run a man on TR, TR translate or delete characters and that is actually a very important characters, not strings, not words. TR works on characters. So let's start with a basic example of TR. So I'm going to echo, this is a line of text and I'm going to pipe it into TR. And then TR takes two arguments. It takes, hey, what we're searching for, the character we're searching for, and then what we're replacing that character with. You can think of kind of like cut was a poor man's awk. You can think of TR in this case as a poor man's said or a poor man's awk because awk can also do some of what said does. But you get this output here where we replaced every lowercase a, there was only one with a capital A. Now remember, TR works on characters and how to really demonstrate this point, how to really hit it over the head is this here. I'm going to TR and this time instead of lowercase a with capital A, I'm going to do A, E, I, O. There's no use, I just did every vowel that was in the line, present in the line and I'm going to replace those with A, E, I, O. Capitalized and you see it's not looking for a specific string that is A, E, I, O. It is actually looking for characters. Think of this as almost mapping, right? It's mapping lowercase a to capital A, lowercase e to capital E, etc. If I run this, you see it replaced all the vowels, the lowercase vowels with capitalized vowels. Now other than translate, replacing these characters essentially is what it's doing. It can also delete characters. You can give TR the dash D flag for delete and it will go and find every A, E, I, O in this case and delete it from the line. And you see, we no longer have A, E, I, O, we have spaces still, which I guess I could specify delete every A, E, I, O and the space. And now we just get a bunch of consonants without any spaces or vowels. Now other than the standard search and replace kind of function or the delete kind of function, TR also has a really cool flag for squeeze and what this does is it will go and find repeated characters. Like if there was more than one A in a row, it will actually squeeze them down into being one A. So let me show you this. So if I go back into echo, this is a line. I'm going to do two vowels everywhere. I might do three A's in this case. I'll do a couple of I's, couple of E's. I'll do three spaces because why not? And then another space and then like five E's. And then TR dash, S, A, E, I, O, space. It's going to find every A, E, I, O and space. And where there were multiples of it is going to condense it back down to just one character. Let me hit enter and you see the output is the regular. This is a line of text. Now the TR command can take classes. So if instead of TR dash, S, A, E, I, O, I could also do this. I could do inside brackets. I could do colon, lower, colon, and then a space. And then inside single quotes, inside brackets again, I could do colon, upper, colon. If I hit enter, you see, I've translated all of the lower case letters into uppercase letters. And we've also squeezed them because we had the dash S flag on. Now I'm going to up arrow and rerun this command from earlier. I'm going to echo, this is a line of text. And then I'm going to do TR dash D for delete A, E, I, O. I told it to delete every A, E, I, O because I want to show you guys this flag dash C for complement D. So typically they're used together dash C, D for complement delete, meaning don't delete A, E, I, O. I want you to delete everything that wasn't an A, E, I, O. And you see how that works. And you'll notice it also deleted the trailing new line, because it's going to delete tabs, spaces, everything that is not A, E, I, O. If I wanted to have it respect the new line, I could, at the end of A, E, I, O, I could actually do backslash N, and now you see it doesn't mess up my prompt when I run that. Because now it outputs the A, E, I, O, and it also respects the new line at the very end. Now something cool you could do with dash C, D for the flags is a lot of people like to generate random passwords. You know, you want some kind of random string, or a long random string for a strong and complicated password, and one of the things a lot of people do is they'll pull that from slash dev slash u random. So if I did a head, grab the first 10 lines from slash dev slash u random, you know, that's the first 10 lines. That's actually a little bit too much output here. Why don't we do head, and let's just do three. So let's just get three lines. So I could use this as a very strong and complicated password. Well not exactly because you see all the weird characters, the weird boxes that have the question mark in it. Those are non-printable characters. Those are not real characters. But with TR, I can actually get rid of some of this stuff. Let me clear the screen here. So what I could do is I could take the head of slash dev slash u random, and I could actually pipe that into TR. And what I'll do is dash CD for compliment delete. And what do I want you to delete? I want you to delete everything that is not a printable character. So I'm gonna do inside the brackets colon print colon. And now it should return an actual normal string of printable characters, yes. So that is something I could actually work with right there. So that was just another example of using classes, kind of like you saw colon lower colon earlier, colon upper. Another thing you could do is colon digit colon. So maybe I wanna do this here, I'm gonna echo. This is a strong and complicated password. And then I'm gonna do dash one, two, three, four is my password, right? And well, I could pipe that into TR and I could do dash CD. And then inside single quotes, I'm gonna give it this. Brackets colon digit colon. So I want you to compliment delete everything that is not a digit. And it pulls out my strong and complicated password, which was one, two, three, four. Now, earlier in the video when I was talking about cut, I showed you some ways that cut and alt kinda resemble each other for some functions. I'm gonna do the same thing with TR and said because said actually can do some of what TR can do. For example, if I ran this command here echo, this is a line of text and I piped it into said and instead of S for substitute, I gave it Y for the said command. That is essentially using said kind of like TR for translate. So it's gonna map lowercase a to capital A, lowercase I to capital I, and if I ran that, that is the same as that very first echo command I ran with TR. Now, said and the Y function in said is not quite like TR. It can't do some of the things that TR does. For example, it does not handle classes. So if I wanted to do colon, lower colon, for example, and then do colon, upper colon here, what this is gonna do is it's gonna find every lowercase and replace it with uppercase. Well, that's what it would do with TR, but said doesn't handle that. You see, I get something completely different going on here. It's actually mapping each character. It's mapping the opening bracket to the opening bracket, the colon to the colon, and then L to U, O to P, W to P. And you can see L in line became U because that's what that character was mapped to. So it's completely different. You can't use colon, lower colon, upper colon, print or any of the classes. Also said Y doesn't have anything that resembles dash C with TR. It doesn't have that compliment delete mode. So that was just a little bit of the basics of the cut command and the TR command. I hope you guys are liking the series that I've been doing on some of these command line utilities. If you guys want me to continue to do these, please tell me in the comments below and also like this video. Now, before I go, I need to thank a few special people. I need to thank the producers of this episode. Absi gave James Mitchell, Paul West, Akami Allen, Chuck Kurt, David, Dylan, Gregory, Irion, Alexander, Peace Arch and Fedora, Polytech Scott, Steven and Willie. These guys, they are my highest tier patrons over on Patreon without these guys. This episode on the cut command and the TR command would not have been possible. The show is also brought to you by each and every one of these ladies and gentlemen as well. All these names you're seeing on the screen right now. These are all my supporters over on Patreon because I don't have any corporate sponsors. I just have you guys, the community. If you like what I do and wanna support my work, consider subscribing to Distro Tube over on Patreon. All right guys, peace.