[ 00:00:19 ] So you know I have been personally working in the big data analytics for the past 18 years or so. You know based upon the recent global big survey. The number one trend in that industry in particular in the media industry as well is customer centricity. The other is about how to personalize things. So when it comes to my session that it is really about you know how we can actually. Leverage a personalizing view view or experience to actually improve the content of your type. So you know Noddy's.
[ 00:01:10 ] I would say a lot of the business entity. They said okay we're already personalized customer experience. But if Repya was I knew a little bit right a lot of people saying okay I'm telling my customers and just for the sake of pegging the customers. But a ways that the insiders in our cognitively inside the platform to look at how to best to personalize services to our customers our audience in this particular case is we're really looking at the entire landscape. So we not only actually get the insight for the audience themselves we use various attributes to understand based upon the audience data the viewership data in this particular case to get to the attributes and the insight into the audiences themselves. More importantly because we are talking about a personalized experience so don't forget those things all the content the site. So that means we have to do something similar. We need to do the content a tagging we need to use various attributes we use machine learning algorithms models to analyze content themselves so that we can best describe the content. Only after you are able to test to understand your content. At the same time your audience then we use a very rich set of the analytics and the models and Elbrus them to use our matching anjing. In another words recommendation anjing to bring the most relevant content to your audience. That is the way we achieve the optimal personalized viewing experience so. There's many different ways you know to categorize the audience right. So seems like those static information the name age and home address those are very simple and straightforward. But nowadays with the introduction with the end of it it's more so with a recent introduction for the adoption of the API in two different industries. People are getting more insight into the customers and audience. So for instance I have been working with so many customers around the globe. I would say was a very interesting example I also share with you is the personality insights. So if you ever go to one simple example here is go to that pad Talk Web site and you fly into my own Twitter handle the shomrei on the skull w n g. Guess what. What law. Actually it immediately pops up more than 20 attributes. Related to Sharma's personal. Insults. That a person has a the insides. The first time when I look at it it really blows me away because I do understand who it is. But you know what. I still have so many attributes which I have not been so consciously aware of in the past. But when I look at the personality inside analysis immediately introduce additional attributes. When I see it yes I knew that's show me and that could best be described Shammi is the same philosophy and a simple code apply to the other customers. And we are using that particular features and functions and the AI capabilities are in many different arenas that is just a one very recent example in terms of how I can introduce and it did arrive a lot more insight into us so that we can make sure that whatever our recommendation we will become more personalized more precise as well. So there's many different the data sources available. Today which can help us to derive or get the Inside Out of our customers or audience. In other words. So for instance every single move. Every every behavioral. Actions. It all generates data that indeed it actually is a very good. Digital Footprint of who you are. What do you like. For example if you go to the Web site the click streams. You know how many times you go to a particular Web site how long you'll stay which particular link you click. It To all the facts who you are right and all those behavioral data is analyzed. This is a one common example we are doing as of today to get the inside of you. Another very common. Example is based upon your social media presence that Twitter Instagram you know snap chat Facebook you name it every single little digital for. Print here. We actually actually combine all of those information. We do the sentimental analysis. Right the social media data is a very good source for the sentimental analyses so that we can understand your thinking behavior so we can get more insight into you when you are watching a movie when you are actually viewing a some news. What is your sentiment. It is so that we can based upon that to provide you the relevant information rather than the services. For example theres another example we actually have our particular. Dress which is one of the atut actors that present here the idea of the collar in York City years ago. That is when the actors walk down the red carpet based upon the social media tricks around her. You know her dress actually will reflect a different the lights that it is actually. Another very interesting is Dempo in terms of how I actually analyze those sentimental. They are into the real time to bring new value or new vision to the world. Privacy is indeed together with security is the number one concern or challenge I may see in these words. When we come into this new era. Right because literally every single digital fruit footprint you have. We are actually allow other people allow those technologist to analyze and understand you. So in order to create harmonize this society all together it is really quizes several issues to all work together. You know at the government level we are actually observe that around the globe every single crunching those new policies coming out to regulate the business and people's behavior. Right. And also it is a business. Entity level. We are actually encouraging the business entities to follow the secret side to follow the government and laws and policies so that we can put a very honest brings practice in the marketplace and also to the people level. We're actually sometimes and more so we need to cover our own. Confidential information very well. So it really requires a convergence of. You know given the level of the collaboration so that we can have a very harmonized society. And also I just want to share with you the common practice that for the business entities like ours what we do is we not only actually follow the government the laws and the policies. And another thing I really want to live together in the larger degree is you know we the common practice for us is we only analyze the data. It is a segmentation novel. We never allow them to analyze individually in the business practice landscape. So yes we are allowed to analyze the data but we will aggregate the similar group analyze get to the. Then the segmentation of that information can be best utilized for business values. So everybody's mind is at peace.