The right product at the right time at the right place is why we would do social media analytics right so that that's like a start to mice to why we're doing such mean analytics so in terms of agenda we have essentially four topics we will wrap you through marketing because obviously, they're not interested why social media war to social media but we will talk about how do you apply that in the overall marketing mix for sure we will talk about how do you measure impact and then we'll jump straight into case studies right so from my point of view this is the fourth thing that I would like you guys to take away from today right the relevance in the overall marketing mix channel from social media has this channel point of view one important thing I want to talk about and focus on is what is the difference between a strategy and a tactic.

We'll talk about examples and not just keep this in the air right and how social media can be applied across the overall business value chain measurements, of course, we talk about frameworks when we talk about metrics that you typically look at me and talk about social media analytics which probably does involve a lot of text analytics as well and of course, we look at the case studies right these are four major takeaways or objectives that you want to end the day with all right a little brief about myself so my name is Sutton Dave I forgot to introduce myself my name is Hudson I currently lead marketing analytics for u.s. insurance firm called Allstate so Allstate essentially is one of the biggest property and casualty insurance company in the world in u.s. they only have operations in the US markets and this set of technology kept up here and in there for the last three years and they're slowly starting the set of the analytics value chain right before this I worked with a company called net app which is in the storage solutions.

I was heading their global marketing operations function which basically boils down to making sense of marketing as a function and does that hit any kind of ROI for the overall organization at all right so that's the single function that I sense he was dealing with for a couple of years ended up writing at a bow is with HP which has a fairly huge of analytics practice here in Bangalore worked across the different business enterprise and consumer for HP helping optimize the business through the use of analytics and before that was with HSBC helping them improve their digital marketing operations through validation right so that's been my background in the analytics industry per se.

I'm the screen engineer from BITS Pilani remember from Ivy's well I do a lot of writing and reading and that's why you would find me on the net alright we'll skip this but I do want to focus on a couple of things in this one right there the typical explanation of what social media is this which is a mouthful and when you read it but I want you to focus on one thing which is about discussing information and experiences with other human beings now in today's context how relevant is that definition you guys have any thoughts about how relevant or how irrelevant that definition is when you see other human beings have you guys taken a look at today's what the supplement for the economic time it's right there outside okay so you obviously heard of okay let's say you want to buy a new in-charge policy and you go to witch website Google and you want to compare insurance policies right so any when you log in when you good policy beside outcome what happens first do you get a pop-up Phaneuf.

Yeah that's that's worth for them to essentially track down your profile per se but even before you do that right you all pop up that pops up and says hello you need a name or it's typically like a generic hello if you've not never interacted with policy bizarre before right oh now that obviously is a chatbot you get a family of the chat pod concept right it's a it's a machine now in this context of conversation with other human beings it's a little dated right now because today be the content that you generate is not just between human beings as well 95% of the content is actually generated by human beings i but I do want to talk about do I take a focus to the fact that there are machines out there which are actually making human beings wrong right if you get a chance do read a book called rise of the robos okay it talks about the application of AI and machine learning specifically rope you know robotics one of you and then it talks about the application of this across different industries you be surprised to know about there are we so you would think that the last frontier that a machine can actually take over is creativity right so say writing.

I'm right I'm passionate about writing but there are there is a sports journal which is hence Lee uses AI to actually compile sports reports about what happened in the previous day's matches right in the US and that's becoming popular a normal day so yeah this definition is probably dated right now because the content is not just the native between human interactions per se all right having said that means more. After all, the rest of it is something that you would know I'm gonna do you guys must sit through the slide because this essentially talks about where things originated it's an interesting slide. After all, you can get to know your favorite social media networks and how that originated.

Where they're going right so early 2003 was when the first few social networks started and that was the launch phase and you look at Facebook is right then in 2004 so awkward I didn't purposely put aquatic because I could probably die around somewhere 2008/9 now that's an interesting observation I want you guys to think about why did we could die alright so yeah so I think we're still talking about why Facebook's features were probably a little more user-friendly live more innovative a little more you know catching up with the trend point of view and hence people who've moved on now the underlying the economics theory for that has to be something called network effect have you guys heard of network effect so network effect is the fact that the more the people more people join the network the more you stand to gain out of it right.

So when I'm joining when I'm deciding to join a fair of a social network for that matter I see there are two options Orkut and Facebook and I see that most of my friends are active on Facebook now they moved on from the market and they're actually liking Facebook a lot more than Orkut and hence I would join Facebook because my group of friends is exclusive on Facebook so when Facebook was kicking off there was a whole exclusivity factor to it so the network effect is that now anybody was coming in new will obviously gain a lot more by joining Facebook as opposed to awkward and then people slowly start dropping off and then nobody else really joined New Yorker right so that's a what a network effect point of view which essentially came into fruition and hence our code started becoming just spam heaven and see a lot of people from Brazil and India start spamming canopic.

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