So, we've talked about the basics of engaging in social media monitoring and some of the common metrics that we can extract. But what I wanted to talk about in this session is what underlies those metrics? Where's this data coming from? And so I talk about it as opinion science and understanding dynamics in terms of user generated content. And so, here's the plan, let's dig into why people are contributing these opinions online. What are the implications that that has both for customers and for businesses? And then let's also talk about some of the dynamics that we observe. All right, so user-generated content, you're exposed to all sorts. This is broader than looking at Facebook or looking at Twitter. User-generated content also encompasses product reviews. And so we can find that on Yelp, we can find that on Amazon. Any place where we're contributing a text review or we're contributing a number of star ratings. If you're familiar with the review website for movies, Rotten Tomatoes, we can look at the ratings given to movies. So what fraction of the comments were a positive versus negative. And we can also look at revenue numbers. And, again, it raises that question of, should we expect the most highly rated, from a user content standpoint, to mirror box office numbers, to mirror performance numbers? All right, and so if we take a look at a movie like Suicide Squad, where 67% of the audience liked it. But from the reviewers' perspective, only 26% liked it. And the movie's doing fairly well. Well, one of the things that this points out for us that the opinions contributed are going to vary significantly, depending on who's contributing that opinion. We've got expert reviewers versus the general audience. And if their preferences are different, they're going to express different overall opinions of the movie in this particular case. So that's something that we want to keep in mind. When we look at the social media metrics, it's very tempting to just look at an aggregate number, to look at that summary number. But we also want to be cognizant of the variation that exists across consumers. And so, here's a very common application for social media listening. A new product has been launched, we're monitoring the conversation actively. And the company has to make a decision based on the comments that they're receiving about the product. Based on those early comments, what kind of marketing activity should we engage in? What kind of PR activity should we engage in? And that might depend on the nature of the comments. So take a moment and think about the advertising that you've seen around the products. Have you ever observed that advertising to shift, right? Part of that shift maybe driven in part by the reaction that consumers are having. So, how could you use those early comments to refine your marketing activity? Well perhaps, if the content of those comments indicates particular features, particular attributes that are appealing often indicates, here is what's most appealing to me about this particular product. Well, that's something that I want to fous on in my marketing activity. It might also be that those early comments give insights that can get used for developing the next generation of the product or for developing a new product altogether. And so in some sense, this is advocating for the use of social media comments and all user generated content really as a large scale focus group. And so let's take a look at who are the people who are ultimately posting comments online. Well, out of all the potential people who might purchase a product, only a fraction of them are going to purchase that product. So we go from the all visitors level of the funnel down to the buyers in the funnel. Now, out of all those people who bought the product, only a fraction of them are actually going to post a comment about that product. All right, so we've got two stages in which we're seeing filtering happening. And so the decisions that we want to look at in terms of why individuals are contributing user generated content, there are a couple of different components here. There's a decision about, do I post a comment at all, yes or no? And that might be related to the decision of, what do I post? What do I say in that comment? Now, that might have to do with the sentiment that's expressed, whether it's an open ended comment, or just one to fives stars. Might have to do with, do I mention a specific product, do I mention a specific attribute? Now, there's another decision that we've already talked about to some degree which is that question of, where do I post? Do I post on the blog, do I post in a discussion form, do I post on Twitter? Well, what I'm able to say and where I say it are potentially interrelated. Twitter limits the number of characters that I can use. I can't get into a very detailed, lengthy post on Twitter. I can do that on a blog and potentially on a discussion forum. But if I'm posting and I'm expecting some sort of engagement from other potential users. If I'm looking for help, I'm more likely to get that help posting on a discussion forum than I am writing my own blog post. So definitely we're going to see what I post and where I post related to each other. And let's explore the link on do I post at all and what do I choose to post.
