: How the Social Data Revolution Changes (Almost) Everything :
Posted on 14-07-2009
Filed Under (audio, sdr, speaking) by aweigend

Download the mp3 of the World Marketing Forum keynote (45MB, 50 minutes, Mexico City, July 1, 2009).


Ladies and gentlemen, it is an honor for me to be here and to talk to you about what I think it the most interesting, the most exciting thing I can talk to you about. I’m actually going to talk to you about a revolution. I’m going to talk to you about the Social Data Revolution.
I’m going to start by giving you a little bit about my background. I want to start by asking you what do you think those terms have in common: physics, finance, e-commerce, and marketing? In the 1980’s the most exciting data sources in the world were in physics. I did my undergrad education at CERN in Geneva, where I felt like the king of the universe, being logged on one computer with other computers on different continents.
Then I figured I needed to learn some computer science, specifically some machine learning; how could I learn what the underlying patters are from collecting data. I did my PhD at Stanford and in the 1990s I was an Assistant and Associate Professor at NYU, where I looked at the patterns people leave in finance on Wall Street. I looked at the traces of traders.
Then of course, the web came along. I started a company called MoodLogic that allowed people to discover songs they didn’t know to look for. The key idea there was that we got people to give us data, metadata about those songs.
I then went to Amazon.com where I worked directly with Jeff Bezos as his Chief Scientist. Again, I was thinking about how we could make sense out of those traces people leave on Amazon.com. Why, you might ask. Ultimately, it was to sell them stuff but the way we did it was slightly different. We wanted to get people to share data with us so we could do a better job in helping them with their decision-making processes. What all of those things have in common is that data is the deep, underlying element.
Let’s talk a little bit about data. There are more than a billion connected Flash Players in the world. Of course, as I was preparing this talk, my computer asked me, “Should we allow se.amazonaws.com to access your camera and microphone?” I said, sure. Remember it’s okay. Think about what that does for marketing. If the computer knows whether I’m sitting there by myself or maybe with a friend of mine and we’re looking at the same stuff, it can do a much better job in showing me marketing messages, by understanding my situation.
Now, while my background of course is the online world, I have a couple of examples from the offline world. I worked with a European company called METRO Group, one of the world’s largest retailers, on understanding how we can measure the behavior of people in the physical store, and each item of that store has an RFID (Radio Frequency Identifier). As you’re walking through that store, you consider that cream cheese, but you’re worrying about losing some weight so you put it back and you go for the low fat version. METRO Group observed that, just like Amazon.com observes what you are doing online.
Here is another example, a car company. What we see here is that you put a device in your car, another physical object, and that device may make life more fair for you because if you’re not driving – like right now; my car is in San Francisco at my garage; I don’t have to pay any insurance. What are you willing to give up for the fairness of only paying when you drive? Also, if you are returning home at 3:00 in the afternoon, versus at 3:00 in the morning, should you be paying more, or should you be paying less? On the one hand, you might be more awake at 3:00 in the afternoon. On the other hand, there might be less traffic at 3:00 in the morning.
Once again, it is about understanding the patterns of people through the underlying data they produce. The examples we have seen so far were collection devices of implicit data. I now want to tell you how marketing can use the explicitly shared data that people willingly and knowingly share with you.
Here are two examples. The first example is YouTube. The movie I just showed you was from YouTube. Every month, 100 years of video get uploaded to YouTube. Another example which was mentioned this morning is Facebook. Every month, 5 billion pieces of content get shared on Facebook, about 1 piece of content per every person on Earth.
Marketing in this Web 2.0 era, people often ask me what is Web 2.0 and I say, “Web 2.0 means People 2.0.” People have shared. People have changed how they see the idea of what sharing data about themselves and about their friends is.
For us as marketers, when we talk “people” what we really mean is customers. After this introduction, I’m going to talk about C2B, which means customers sharing with business. Then C2C, which is customers sharing with other customers. We’ll do a little exercise and then I will talk about C2W, which is customers sharing with the world. I’ll give you some insights, and then close with a couple minutes about a domain I’m very interested in, namely travel.
Let’s start with C2B, customers sharing with business. Imagine that for all the people in the room, you knew all the things they have bought. Imagine that you also knew all of their friends, both within the room and in the outside world. Finally, imagine that you knew all of their secret desires. What could you do with that?
Is that some dream far in the future, or is it already reality? Let me give you some examples from Amazon.com. One of the ways in which people share data is they share reviews with Amazon.com. First, it’s about that hard drive. They had 116 reviews and you know it’s a pretty good hard drive. People willingly and knowingly share those data.
What do you think is the impact of recommendations? Is it 1%, 2%, 5%, 10%, or 20%? If it was 1%, HSM would not have invited me to come here. If it was more than 50%, then I wouldn’t come here either. It must be something in the middle and indeed, it depends on product group, the price point, and also on the gender of the person who is looking for it. It’s something between 10% and 25% of increase.
Deep down in recommendations is Amazon’s C2B data strategy, purchases, clicks, reviews, wish lists; everything you can get, recommendations based on view data, on click data and on purchase or buy data.
In the simplest case, “Customers who viewed this item also viewed…” which means you collect the clicks as you go along and you leverage the collective intelligence of the people. You collect what they do and you combine it in a way that new people can have their decision-making process supported by what other people have thought about, prior to them. “That’s customers who viewed … eventually viewed …”.
Now, you can do the same for buying data. “Customers who bought this item eventually bought…” What is the difference? Viewing means that you see alternatives you can buy. Buying means you see products that you buy in addition to what you are buying, cross selling, up selling.
I think the best of all is “Customers who viewed this item ultimately bought that item.” Going back to our hard drive here, Amazon.com helping people make decisions based on collective intelligence, it turns out that 42% of people who looked at that item eventually bought that item. That makes you feel you can’t be all that stupid by buying that item.
I promised you something about the secret desires. How does Amazon know about the desires of people, about their intentions? The answer is through search. Who here trusts their husband or wife more than you trust Google? Who here shares more with Google than with your spouse? [Laughter] Okay, so for instance, I shared with Amazon that I was looking for video on demand, specifically for the HSM Management TV. Now, Amazon knows what I’m interested in. That’s what I mean by C2B, the customer sharing with the business. I ask you, if you have a website, do me the favor, and spend one hour tomorrow, or next week, looking at the search terms people enter. You will understand what peoples’ desires are, desires they might not even share with their spouses.
Here is an example of how people desperately want to cancel AOL, all the variations from a search log. At Amazon.com, we tried to implement whatever we can to make it very easy, as lightweight as possible for people to share with us in a C2B way.
For instance, at the bottom of every single page, there is this feedback box. You can say if something is broken, or if an image is not right, or if the language is inappropriate. Per day, Amazon gets about 1,000 such comments, out of a million-plus people visiting. You could say that’s not that much, on the other hand, you have your entire customer base debugging the site for you. If you capture the context as well, such as the page where people make this comment, then you have a very powerful way of collecting the intelligence of people to help you do a better job in the context in which people are.
Let’s summarize what we have learned so far. We have talked about a few data sources. We’ve talked about intention data through search. We have talked about attention data, such as transactions and clicks. We have not really talked yet about situation data, which would be the device you have. Are you searching from your iPhone, your BlackBerry, or your mobile phone? Are you searching from the web? By the way, where are you? Are you in Mexico, are you in Buenos Aires, are you in Germany? Those are all data sources which are very important for the marketer, which in traditional marketing you have almost no idea about.
I figured I would share some ideas for you about connection data, about data between people, and specifically this is what AT&T did in the United States, where they tried to market a new phone product. We compared traditional segmentation such as demographics, psychographics, loyalty data with simply looking at the connection data; who calls whom, in other words, the calling network.
The set up is that AT&T has a new product. They want to compare how much they get with traditional segmentation and it turned out they got a rate of .28%. They threw away all the traditional segmentation and only looked at the calling data. What is your feeling? Do you think it is better if you only use one data source than this 2.8%, or do you think it is worse? The recommendation I might make right now is looking at the data, such as Eduardo makes a phone call to me. Eduardo has bought the product, and then AT&T says, “Andreas, would you like to buy that product,” as opposed to saying, “Andreas is 49 years old, he was born in Germany, lives in San Francisco, has a house in Shanghai; he might be a good candidate for that product.” What is your feeling? Who thinks it’s better if we just look at the data between Eduardo and I? No hands up. Who thinks it’s worse if we just look at the one data source?
This reminds me; people say that 17 minutes into a talk, half of the audience will have fallen asleep and the other half will be having sexual fantasies. [Laughter] Let’s try again. Who here thinks that we’re doing better? Okay, because otherwise, why would I show the example? How much better – it’s actually by a factor of 4.8, not 4.8%, but 4.8X, 380% better, which is a pretty amazing lift, just using one new data source. That would be my advice for the gentleman from the phone company beforehand; look at data other people don’t have. Don’t be stuck in the old way of how things have always been done. This century is a century of data.
By the way, data double about every other year. That means this year, mankind will produce about as much data and share about as much data as the entire history of mankind has produced to the end of last year.
In the Bay area, a lot of new companies emerge that try to give us these data. One company I invite you to play with is called Skydeck. With Skydeck, if you have a BlackBerry you can download a client. If you have an iPhone, you can download a client. Otherwise you can do the website. It analyzes your calling behavior and it’s one of the most powerful tools for a sales force, by reminding you who you should be calling. It’s also very interesting. For example, my friend Go, I called him much more often than he called me. What does that mean?
To summarize this part, businesses try to reach consumers. That is how the conversations use to go. As Phil Kotler said in the morning, “Marcom trying to hire people who get the message out,” but what we are seeing is that is not where the conversations are. The conversations are primarily between customers, C2C conversations.
That is why we now move to the second part of the talk, after we talked about C2B data, we are now going to talk to the C2C aspect of data and the Social Data Revolution. The Social Data Revolution means data that is shared knowingly and willingly.
I am not interested in going through the digital trash or sniffing the digital exhaust. First of all, it can be bad for your health and secondly, it’s a lot of work to find maybe a few nuggets somewhere. Instead, listen to people; listen to what they say to each other. C2C means consumer-to-consumer, and C2W means consumer sharing with the world.
At Amazon.com, when you buy a book, after you have checked out, Amazon asks you, “Do you have some friend who might be interested in that book?” “Yeah, I can think about somebody.” If that person buys that book within a week, he gets a 10% discount and we don’t want you to go empty handed. You will get the same dollar amount credited toward your next purchase. Ah – repeat customers.
The conversion rates were absolutely amazing. Why? Because you just bought the book which means you determined the context. You actually determined the item, that very book, the content, and you also help Amazon do marketing. You determine the connection because you tell Amazon.com to “Please, mail my friend and tell him that I bought that book.” In this case, people know that I’m smart and maybe I’ll make some money, as well.
That has been brought to perfection with this one button, with a company that is about 5 years old – “share” – that is the most important button of this decade. Each month, 5 billion items get shared on Facebook. Let’s spend a couple of minutes on how that works and then we’ll discuss it together. I’ll give you a few minutes for an exercise on how you can use this in your company. I want to show you; first of all, that Facebook is highly relevant, growing faster in Latin America than anywhere else. It’s doubling every four months. The current numbers in Brazil is about a million people, but in four months it will be 2 million. In eight months, it will be 4 million, and in twelve months, it will be about 8 million people. That’s growing quickly.
Worldwide, every given day, about 100 million people come to Facebook. Here is an example of sharing. In my course at Stanford this year, I had Reid Hoffman who is an old friend of mine from Stanford come, he started PayPal, and then he started LinkedIn. He talked to my students about what it really means to be part of that Consumer Data Revolution, or that Social Data Revolution.
With a quick video loaded on YouTube, you can watch it. I shared that with my friends on Facebook. With a push of one button – that is what is new – I can reach everybody who has a confirmed relationship with me. I come back a few minutes later and it turns out that already three people said they like what I just shared. People start tagging stuff, so people interact. Somebody took a photo of me. Somebody else says, “That’s Andreas standing in the room giving a seminar to executives,” and tags me with “Andreas Weigend.” Those are all those lightweight interactions that are happening on Facebook.
Distribution is key there. As an experiment for my course at Stanford, I made a page called “Social Data Revolution” at www.facebook.com/socialdatarevolution where people share what they find interesting. It has been an extremely rich source of information from hundreds of people contributing. What the metrics are is not unique users, not the number of people who have subscribed to that page, but what they do there. Do they comment, post, like things, and so on? Those are the new metrics of engagement.
The difference is they do things knowingly and willingly. Here, “Wow!!! Golden Earrings! Thank you Darling! That’s so cute! But who has got the second pair you’ve bought?” You have to be very careful with what information you grab from people’s behavior which they might not be all that happy to have shared with their 500 best friends.
I want to give you an example from a company in Mexico, called Burger King. You know the term “viral marketing.” In viral marketing, typically the goal is to bring new people to your site. Burger King decided the opposite. Burger King said, “Dump 10 friends; get rid of ten friends, and we’ll give you one free burger.” They executed that on the Facebook platform, similar to the iPhone App Store, an ecosystem for third party applications. It’s about a million developers, a million programmers working and trying to write apps, doing this for little money for companies like Burger King. There are a lot of games there, as well. Here is what happened.
Friendship is strong, but the Whopper is stronger. Dump ten friends and get a free whopper. In the end, your love for the Whopper sandwich proved to be stronger than 230,906 friendships. What happened? After ¼ million people were dumped, Facebook shut it down and said, “We don’t like that app anymore.”
Here are a couple of other networks. LinkedIn one week ago has 236,000 people in Mexico and has grown by more than a factor of 2 in the last year. LinkedIn is a professional network. The idea is that you tease people with some information.
For instance, as I last logged in it said, “Your profile has been viewed by 115 people in the last 15 days, including…” – and then there is some generic description. “If you want to know who these people are, you need to subscribe to the service.” The lowest level is $25 a month and you can also subscribe for the $250 a month to actually get access to a lot of information about people. That’s not cheap, but if you think about your sales or marketing it is cheap. If you just do one good sale, it’s nothing compared to that sale.
One of the features of LinkedIn is that you might want to be introduced to somebody, which is very important for sales. For instance, a German VC, Kolja Hebenstreit, asked me whether I could introduce him to a friend of mine, Amy Jo Kim]. Of course. Short endorsement to Amy: “Kolja is great!”. Done.
For those of you who are interested in buying aggregate data, maybe for sales leads, for risk reduction; here are a couple of examples of what is popular in the U.S., right now. Unbound Technologies in Palo Alto, California; RapLeaf in San Francisco, California; 33 Across in Mountain View, California.
Here are two examples of what these companies provide you with; they look at all these social networks. I just gave you two examples of Facebook and LinkedIn. High 5, Orchid, or whatever ones you think about, they try to understand who your friends are, and produce a list of prospects for a high end hotel chain. If I’m staying in high end hotels, chances are my friends also like to have a decent hotel. They look at my friends, they try and relate with their friends, and then they deliver a prospect list. That’s a very different segmentation from what you’re used to. It’s much similar to the AT&T example than to traditional segmentation examples.
It’s not only about making money; it’s also about not losing money. The example I want to give you for that is fraud reduction. They get claims, all the time, and they need to decide “Should we spend a lot of resources to investigate this claim, or should we just pay it and be done?” It turns out that not only “birds of feather shop together,” but also “birds of a feather steal together.” If my friends are short of shady in the sense that there are a lot of claims coming in that we’re not sure about, they better spend a lot of resources investigating my claim. On the other hand, if my friends are all clean, then no worries; no need to spend any money on me.
What we have seen in this part of the talk is a spectrum from very private data, on the one extreme; to very public data on the other extreme. Consumers have become quite good at asking “What do we get in return for sharing data?” What is relatively new is that they’re willing to share data that we never expected them to share.
In order to give you a little break, what I want to do in the next 8 minutes is I want you to talk to your neighbor. Have a conversation with them, and from the plethora of examples I have given to you about C2C data, figure out one marketing idea, based on C2C data. Think about Facebook, LinkedIn, and try to be specific; what would be your first step, and what would be your measure of success? Write your key idea on a piece of paper. We will have some of the assistants here run through, collect them, and then I will pick a few of them and we’ll discuss them. Talk to your neighbor, figure out one idea; how can you take what I have talked about using a lot of examples and make it concrete? Write it on a piece of paper; get it to me in 6 minutes. I will have 2 minutes to look through them and we’ll discuss 3 to 5 of them.
Thank you for your comments. Somebody says, “Make a section on a webpage where the customers can share opinions.” That is interesting but I have bad news for you. Most people don’t come to your webpage.
I did some work for Nokia. It turned out that for the top ten search results at Google for Nokia Map Activation, none of them were Nokia. The power of what we have here on Facebook, as an example, is that people distribute what they find interesting to their friends. What about influencers here on Facebook?
First of all, there are traditional demographics you can get if you want to target people. Traditional ads allow you to get very rich targeting data because people on Facebook are honest about their gender. Think about it; if they were lying about their gender, their friends would immediately say, “What’s up with that? You always said you’re a man and now you’re suddenly a woman? No way.”
Here is a question about influencer marketing. “What’s the difference between real life and Facebook?” You have all heard about influencer marketing which means indentifying those people who are influential and marketing to them. By marketing to them, you then reach all of their friends for free.
In real life, the chain length between people, for 38% of people, is 4 or longer. With Facebook, 86% of all chain length – work of mouth and mouth-to-mouth communication is 4 or more people. Why is that the case? Pushing a button – “share” is easier than talking to somebody. Besides, by pushing a button you reach all of your friends, whereas by talking, very few people are as lucky as me having hundreds of people who actually listen to them.
That key difference of 38% versus 86% means what you know from the real life world is not true in the virtual world. In real life, what matters is to have influencers tell their friends stuff. What matters on Facebook is how good your message is. Don’t try to really massage the message. Try to use the feedback you get in making the product better, or said very simply, “Don’t focus on the influencers; focus on the product.”
I have many more answers by you but in the interest of time, I want to move onto the next part, our third part which is C2W. I started a search on that other computer for “moon food.” Do you know what moon food is? I didn’t know either, but I just looked at what is a popular search term on Twitter right now, and it turned out that between starting my talk and right now, 10,000 people sent out tweets about moon food. We can refresh this here; the point is while we don’t really know what it means, some people, namely 10,000 people in the last hour found it was worth talking about. That’s an interesting buzz, isn’t it? It’s free. People talk about it and nobody pays for it. You have peoples’ attention if you talk about moon food. At the end of today, we’ll try to figure out together what moon food means.
New media tend to start off as better old media, but then do something very different. Just like television in the early days was people standing around a microphone; TV is not just a better radio but is very different. The web is not just better television, but Facebook with interaction is very different. Twitter is not just better short messages, but it’s very different.
Here is my friend Go Kasai again. Here is his wish list. These are the books he tells the world he is interested in. “This is what I want. This is who I am. This is what I’m interested in.” They share their desires, and they share their intentions.
Here is a video. Nike Plus had the following idea. You get people to share information about themselves with the world, C2W. In this case, it was about running together. You buy a device that you put in your shoe and as you go running that device records where you’re running by GPS, how fast you’re running etc. Then you upload what you have just done, you upload your run to a website called www.NikePlus.com and the world can see where you’re running.
I know people always have security concerns. The world could track you down and do funny things with you, but they can do that anyway. The key thing here is that you have now found, as a marketer, a very different way to connect with your consumers. People buy something from you, shove it in their shoe, connect it to their iPod, and now people come, on average three times a week, to your website. Isn’t that a marketer’s dream? How often would you go to Nike’s website beforehand? Probably never, but once you got that device, you’ve starting going to the website three times a week to compare what you’re doing, to compare yourself to the others, to run with others, to hook up with people and say, “Let’s go running together.”
Trevor Edwards, who is Nike’s corporate Vice President of Global Brand and Management says, “We’re not in the business of keeping the media companies alive. We’re in the business of connecting with consumers and also of consumers connecting with consumers.”
I deliberately chose that example as a very physical example, something you shove into your shoe. Something where the consumer shares with the world what data he is creating. Here are some other examples.
In the virtual world, there is something called Delicious, which was bought by Yahoo a couple of years ago. I used to work with Joshua Schachter, who created Delicious. What people share with the world through Delicious are bookmarks, their bookmarks, the things they find interesting, URLs. Delicious now allows you to explore. If you will, there is a web on top of the web.
HSM controls the links that it puts elsewhere, but this is what users find useful. You can of course follow HSM’s links, but you could also follow the links or connections that people put on top of the web. That is Delicious.
The example that is in everybody’s mouth right now is Twitter. I just want to make the point that whereas with Delicious you share URLs with the world, Twitter is even easier. We were actually considering for the conference to allow you to tweet in and to have, behind me, displayed what your questions are and what your comments are. I tried it out in my last class at Stanford last week, and all the students did were they wrote jokes behind my back. That’s one use of Twitter, to have real time commenting on what’s going on in real life.
I looked up marketing and that was when I made the slides for this talk, a couple of weeks ago. There was a social marketing conference in Chicago, and it was interesting how all these things were less than 20 seconds old. It really is real time. If I want to know what food is good in a certain restaurant, I tweet, I search for that restaurant and it will tell me that tonight at the Taco Al Pastor, this is what you should really get. That is real time search.
Here is John Batelle who started the Web 2.0 conference. He tweets saying, “Just landed in Atlanta – very long trip. Yargh.” Somebody says, “Hey, have you followed what I have been doing with …” and then his random website. We can push this ever further with this little cartoon – what companies actually do.
BestBuy monitors Twitter for what people are saying about BestBuy. BestBuy has people who constantly watch for the BestBuy tag on Twitter, as well as related tags. Some people are happy and say, “BestBuy so totally rocks. I just bought this game station and it works so well. I had awesome service. The Geek Squad came and they fixed all my problems,” and other people are not happy. They share it in a C2W way with the world.
If somebody is unhappy there, the customer service agent immediately gets online and tries to have a conversation with that person by saying, “Hey, I work for BestBuy. I saw your tweet. I saw you’re unhappy. Here is what I can do for you. Do you want me to call you right now? How can I help you?”
Think about the difference from traditional marketing. You have people, in a moment, who think about your product and who think about your company and you can reach them right there, right at that moment, on Twitter. You need basically no infrastructure. You need some person who has access to the computer and knows how to type. Not only about people who might be unhappy with your own product, but think about people talking about your competitors.
Let’s say somebody is not happy with a washing machine they bought at Sears. There is nothing wrong with BestBuy talking to that person and saying, “I saw your tweet and you’re not happy with your washing machine. Let’s have a conversation. Let’s see how we can help you.” Or somebody has computer problems. “Don’t worry about it. Let’s send the Geek Squad over to your house.” For marketing or customer service, these are truly unprecedented ways.
Slightly more traditionally, Dell using Twitter for promotions. In the first eighteen months which ended in December of last year, Twitter had a total of 7,000 people who were following Dell. They sold stuff for a million dollars. It has exploded in the last six months, in the sense that it’s ten times more people than there were six months prior to this. That is a factor of 10 over a half year. Ten times ten with the same growth is a factor of 100 over the year and that’s an amazing growth.
The revenues are small. They just sold stuff worth $3 million right now. The fixed cost for doing this is essentially zero. You can start tomorrow, coming up with some promotion you want to run on Twitter, and create your own experiences there.
If we think back, ladies and gentlemen, the task used to be connecting computers. Then we moved from connecting computers to connecting pages, about fifteen years ago. Then, the last couple of years, we moved to connecting people. Think about Facebook as an example here. What I’ve been trying to get across to you in the last hour was that what the web is really about is connecting data.
I showed you that the car is basically a chip with wheels. The shoe is essentially a chip with heels. You thought you owned the customer because the costs of the customer going somewhere else were quite high. Unfortunately ladies and gentlemen, I have bad news for you as marketers. You don’t own the customer anymore. The customer is quite able to check out other places where they might get products that suit them better. Remember, I told you one of the key things about Amazon.com was that Amazon was supporting the decision making process of the customer. You don’t own the customer.
You would say, “But the product, I know about my product.” I have bad news there, too. Google knows more about your product than you do. Maybe the brand? “At least we own the brand,” but no, if you do a search the brand is owned by the people who talk about your brand, and no longer about you.
What’s left? What is left are sites that are platforms, like Get Satisfaction, where people are going in order to get customer service. They go to a neutral site and there is a little button that says, “I have this problem too” and people enter what they are interested in.
Another example here is how we moved from controlled production for the masses to uncontrolled production by the masses; that’s why you’ve lost your brand. Starbucks, My Starbucks Idea – whereas Get Satisfaction is a neutral platform, this site is owned by Starbucks and it is about sharing, voting, discussing and seeing what other ideas other people have. 60,000 contributions were there when I checked a few weeks ago.
What the Social Data Revolution is really about is how the mindset of consumers has shifted. People trust reviews. People trust their friends more than they trust official specs. People use their friends’ attention as a filter for information and as a way of discovering things.
The main insight for marketing is that you have to come up with ways for how you use that social filter to have people discover your products and services. In closing, I have a few examples from travel.
One website is called Flatseats.com where people discuss in gory detail, first and business class seats in much more detail than any airline would share with you. For instance here, early this year, United came out with a new business class and within days – January 2, January 3, January 6, we had detailed reviews and the question was, “I just don’t understand why United Airlines could not think outside of the box.” Did United listen to them? No.
The second example is SeatGuru. Do you want to know which seat you want to sit in? SeatGuru has seats labeled in each aircraft by tens of thousands of people. You know whether that one has that back which doesn’t recline fully, or that missing arm rest on the lovely exit seat.
What about hotel rooms? TripKick is an example where every single hotel room gets rated. It’s not enough to know that you’re staying at the Hilton Hotel in Mexico City. It turns out that rooms with 04 at the end have an oversized room, a nice quiet corner room. On the other hand, rooms with 61 are possibly next to the ice machine, with a lot of noise and next to the elevator. You probably don’t want to stay in that one. Would the hotel tell you that information? Of course not. If you call the central Hilton reservation line, would they know about it? Probably not. Does the web know about it? Yes.
Booking.com, which was purchased by Priceline, is now four times larger than Priceline itself. It gives you reviews based on your own status. Let’s say if you’re a single traveler and you really loved that hotel, chances are if you are a family with seven children you might not love that hotel. By conditioning on your specific purpose of traveling and by who you are, the reviews they extract from you are more honest and help other people more.
Booking.com, Agoda.com – the Asian counterpart, PriceLine.com are of course in the business of helping you as a customer to make better decisions. Sometimes, we want to get closer to the intentions. We want to get closer to the future. Here is a company called VirtualTourist, which allows you to talk about not only where you have been, but also (in green) to about where you want to visit. You create your own map and then say where you want to go. Suddenly, in this case Lufthansa says, “We can help you out. If that’s where you want to go, these are the special deals you can get.” By you sharing the airlines know your intent, your friends know your intent, and they can make you special deals.
Dopplr is a company that allows you to share your trips and it’s very powerful. If you happen to go to the same cities as some of your friends, a couple of times a year, you can be pretty sure they’re going to the same conference you’re going to.
Jet Blue airways uses the C2W world of Twitter, of giving people special deals. I was told that they even added flights based on peoples’ intent shown on Twitter.
My last slide here is a few questions for you. Who talks to whom? It’s ultimately consumers talking to consumers. Who trusts whom? We have seen the shift in trust from institutions to individuals. Who is in control? Business Week quotes me as having invented the word “me-business” a while ago. We’ve moved from e-business, where the company is in control to me-business or in other words, from CRM (Customer Relationship Management) to CMR (Customer Managed Relationships). Customers want to manage the relationships, not to be managed by the companies. Finally, who pays whom? It’s not that obvious. If you have a GPS device, and you leave it on so certain companies can improve their maps on it, shouldn’t those companies be paying you for helping them make their product better?
I want you to remember one thing from this talk. It is that this pyramid, what used to be on the top is actually turning upside down. It’s now the customer on top. You’re not helpless, because they’re sharing with you as a business, C2B. They’re sharing on platforms with their friends, C2C, and they’re sharing with the world, C2W. Gracias, thank you very much.

Audio: http://weigend.com/files/audio/Weigend_MEX_2009.07.01.mp3
Transcript: http://weigend.com/files/audio/Weigend_MEX_2009.07.01.doc

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  4. Social Data Revolution, Part 2 — Why We Need a Sound Data Strategy
(1) Comment   


Thomas Treutler on 5 February, 2010 at 8:19 am #

Loved the mp3, thanks for putting it up! Any talks planned in Europe?

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