Well, this week, after reading the "Secret of Googlenomics" (twice), I decided to focus on Google...
We saw in the Breeze session that digital advertising only accounts at this point for 16% of all advertising spend. Of that 16%, 55% goes to Google, and 75% of all advertisement $ goes to search-based ads, not display ads. Search-based ads are were Adwords comes in, as Adwords generate 98% of revenue at Google, says Eric Schmidt, Google CEO.
The Secret of Googlenomics
The highlights of the article for me were the following:
1. "Anything that increases Internet ultimately enriches Google"
2. "Selling ads doesn't generate only profits; it also generated torrents of data about users' tastes and habits..."
3. Revolutionizing ads pricing by using the second-price auction model - Like the folks at Heineken would say, "Brilliant!"
4. "The bids themselves are only a part of what ultimately determines the auction winner." Whether it is fair or not (see Not everyone's a fan of Google), Google supplements the bid with a "quality score" which is determined based on the relevance to specific key words, quality of the landing page, click throughs and other things. Theoretically, this should be a win-win: the users finds what he is looking for, the advertiser realizes a sale. Does this give Google too much control?
Not everyone's a fan of Google
In his post on TechCrunch titled "Why advertising is failing on the internet" Eric Clemons ascribes Google's business model to "misdirection." He writes: " Misdirection most frequently takes the form of diverting customers to companies that they do not wish to find, simply because the customer’s preferred company underbid." This is certainly a risk, and this concern is likely one of the elements fueling the anti-trust charges Google is facing.
Google and Daily Deals Models
Another area Google has toyed with is partnering/competing with Groupon, or the "499" Groupon copycats as Andrew Mason reported to Matt Lauer this past January. Indeed, the business model is very easily copyable, and many have. I was intrigued, and googled the key words "Google Groupon." I uncovered some interesting information. The first link I followed talked about the launch on July 19, 2011 of a "new deals platform" " named "Link, Like, Love" powered by American Express and Facebook. You link your Amex account to Facebook, register for the deal, and the deal appears on your credit card bill in the form of a credit. (http://techcrunch.com/2011/07/19/160-year-old-american-express-out-innovates-google-and-groupon/) . Another link I clicked was a blog post on Wired.com introducing Google Offers, Google's daily deal site, in April 2011. (http://www.wired.com/epicenter/2011/04/google-groupon-2/). The battle is heating up. It appears all these websites are still primarily focus on large urban areas. The areas closest to me served by Groupon are Springfield, MO, about 70 miles East on I-44, and Tulsa, OK about 100 miles West on I-44. And yes, I signed up...
Google in the words of its CEO
The interview of Eric Schmidt by Charlie Rose was very interesting, though the link ended a few seconds past the 19 minute mark... I also decided to explore the Google website a little. I stumbled upon the Adwords new-user training video, where it explained a lot of the same things Schmidt and the article shared about how it works, and how to set it up. I'm finally starting to understand...
First, I thought it was very interesting that Charlie Rose's line of questions paralleled somewhat the summary of findings of the "Future of the Internet III" by Pew Internet and ALP we saw last week. Schmidt agreed that "the mobile device will be the primary connection tool to the internet." In our lifetime, and I paraphrase, he recognizes that we've gone from a world of zero communication ability to nearly 100% communication, from zero access to references to access to nearly every resource ever created. Spotify claims that it gives us access to every song ever recorded... He also touched on the role of transparency, and the world's increased transparency in consequence of the development of the internet. I liked his joke about working on a Politician BS Detector, cross-referencing anything they've ever said for consistency... He also addressed what his intellectual property philosophy/model is, which is also one of the issues raised by Pew and ALP. his stance reminded me of Pandora's Tim Westergren, where the royalties would flow straight to the right holders, on a per unit basis.
Second, Schmidt discussed Google on a more societal level... He recognizes the proliferation of user-generated content, which we talked about in a previous blog. He sees this content generation as a "defining expression of humanity." He came back to that when later in the interview, he discussed the turn the internet and media in general is taking to make our experiences more "personal." As more and more elaborate models are created to understand us, at the individual level, the more spot on the advertisement is likely to become. Ads will be less and less an annoyance, more and more a help in finding what we are looking for. As Levy writes, Page and Brin "also believed that ads should be useful and welcome - not annoying intrusions."
Finally, one cannot talk online business models without trying to figure out the monetization piece. Schmidt describes a very simple tiered model, based on page views. He proposes that 2 billion+ views should use ads to generate revenue, 2 million+ views should use micro-payments (a few cents per view), while highly specialized sites ought to use a subscription mechanism. He does not give any details on how this would work, and the logistics behind a micro-payment model seem daunting...
All in all, this week has allowed me to become more familiar with Google, and the impact it has on the internet. I do hope Schmidt is wrong on at least one point, namely that "great entrepreneurs break out early."
Saturday, July 23, 2011
Saturday, July 16, 2011
#501 - Week V - Part II - The Future of the Internet
The Pew Internet and American Life Project have produced their third and most recent report on the future of the internet in 2020. They surveyed Internet specialists and analysts, proposing a variety of scenarios, and assessing their responses.
I will go over the 8 scenarios proposed, and in one or two sentences describe why I do or do not agree with it, and compare that to the prevailing thought. I'll formulate my opinion before looking to see how the experts felt.
1. The mobile phone is the primary connection tool for most people in the world. Whether it is a phone, or another mobile device, this seems inevitable. The increase in computation power of these devices alone makes it likely that they'll be able to meet the needs of most. 77% of the experts also agreed
2. Social tolerance has advanced significantly due in great part to the internet. I'm having a hard time seeing a strong relation there. To the contrary, the internet could be a way to anonymously associate with people of like persuasion, and exacerbate intolerance. Only 32% agreed, while 56% disagreed.
3. Content control through copyright-protection technology dominates. I do not see that happening either. I believe as user-generated content continue to grow, the power of collective knowledge will dominate, and that we will see less and less copyright-protection sought. Once again, 60% of experts also disagreed.
4. Transparency heightens individual integrity and forgiveness. No doubt on the first one, as I believe it is already happening. I find it incredibly arrogant for celebrities or politicians to misbehave and think they can get away with it in this day and age. I would love for forgiveness to be on the rise also... Experts are split, 45% agreeing, 44% disagreeing, mostly citing wrongful accusations, and the need to rebuild one's wrongly tarnished reputation... not convinced.Wiener is one example of the former. When it comes to the latter, maybe, The jury is still out on IMF's DSK.
5. Many lives are touched by the use of augmented reality or spent interacting in artificial spaces. I guess this is where the movie "Surrogate" comes in. Great movie. That extreme will not be here by 2020, but I can see this as being appealing to many. So I think the idea valid. 55% of experts agree.
6. Talk and Touch are common technology interfaces. I think of all the scenarios so far, this is the easiest to see coming to reality very soon. Touch for sure will be the primary means to control interfaces. The days of the mouse are counted. People I know already use voice recognition technology to write essays and documents. I love the voice commands in my 2006 car. If we can do 3D, no doubt, this will happen. I am surprised that as many as 21% of experts disagree.
7. Next-generation research will be used to improve they current internet; it won't replace it. I think it depends how you define the internet. Is the Cloud still the internet? Wow, slam-dunk: 78% of expert agree! It seems they see the internet like a car, starting as a model T and always getting better, without changing its basic components... Unless you think more along the lines of David Hakken, a professor of anthropology at the Indiana University School of Informatics who studies social change and the use of automated information and communication technologies who predicts “By 2020, two major advances will have significant impact. The first is bioengineering and nanotechnology, allowing the Net to be ‘embedded’ into individual humans (scary, eh?); the second is quantum computing that will significantly alter the current electrically loaded computing engines.”
8. Few lines divide professional time from personal time, and that's OK. If we are all to become free-agents, then I guess this is true. I do not see us all becoming free-agents by 2020. Another reason I do not see this happening by 2020 is the fact that today devices are still really strong in one area: the iphone is great for surfing the internet, the blackberry is still the "professional" platform for e-mail. However, 56% of experts agree, seeing a "net-positive" impact. I'm not yet convinced...
I will go over the 8 scenarios proposed, and in one or two sentences describe why I do or do not agree with it, and compare that to the prevailing thought. I'll formulate my opinion before looking to see how the experts felt.
1. The mobile phone is the primary connection tool for most people in the world. Whether it is a phone, or another mobile device, this seems inevitable. The increase in computation power of these devices alone makes it likely that they'll be able to meet the needs of most. 77% of the experts also agreed
2. Social tolerance has advanced significantly due in great part to the internet. I'm having a hard time seeing a strong relation there. To the contrary, the internet could be a way to anonymously associate with people of like persuasion, and exacerbate intolerance. Only 32% agreed, while 56% disagreed.
3. Content control through copyright-protection technology dominates. I do not see that happening either. I believe as user-generated content continue to grow, the power of collective knowledge will dominate, and that we will see less and less copyright-protection sought. Once again, 60% of experts also disagreed.
4. Transparency heightens individual integrity and forgiveness. No doubt on the first one, as I believe it is already happening. I find it incredibly arrogant for celebrities or politicians to misbehave and think they can get away with it in this day and age. I would love for forgiveness to be on the rise also... Experts are split, 45% agreeing, 44% disagreeing, mostly citing wrongful accusations, and the need to rebuild one's wrongly tarnished reputation... not convinced.Wiener is one example of the former. When it comes to the latter, maybe, The jury is still out on IMF's DSK.
5. Many lives are touched by the use of augmented reality or spent interacting in artificial spaces. I guess this is where the movie "Surrogate" comes in. Great movie. That extreme will not be here by 2020, but I can see this as being appealing to many. So I think the idea valid. 55% of experts agree.
6. Talk and Touch are common technology interfaces. I think of all the scenarios so far, this is the easiest to see coming to reality very soon. Touch for sure will be the primary means to control interfaces. The days of the mouse are counted. People I know already use voice recognition technology to write essays and documents. I love the voice commands in my 2006 car. If we can do 3D, no doubt, this will happen. I am surprised that as many as 21% of experts disagree.
7. Next-generation research will be used to improve they current internet; it won't replace it. I think it depends how you define the internet. Is the Cloud still the internet? Wow, slam-dunk: 78% of expert agree! It seems they see the internet like a car, starting as a model T and always getting better, without changing its basic components... Unless you think more along the lines of David Hakken, a professor of anthropology at the Indiana University School of Informatics who studies social change and the use of automated information and communication technologies who predicts “By 2020, two major advances will have significant impact. The first is bioengineering and nanotechnology, allowing the Net to be ‘embedded’ into individual humans (scary, eh?); the second is quantum computing that will significantly alter the current electrically loaded computing engines.”
8. Few lines divide professional time from personal time, and that's OK. If we are all to become free-agents, then I guess this is true. I do not see us all becoming free-agents by 2020. Another reason I do not see this happening by 2020 is the fact that today devices are still really strong in one area: the iphone is great for surfing the internet, the blackberry is still the "professional" platform for e-mail. However, 56% of experts agree, seeing a "net-positive" impact. I'm not yet convinced...
X501 - Week V - Part I - Using Six Sigma to Model Human Behavior
The main idea behind web analytics is solving Y = f(x), where Y is our behavior, and x are all the inputs that lead us to behave the way the do.
In that regard, numerati and web analysts use many of the same tools six sigma practitioners, in particular black belts use as they go through the 5 step DMAIC process. That is a key reason I agree with the 10/90 rule. Analytics software is a lot like a vending machine. You plug in numbers, and it will spit out statistics. However, if you do not ask the right question, you will not collect the right data, and will not be able to use any output generated by the software. It is not about data, it is about the right data, collected the right way, to answer the right questions. You need people (six sigma black belts or analysts) to figure out the right questions, and build the data collection plans. As Avinash Kaushik writes in Web Analytics: An Hour a Day: "How data is captured is perhaps the most critical part of an analyst's ability to process the data and find insights."
I will now show how web analytics parallel the six sigma DMAIC process
1. Define - What is the practical business question we are asking, what is the problem we want to solve?
That's the starting point of any scientific inquiry. Since the purpose of analytics is solving Y=f(x), we need to define Y! The question can be very specific, like "why do romantic-movie lovers click on rental car ads," or more universal, as in "what drives consumer purchasing decisions?"
2. Measure - You start collecting data on your website. Kaushik writes: "Measuring how your website is delivering for your customers will help you focus your web analytics program and cause you to radically rethink the metrics that you need to measure to rate the performance of a website." You also start mapping the process by which you currently use analytics.
3. Analyze - In a typical six sigma sense, this is where you look for the root causes of your output performance. At this point, you are turning your practical business problem into a statistical problem. You begin by using divergent thinking to identify all the potential inputs into your process. There are millions of bits of information to sift through. Tacoda "harvests 20 billion of these behavioral clues every day." You begin to collect all the x's that may make up your model. Next, you go into convergent thinking, where you narrow down all your inputs to the critical few, foregoing the trivial many. The skill comes in finding correlation between the inputs and the outputs, and starting to build theoretical models of behavior, based on these inputs, or, as Stephen Baker writes in The Numerati, "the key to this process is to find similarities and patterns." One of the most intriguing points in the introduction to Numerati is how correlations can be built through indirect relationships and assumptions. Using the movies (Netflix, Hulu, Youtube?) or the music we listen to (say Pandora, Spotify), one could make an assumption about our mood, and use our mood to figure out what products we may be interested in... There are so many opportunities for discovery. A pioneering book on behavioral economics is Dan Ariely's "Predictably Irrational." Ariely writes on his blog:
"Good news. There is a science called Behavioral Economics. This attempts to understand people’s day to day decisions (where do I get my morning coffee?) and people’s big decisions (How much should I save for retirement?). Understanding HOW your users make decisions and WHY they make them is powerful. With this knowledge, companies can build more effective products, governments can create impactful policies and new ideas can gain faster traction."
4. Improve - At this point, you have an hypothesized model, and you must evaluate its accuracy, or more correctly, its usefulness. As statistician George Box said, "all models are wrong, some are useful." The criteria for a good model are, as described by Baker, that "they [the variables] must interact with one another mathematically just the way they do in the real world." Experimentation is the role of this stage in the development of models.
5. Control - Once you have a statistical model that works, you need to convert that statistical knowledge, or solution, to a practical solution, and use it in your marketing strategy. As you continue to refine this solution set, it is likely that the statistical equation you derive gets simplified. "All things being equal, the simplest solutions tends to be the best one." Will one model be enough? Of course not, as each model is only valid within the dataset it was developed with, i.e. its inference space. Baker alludes to this when he writes: "In the coming decade... we'll be modeled as workers, patients, soldiers, lovers, shoppers, and voters."
Baker goes even further, hinting at the idea of the "long tail," when he writes: "The trick is now to deliver to each of us the precise flavor and texture and color we want, at just the right price." Analytics are key, and Six Sigma can help!
In that regard, numerati and web analysts use many of the same tools six sigma practitioners, in particular black belts use as they go through the 5 step DMAIC process. That is a key reason I agree with the 10/90 rule. Analytics software is a lot like a vending machine. You plug in numbers, and it will spit out statistics. However, if you do not ask the right question, you will not collect the right data, and will not be able to use any output generated by the software. It is not about data, it is about the right data, collected the right way, to answer the right questions. You need people (six sigma black belts or analysts) to figure out the right questions, and build the data collection plans. As Avinash Kaushik writes in Web Analytics: An Hour a Day: "How data is captured is perhaps the most critical part of an analyst's ability to process the data and find insights."
I will now show how web analytics parallel the six sigma DMAIC process
1. Define - What is the practical business question we are asking, what is the problem we want to solve?
That's the starting point of any scientific inquiry. Since the purpose of analytics is solving Y=f(x), we need to define Y! The question can be very specific, like "why do romantic-movie lovers click on rental car ads," or more universal, as in "what drives consumer purchasing decisions?"
2. Measure - You start collecting data on your website. Kaushik writes: "Measuring how your website is delivering for your customers will help you focus your web analytics program and cause you to radically rethink the metrics that you need to measure to rate the performance of a website." You also start mapping the process by which you currently use analytics.
3. Analyze - In a typical six sigma sense, this is where you look for the root causes of your output performance. At this point, you are turning your practical business problem into a statistical problem. You begin by using divergent thinking to identify all the potential inputs into your process. There are millions of bits of information to sift through. Tacoda "harvests 20 billion of these behavioral clues every day." You begin to collect all the x's that may make up your model. Next, you go into convergent thinking, where you narrow down all your inputs to the critical few, foregoing the trivial many. The skill comes in finding correlation between the inputs and the outputs, and starting to build theoretical models of behavior, based on these inputs, or, as Stephen Baker writes in The Numerati, "the key to this process is to find similarities and patterns." One of the most intriguing points in the introduction to Numerati is how correlations can be built through indirect relationships and assumptions. Using the movies (Netflix, Hulu, Youtube?) or the music we listen to (say Pandora, Spotify), one could make an assumption about our mood, and use our mood to figure out what products we may be interested in... There are so many opportunities for discovery. A pioneering book on behavioral economics is Dan Ariely's "Predictably Irrational." Ariely writes on his blog:
"Good news. There is a science called Behavioral Economics. This attempts to understand people’s day to day decisions (where do I get my morning coffee?) and people’s big decisions (How much should I save for retirement?). Understanding HOW your users make decisions and WHY they make them is powerful. With this knowledge, companies can build more effective products, governments can create impactful policies and new ideas can gain faster traction."
4. Improve - At this point, you have an hypothesized model, and you must evaluate its accuracy, or more correctly, its usefulness. As statistician George Box said, "all models are wrong, some are useful." The criteria for a good model are, as described by Baker, that "they [the variables] must interact with one another mathematically just the way they do in the real world." Experimentation is the role of this stage in the development of models.
5. Control - Once you have a statistical model that works, you need to convert that statistical knowledge, or solution, to a practical solution, and use it in your marketing strategy. As you continue to refine this solution set, it is likely that the statistical equation you derive gets simplified. "All things being equal, the simplest solutions tends to be the best one." Will one model be enough? Of course not, as each model is only valid within the dataset it was developed with, i.e. its inference space. Baker alludes to this when he writes: "In the coming decade... we'll be modeled as workers, patients, soldiers, lovers, shoppers, and voters."
Baker goes even further, hinting at the idea of the "long tail," when he writes: "The trick is now to deliver to each of us the precise flavor and texture and color we want, at just the right price." Analytics are key, and Six Sigma can help!
Tuesday, July 12, 2011
Week 5 - Plan of Attack
Alright, Klout Score up to 32 - Makes me a Socializer. Sweet!
So this week's topic is Web Metrics and Marketing Research...
Yesterday, I watched a couple of videos on the history of the Internet. After watching the 8 minute Brief History of the Internet on Youtube, it was much easier to follow Frank Acito on his more detailed review... Vaguely reminds me of a movie, can't remember... oh yes Terminator... More on this later this week.
Got some reading left to do, namely the intro to "The Numerati" (Da Vinci Code anyone?), and the chapter about the "Critical Components of a Successful Web Analytics Strategy" since I dabble in business analytics professionally...
Finally, since I started the week looking at the past of the internet, it seems fitting that I end the week looking at what experts expect the future of the internet to be...
I'll Be Back!
So this week's topic is Web Metrics and Marketing Research...
Yesterday, I watched a couple of videos on the history of the Internet. After watching the 8 minute Brief History of the Internet on Youtube, it was much easier to follow Frank Acito on his more detailed review... Vaguely reminds me of a movie, can't remember... oh yes Terminator... More on this later this week.
Got some reading left to do, namely the intro to "The Numerati" (Da Vinci Code anyone?), and the chapter about the "Critical Components of a Successful Web Analytics Strategy" since I dabble in business analytics professionally...
Finally, since I started the week looking at the past of the internet, it seems fitting that I end the week looking at what experts expect the future of the internet to be...
I'll Be Back!
Saturday, July 2, 2011
Expanded Week IV - Show Me the Money!
Yes, "Show me the Money!" summarizes this week's reading very well...
How do you make money on the Web? I love how Jun Loayza begins in 5 Business Models for Social Media Start-up: "During the first internet boom, the most common business model was probably, 'get a ton of traffic, then figure out how to make money.'" It appears not that much has changed with Web2.0, though Social Media behemoths are launching IPOs left and right, and raising huge capital... I will use professor Rappa's framework as a starting point, expand on it by adding new examples, and finally wrap up with monetizing Tweeter.
1. Brokerage model - Websites that serve as middlemen, connecting sellers and customers. I look at these websites as Divergent/Convergent search engines. They first give you a large range of choices, and then you may cascade through other websites to narrow down the search. My experience with these broad search vehicles is that they come back with dozens of links. When you click on any of these links, you end up on seemingly independent merchants. However, under closer scrutiny, it often looks like you are dealing with the same vendor, using separate storefronts. The prices are the same, the descriptions are the same verbatim, even the pictures are exactly the same. I'm not a big fan of the brokerage model, as this is another example where more is not more. Charlie Kim, founder of NextJump, B2B Analytics company agrees: Offering 6 million products for customers to choose from is not smart. The same idea is developed by Richard Thaler in his best-selling book "Nudge." Websites that follow this model are Amazon.com, YahooShopping.com, PriceGrabber.com, Nextag.com. I think this is where branding, and brand loyalty come in. I develop brand loyalty, and go directly to the brand's website, bypassing "brokers." Not a big fan of this model... Interesting how American chose to remove its fare from Expedia, but was forced back in... AA still highly promotes its own website for booking, offering a very extensive "lowest price guarantee."
2. Advertising Model - To some extent, all websites dabble in advertising. It may be more or less targeted, but they all do it. This seems to be the obvious financing mechanism for many websites. Yahoo, Google and Facebook all collect customer data that they then use to assign their members to customer segment and target advertising. You come to expect banners on all free websites. Sometimes they're pretty subtle, sometimes, they are part of the interface. On Grooveshark, the advertiser fills out practically the entire screen, quite a turn-off.
3. Infomediary Model - Reid Hoffman, venture capitalist and founder of LinkedIn writes: "People think, "Oh no! This company has data about me!" To that I say: OK, so a website or mobile application knows that you're a man or a woman, and it's giving you ads based on that. That's a benefit, not a bug." I tend to agree. If you volunteer information, why wouldn't companies use that data to serve you better? Going back to Nudge, Thaler advocates freedom of choice, but making it easy for people (in this case customers) to choose the best solution to their need. Customer data can do that! Furthermore, Charlie Kim's best point was that companies should not use data "to guess." If they guess wrong, you end up with spam, which no one likes... But if you collect too much data, customers might feel violated by the perceived privacy breech and lose trust. Businesses will find themselves somewhere along this continuum... NextJump is a great example of helping businesses take the guess work out of targeted advertising. As long as these companies are transparent about what data is collected, and how it is used, I have no issues with this; I believe it can help them serve us better, but maybe I am too naive...
4. Merchant Model - Wholesaler. Most of the websites I visit in this category are "Click and Mortar" (I love that play on brick and mortar!) These models are able to build on the brand loyalty developed over years of patronizing the physical store. They are especially handy if you have to relocate and your favorite clothing store does not have a retail store where you live now. These companies probably have higher overheads, but are able to build brand loyalty, thereby increasing the percentage of repeat customers to their stores/website. Merchant models take the traditional shopping model, and move it to a new media. At this point, the only "Bit vendor" (another great terminology) I use is iTunes. I have not bought an actual CD in years, and don't think I ever will again. It's been interesting to see the music section in stores like Walmart or Target simply shrink and atrophy over the last few years. It used to be a must stop area in the store growing up... Jen Beckman's pitch for 20/200 was passionate. She has a very clear mission: "turning customers into connoisseurs of art." She is sharing the art she is so passionate about and making it accessible to the masses. Rebecca Thorman made a great pitch for Alice.com. I've registered and plan to try it out. It looks like the site offers adequate choice of my favorite brands and products. I am likely to convert if Alice.com is able to come through on its promise of better pricing than brick and mortar grocers.
5. Manufacturer (Direct) Model - Rappa gives the example of Dell. Other examples are Apple, Adidas, Banana Republic, Fossil (wink!) I find it interesting that some companies (TagHeuer for instance) refer you to licensed and authorized retailers, but do not sell their products on their website. I'm not sure there would be a downside to doing so...
6. Affiliate Model - B2B business model, likely used in conjunction with another business model...
7. Community/Subscription/Utility Models - Parra writes that these models are based on "user loyalty." This is where the Jun Loayza comes in. Typical revenue is generated through premium service subscription (Freemium model, like LinkedIn, Pandora...); sales of ancillary products and services (Affiliate Model); Content services (Subscription Model like Netflix), voluntary contributions (Virtual Goods Model), and contextual advertising (Advertising Model). I wonder if the utility model will become more prevalent, with limits on bandwidth, or if the infrastructure is able to keep up with increased usage, if this model will go the way of the dodo...
So, with all these business models out there, how does Twitter plan to make money? Currently, 97% of spending at Tweeter is going to the product and the technology. Evan Williams' purpose, he says, is to provide the best, freshest information available. Tweeter is not a social network, he continues, it is an information network. Who owns news? Is tweeter the new CNN? A timely Opinion piece by Gordon Crovitz in the Wall Street Journal address the legal side of who owns the news. I will not quote the entire "Technology Trumps Law" article, which can be found here and is worth the read:
http://online.wsj.com/article/SB10001424052702304569504576405672792064908.html , but here is a key extract: "But just because the law can't control how news spreads does not make technology a pure good. Google and Twitter filed a brief in Theflyonthewall, warning: "Hot news becomes cold in a nanosecond in the modern world." They don't want restriction on their business practices." When John Battelle insists, and rephrases his question, Evan still does not really answer. From his body language, I could not tell if he really did not know, or was unto something so revolutionary that he did not want to give it away... My money is on the latter...
How do you make money on the Web? I love how Jun Loayza begins in 5 Business Models for Social Media Start-up: "During the first internet boom, the most common business model was probably, 'get a ton of traffic, then figure out how to make money.'" It appears not that much has changed with Web2.0, though Social Media behemoths are launching IPOs left and right, and raising huge capital... I will use professor Rappa's framework as a starting point, expand on it by adding new examples, and finally wrap up with monetizing Tweeter.
1. Brokerage model - Websites that serve as middlemen, connecting sellers and customers. I look at these websites as Divergent/Convergent search engines. They first give you a large range of choices, and then you may cascade through other websites to narrow down the search. My experience with these broad search vehicles is that they come back with dozens of links. When you click on any of these links, you end up on seemingly independent merchants. However, under closer scrutiny, it often looks like you are dealing with the same vendor, using separate storefronts. The prices are the same, the descriptions are the same verbatim, even the pictures are exactly the same. I'm not a big fan of the brokerage model, as this is another example where more is not more. Charlie Kim, founder of NextJump, B2B Analytics company agrees: Offering 6 million products for customers to choose from is not smart. The same idea is developed by Richard Thaler in his best-selling book "Nudge." Websites that follow this model are Amazon.com, YahooShopping.com, PriceGrabber.com, Nextag.com. I think this is where branding, and brand loyalty come in. I develop brand loyalty, and go directly to the brand's website, bypassing "brokers." Not a big fan of this model... Interesting how American chose to remove its fare from Expedia, but was forced back in... AA still highly promotes its own website for booking, offering a very extensive "lowest price guarantee."
2. Advertising Model - To some extent, all websites dabble in advertising. It may be more or less targeted, but they all do it. This seems to be the obvious financing mechanism for many websites. Yahoo, Google and Facebook all collect customer data that they then use to assign their members to customer segment and target advertising. You come to expect banners on all free websites. Sometimes they're pretty subtle, sometimes, they are part of the interface. On Grooveshark, the advertiser fills out practically the entire screen, quite a turn-off.
3. Infomediary Model - Reid Hoffman, venture capitalist and founder of LinkedIn writes: "People think, "Oh no! This company has data about me!" To that I say: OK, so a website or mobile application knows that you're a man or a woman, and it's giving you ads based on that. That's a benefit, not a bug." I tend to agree. If you volunteer information, why wouldn't companies use that data to serve you better? Going back to Nudge, Thaler advocates freedom of choice, but making it easy for people (in this case customers) to choose the best solution to their need. Customer data can do that! Furthermore, Charlie Kim's best point was that companies should not use data "to guess." If they guess wrong, you end up with spam, which no one likes... But if you collect too much data, customers might feel violated by the perceived privacy breech and lose trust. Businesses will find themselves somewhere along this continuum... NextJump is a great example of helping businesses take the guess work out of targeted advertising. As long as these companies are transparent about what data is collected, and how it is used, I have no issues with this; I believe it can help them serve us better, but maybe I am too naive...
4. Merchant Model - Wholesaler. Most of the websites I visit in this category are "Click and Mortar" (I love that play on brick and mortar!) These models are able to build on the brand loyalty developed over years of patronizing the physical store. They are especially handy if you have to relocate and your favorite clothing store does not have a retail store where you live now. These companies probably have higher overheads, but are able to build brand loyalty, thereby increasing the percentage of repeat customers to their stores/website. Merchant models take the traditional shopping model, and move it to a new media. At this point, the only "Bit vendor" (another great terminology) I use is iTunes. I have not bought an actual CD in years, and don't think I ever will again. It's been interesting to see the music section in stores like Walmart or Target simply shrink and atrophy over the last few years. It used to be a must stop area in the store growing up... Jen Beckman's pitch for 20/200 was passionate. She has a very clear mission: "turning customers into connoisseurs of art." She is sharing the art she is so passionate about and making it accessible to the masses. Rebecca Thorman made a great pitch for Alice.com. I've registered and plan to try it out. It looks like the site offers adequate choice of my favorite brands and products. I am likely to convert if Alice.com is able to come through on its promise of better pricing than brick and mortar grocers.
5. Manufacturer (Direct) Model - Rappa gives the example of Dell. Other examples are Apple, Adidas, Banana Republic, Fossil (wink!) I find it interesting that some companies (TagHeuer for instance) refer you to licensed and authorized retailers, but do not sell their products on their website. I'm not sure there would be a downside to doing so...
6. Affiliate Model - B2B business model, likely used in conjunction with another business model...
7. Community/Subscription/Utility Models - Parra writes that these models are based on "user loyalty." This is where the Jun Loayza comes in. Typical revenue is generated through premium service subscription (Freemium model, like LinkedIn, Pandora...); sales of ancillary products and services (Affiliate Model); Content services (Subscription Model like Netflix), voluntary contributions (Virtual Goods Model), and contextual advertising (Advertising Model). I wonder if the utility model will become more prevalent, with limits on bandwidth, or if the infrastructure is able to keep up with increased usage, if this model will go the way of the dodo...
So, with all these business models out there, how does Twitter plan to make money? Currently, 97% of spending at Tweeter is going to the product and the technology. Evan Williams' purpose, he says, is to provide the best, freshest information available. Tweeter is not a social network, he continues, it is an information network. Who owns news? Is tweeter the new CNN? A timely Opinion piece by Gordon Crovitz in the Wall Street Journal address the legal side of who owns the news. I will not quote the entire "Technology Trumps Law" article, which can be found here and is worth the read:
http://online.wsj.com/article/SB10001424052702304569504576405672792064908.html , but here is a key extract: "But just because the law can't control how news spreads does not make technology a pure good. Google and Twitter filed a brief in Theflyonthewall, warning: "Hot news becomes cold in a nanosecond in the modern world." They don't want restriction on their business practices." When John Battelle insists, and rephrases his question, Evan still does not really answer. From his body language, I could not tell if he really did not know, or was unto something so revolutionary that he did not want to give it away... My money is on the latter...
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