58 percent of nearly 800 users of social networking sites say that very few of the ads and offers they're currently seeing on social networking sites match their specific interests and preferences, and another 29 percent say none of them do, as reported in a recently released Prospectiv poll. Only 13 percent say that "most" ads meet their interests and preferences.
56 percent polled said the quality of their online experience would be improved if social networking sites provided more targeted advertisements and offers tailored to their specific interests and preferences.
According to the survey, consumers said the types of tailored ads and offers they would respond to are:
One-off coupons and discount offers from the brands and products they buy (62 percent)
E-newsletters featuring coupons, discounts, news and tips about favorite brands (24 percent)
Invitations to join interactive email groups, online forums and social networks for sharing and communicating (14 percent)
85 percent of consumers said they are more likely to join a free social networking site supported by advertisements and offers targeted to their interests rather than a paid social networking site without commercial advertisements. The report says that:
54 percent of consumers never click on advertisements on social networks
39 percent of consumers occasionally will respond to ads
7 percent will often respond to ads
Jere Doyle, Prospectiv's CEO, concludes that "... members of social networking sites are open to offers and promotions as long as they are targeted to their interests... the web publishing industry seeking to monetize their online communities (needs) to improve ad relevance..."
At the same time, a recent eMarketer study says that "Social networks... show some promise in developing new forms of online advertising. MySpace's HyperTargeting initiative, for example, has helped double CPMs at the site, and 75% of advertisers that have tried it have come back for more, according to News Corp..."
The eMarketer projections say that combined, MySpace and Facebook are expected to account for 72% of the total US social network ad spending pie this year. Spending at all other online social network sites, including general social networks, niche networks and marketer-created networks, is expected to reach $370 million, while widget and application ad spending is projected to rise to $40 million this year.
US Online Social Networking Ad Spending (Billion Dollars)
Social Network Ad Spend
Showing posts with label relevance. Show all posts
Showing posts with label relevance. Show all posts
Friday, May 30, 2008
Tuesday, January 29, 2008
Platforms, Applications and the Future of Digital Marketing
REST APIs, Rules and Relevance
In the user controlled medium that is digital advertising success is predicated on delivering relevance. Nowhere is this exemplified better than the success of search where there is a data input (rule 1) and multiple additional rules (geo and behavioral) that results in the delivery of content believed to be most relevant to the goals of the user. There is no question that the race to gain access to more implicit and explicit input data from users and from publishers to create rules will continue to increase the ability for marketers to deliver relevance in the coming years.
There are three components of this that marketers need to understand.
1. The tools for gathering and structuring content into a marketing corpus (ads, articles, products, whatever)
2. The tools for creating rules based delivery (testing, targeting)
3. The methodologies for executing and presenting optimized creative
In the next 12-24 months online marketing success will continue to be less and less about banners and websites and more and more about the dynamic experience everywhere. We need to look “under the hood” at content as being a database platform that improves our ability to present and deliver content. The changes this effects with the strategic and creative use of data through APIs and algorithms is profound.
Pull it Forward
Once content is free from the restrictions and limitations of site architecture and reliance on traffic sources marketers are empowered to create more compelling and relevant digital solutions. This can take the form of advertising unit widgets, dynamic landing pages, microsites, search interfaces and a host of new and useful applications.
Increased relevance will be delivered in the what (messages) but more impact and success for advertisers and publishers will be felt in the where -- bringing tools to deliver relevance closer to users creates better experiences. The same basic principles that apply for search should be your guide and inspiration to create an API that you can use to deliver relevance anywhere, especially in display (where successful ad units are increasingly more dynamic and interactive) or the emerging use of widgets/gadgets.
Distributing user controlled functionality into your business at multiple touch-points is the core idea behind the distributed web or web as a platform. Though this is not new for search engines or publishers (think toolbars or syndication) we are just beginning to scratch the surface of it as a highly optimized advertising solution. Just today Union Square Ventures announced funding of a platform based company that doesn’t even have a website!
Relevance Breeds Emotion
The net result of all this is that deeper and more engaged user interactions are taking place and breeding higher levels of emotional connection to digital -- as the web becomes more intelligent it becomes more relevant. This connection with intelligence leads to higher returns both in transactional measurements and brand value. It’s how Google has built one of the strongest brands in the world while at its core it is the greatest direct marketing platform the world has known. Platform marketing allows you to apply these same principles to achieve success with your online business.
There is one important last piece that can’t be overlooked to ensure success. Marketers and creative folks must begin to understand technology and learn how to use it creatively. This will be the biggest hurdle to success. The days of siloed IT and Marketing, of Creative Directors that don’t know their clients Content Management Systems will end in a fiery furnace filled with ashen businesses and agencies.
In the first decade of the commercial net access to data smote a number of verticals like travel and music. In the next decade far greater access to data will continue to destroy a number of now successful businesses and advertising models. It will also create many revolutionary opportunities and digital success stories. Which will you be? The answer probably rests in if you have or will create a plan in the next 6-12 months for creating the platform, rules and delivery of your marketing content.
NOTE 1/16: Paid Content has an interview today with Google's Andy Berndt where he touches on creating marketing platforms.
"all new platforms give an early advantage to those who can best manipulate the technology itself, the best technicians. After the platform becomes user friendly, when it is opened up to the best storytellers and designers and communicators, they tend to add another level to it. The rare time when you find people who really appreciate both sides of that coin (innovation and storytelling) is where truly amazing things happen."It's a good read. More here
Tuesday, January 8, 2008
What is the Recommender Industry?
GUEST COLUMN: What is the Recommender Industry?
Author: MSG Staff
By Dr. Rick Hangartner
Dr. Rick Hangartner, Chief Scientist, MyStrands, has nearly 30 years experience developing computing hardware and software in the aerospace, data communications, heavy-trucking, and supercomputing industries. Prior to joining MyStrands, he worked for seven years at Cray, Inc. developing high performance computing hardware and software.
No, the headline on this entry is not a careless grammatical error. Nor is the question really “What is the recommender market?” That would imply that “recommenders” are mature, well-defined technologies that deliver specific features and value to the online world. Emerging recommendation technologies are currently setting the standards for discovery and personalization in today’s social networking-dominated Web 2.0 environment-and the future of online social networking is all about discovery and personalization. While search engines help you find things you know you are looking for, discovery helps you find the rest.
If we accept that every business must make its case in 10 to 20 seconds on its Web site, then we are all but forced to admit that recommenders, more than anything else, represent the conceptual answer to the question, “How can I get that visitor/user/customer to realize that I offer something of value to him or her?”
Although venture capitalists and Web 2.0 users may find that claim to be just the tiresome excuse they need for hitting the “Back” button, the point is that a good argument can be made that unlike search engines, the recommender idea is a formal concept that has as many different concrete examples as there are separate market applications.
The recommender industry really is the business of pulling three components together into a system that helps a user-driven business convince their potential customers that they should stay for a while. These three elements include,
1) An effective model that relates the needs visitors have to what the business offers,
2) Quality data to build a model instance that relates specific needs to specific offerings, and
3) Unobtrusive means for easily and quickly determining an individual user’s needs.
Note that these three components are not quite as simple as “good (statistical) algorithms,” “a lot of data,” or “simple user interfaces.” In the coming years, defining an effective model will increasingly involve a scientific approach to understanding user needs and the market strategy of the business. Gathering quality data will require more sophisticated understanding of which data are actually relevant to the model. Devising means for characterizing an individual user’s needs will depend on a refined understanding of how people implicitly and explicitly signal needs that they themselves may not even fully understand.
In short, the recommender industry is the evolving business of building and deploying systems that reify some of the psychology of human economic transactions. What this means for the marketplace seems relatively clear: Search engines as we know them will never disappear. In the near term, search engines will increasingly incorporate simple recommender technologies to handle approximate queries (e.g., “You asked for this, and based on similar queries/behavior by others, you might be looking for this.”). But in the long term, the recommender industry will be larger, and recommender technologies will be more pervasive than the search industry and search technology as we know it.
Beyond that, some general themes about the future of the recommender industry that seem to be worth watching for include,
Multiple revenue models: Unlike search engines, which primarily are monetized through contextual ads of some form, recommender systems will be monetized in multiple ways. Recommender technology suppliers will continue to partner with customer businesses to derive revenue as a share of explicit sales increases directly accredited to the recommender system. In the longer term, recommender technology will increasingly enable business models, including advertising schemes, which could not exist without it. An implicit valuation for a specific application of a recommender system will be derived from the enabled economic activity.
Increasing focus on how users require change over time: In that recommender systems reify aspects of the psychology of economic transactions, there is an increasing appreciation for the probable value of responding to how economic behavior changes over time. This includes how an individual’s needs change over time and how the needs of the community evolve. The former can, in part, be accommodated by simply taking care to build a recommender system instance using data that is an adequate sampling of individuals whose needs are changing. Adapting to the latter may require recommender system models that explicitly incorporate features of how community needs to evolve.
New concepts of personalization: One of the recent trends in personalization is using information about an individual’s social network to better characterize that individual’s needs and interests. This may be just one aspect of a new concept of personalization that puts the focus not on delivering an isolating, customized experience to a person, but rather on connecting an individual with affinity communities who can provide information of value to that individual. Few people really want to be out there all alone. And for those explorers who do, they might, in reality, be hoping to build a community of like-minded souls or be waiting for others to catch up with them.
More than anything, the future of the recommender industry is a business that will continue to grow and become more sophisticated as the science of recommenders greatly develops to increasingly encompasses computer science, psychology, economics and cognitive science.
Author: MSG Staff
By Dr. Rick Hangartner
Dr. Rick Hangartner, Chief Scientist, MyStrands,
No, the headline on this entry is not a careless grammatical error. Nor is the question really “What is the recommender market?” That would imply that “recommenders” are mature, well-defined technologies that deliver specific features and value to the online world. Emerging recommendation technologies are currently setting the standards for discovery and personalization in today’s social networking-dominated Web 2.0 environment-and the future of online social networking is all about discovery and personalization. While search engines help you find things you know you are looking for, discovery helps you find the rest.
If we accept that every business must make its case in 10 to 20 seconds on its Web site, then we are all but forced to admit that recommenders, more than anything else, represent the conceptual answer to the question, “How can I get that visitor/user/customer to realize that I offer something of value to him or her?”
Although venture capitalists and Web 2.0 users may find that claim to be just the tiresome excuse they need for hitting the “Back” button, the point is that a good argument can be made that unlike search engines, the recommender idea is a formal concept that has as many different concrete examples as there are separate market applications.
The recommender industry really is the business of pulling three components together into a system that helps a user-driven business convince their potential customers that they should stay for a while. These three elements include,
1) An effective model that relates the needs visitors have to what the business offers,
2) Quality data to build a model instance that relates specific needs to specific offerings, and
3) Unobtrusive means for easily and quickly determining an individual user’s needs.
Note that these three components are not quite as simple as “good (statistical) algorithms,” “a lot of data,” or “simple user interfaces.” In the coming years, defining an effective model will increasingly involve a scientific approach to understanding user needs and the market strategy of the business. Gathering quality data will require more sophisticated understanding of which data are actually relevant to the model. Devising means for characterizing an individual user’s needs will depend on a refined understanding of how people implicitly and explicitly signal needs that they themselves may not even fully understand.
In short, the recommender industry is the evolving business of building and deploying systems that reify some of the psychology of human economic transactions. What this means for the marketplace seems relatively clear: Search engines as we know them will never disappear. In the near term, search engines will increasingly incorporate simple recommender technologies to handle approximate queries (e.g., “You asked for this, and based on similar queries/behavior by others, you might be looking for this.”). But in the long term, the recommender industry will be larger, and recommender technologies will be more pervasive than the search industry and search technology as we know it.
Beyond that, some general themes about the future of the recommender industry that seem to be worth watching for include,
Multiple revenue models: Unlike search engines, which primarily are monetized through contextual ads of some form, recommender systems will be monetized in multiple ways. Recommender technology suppliers will continue to partner with customer businesses to derive revenue as a share of explicit sales increases directly accredited to the recommender system. In the longer term, recommender technology will increasingly enable business models, including advertising schemes, which could not exist without it. An implicit valuation for a specific application of a recommender system will be derived from the enabled economic activity.
Increasing focus on how users require change over time: In that recommender systems reify aspects of the psychology of economic transactions, there is an increasing appreciation for the probable value of responding to how economic behavior changes over time. This includes how an individual’s needs change over time and how the needs of the community evolve. The former can, in part, be accommodated by simply taking care to build a recommender system instance using data that is an adequate sampling of individuals whose needs are changing. Adapting to the latter may require recommender system models that explicitly incorporate features of how community needs to evolve.
New concepts of personalization: One of the recent trends in personalization is using information about an individual’s social network to better characterize that individual’s needs and interests. This may be just one aspect of a new concept of personalization that puts the focus not on delivering an isolating, customized experience to a person, but rather on connecting an individual with affinity communities who can provide information of value to that individual. Few people really want to be out there all alone. And for those explorers who do, they might, in reality, be hoping to build a community of like-minded souls or be waiting for others to catch up with them.
More than anything, the future of the recommender industry is a business that will continue to grow and become more sophisticated as the science of recommenders greatly develops to increasingly encompasses computer science, psychology, economics and cognitive science.
Monday, December 17, 2007
MediaTrust ALERT : new oneQube home page
Chris Smith and Joe have turned out a new home page for oneQube . Nice new look as we move forward into 2008 launches.
In the first week of January we will be giving a company wide update on oneQube. This company session will start to be a regular series on oneQube and other areas of MediaTrust.
In the first week of January we will be giving a company wide update on oneQube. This company session will start to be a regular series on oneQube and other areas of MediaTrust.
Sunday, October 7, 2007
Why So Little Relevance?
Why So Little Relevance?
By Dave Morgan
I've written about this topic before, but it keeps coming up -- I heard it a lot during Advertising Week -- so I thought that I should address it again. We all know that online advertising has the capacity to do extraordinary things when it comes to delivering highly addressable and measured advertising. Many of us well remember the DoubleClick trade campaigns in the late '90s about delivering "the right ad to the right person at the right time." The ability of our industry to deliver highly targeted advertising has advanced significantly since those days. Now we have sophisticated search targeting, contextual targeting, behavioral targeting, and e-commerce recommendation engines.
How is it then, many ask, when you go to most Web pages, you get the same old ads that you see everywhere, and you rarely see ads that are truly relevant to you? Conversely, how many times have you browsed to a Web page and exclaimed, "Wow. Those are really great ads!" It happens with television and magazines a whole lot more than it happens on the Web. Only on search results pages do most folks find a whole lot of relevance in ads as a regular part of the experience. Although such ads may not evoke exclamations of "Great ads!" they generally lead to a favorable action for marketers, since they are highly relevant to the user at that moment.
Why is that? Why don't we find more relevant ads online more often, in more places? It is certainly not a matter of technology. We now have ad delivery technologies that can do with ads just about anything that you could imagine.
In my opinion, it isn't the lack of ability to deliver a relevant ad that is holding us back; rather, it is the lack of relevant ads to deliver. We just don't have creative enough arrows in the quiver. We don't have enough different ads with enough unique and differentiating elements that can communicate specific relevant messages to consumers. What can be done? Lots, I believe.
Scale. We need more scaled platforms. More scale in the ad delivery platforms, and more coordination of the messages being delivered to the consumers at each point of contact, means a much greater ability to manage relevance at the browser level.
Creative Focus. We need much, much more focus on creative. We have seen some taking the lead in this space like Alan Schulman of imc2, but we need many more. We need agencies and advertisers to push harder to create dynamic advertising units that can be segmented to consumers to communicate more relevant messages. Creatives need to focus more and more on building relevance with their messages.
Dynamic Creative Technologies. We need more and better technologies to manage better and more sophisticated creatives. Yahoo's SmartAds is a good step. We need more.
Restraint. We need publishers, advertisers, agencies and ad networks to show much more restraint in their senseless bombardment of consumers with irrelevant ads. One of the best ways to show consumers that we can deliver more relevance is to stop delivering so much irrelevance. Fewer, more relevant ads; that should be our mantra.
By Dave Morgan
I've written about this topic before, but it keeps coming up -- I heard it a lot during Advertising Week -- so I thought that I should address it again. We all know that online advertising has the capacity to do extraordinary things when it comes to delivering highly addressable and measured advertising. Many of us well remember the DoubleClick trade campaigns in the late '90s about delivering "the right ad to the right person at the right time." The ability of our industry to deliver highly targeted advertising has advanced significantly since those days. Now we have sophisticated search targeting, contextual targeting, behavioral targeting, and e-commerce recommendation engines.
How is it then, many ask, when you go to most Web pages, you get the same old ads that you see everywhere, and you rarely see ads that are truly relevant to you? Conversely, how many times have you browsed to a Web page and exclaimed, "Wow. Those are really great ads!" It happens with television and magazines a whole lot more than it happens on the Web. Only on search results pages do most folks find a whole lot of relevance in ads as a regular part of the experience. Although such ads may not evoke exclamations of "Great ads!" they generally lead to a favorable action for marketers, since they are highly relevant to the user at that moment.
Why is that? Why don't we find more relevant ads online more often, in more places? It is certainly not a matter of technology. We now have ad delivery technologies that can do with ads just about anything that you could imagine.
In my opinion, it isn't the lack of ability to deliver a relevant ad that is holding us back; rather, it is the lack of relevant ads to deliver. We just don't have creative enough arrows in the quiver. We don't have enough different ads with enough unique and differentiating elements that can communicate specific relevant messages to consumers. What can be done? Lots, I believe.
Scale. We need more scaled platforms. More scale in the ad delivery platforms, and more coordination of the messages being delivered to the consumers at each point of contact, means a much greater ability to manage relevance at the browser level.
Creative Focus. We need much, much more focus on creative. We have seen some taking the lead in this space like Alan Schulman of imc2, but we need many more. We need agencies and advertisers to push harder to create dynamic advertising units that can be segmented to consumers to communicate more relevant messages. Creatives need to focus more and more on building relevance with their messages.
Dynamic Creative Technologies. We need more and better technologies to manage better and more sophisticated creatives. Yahoo's SmartAds is a good step. We need more.
Restraint. We need publishers, advertisers, agencies and ad networks to show much more restraint in their senseless bombardment of consumers with irrelevant ads. One of the best ways to show consumers that we can deliver more relevance is to stop delivering so much irrelevance. Fewer, more relevant ads; that should be our mantra.
Sunday, July 29, 2007
TrustedOpinion: Another spin on recommendation services
TrustedOpinion: Another spin on recommendation servicesTrustedOpinions calls this the Radar Score, and it does a very good job of simplifying the data. The system also shows you how your own calculated rating on a product is different from the site-wide average.One score does not fit all. ...Original Signal - Transmitting Web 2.0 - http://web20.originalsignal.com
Monday, July 9, 2007
What's next for the Internet
Nova Spivack is racing to bring meaning and order to the chaos of the Internet. And he's not alone. Business 2.0 reports.
(Business 2.0 Magazine) -- After taking one of the first Internet companies -- EarthWeb -- public in 1998, Nova Spivack joined some friends at a weedy airstrip deep inside the new Russia for a trip into Earth's stratosphere.
Having space travel on your resume is de rigueur for Internet entrepreneurs these days, but this was 1999, and not even the Russian pilots were sure how the flight would turn out. As Spivack was being strapped into a MiG-25 and prepped for his trip at Mach 3, about 20 miles straight up, he looked around for an ejection button or lever in case things went south.
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| To build a smarter Web, Nova Spivack is finding ways for machines to do more of the work. |
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| John Giannandrea, Danny Hillis, and Robert Cook founded Metaweb Technologies with the goal of building a semantic Web structure -- think of it as a semantic Wikipedia -- for all the world's knowledge. |
|
There wasn't one. "'Don't worry about eet,' the pilot told me," says Spivack, mustering his best Russian accent. "At the speed you will be going, even if you could eject, first your body would explode into vapor, then the vapor would freeze into ice crystals, and then the crystals would burn up on reentry."
With that, they taxied down the runway for a quick ride to the edge of space.
Spivack returned in one piece ready to launch more startups, but the image of his body exploded into ice crystals and skittering into the stratosphere never left him. And in fact, it's not a bad metaphor -- in reverse -- for what his newest venture is trying to do.
If you think of the World Wide Web as a cloud of largely undifferentiated information, the mission of the company he's about to unveil, Radar Networks, is to take that cloud and impose order on it. Not just any order, but a very special kind known to experts by one of the hottest buzzwords in computer science today: the semantic Web.
For all the wonders that today's Web can deliver to your fingertips -- the Norwegian word for ice cream, a seat on the next flight to Paris, the best price for a Clash CD -- it has a fundamental flaw.
It's basically a compendium of billions of text documents designed to be read by humans. You can search it for keywords, but the results aren't much use until you sort through them to find the page that has the info you want.
To take the Web to the next level -- to move from Web 2.0 to Web 3.0 -- the information in those documents will have to be turned into data that a machine can read and evaluate on its own. Only then will computers be able to take over tasks we now do by hand: find the nearest restaurant, book the best flight, buy the cheapest CD.
Think of it as the difference between two dimensions and three dimensions. "People will see the Web start to become smarter," Spivack says. "Eventually it will have some reasoning capabilities built into it."
We'll get to how that happens in a bit. For Spivack, however, the semantic Web begins now with the data engine and user applications he and his team are prepping for launch -- and ends somewhere in the future with artificially intelligent software agents handling all the online drudgery of your business and professional life.
Radar Networks isn't the only company exploring the potential of the semantic Web. It's a disruptive technology with the power to unseat today's Internet titans -- especially search engine giants like Google (Charts, Fortune 500) and Yahoo (Charts, Fortune 500) -- and it's being vigorously pursued by startups like Garlik, Metaweb Technologies, Powerset, and ZoomInfo, as well as big corporations like Citigroup (Charts, Fortune 500), Eli Lilly, Kodak (Charts, Fortune 500), Oracle (Charts, Fortune 500), and Google and Yahoo themselves.
One estimate pegs the market for products and services stemming from semantic Web technologies at $50 billion by 2010, up from about $7 billion today.
But for all the entrepreneurs ready to spin gold out of the semantic Web, there are as many skeptics convinced that it's a pipe dream -- a fancy name for a problem that will never be fully solved. Spivack, with the confidence of a man who has been to space without a safety net, is determined to prove them wrong.
Radar Networks is housed in a renovated warehouse not far from the ballpark where the San Francisco Giants play. Inside, massive redwood timbers span the high ceilings alongside thick clusters of data cable. A Nintendo Wii and a shiny new De'Longhi espresso machine are the only outward signs of anything being done here but mind-bending work.
There are 20 people at the company now, but there's space for 50, and with just a bit less than $10 million in venture funding, Spivack and his senior executives are busy hiring.
The background of the Radar team includes deep expertise in statistics, bioinformatics, and artificial intelligence. Radar's chief architect, Jim Wissner, is a Java ace. Chris Jones, director of products and operations, is a design and user interface whiz. CTO Lew Tucker got his start by mapping neural transmitters in the brain. Tucker and Spivack go back to the late '80s, when they both worked for Danny Hillis at Thinking Machines.
Given all the firepower assembled at Radar Networks, you get the sense that this is not your typical Web startup. And it's not. The task the company has set for itself -- bringing the power of the semantic Web to the Internet -- is not easy to describe. Even the man who invented the Web, Tim Berners-Lee, needs a little room to explain why it's important.
The term "semantic Web" first gained prominence in a 2001 article by Berners-Lee and two coauthors, James Hendler and Ora Lassila, in Scientific American. In it they described software agents roaming across the Web, making travel arrangements and doctor's appointments and muting the stereo when the telephone rings.
It was a great vision, but it couldn't be achieved with today's Internet.
For the semantic Web to work, online information needs to be made readable by machines. Services like Google do a great job of sifting through all those webpages, but it's up to people to recognize the things they want when they see them in the results. It's also up to people to combine information to, say, plan a long-overdue ski trip.
The Web just isn't very smart yet; one webpage is the same as any other. It might have a higher Google ranking, but there's no distinction based on meaning.
The semantic Web in the Berners-Lee vision acts more like a series of connected databases, where all information resides in a structured form. Within that structure is a layer of description that adds meaning that the computer can understand. ("Semantics" is the branch of linguistics concerned with meaning.)
On the semantic Web, a person -- Nova Spivack, for example -- isn't just a name that comes up on webpages when you google him. He's a fully described object endowed with certain well-defined properties: a date of birth, a job title, a home address, specific hobbies, the fact that he is the grandson of legendary management thinker Peter Drucker.
People on the semantic Web have unambiguous connections to the places they work, the people they're related to, their friends, their calendars, and the things they're interested in. Being able to connect those properties in seen and unseen ways is what gives the semantic Web its power.
Consider this scenario: Say you want to arrange a dinner at an upcoming conference. Today you might go through your address book and ping folks by e-mail to see who's attending. Then you probably send out e-mail invitations to dinner. You go back and forth with the group on the place and time, somehow you all agree, and then somebody makes a reservation. Files fly back and forth, with humans at the center.
In the semantic Web, your software agent will "know" in advance what's involved in arranging a dinner. Instead of you sending out a flurry of e-mails, the agent could cull the conference attendees and make a list of potential invitees.
It might also look through your address book to see which of your friends live in the city where the conference is being held. Once a list of potential dinner guests has been approved by you, the agent would negotiate the date and time with everyone else's agents via a calendar database, pick a restaurant from another database based on availability and your personal preferences, make the reservation, and send out directions. In a GPS-enabled world, it could even let you know how far a guest who is running late has to go.
Of course, it's been six years since Berners-Lee put his vision out there, and you still can't get that sort of service. Tagging is a start, and services like Flickr offer a sort of crude Web 2.0 version of the semantic Web. Google Base is another stab at bringing semantic technologies to the wider Web, serving as a place where anyone can enter data and have it searched, but it doesn't use the semantic approach from start to finish.
Bringing a true semantic Web to the world is a chicken-and-egg problem. Until there's enough data rendered in computer-readable form (resource description framework, or RDF, is the leading standard) with enough metadata attached to it to make it meaningful, nobody is going to be able to create any interesting services.
The agents of the semantic Web need the raw ingredients before they can make their soufflés.
But you can do some interesting things within subsets of the Web. Large pharmaceutical companies like Eli Lilly (Charts, Fortune 500) have been experimenting with adding a semantic layer on top of their drug discovery databases to help scientists see connections between drug molecules and diseases.
Amazon.com (Charts, Fortune 500) is keen on using semantic technologies to help customers search its databases. Kodak wants semantic tagging to help photographers organize their snapshots online. The CIA has been loading its databases of overseas phone taps into semantic "mills" to make it easier to sift for connections between people, places, and incidents -- hoping to spot terror threats before it's too late.
"But how do you make this thing really useful for ordinary people?" asks Radar CTO Tucker. "Not everyone is a CIA analyst."
Spivack's answer grew out of conversations he had with Drucker in the summer of 2001, about four years before the professor's passing. "We would meet for two hours a day and talk about organizations vs. organisms," Spivack says. Drucker was particularly interested in what he called the intelligence of organizations. "My grandfather helped me think about group minds," Spivack says. "How groups get more intelligent, and how connections play into that."
Since bringing the semantic Web into the world is a chicken-and-egg proposition, Radar Networks has built both the chicken and the egg. The chicken is the underlying engine the team has created that not only turns data into simple but meaningful digital objects via RDF but also scales up to hold hundreds of millions of objects that can be searched, swapped, and connected to one another. The egg is the user application that rides on top of it all.
The first consumer app Radar plans to launch is a sort of personal data organizer. It will allow you to bring in e-mail, contacts, photos, video, music --anything digital, really -- from anywhere on the Web, turn it into RDF, and access it in one place.
Semantic tags are added manually, or automatically if the item is a photo from Flickr or a video from YouTube. "We add a new level of order to connect and interact with these things at a higher level than is possible today," Spivack says. "We are letting you build a little semantic Web for your project, your group, or your interest."
When it's done, it should be like the best wiki you've ever used. To illustrate, Spivack flips open his computer and pulls up his own Radar-enabled page. On it are groups of people he knows and interests he's pursuing, including the space industry, alternative energy, physics, Internet-related technology, and skiing. In each of these categories are objects that Spivack has collected and tagged or, if it is a topic that has multiple people included, that they have collected and tagged.
In the skiing topic, for example, Spivack has posed a question: Where should we go skiing? One of the responses is Alta, Utah. When Spivack clicks on that item, the Radar engine goes out and finds all the things in the Radar Networks database related to Alta. It "knows" that Alta, in this case, refers to a place (as opposed to the Spanish word for "high"), so there are hotel suggestions. There are also photos, videos, trail maps, and comments from people in his group who have skied there before.
In a sense, what Radar allows Spivack to do is build a database around any question, project, or interest he may have and then start looking at it from different perspectives: cost, distance from San Francisco, snow conditions in March, nearby restaurants, what his friends liked about a particular resort.
And if they liked Alta, what other places did they like? "You start to see new ways to look at the information," Spivack says. "What gets me excited is what we can do when we have billions of objects and 10 million people using them."
For that to happen, of course, people need to start adding their own digital stuff to the mix. The digital life organizer is the bait Spivack and his team are using to try to draw them in. The team will also open Radar Networks to outside developers to write their own applications. Those might involve travel, food, or a better way to manage large projects.
Radar hopes to be the engine powering all that, providing a massive, meaning-filled Web of data that can be infinitely poked and prodded and leveraged. The company will make its money from advertising and premium subscriptions; the basic service will be free.
But don't expect a sci-fi software agent that takes care of your every whim -- Spivack is quick to say that's not what Radar is launching. "Those people who think we will be offering Hal 9000 when this goes public in October will be disappointed," he says. "We've had the problem of overpromising in this industry; a lot of us who were working on semantic Web technologies early on saw the potential and got a little excited. It has taken much longer to realize than we thought. One thing Web 2.0 has taught everybody is that simpler is better. Find something useful and iterate on that."
Tom Coates, whose day job at Yahoo involves working on just these issues, thinks the Web 2.0 crowd is already taking care of the problem. He points to tagging and microformats that add some of the same metadata to webpages that semantic technologies offer.
"I call it the dirty semantic Web," Coates says from his London office. "It may not be the pristine Berners-Lee view of the world, but it is headed in the right direction."
On a lark, Coates and a colleague created a site called Astronewsology that demonstrates the power of a semantic approach by combining news reports and horoscopes. Using it, you can search the news by the sign Capricorn and see whether that day's horoscope had any bearing on what happened to people born between Dec. 22 and Jan. 20. Coates's point is that you can extract meaning from the data without adopting the exacting standards proposed by Berners-Lee.
Things get even more interesting when the data starts to become interconnected.
"It's in the combination that the real power of this comes out," Coates says. "The mashup is an early example of the Web that is to come. Semantic technologies have not taken off as much as we'd hoped because people are finding more utility in other Web 2.0 technologies at the moment. The goal is the most important thing: reusable, repurposable, and reconnectable data. How we get there is not as important."
The shift to a semantic Web is still in its very early days. Spivack envisions a time line of five to seven years. But the shift is clearly under way. James Hendler, one of the coauthors of that seminal Scientific American article, sees the same dynamics he did when the Web was first forming.
"Those of us who were involved saw little islands of the Web being created," he says. "To most people, the Web seemed to happen overnight, because they hadn't seen the first six to eight years of effort. We're in that early phase of the semantic Web."
Radar Networks, Google Base, and even Flickr are the first islands to pop into public view. Larger islands are being formed by corporations and government agencies. Many more will rise.
Spivack is counting on those islands to eventually coalesce. That's when the potential becomes reality. That's when we can all kick back and let our software agents go out and bring some order to the chaos of our digital lives.
Michael V. Copeland is a senior writer at Business 2.0.
Web 3.0 Promises Semantic Revolution · MarketingVOX
Web 3.0 Promises Semantic Revolution · MarketingVOX: "Web 3.0 Promises Semantic Revolution
Glowing with life force ...
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A company manned by one of the Internet's first pioneering businessmen is guiding the next stage of the Web's development, reports Business2.0.
The so-called 'semantic web' is one that will make many daily decisions for us. By compiling data available on users, it will know what information to retrieve, what arrangements to make and what surfers are likely to buy.
Radar Networks, headed by Nova Spivack, is playing a large role in that next iteration's development. Spivak's team consists largely of statisticians and analysts looking for patterns in the copious amounts of data that can be used to further the Web's intelligence.
One stumbling block is that so much of today's information is not readable by machines and must to be made so in order for those machines to begin learning.
An advantage of the semantic web is that it is able to paint a more complete portrait of a person. Instead of reducing them to a series of links, it can compile facts to give searchers a more well-rounded picture of who users are. In an ideal world, this process can simplify ad targeting and service production for niche pockets of consumers.
Events/Webcasts:"
Glowing with life force ...
your life force
A company manned by one of the Internet's first pioneering businessmen is guiding the next stage of the Web's development, reports Business2.0.
The so-called 'semantic web' is one that will make many daily decisions for us. By compiling data available on users, it will know what information to retrieve, what arrangements to make and what surfers are likely to buy.
Radar Networks, headed by Nova Spivack, is playing a large role in that next iteration's development. Spivak's team consists largely of statisticians and analysts looking for patterns in the copious amounts of data that can be used to further the Web's intelligence.
One stumbling block is that so much of today's information is not readable by machines and must to be made so in order for those machines to begin learning.
An advantage of the semantic web is that it is able to paint a more complete portrait of a person. Instead of reducing them to a series of links, it can compile facts to give searchers a more well-rounded picture of who users are. In an ideal world, this process can simplify ad targeting and service production for niche pockets of consumers.
Events/Webcasts:"
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