What are the implications for the creation, management, and analysis of rich media content as the entrenchment of mobile access drives the world towards a haiku communications paradigm? Several items….

First, vastly higher volumes of data; User Generated Content (UGC) is already creating billions of transactional content snippets per day, each with a payload that needs to be categorized, cross-referenced, tracked, and subsequently processed for analytic manipulation.

Second, a more stringent need for analytic applications geared towards the peculiar nature of mobile computing. Because mobile devices generate dynamic IP addresses, the only consistent way to track the source of mobile data (which is needed not just for schematic purposes, but also for data syndication) is through the phone number, which carriers protect like the family jewels.

Third, a genuine and wide-spread need for data abstraction and simplification; we are rapidly approaching the point where petabytes of data are the operational baseline framework (some companies like eBay are already past this point). How do you interpret and manage that level of data? Tables, columns and rows are useless, the numbers by themselves are becoming so large they’re hard to grasp; the further this trend proceeds, the less likely business types will be able to get their arms around what they have.

So what we have at the moment are terabytes of content being generated by billions of users in increasingly smaller pieces, no particular emerging standard for categorization, and a level of complexity that limits understanding of the information to highly skilled data analysts. This is also no longer a problem that affects only large companies, even mid-range and smaller companies are being inundated with higher volumes of smaller data sets, and they literally have no way to interpret what they have.

The folks who have the highest need for actionable information (those with a bottom line responsibility such as sales and marketing), are forced to wait days (if they’re lucky) to get access to processed information from their analytics team (assuming they work for a company big enough to afford an analytics team). There also appears to be a significant gap between the results claimed by analytic (and by association, content management) vendors, and what those vendor’s customers see as results.

The core driver for both content management and analytics applications is therefore likely to be data visualization; the higher the volume of information, the more urgent the need for abstraction. This not only allows a better grasp, but it brings manipulation of the underlying information into the hands of people who are in the best position to benefit.

Several months ago we watched a behavioral targeting software company called NebuAd go straight off a cliff, burst into flames, and crash in a truly spectacular fashion. Having watched one of its cohorts completely self-destruct, the folks at behavioral targeting software company Phorm apparently thought it would be interesting to do the exact same thing. And then, oddly enough, they did. Once word got out that Phorm relies on deep packet inspection (DPI) to track consumer behavior, just like NebuAd, the same sequence of events played out, in almost the exact same fashion. Phorm’s customers are distancing themselves just as fast as they can, the privacy advocates are hollering at the top of their lungs, legislators are starting to sit up, and Phorm has just burst into flames (crash to follow soon).

What is the lesson here? Although errors in judgment are often easy to spot in hindsight, one rarely has the opportunity to apply foresight to an error in judgment. Phorm had that opportunity, and they still managed to blow it. The painful lesson (learned twice) is that deep packet inspection as a targeting mechanism is not going to fly. The problem with DPI is not just a lack of awareness on the part of the consumer that they’re being tracked, it’s that the tracking mechanism is deeply embedded in the user experience without any contextual framework. DPI does not track explicit behavior, but implicit behavior. As an example, when I’m on line I tend to hit around 12-15 sites per any given session; I go to my bank, check my e-mail, hit Amazon, zip through Facebook, etc. In each case I am explicitly identifying myself to the site in question (usually by logging in); I announce “I am here, now cater to me!” and the site owner does (as they should).

If I’m at an e-commerce site and I click on a banner ad, it’s reasonable for that merchant to assume I’m interested in the product or service, and track my behavior accordingly. But I have made an explicit choice to go to that site, and to click on that banner (or enter a search query, etc.).

The problem with DPI is the lack of any operating context (it doesn’t matter where you are or what you’re doing, we’re going to track you). Because ISPs provide the access infrastructure, they touch everything the consumer does, and most of the time they’re invisible. They’re in an ideal position to know everything you do, and there’s been a tacit understanding that the information would be kept private. The folks at NebuAd and Phorm were smart enough to see the value of Deep Packet Inspection, and dumb enough to rush forward without gauging public reaction, resulting in two very entertaining events.

The mobile internet has been defined as the 7th mass media channel. For those unfamiliar with the expression, the prior six mass media channels are print, recordings, cinema, radio, television, and the internet, which is distinct from the mobile internet. What makes this particularly interesting are the usage numbers; 900 million personal computers in use at the end of 2007, 1.3 billion internet users, but over 3.3 billion mobile subscribers (including 798 million WAP users- the mobile version of the internet, and 2.4 billion people using their phones for SMS texting). Not only the usage numbers for mobile internet far larger, they are growing far faster than the numbers for the traditional (PC-centric) internet.

Why do these numbers matter? Because they indicate a permanent shift in how people receive and send information. It’s a reasonably safe assumption that if you’re reading this, you have a PC somewhere, which you access frequently. It’s an ironclad assumption you have a cell phone, which is always with you, and always on. Is your PC always with you and always on? Unlikely, even if it’s a small laptop.

In addition to the always on/always with you convenience of mobile devices, the other core influence for the mobile experience is the size of display real-state on a mobile device; the small footprint forces efficiency in visual communications. Combine that with text limitations of 140 characters per SMS message, and you have literally billions of people who are evolving to a lifestyle where they only receive information in bite-sized chunks.

Because mobile devices are now the dominant information tool for the mass-market, there is also a corollary shift underway in how information is created, managed, and delivered. This is one area where rich media component content management systems are actually ahead of the curve; these systems were designed against standards that demand a minimalist efficiency (such as DITA), and are set up on the assumption that fast access and pithy delivery are the key drivers.

Similar to the social sites need for a hierarchical rich media content management infrastructure, the mobile internet requires structured access to broad stores of information, but delivered with a more condensed payload, a faster cycle time, and lots more potential for re-use and syndication. Traditional CMS systems are going to find themselves in a world of hurt with this new model, while component content management vendors are going to be facing a near Greenfield opportunity.

One of the good news/bad news developments playing out with social networks revolves around the vast amount of data being created and uploaded every minute. On one level the model works; sites like Facebook, MySpace, Hi5, etc. are pulling in members at enviable rates, but more importantly, the members are active users of a broad range of rich media technologies. User generated content is the key driver for success for social networks, and it is being generated in staggering volumes. That’s the good news.

The not so good news is that this content is poorly organized; the vast majority of people uploading rich media files onto social networks haven’t got the slightest idea of what metadata or vertical taxonomies are, much less how to classify what is being uploaded. While taxonomies or metadata may sound like wonk-speak to most people, they are a core requirement if anyone plans to find anything on a social network website.

By comparison, most content generated in a corporate setting is created by professionals who categorized the information, either manually, or using applications delivered by content management systems. This works because most corporations have a vertical taxonomy that is specific to their use of language; pharmaceutical companies, chemical manufacturers, medical device manufacturers, etc. all use language that is specific to what they do. The information is categorized according to the organizational rules for that taxonomy, on the assumption that easy access is the key deliverable for any content generated.

This model works fairly well for text-centric content in a structured corporate setting, but less so in an unstructured social setting, and even less so for rich media such as videos, audio files, ad hoc web pages (think of anything on Facebook). The social scenario is further exacerbated by the fact that users create rich media content, upload it to their computer, then upload it again to a (e.g.) photo site like flicker or photobucket, where is then shared far and wide across a broad range of applications and networks, and/or is subsequently syndicated.

So the challenge here is how can rich media be categorized in a semi-automatic fashion, using tools that are easy enough to use that any Facebook user will intuitively start categorizing their data, ideally without even knowing they’re doing it? And this only covers the search angle within the first place the data lands after it leaves the user’s computer. How about all those folks trying to syndicated videos, where there are multiple layers of use and re-use? Using distribution tools like RSS feeds to syndicate data across a broad range of integrated social networks is like firing into the dark.

And finally, who is in the best position to drive the development and implementation of a standard to define categorization of rich media? It won’t be the end users; they’ll just move on if things don’t work the way they’re supposed to. Standards bodies are a viable choice, several like OASIS are already driving initiatives across a broad range of content schemas like DITA; this would be a natural fit for them. However, the sector that really has its neck stuck out are the social networks; the development of categorization standards for social networks goes beyond basic exchange of information (for example, Open Social), and needs to focus on core value deliverables such as search and syndication. Social network’s value is in their content, that’s the whole point of the network. If millions of users can’t find anything, and can’t find a graceful way to distribute what’s been uploaded across all the multiple social sites to which most of them belong, the entire thing will eventually collapse under its own weight.

There’s been a recent burp in the market for on-line content management, driven primarily by the increasing adoption of in-text advertising. For those who are unfamiliar with the term, it’s pretty much as it sounds; keyword based advertising within the body of text-centric copy, triggered by a double hyperlinked word. Or in other words, if you’re reading an article and you see a word that is double underlined and run your mouse over it, a pop-up window appears with specifics on that word, if you click on it, you’re taken to the sponsor’s site.

Somewhat surprisingly, the overall reaction to this technology appears to be negative. “Intrusive”, “Annoying”, “Distracting”, are the most common terms used by consumers to describe this type of service. This once again tells me there is a lack of pompetus (if this makes no sense, check my blog from 1.24.09). Advertising can and should be incredibly useful and effective, if it’s done correctly (the right message to the right person at the right time); if not, words like intrusive, annoying, and distracting will follow in your wake. The most likely cause for all the negativity is not a lack of proper context for the ad (after all, the in-text word is in an article, which pretty much cements in context), it is most likely related to lack of proper positioning and a clearly articulated value proposition for the service itself.

Not many folks outside the advertising domain are going to know what in-text advertising is, or how it works; the comments I’ve seen posted on blogs indicate a pretty fundamental lack of understanding. There’s no particular reason to be waving your mouse all over an article as you read it (which is what triggers the pop-up), which tells me the people complaining probably need remedial mouse lessons. The concept itself makes a huge amount of sense; if I’m reading an article about Alzheimer’s and the word “Aricept” is double-linked, and that link takes me to the manufacturer’s page, that’s incredibly useful information delivered in context, which in theory should have a high pompetus factor.

The issue here is not the technology, it’s the marketing of the technology. Most people are easily intimidated by new technology, particularly if they think they’ve done something wrong. Proper marketing would have put the word out far and wide that this new capability is being introduced, why, and what the benefits are to the end user. None of that has happened (apparently) and so instead of having large numbers of people taking advantage of a really useful service, the overall tone is one of anger and mistrust. The really annoying thing to me as a marketer is that the whole market response to this was completely avoidable.

The Behavioral Targeting space had a huge rock dropped in the middle of its pond with the announcement of Google Latitude. This is a new service that allows users to identify their location (or more precisely, their cell phone’s location), and have the results displayed on a Google map. As is typical of anything Google does, it potentially affects a large number of people, so it’s a service worth closer scrutiny.

Predictably, the Privacy Advocates are already panicking: “People will know where I am!” (right, that’s the point –if you don’t want people to know where you are, don’t sign up). “The system could be subject to abuse!” (any system is subject to abuse – should we shut down the credit system because of the threat of identity theft?). “Employers could use the system to track phones given to their employees!” (and your point is?), etc.

This is not that different from Twitter, where people broadcast every little transactional detail of their lives, or it’s corollary application, Facebook, where people pretty much put their entire lives on display. Millions of people have chosen to step into a real-time information ecosystem, this is just another incremental step in the same direction.

The folks at Google, with their big brains and deep pockets, are putting a lot of thought into systems security (presumably to avoid liability, since they’re a great target for lawsuits). Will there be abuse of the system? Of course there will be, but if it’s like any other service in this ecosystem, abuses will be a statistical anomaly, and for the most part people who want to play in this space will, and those who don’t, won’t. The panicky hand-wringing of the privacy advocates is unavoidable; if it wasn’t this, it would be something else.

My six year old son recently discovered the Steve Miller band, and has honed in on “The Joker” as his current favorite to sing at the top of his lungs as I drive him to school each morning. One of his first questions was ‘what does pompetus mean?", for which I could not give a ready answer. I did a bit of research, and discovered that the closest working definition was a secret language used by people who share a tight connection. This got me thinking that there is, in fact, a pompetus of marketing, and from what I can tell, very few marketers can speak it.

A true marketing pompetus is a combination of what is said, to who, and how. If you nail it, then you’ve reached the zone where your message truly resonates; you’re saying the right thing, to the right person, in the right way, and you get the results you want. Unfortunately, most marketing efforts measure returns in the very low percentages (2% is the current standard–which means a 98% failure rate). No pompetus here.

So how can we become marketing Maurices (the one who speaks of pompetus)? Current customer analytic applications are either disconnected from outbound marketing efforts, or they’re flat out wrong–how else do you explain a 2% response rate? There is so much information available to work with; people put so much of themselves on-line that there is a staggering wealth of information available–and yet we sit at 2%. One of the challenges is that moving above two percent tends to set off privacy triggers, and there is a shrill minority out there that will scream their heads off if they think someone is trying to reach out to them more accurately. This limitation can be dealt with; as I’ve mentioned on prior blogs, marketers ignore the privacy advocates at their own peril. These people are not going away, so we need to learn to deal with them constructively.

But what of the pompetus itself? How do you truly connect with someone in a way that compels them to do business with you? This requires a deeper level of understanding, and an analytic framework that goes way beyond existing solutions. You need to address the who (demographic), what (transactional and collaborative apps), where (GIS and Mobile apps), when (temporal data), how (clickstream), and why (psychometrics). But more importantly, it needs to be understandable. Sophisticated analysis is the province of highly trained analysts, but the end user is always a marketing or business person. How do you take complex multivariate data and make it accesible to the masses?

This is where visualization tools start to earn their keep. The more complex the data set, the greater the need for abstraction and visualization, and fortunately (or unfortunately, depending on which side of the table you’re sitting on) this whole domain is vastly underdeveloped. A good visulization tool provides the operating context for a good pompetus, and if you can also pompetize your way through the privacy quagmire, maybe people can finally start getting the kind of information they need, when they need it.

What is the right role for a social network to play in the marketing mix? There’s two primary variants of social networks that marketers need to track; the first is the external social network, such as Facebook or LinkedIn, where anyone with an opinion can (and does) shout at the top of their lungs. The second is the quasi- internal or co-opted social network, which can include corporate support networks or sites that are the domain of user groups. This second category tends to be populated by newbies looking for help, and grizzled veterans who are very knowledgeable about the technology in question. While the second option may be closer to having a corporate imprimatur, both alternatives are options that need to be treated with caution. I’m not saying this is something to avoid or be scared of, but these applications have shifted the voice of influence away from the marketer and towards the end user. The problem for the marketer is that the end user will have a much more tactical and narrowly focused perspective on the product, while most marketers tend to have a strategic arc on anything under development or commercialization.

The worst thing a marketer can do is to avoid or ignore social networks. The bottom line is they’re out there, they’re heavily used, and you won’t have any control over them. This will require a fundamental shift in how marketers think; the illusion of control is well on the path towards extinction, however, a quick adaptation in terms of understanding the group dynamic can let you survive and potentially influence the tone and focus of the conversations. Not getting actively involved is not an option; if you don’t, your competitors will, and you can rest assured they will not have your best interest at heart.

Arguing with upset users in a public setting will only get you slammed, and in fact, they are likely to dog-pile you. Acknowledge that there is a problem (even if you think there isn’t), and try to understand what is really going on. If this is handled properly, you can 1) turn a foe into an advocate, 2) get some really useful feedback on ways to improve your product or service, and 3) turn a potentially negative situation to your advantage on a broader scale. The great thing about social networks is that if your ideas or comments are well thought through and responsive to end-user needs, you’re in an excellent position to wield huge influence in a non-obtrusive way.

The short version of all this is, if you’re standing on the beach and see a fifty foot wave headed in your direction, do you 1) freeze in place, 2) run like hell for higher ground, or 3) grab your surfboard and run straight at the wave? In my opinion, surf’s up. Let’s grab our boards and take advantage of what could turn out to be a really awesome ride.

There is a shift underway in how Facebook users communicate with each other; specifically with the increased use of one-to-one, or one-to-a-few video communications. Video as a base concept has already received strong traction on-line, but as anyone who has killed time on YouTube knows, the model so far has been one to many. This is effectively entertainment video, which is not the same thing as communications-centric video. A good corollary would be the introduction of enhanced network services on the wireless network a few years back, the most obvious example being integrated voice mail that is part of the service delivery of any wireless carrier. Voice messages are not left for entertainment purposes (most of the time), but to provide specific information to the recipient. The increasing use of video within social networks is likely to follow a similar pattern, with the exception that because there is an additional, significant dimension, the overall behavior of users is likely to shift. As an example, sit down with someone and ask them a few simple questions, then do the same thing with a video camera pointed at them. People are way more self-conscious when on camera, and as a result they behave and communicate differently.

I think once people become acclimated to transactional communications in a video format, the self-consciousness will start to ease, and this will just become another evolution in network based social communications. Now of course, the real question for the folks who provide the technology and enabling infrastructure is, how do we make money at this? While YouTube has been wildly successful in terms of usage, the company is still struggling to monetize its vast content repository, and this is likely to be even more the case for one-to-one video communications, since it is not entertainment oriented (does anyone want to watch a video of my wife telling me what to pick up at the grocery store? Heck, I don’t even want to watch it.).

The value of any network based service is driven by how many people use it; hotmail is a great example of this. The value of any one hotmail user to generate revenue is limited, but the value of the aggregated hotmail installed base is worth millions or billions. For social networks like Facebook who are sticking out their neck and offering video messaging, the same thing applies; don’t worry about the monetization aspects yet, instead focus on delivering an intuitive, high-value service. If Facebook (or others) can create a vast network of transactional video communicators, it will become worth multiple billions within a (relatively) short period of time.

Politics is once again rearing its empty head in the form of “Do Not Track” legislation. There is a bill working its way through the New York legislature that would effectively limit the ability of web advertisers to collect information about consumers as they move around the internet. The corollary most often cited is that this is the on-line version of the “Do Not Call” lists that became so popular a few years back.

If this legislation plays out like others of its ilk, a noisy, self-righteous minority will rock a large, successful industry back on its heels, and the ultimate loser will be all of us. There are some fundamental differences between what drove the Do Not Call (DNC) initiative vs. what is driving Do Not Track (DNT). We’ve all had telemarketers call at dinner, trying to sell us something we don’t want. It’s annoying because 1) we’re having dinner, and 2) we are unlikely to want what they sell. When the telemarketing industry was in its heyday in the late 90s and early 2000s, the internet was in a very nascent stage, particularly compared to what it’s like now. The only way to reach people then was snail mail or phone, and phone calls gave that critical real-time contact. The timing is annoying, but there’s no point in calling during the day if no one is home. The real issue is not timing, but content, and part of the reason the telemarketing industry has such a bad reputation is due to poor targeting capabilities.

That whole paradigm has shifted very rapidly in recent years with the rise of on-line behavioral targeting applications. The internet as an access mechanism is vastly more data-centric than telemarketing could ever hope to be, which means that telemarketing’s two strongest limitations (bad timing and irrelevancy) are not applicable. E-mails do not interrupt the way phone calls do, and if the right targeting applications have been put in place, the information you get is actually on point. I mean, what is wrong with advertising that matches what you’re trying to find?

The worst people to define technology usage are politicians. They’re not technologists, they’re not even business people; they pander to the loudest voice, and it’s always the extremists. I don’t think most people honestly give much thought to being tracked on-line, they just go about their business, blissfully unaware. Agitators with too much time on their hands feel compelled to get the slumbering masses all wound up by screaming “privacy violation” at the top of their lungs, and they learned very quickly that the fastest panic response will come from politicians. Meanwhile, the ad networks are too busy sniping at each other to notice they’re all about to get a NebuAd style whupping (again). Hope you enjoy getting spam, because if this legislation passes, you’re going to start getting a whole lot more.

One of the things that has always puzzled me are position descriptions for a “Sales and Marketing” VP. The fact that sales and marketing are often mentioned in the same breath demonstrates a lack of understanding of the fundamental difference between sales and marketing, particularly in smaller firms. Having worked with both domains extensively for years, I continue to be surprised by the extent of the number of people at a senior level who don’t understand the difference.

There are lots of analogies at play here, the best I’ve come up with (so far) is the race car model. If Sales is the guy driving the Formula 1, Marketing designed the engine, built the car, paved the road, went out and got sponsors, provided detailed performance specifications on the other cars and drivers, and provides pit crew support (including spare parts, personnel, and fuel).

Designed the engine. In most companies Product Management resides within Marketing. This is the function that essentially tells engineering what to build through process-centric deliverables such as Product Requirements Documents (PRDs), and Market Requirements Documents (MRDs). The MRD/PRD is based on market requirements driven by extensive research on customer needs, competitive offsets, channel requirements, etc. They are generally long, very detailed, and updated continuously in parallel with engineering development efforts.

Build the car. What defines the user experience? How easy to use and intuitive is the product or service? What does packaging and pricing look like? Product Marketing owns this function, and again, serves as a strong bridge between end-users and engineering. The work is (like most marketing efforts) very detailed and surprisingly technical.

Pave the road. Arguably the most complex task. Raising awareness of your product/service requires reaching out to potential customers, channel partners, analysts, journalists, bloggers, as well as competitors (whom you’ll reach whether you want to or not). This is where the analytic aspect of marketing kicks in; Search Engine Optimization, Search Engine Marketing, optimizing landing pages, creation and tracking of microsites, multi-level, multi-touch rich media outreach campaigns, portal placements, using blogs as media advisories, the list goes on for quite a while, and each aspect has a detailed metrics component that needs to tie into profitability analysis both for the individual product and the overall product portfolio. This particular aspect of marketing has become incredibly more complex as the Internet grows into a major distribution and information channel for most companies.

Get sponsors. One of the most valuable assets in a marketing portfolio is a happy customer who is willing to serve as a reference. This is one area where sales gets involved (since they own the customer), but Marketing spends a lot of time cultivating and grooming the customer champion for events that include analyst and media interviews, participation in webinars and public panels, guest blogging, etc.

Competitive analysis. Who is sales going to be going up against, and how are they likely to be attacked? What is the best offense to counter their defense? Detailed, continuous due diligence on competitors and their ecosystem is the province of marketing, and is one of the most useful tools supplied to sales reps before they walk in to speak with a prospect.

Pit crew. Marketing provide sales with a steady stream of qualified leads, provides all support materials they need (both on-line and off-line), schedules participation in industry events–as well as pre-show promotion, post-show follow-up, plus managing the show itself and all the leads that are generated.

All of this is very different from a Sales skill set. Sales has always been more about relationship management (herding the rabid cats), which has an entirely different set of requirements. The main difference? Sales is difficult, Marketing is complicated. I would also point out that Sales is by far the most critical role in a company. No sales, no revenue. No revenue, no company. It doesn’t matter how brilliant your engineering is, or how clever your marketing is, if people aren’t buying, none of that matters. However, sales cannot succeed without marketing; finding someone with the skill set to manage both functions is nearly impossible, because the skills required are so very different. On the other hand, finding someone who understands both functions and is smart enough to hire genuine experts at each should (in theory) be more straightforward, and can provide a genuine framework for success.

Last month the “Future of Privacy Forum” had its public unveiling. Privacy advocates who are long on rhetoric and short on grasp lined up to hammer the on-line advertising industry for “violating” consumer privacy “rights” by tracking on-line behavior in order to serve ads that are more consistent with what the consumer is actually trying to find. There has been a cry for regulation at both the state and federal levels to contain advertisers who are trying to do a more effective job of serving ads that consumers might actually be interested in. This triggers several concerns.

People have to get past the notion that they have a “right” to privacy. If you want privacy, get off the grid. The whole point of being on-line is to have access to unlimited information, and the corollary to that is everyone has some level of access to you (that’s why the information is unlimited, everyone participates). If you’re moving around on-line and looking for something, what is the problem with someone trying to help? It’s hard enough to find information as it is (e.g. 52,000,000 search returns in 0.07 seconds, when I’m only looking for one thing).

Do you enjoy getting spam? Of course not. You know who likes it even less? The people who send it out. They’re looking to make money, not waste your time. Any tracking technology is designed to reduce the amount of irrelevant advertising people receive; you get less spam, the advertising companies don’t waste your time or their money, the ads you do get resonate because they’re relevant, the advertisers make more money, the economy grows, people work, etc. Forcing advertisers to guess by deleting cookies or tightening browser privacy settings takes the irrelevancy aspect of advertising and shoots it through the roof, forcing vast inefficiencies throughout the system; advertisers make less money, the economy shrinks, etc.

And a state level regulatory framework? This is arguably the worst thought through idea in the lot. More people are moving their on-line experience to a mobile paradigm, now privacy advocates want advertisers to comply with arbitrary laws driven by random consumer locations as they cross imaginary lines?

Who is to blame for this morass? The advertising industry. That’s right. If they want to make money, they need to find a way to co-opt the privacy advocates. This will imply compromise (any idea that works for everyone is based on compromise, on-line advertising is no different), but the current stance taken by the ad industry is clearly not resonating. Even if no regulatory oversight is put in place, the ambient noise is still a distraction from their core business. Bottom line? The advertising industry needs to get over themselves and get ahead of this curve, the alternative will cripple what is already a rapidly weakening business sector.

For years the content and data worlds co-existed in relative isolation from each other. Content was the province of authors, reviewers, editors, people who were responsible for communications in written form. The data analysts, architects and developers operated in their own little esoteric world, and rarely came in contact with the content folks. The sudden rise of the internet triggered a fundamental shift in the content model, which has accelerated with the expansion of integrated rich media applications driven by meta-data management. Because of the increasing prevalence of application frameworks such as XML, the content world is finally catching up to the data world in terms of creation, distribution, and manipulation of their operational models.

Data-centric models have always had a huge advantage over content-centric models because of the level of granularity and manipulation they afforded end users. Now that content can be reduced into snippets that still maintain context and relevancy, these content elements can be stored in an object database and manipulated by ontology-driven tools. It appears the content world has finally caught up to the data world in terms of developing a fine-tuned grasp of it’s underlying information.

The implications of this are significant; for decades the advertising and marketing industries have been limited to a one-size-fits-all consumer outreach model, even now the best alternative offered by behavioral targeting firms is a cluster than numbers in the thousands and still only manages a response rate of less than 2%. Content needs to be architected, just like data; this has nothing to do with the narrative or creative process, it has to do with how information will be managed so that it can be reused, repurposed, and targeted to a much finer level of execution. When the content folks finally figure out what the data folks have know for years, you’ll start to see response rates on marketing initiatives climb steeply, because the customer experience has become much more relevant, or as I prefer to say, we can now target a cluster of one.

As social media continues to evolve, expand, and refocus, it triggers the obvious questions of where to next, and why? A number of “traditional” social networks such as Facebook and MySpace have started seeping into the corporate domain, and more business oriented social networks such as LinkedIn are going in at full speed. Most social network companies that are expanding their focus to the corporate market are doing so from a perspective that maps to their comfort zone. The result is a service that has a very similar look and feel to the non-corporate social network, just not as entertaining. This is probably a good idea, since most of what I’ve seen posted on MySpace pages is not something I would want associated with me on an enterprise network (friends are friends, colleagues are colleagues). I’m friendly with my colleagues, but it’s not the same dynamic as with my friends.

The real issue, however, is what is the proper operating context for a corporate social network? You can create extended interest groups around new hires, corporate alumni, customers, etc. but to a certain extent this demarcation is arbitrary. The real value develops when a group finds it’s collaborative efforts have accelerated because of a more effective communications framework (which is really the primary deliverable for a social network). I’ve been responsible for driving cross-functional integration efforts in the past, and the closest analogy I can find is herding rabid cats. This is particularly the case when people are forced to operate outside their comfort zone. A tool that allows professionals with disparate views (for example, marketing, engineering, and operations) to truly understand each other’s needs in aggregate, and in real-time, would be a huge step forward in collaborative thinking. Batting e-mails back and forth won’t do it; there are people who should be in the loop that aren’t, and some who are that should not be. The whole point of a social network is to share more of yourself with others, and in so doing, create a stronger connection. Focusing the objective of a stronger group connection towards a complex project (such as a global product launch) is an ideal venue for a corporate social network. Once this type of deployment gets traction, I think the whole collaborative/social space will really take off.

Now that behavioral targeting vendor NebuAd has skidded off a cliff and burst into flames, it appears that it’s counterpart in Europe, a company called Phorm, is about to follow the same trajectory, and for essentially the same reasons. In both cases the companies have massively underestimated the public response to having a third party track their on-line behavior, and even worse, then sell that data to the highest bidder. The argument that it provides higher relevancy on ads served does not appear to be holding water. It also makes you wonder how carefully this technology was vetted prior to Phorm running out in public screaming “look at me!” I mean, at a minimum they must have seen the whupping NebuAd just went through, and then they go and do the exact same thing? And keep in mind, Europeans are even more finicky about their privacy than Americans, so Phorm is about to step into an even more hostile environment.

How do you get around this type of morass? Embrace your enemy, convert your foes. The first people they should have spoken to were the privacy advocates; there is a way to co-opt people like this, it will be complicated, and may require compromise, but it beats the public humiliation they’re about to go through. This same process has to be followed for analysts and the media that track this space, get the pundits to understand and buy into what you’re selling. There is probably a bit more compromise here as well, but this is what a market-driven launch should look like. Both Phorm and NebuAd are clear examples of an engineering-driven launch, and we can all see how that’s working out.