Author Archives: ghotchkiss

Evolving on the Fly: Growth Hackers, Agile Marketers, Bayesian Strategists and CMTs

First published January 10, 2013 in Mediapost’s Search Insider

If you are a Darwinist, one of the questions you may have asked yourself is, on what timescale does evolution play out? Is it a long, gradual development of new and differentiated species? Or, as Stephen Jay Gould and Niles Eldridge believe, does evolution happen in short spurts, separated by long periods of stasis (their theory is called Punctuated Equilibrium)?

The next question you might ask is, what does this have to do with marketing?

I venture to say: everything. Bear with me.

If you believe, as I believe, that evolution happens in spurts, then it’s important to understand what causes those spurts. Among many contentious alternatives, one that seems to be more commonly accepted is a sudden dramatic change in what evolutionists call the adaptive landscape.  This is the real world that species must adapt to in order to survive. “Flat” landscapes create an even playing field for all species to survive, resulting in relative stasis. “Rugged” landscapes significantly favor some species over others, accelerating evolution dramatically. “Rugged” landscapes generally emerge after some big event, like a catastrophe.

I propose that marketing is currently a very rugged adaptive landscape. Some marketers are going to thrive, and others are going to disappear from the face of the earth. We’re already seeing exciting new species emerge.

Growth Hackers

If you haven’t heard about them, Growth Hackers are “the next big thing,” at least, according to Fast Company.  A post by Andrew Chen is referenced, where he explains, “Growth hackers are a hybrid of marketer and coder, one who looks at the traditional question of ‘How do I get customers for my product?’ and answers with A/B tests, landing pages, viral factor, email deliverability, and Open Graph.” Think of hackers as tech-savvy marketing guerillas. They move fast, exploit technical opportunities, and track and test everything.

Agile Marketers

According to the Agile Marketing Manifesto, this offshoot of Agile Development enshrines customer focus, validated learning, iterative approaches, flexibility and learning from our mistakes. In the words of my friend Mike Moran, it’s learning how to “Do It Wrong Quickly.” As opposed to Growth Hackers, which is more of a job description, Agile Marketing is a corporate philosophy that encourages (demands) rapid evolution. It embraces the realities of a “rugged” adaptive landscape.

Bayesian Strategists

This was top of mind after my last column, so I added this in as my contribution. As stated last week, I envision strategic thinking to become less of a “shot in the dark” and more of a “testable hypothesis.”  I would never want to see “Big Thinking” give way to “Big Data,” but I believe the two can co-exist, and co-evolve, quite nicely.

Chief Marketing Technologist

Finally, under whose watch does all of this fall? If you believe Scott Brinker (which I invariably do — he’s from Boston and he’s “wicked smaaht”) it falls quit nicely into the job description of the Chief Marketing Technologist. I’ll let him explain in his own words: “A chief marketing technologist (CMT) is the person responsible for leading an organization’s marketing technology.”

A CMT sits astride the rapidly colliding worlds of marketing and technology and makes sure an organization does not fall prey to the all-too-common trap of having these overseen by two completely separate (and often outrightly hostile) departments.

A CMT understands the following realities:

Everything is Marketing

Everything is Changing

Everyone Must Be Agile

In the words of Peter Drucker, “Business has only two basic functions: marketing and innovation.” In today’s world, those two functions are inextricably linked. As a marketer, you have two choices: adapt and survive, or stand still and die. The ones who do the first the best will emerge at the top of the marketing food chain.

The Evolution of Strategy

First published January 3, 2013 in Mediapost’s Search Insider

Last week I asked the question, “Will Big Data Replace Strategic Thinking?”  Many of you answered, with a ratio splitting approximately two for one on the side of thinking. But, said fellow Search Insider Ryan Deshazer, “Not so fast! Go beyond the rebuttal!”

I agree with my friend Ryan. This is not a simple either/or answer. We  (or at least 66% of us) may agree that models and datasets, no matter how good they are, can’t replace thinking. But we can’t dismiss the importance of them,either. Strategy will change, and data will be a massive driver in that change.

Both the Harvard Business Review and the New York Times have recent posts on the subject. In HBR, Justin Fox tells of a presentation by Vivek Ranadive, who said, “I believe that math is trumping science. What I mean by that is you don’t really have to know why, you just have to know that if a and b happen, c will happen.”

He further speculates that U.S. monetary policy might do better being guided by an algorithm rather than bankers: “The fact is, you can look at information in real time, and you can make minute adjustments, and you can build a closed-loop system, where you continuously change and adjust, and you make no mistakes, because you’re picking up signals all the time, and you can adjust.”

The Times’ Steve Lohr also talks about the recent enthusiasm for a quantitative approach to management, evangelized by Erik Brynjolfsson, Director of the MIT Center for Digital Business, who says Big Data will “replace ideas, paradigms, organizations and ways of thinking about the world.”

However, Lohr and Fox (who wrote the excellent book, “The Myth of the Rational Market”) caution about the oversimplifications inherent in modeling. Take, for example, some of the potentially flawed assumptions in Ranadive’s version of an algorithmically driven monetary policy:

–       Something as complex as monetary policy can be contained in a closed loop system

–       The past can reliably predict the future

–       If it doesn’t — and things do head into uncharted territory, — you’ll be able to “tweak” things into place as new information becomes available.

Fox uses the analogy of a Landing Page A/B (or multivariate) test as an example of the new quantitative approach to the world. In theory, page design could be left to a totally automated and testable process, where real-time feedback from users eventually decides the optimal layout. It sounds good in theory, but here’s the problem with this approach to marketing: You can’t test what you don’t think of. The efficacy of testing depends on the variables you choose to test. And that requires some thinking. Without a solid hypothesis based on a strategic view of the situation, you can quickly go down a rabbit hole of optimizing for the wrong things.

For example, most heavily tested landing pages I’ve seen all reach the same eventual destination: a page optimized for one definition of a conversion. Typically this would be the placement of an order or the submission of a form. There will be reams of data showing why this is the optimal variation. But what about all the prospects that hit that page for which the one offered conversion wasn’t the right choice? How do they get captured in the data? Did anyone even think to include them in the things to test for?

Fox offers a hybrid view of strategic management that more closely aligns with where I see this all going — call it Bayesian Strategic management. Traditional qualitative strategic thinking is required to set the hypothetical view of possible outcomes, but then we apply a quantitative rigor to measure, test and adjust based on the data we collect. This treads the line between the polarities of responses gathered by last week’s column – it puts the “strategic” horse before the “big data” cart. More importantly, it holds our strategic view accountable to the data. A strategy becomes a hypothesis to be tested.

One final thought. Whether we’re talking about Ranadive’s utopian (or dystopian?) vision of a data driven world or any of the other Big Data evangelists, there seems to be one assumption that I believe is fundamentally flawed, or at least, overly optimistic: that human behaviors can be adequately contained in a predictable, rational, controlled closed loop system. When it comes to understanding human behavior, the capabilities of our own brain far outstrip any algorithmically driven model ever created — yet we still get it wrong all the time.

If Big Data could really reliably predict human behaviors, do you think we’d be in financial situation we are now?

Will Big Data Replace Strategy?

First published December 27, 2012 in Mediapost’s Search Insider

Anyone who knows me knows I love strategy. I have railed incessantly about our overreliance on tactical execution and our overlooking of the strategy that should guide said execution. So imagine my discomfort this past week when, in the midst of my following up on the McLuhan theme of my last column, I ran into a tidbit from Ray Rivera, via Forbes, that speculated that strategic management might becoming obsolescent.

Here’s an excerpt: As amounts of data approaching entire populations become available, models become less predictive and more descriptive. As inference becomes obsolete, management methods that rely on it will likely be affected. A likely casualty is strategic management, which attempts to map out the best course of action while factoring in constraints. Classic business strategy (e.g., the five forces) is especially vulnerable to losing the relevance it accumulated over several decades.

The crux of this is the obsolescence of inference. Humans have historically needed to infer to compensate for imperfect information. We couldn’t know everything with certainty, so we had to draw conclusions from the information we did have. The bigger the gap, the greater the need for inference. And, like most things that define us, the ability to infer was sprinkled through our population in a bell-curved standard distribution. We all have the ability to fill in the gaps through inference, but some of us are much better at it than others.

The author of this post speculates that as we get better and more complete information, it will become less important to fill in the gaps to set a path for the future — and more important to act quickly on what we know, correcting our course in real time: With access to comprehensive data sets and an ability to leave no stone unturned, execution becomes the most troublesome business uncertainty. Successful adaptation to changing conditions will drive competitive advantage more than superior planning.

Now, just in case you’re wondering, I don’t agree with the premise, but there is considerable merit to Rivera’s hypothesis, so let’s consider it using a fairly accessible analogy: the driving of a car. If we’re driving to a destination where we’ve never been before, and we don’t know what we’ll encounter en route, we need a strategy. We need to know the general direction, we need a high-level understanding of the available routes, we need to know what an acceptable period of time would be to reach our destination, and we need some basic strategic guidelines to deal with the unexpected – for example, if a primary route is clogged with traffic, we will find an alternative route using secondary roads. These are all tools we use to help us infer what the best way to get from point A to B might be.

But what if we have a GPS that has access to real-time traffic information and can automatically plot the best available route? Given the analogous scenario, this is as close to perfect information at we’re likely to get. We no longer need a strategy. All we need to do is follow the provided directions and drive. No inference is required. The gaps are filled by the data we have available to us.

So far, so good. But here is the primary reason why I believe strategic thinking is in no danger of expiring anytime soon. If strategy was only about inference, I might agree with Rivera’s take (by he way, he’s from SAP, so he may have a vested interest in promoting the wonders of Big Data).

However, I believe that interpretation and synthesis are much more important outcome of strategy.  The drawback of data is that it needs to be put into a context to make it useful.  Unlike traffic jams and roadways, which tend to be pretty concrete concepts (stop and go, left or right — and yes, I used the pun intentionally), business is a much more abstract beast. One can measure performance indicators ad nauseam, but there should be some framework to give them meaning. We can’t just count trees (or, in the era of Big Data, the number of leaves per limb per tree). We need to recognize a forest when we see one.

Interpretation is one advantage, but synthesis is the true gold that strategic thinking yields. Data tends to live in silos. Metrics tend to be analyzed in homogenous segments (for example, Web stats, productivity yields, efficiency KPIs). True strategy can bring disparate threads together and create opportunities where none existed before. Here, strategy is not about filling the gaps in the information you have, it’s about using that information in new ways to create something remarkable.

I disagree most vehemently with Rivera when he says: While not disappearing altogether, strategy is likely to combine with execution to become a single business function.

I’ve been working in this business for going on three decades now. In all that time, I have rarely seen strategy and execution combine successfully in a single function (or, for that matter, a single person). They are two totally different ways of thinking, relying on two different skill sets. They are both required, but I don’t believe they can be combined.

Strategy is that intimately and essentially human place where business is not simply science, but becomes art. It is driven by intuition and vision. And I, for one, am not looking forward to the day where it becomes obsolescent.

McLuhan 50 Years Later

First published December 20, 2012 in Mediapost’s Search Insider

My daughter, who is in her senior year of high school, recently wrote an essay on Marshall McLuhan. She asked me to give my thoughts on McLuhan’s theories of media. To be honest, I hadn’t given McLuhan much thought since my college days, when I had packed away “Understanding Media: The Extensions of Man” for what I thought would likely be forever. I always found the title ironic. This book does many things, but promoting “understanding” is not one of them. It’s one of the more incomprehensible texts I’ve ever encountered.

My daughter’s essay caused me to dig up my half-formed understanding of what McLuhan was trying to say. I also tried to update that understanding from the early ‘60s, when it was written, to a half-century later, in the world we currently live in.

Consider this passage from McLuhan, written exactly 50 years ago: The next medium, whatever it is—it may be the extension of consciousness—will include television as its content, not as its environment, and will transform television into an art form. A computer as a research and communication instrument could enhance retrieval, obsolesce mass library organization, retrieve the individual’s encyclopedic function and flip into a private line to speedily tailored data of a saleable kind.

(See, I told you it was incomprehensible!)

The key thing to understand here is that McLuhan foretold something that I believe is unfolding before our eyes: The media we interact with are changing our patterns of cognition – not the message, but the medium itself. We are changing how we think. And that, in turn, is changing our society. While we focus on the messages we receive, we fail to notice that the ways we receive those messages are changing everything we know, forever. Twitter, Facebook, Google, the xBox and Youtube – all are co-conspirators in a wholesale rewiring of our world.

Now, to borrow from McLuhan’s own terminology, no one in our Global Village could ignore the horrific unfolding of events in Connecticut last week. But the channels we received the content through also affected our intellectual and visceral connection with that content. Watching parents search desperately for their children on television was a very different experience from catching the latest CNN update delivered via my iPhone.

When we watched through “hot” media, we connected at an immediate and emotional level. When the message was delivered through “cool” media, we stood somewhat apart, framing the messaging and interpreting it, abstracted at some length from the sights and sounds of what was unfolding. Because of the emotional connection afforded by the “hot” media, the terror of Newtown was also our own.

McLuhan foretold this as well: Unless aware of this dynamic, we shall at once move into a phase of panic terrors, exactly befitting a small world of tribal drums, total interdependence, and superimposed co-existence. […] Terror is the normal state of any oral society, for in it everything affects everything all the time.

My daughter is graduating next June. The world she will inherit will bear little resemblance to the one I stepped into, fresh from my own graduation in 1979. It is smaller, faster, more connected and, in many ways, more terrifying. But, has the world changed as much as it seems, or is it just the way we perceive that world? And, in that perception, are we the ones unleashing the change?

The “Savanna” Hypothesis of Online Design

First published December 6, 2012 in Mediapost’s Search Insider

I’m currently reading a fascinating paper titled “Evolved Responses to Landscapes” by Gordon Orians and Judith Heerwagen that was written back in 1992. The objective was to see if humans have an evolved preference for an ideal habitat. The researchers called their hunch the Savanna Hypothesis, noting that because homo sapiens spent much of our evolutionary history on the plains of tropical Africa, we should have a natural affinity for this type of landscape.

Your typical savanna features some cover from vegetation and trees, but not too much, which would allow natural predators to advance unnoticed. The environment should offer enough lushness to indicate the presence of ample food and water. It should allow for easy mobility. And it should be visually intriguing, encouraging us to venture and explore our habitat.

Here’s a quote from the paper: “Landscapes that aid and encourage exploration, wayfinding and information processing should be more favored than landscapes that impede these needs.”

The researchers, after showing participants hundreds of pictures of different landscapes, found significant support for their hypothesis. Most of us have a preference for landscapes that resemble our evolutionary origin. And the younger we are, the more predictable the preference. With age, we tend to adapt to where we live and develop a preference for it.

In reading this study, I couldn’t help but equate it to Pirolli and Card’s Information Foraging Theory. The two PARC researchers said that the strategies we use to hunt for information in a hyperlinked digital format (such as a webpage) seem to correspond to evolved optimal foraging strategies used by many species, including humans back in our hunting and foraging days. If, as Pirolli and Card theorized, we borrow inherent strategies for foraging and adapt them for new purposes, like looking for information, why wouldn’t we also apply evolved environmental preferences to new experiences, like the design of a Web page?

Consider the description of an ideal habitat quoted above. We want to be able to quickly determine our navigation options, with just a teaser of things still to explore. We want open space, so we can quickly survey our options, but we also want the promise of abundant rewards, either in the form of food and sustenance — or, in the online case, information and utility. After all, what is a website but another environment to navigate?

I find the idea of creating a home page design that incorporates a liberal dose of intrigue and promise particularly compelling. In a physical space, such an invitation may take the form of a road or pathway curving behind some trees or over a gentle rise. Who can resist such an invitation to explore just a little further?

Why should we take the same approach with a home page or landing page? Orians and Heerwagen explain that we tend to “way-find” through new environments in three distinct stages: First, we quickly scan the environment to decide if it’s even worth exploring. Do we stay here or move on to another, more hospitable location? This very quick scan really frames all the interactions to take place after it. After this “go-no/go” scan, we then start surveying the environment to gather information and find the most promising path to take. The final phase — true engagement with our surroundings — is when we decide to stay put and get some things done.

Coincidentally (or not?), I have found users take a very similar approach to evaluating a webpage. We’ve even entrenched this behavior into a usability best practice we call the “3 Scan Rule.” The first scan is to determine the promise of the page. Is it visually appealing? Is it relevant? Is it user-friendly? All these questions should be able to be answered in one second or less. In fact, a study at Carleton University found that we can reliably judge the aesthetic appeal of a website in as short a span as 50 milliseconds. That’s less time than it takes to blink your eye.

The second scan is to determine the best path. This typically involves exploring the primary navigation options, scanning graphics and headings and quickly looking at bullet lists to determine how “rich” the page is. Is it relevant to our intent? Does it look like there’s sufficient content for us to invest our time? Are there compelling navigation options that offer us more? This scan should take no more than 10 seconds.

Finally, there’s the in-depth scan. It’s here where we more deeply engage with the content. This can take anywhere from several seconds to several minutes.

At this point, the connection between the inherently pleasing characteristics of the African savanna and a well-designed website is no more than a hypothesis on my part. But I have to admit: I find the concept intriguing, like a half-obscured pathway disappearing over a swell on the horizon, waiting to be explored.

Pursuing the Unlaunched Search

First published November 29, 2012 in Mediapost’s Search Insider

Google’s doing an experiment. Eight times a day, randomly, 150 people get an alert from their smartphone and Google asks them this question, “ What did you want to know recently?” The goal? To find out all the things you never thought to ask Google about.

This is a big step for Google. It moves search into a whole new arena. It’s shifting the paradigm from explicit searching to implicit searching. And that’s important for all of the following reasons:

Search is becoming more contextually sensitive. Mobile search is contextually sensitive search. If you have your calendar, your to-do list, your past activities and a host of other information all stored on a device that knows where you are, it becomes much easier to guess what you might be interested in. Let’s say, for example, that your calendar has “Date with Julie” entered at 7 p.m., and you’re downtown. In the past year, 57% of your “dates with Julie” have generally involved dinner and a movie. You usually spend between $50 and $85 dollars on dinner, and your movies of choice generally vacillate between rom-coms and action-adventures (depending on who gets to choose).

In this scenario, without waiting for you to ask, Google could probably be reasonably safe in suggesting local restaurants that match your preferences and price ranges, showing you any relevant specials or coupons, and giving you the line-up of suggested movies playing at local theatres. Oh, and by the way, you’re out of milk and it’s on sale at the grocery store on the way home.

Can Googling become implicit? “We’ve often said the perfect search engine will provide you with exactly what you need to know at exactly the right moment, potentially without you having to ask for it,” says Google Lead Experience Designer Jon Wiley, one of the leads of the research experiment.

As our devices know more about us, the act of Googling may move from a conscious act to a subliminal suggestion. The advantage, for Google and us, is that it can provide us with information we never thought to ask for.  In the ideal state envisioned by Google, it can read the cues of our current state and scour its index of information to provide relevant options. Let’s say we just bought a bookcase from Ikea. Without asking, Google can download the user’s manual and pull relevant posts from user support forums.

It ingrains the Google habit. Google is currently in the enviable position of having become a habit. We don’t think to use Google, we just do. Of course, habits can be broken. Habits are a subconscious script that plays out in a familiar environment, delivering an expected outcome without conscious intervention. To break a habit, you usually look at disrupting the environment, stopping the script before it has a chance to play out.

The environment of search is currently changing dramatically. This raises the possibility of the breaking of the Google habit. If our habits suddenly find themselves in unfamiliar territory, the regular scripts are blocked and we’re forced to think our way through the situation.

But if Google can adapt to unfamiliar environments and prompt us with relevant information without us having to give it any thought, the company not only preserves the Google habit but ingrains it even more deeply. Good news for Google, bad news for Bing and other competitors.

It expands Google’s online landscape. Finally, at this point, Google’s best opportunity for a sustainable revenue channel is to monetize search. As long as Google controls our primary engagement point with online information, it has no shortage of monetization opportunities. By moving away from waiting for a query and toward proactive serving of information, Google can exponentially expand the number of potential touch points with users. Each of these  touch points comes with another advertising opportunity.

All this is potentially ground-breaking, but it’s not new. Microsoft was talking about Implicit Querying a decade ago. It was supposed to be built into Windows Vista. At that time, it was bound to the desktop. But now, in a more mobile world, the implications of implicit searching are potentially massive.

Google’s Personality Crisis

First published November 15, 2012 in Mediapost’s Search Insider

“Be not afraid of marketing: some are born marketers, some achieve marketing, and some have marketing thrust upon them.” — (paraphrased from) William Shakespeare.

Google has never been comfortable as a marketing company. The only reason it became a marketing company (or worse, a media company) is because it happened to stumble on the single most effective marketing channel of all time and had to figure out some way to monetize it. Even then, Adwords wasn’t Google’s idea, but Goto’s (which became Overture, which became Yahoo). Google just stole it and tweaked it a little. Because that’s what engineers do. And that’s what Google is, first a foremost, a company of engineers. Google has worn its marketing mantle the same way I wear a Speedo: uncomfortably (and yes, a little incongruously).

Anytime Google has tried to embrace its inner “marketingness,” the results have ranged from vaguely boring to disastrous. Asking Google to become a marketer is kind of like asking Stephen Hawkins to enter a wet T-shirt content — a terrible waste of cranial processing power (and frankly, not something I’d particularly want to see).

Google had the questionable luck to become fabulously profitable as a marketer, simply because it created a utility that just happened to capture eyeballs when they were attached to wallets ready to spring into action. It was like stealing candy from a baby. But then the hard cold reality hit home. Google became a public company, which meant it had a lot of shareholders who fully expected the stroke of fate that poured money into Google’s coffers to continue. So the company had to find other marketing channels, which in turn meant its strategists had to get over their distaste of marketing in general.

So they, being resolutely Googlish, decided to reinvent marketing to make it less, well, ”markety.” They would introduce their idea of marketing, infused with a pure geekish streak of scalability, market efficiency and engineering precision. I think we all know how that turned out, as the echoes of Google TV, Google Print and Google Radio still reverberate in the Hall of Stupendously Spectacular Failures.

Face it Google. You don’t get marketing, so stop trying. Step away from the bling and tchotchkes. Retreat to the warm embrace of your slide rules and HP scientific calculators.

But, whether it gets marketing or not, Google’s dilemma remains. Its revenues depend on marketing. And marketing revenues can be staggeringly profitable, yet notoriously fickle. It’s all about eyeballs, preferably with wallets attached. Where can Google get more of the same, if not from marketing?

If we break this down, we can assume a few things to be true. Eyeballs will increasingly turn their gaze online, at some screen or another. Also, those eyeballs will be looking for ever-more-relevant stuff to do something with. Finally, if that “stuff” has something to do with buying things, then there’s a good opportunity for companies who market those things.

Let’s look at what Google is good at. Google is good — make that great — at engineering scalable, efficient, redundant systems.  Google strategists believe that if they could totally remove human “noise” from the equation, the world would be a much happier place. It’s Nirvana as envisioned by Stanley Kubrick: a little sterile, but oh-so-dependable.

That skill set is a horrible match for marketers, where empathy is kind of important. But it’s a great match for utility providers. At its roots, that’s what Google was, right from the first inception of “Backrub” running surreptitiously from a Stanford dorm room: it was a tool.

Google has tentatively ventured down this path — with WiFi access, Android, and, most recently, by rolling out high-speed Internet access for Google TV subscribers. But in each of those cases, the utility was not the end goal – it was to provide a platform for more marketing.

At what point will Google principals realize they suck at marketing, but are damned good at providing the underlying infrastructure required? It’s not as sexy, or as profitable, but as Google approaches middle age, isn’t it time they started getting comfortable in their own skin?

The Swapping of the Old “Middle” for the New

First published November 8, 2012 in Mediapost’s Search Insider

For the past several columns, I’ve been talking about disintermediation. My hypothesis is that technology is driving a general disintermediation of the marketplace (well, it’s not really my hypothesis — it’s a pretty commonly held view) and is eliminating a vast “middle” infrastructure that has accounted for much of the economic activity of the past several decades. It’s a massive shift (read “disruption”) in the market that will play out over the next several years.

But every good hypothesis must stand up to challenge, and an interesting one came from a recent article in Slate, which talks about the growth of a brand new kind of “gatekeeper,” the new “bots” that crawl the Web and filter (or, in some cases, generate) content based on a preset algorithm. These bots can crawl blog posts, pinpointing spam and malicious posts so they can be removed. The sophistication is impressive, as the most advanced of these tap into the social graph to learn, in real time, the context of posts so it can make nuanced judgment calls about what is and isn’t spam.

But these bots don’t simply patrol the online frontier, they also contribute to it. They can generate automated social content based on pre-identified themes. In other words, they can become propaganda generators. So now we have a new layer of “middle” that acts both as censor and propagandist. Have we gained anything here?

The key concept here is one of control. The “middle” used to control both ends of the market. It did so because it controlled the bridge between the producers and consumers.  This was control in every sense: control of the flow of finance, control of the physical market itself, and control of communication.

With disintermediation, direct connections are being built between producers and consumers. With this comes a redefinition of control. In terms of financial control, disintermediation should (theoretically) produce a more efficient marketplace, resulting in more profit for producers and better prices for consumers. That drastically oversimplifies the pain involved in getting to a more efficient marketplace, but you get the idea.  In this case, the only loser is the middle, so there’s no real incentive for the producers or consumers to ensure its survival.

Disintermediation of the physical market essentially works itself out. If the product needs a face-to-face representative, the middle will survive. If not, then we’ll figure out how to facilitate the sale online, and you can expect to see a lot of UPS vans in your neighborhood. We consumers may mourn the loss of a “face” in some segments of our marketplace, but we’ll get over it.

When it comes to control of communication, it’s more difficult to crystal-ball what might happen in the future. This area is also where new gatekeepers are most likely to appear.

Communication between marketers and the market used to be tightly channeled and controlled by the “middle.” It also used to flow in essentially one direction – from the marketer to the market. It was always very difficult for true communication to flow the other way.

But now, content is sprouting everywhere and becomes publicly accessible through a multitude of online touch points. It could soon become overwhelming to navigate through, both for consumers and producers. In this case, arguably, the middle served a very real service to both producers and consumers. The middle could edit communication, saving us from wading through a mountain of content to get what we were looking for.  It could also ensure that the messages producers wanted to get to the market were effectively delivered. The channels were under the control of the marketplace. For this reason, both marketers and the market may be reluctant to see disintermediation when it comes to communication.

The new gatekeepers, such as those featured in the Slate article, seem to serve both ends of the market. They help consumers access higher quality information by weeding out spam and objectionable content. And they help producers exercise some degree of control over negative content generated by the marketplace. In the absence of tight control of channels, a concept that’s gone the way of the dodo, this scalable, automated gatekeeper seems to serve a purpose.

If the need is great enough on both sides of the market, we are likely to find a new “middle” emerge: an “infomediary,” to use the term coined by John Hagel, Marc Singer and Jeffrey Rayport. According to this definition of the middle, Google emerges as the biggest of the “infomediaries.”

The question is, how much control are we willing to give this new evolution of the middle? In return for hacking some semblance of sanity out of the chaos that is an unmediated information marketplace, how much are we willing to pay in return? And, where does this control (and with it, the associated power) now live?  Who owns the new gatekeepers?  And who are those gatekeepers accountable to?

Disintermediation of a New, More Connected World

First published November 1, 2012 in Mediapost’s Search Insider

On Monday, one of the byproducts of disintermediation hit me with the force of, well — a hurricane, to be exact. We are more connected globally than ever before.

This Monday and Tuesday, three different online services I use went down because of Sandy. They all had data centers on the East Coast.

Disintermediation means centralization, which means that we will have more contact with people and businesses that spread across the globe.

The laptop I’m writing this column on (a MacBook Pro) was recently ordered from Apple. I was somewhat amazed to see the journey it took on its way to me. It left a factory in China, spent a day in Shanghai, then passed through Osaka, Japan on its way to Anchorage, Ala. From there it was on to Louisville, Ky. (ironically, the flight path probably went right over my house), then back to Seattle, Vancouver and then to my front door. If my laptop were a car, I would have refused delivery – it already had a full year’s worth of miles on it before I even got to use it.

A disintermediated world means a more globally reliant world. We depend on assembly factories in Taiyuan (China), chip factories in Yamaguchi (Japan), call centers in Pune (India), R&D labs in Hagenberg (Austria), industrial designers in Canberra (Australia) and yes, data centers in lower Manhattan. When workers brawl, tsunamis hit, labor strikes occur and tropical storms blow ashore, even though we’re thousands of miles away, we feel the impact. We no longer just rely on our neighbors, because the world is now our neighborhood.

This adds a few new wrinkles to the impacts of disintermediation, both positive and negative.

On the negative side, as we saw forcefully demonstrated this week, is the realization that our connected markets are more fragile than ever. As production becomes concentrated due to various global advantages, it is more vulnerable to single-point failures. One missing link and entire networks of co-dependent businesses go down. This lack of redundancy will probably be corrected in time, but for now, it’s what we have to live with.

But, on the positive side, our new connectedness also means we have to have interest in the well being of people that would have been out of our scope of consciousness just a mere decade ago. We care about the plight of the average worker at Foxconn, if for no other reason than it will delay the shipment of our new Mac. I exaggerate here (I hope we’re not that blasé about human rights in China) to make a point: when we have a personal stake in something, we care more. When you depend on someone for something important to you, you tend to treat them with more consideration. Thomas Friedman, in his book “The World is Flat,” called it the Dell Theory of Conflict Prevention:

“The Dell Theory stipulates: No two countries that are both part of a major global supply chain, like Dell’s, will ever fight a war against each other as long as they are both part of the same global supply chain.”

To all of you who weathered the storm, just know that you’re not alone in this. We depend on you – so, in turn, feel free to depend on us.

The Balancing of Market Information

First published October 25, 2012 in Mediapost’s Search Insider

In my three previous columns on disintermediation, I made a rather large assumption: that the market will continue to see a balancing of information available both to buyers and sellers. As this information becomes more available, the need for the “middle” will decrease.

Information Asymmetry Defined

Let’s begin by exploring the concept of information asymmetry, courtesy of George Akerlof, Michael Spence and Joseph Stiglitz.  In markets where access to information is unbalanced, bad things can happen.

If the buyer has more information than the seller, then we can have something called adverse selection. Take life and health insurance, for example. Smokers (on the average) get sick more often and die younger than non-smokers. If an insurance company has 50% of policyholders who are smokers, and 50% who aren’t, but the company is not allowed to know which is which, it has a problem with adverse selection. It will lose money on the smokers so it will increase rates across the board. The problem is that non-smokers, who don’t use insurance as much, will get angry and may cancel their policy. This will mean the “book of business” will become even less profitable, driving rates even higher.   The solution, which we all know, is simple: Ask policy applicants if they smoke. Imperfect information is thus balanced out.

If the seller has more information than the buyer, then we have a “market for lemons” (the name of Akerlof’s paper). Here,  buyers are  assuming risk in a purchase without knowingly accepting that risk, because they’re unaware of the problems that the seller knows exists. Think about buying a used car, without the benefit of an inspection, past maintenance records or any type of independent certification. All you know is what you can see by looking at the car on the lot. The seller, on the other hand, knows the exact mechanical condition of the car. This factor tends to drive down the prices of all products –even the good ones — in the market, because buyers assume quality will be suspect. The balancing of information in this case helps eliminates the lemons and has the long-term effect of improving the average quality of all products on the market.

Getting to Know You…

These two forces — the need for sellers to know more about their buyers, and the need for buyers to know more about what they’re buying — are driving a tremendous amount of information-gathering and dissemination. On the seller’s side, behavioral tracking and customer screening are giving companies an intimate glimpse into our personal lives. On the buyer’s side, access to consumer reviews, third-party evaluations and buyer forums are helping us steer clear of lemons. Both are being facilitated through technology.

But how does disintermediation impact information asymmetry, or vice versa?

If we didn’t have adequate information, we needed some other safeguard against being taken advantage of. So, failing a rational answer to this particular market dilemma, we found an irrational one: We relied on gut instinct.

Relying on Relationships

If we had to place our trust in someone, it had to be someone we could look in the eye during the transaction. The middle was composed of individuals who acted as the face of the market. Because they lived in the same communities as their customers, went to the same churches, and had kids that went to the same schools, they had to respect their markets. If they didn’t, they’d be run out of town. Often, their loyalties were also in the middle, balanced somewhere between their suppliers and their customers.

In the absence of perfect information, we relied on relationships. Now, as information improves, we still want relationships, because that’s what we’ve come to expect. We want the best of both worlds.