The Medium is the Message, Mr. President

Every day that Barack Obama was in the White House, he read 10 letters. Why letters? Because form matters. There’s still something about a letter. It’s so intimate. It uses a tactile medium. Emotions seem to flow easier through the use of cursive loops and sound of pen on paper. They balance between raw and reflective. As such, they may be an unusually honest glimpse into the soul of the writer. Obama seemed to get that. There was an entire team of hundreds of people at the White House that reviewed 10,000 letters a day and chose the 10 that made it to Obama, but the intent was to give an unfiltered snapshot of the nation at any given time. It was a mosaic of personal stories that – together – created a much bigger narrative.

Donald Trump doesn’t read letters. He doesn’t read much of anything. The daily presidential briefing has been dumbed down to media more fitting of the President’s 140 character long attention span. Trump likes to be briefed with pictures and videos. His information medium of choice? Cable TV. He has turned Twitter into his official policy platform.

Today, technology has exponentially multiplied the number of communication media we have available to us. And in that multiplicativity, Marshall McLuhan’s 50-year-old trope about the medium being the message seems truer than ever. The channels we chose – whether we’re on the sending or receiving end – carry their own inherent message. They say who we are, what we value, how we think. They intertwine with the message, determining how it will be interpreted.

I’m sad that letter writing is a dying art, but I’m also contributing to its demise. It’s been years since I’ve written a letter. I do write this column, which is another medium. But even here I’m mislabeling it. Technically this is a blog post. A column is a concept embedded in the medium of print – with its accompanying physical restriction of column inches. But I like to call it a column, because in my mind that carries its own message. A column comes with an implicit promise between you – the readers – any myself, the author. Columns are meant to be regularly recurring statements of opinion. I have to respect the fact that I remain accountable for this Tuesday slot that MediaPost has graciously given me. Week after week, I try to present something that I hope you’ll find interesting and useful enough to keep reading. I feel I owe that to you. To me, a “post” feels more ethereal – with less of an ongoing commitment between author and reader. It’s more akin to a drive-by-writing.

So that brings me to one of the most interesting things about letters and President Obama’s respect for them. They are meant to be a thoughtful medium between two people. The thoughts captured within are important enough to the writer that they’re put in print but they are intended just for the recipient. They are one of the most effective media ever created to ask for empathetic understanding from one person in particular. And that’s how Obama’s Office of Presidential Correspondence treated them. Each letter represented a person who felt strongly enough about something that they wanted to share it with the President personally. Obama used to read his ten letters at the end of the day, when he had time to digest and reflect. He often made notations in the margins asking pointed questions of his staff or requesting more investigation into the circumstances chronicled in a letter. He chose to set aside a good portion of each day to read letters because he believed in the message carried by the medium: Individuals – no matter who they are – deserve to be heard.

The Death of Sears and the Edge of Chaos

So, here’s the question: Could Sears – the retail giant who has become the poster child for the death of mall-based retail shopping – have saved themselves? It’s an important question, because I don’t think Sears was an isolated incident.

In 2006, historian Richard Longstreth explored the rise and fall of Sears. The rise is well chronicled. From their beginnings in 1886, Richard Sears and Alvah Roebuck grew to dominate the catalog mail order landscape. They prospered by creating a new way of shopping that catered specifically to the rural market of America, a rapidly expanding opportunity created by the Homestead Act of 1862. The spreading of railroads across the continent through the 1860’s and 70’s allowed Sears to distribute physical goods across the nation. This, combined with their quality guarantee and free return policy, allowed Sears to rapidly grow to a position of dominance.

In the 1920’s and 30’s, Robert E. Wood, the fourth president of Sears, took the company in a new direction. He reimagined the concept of a physical retail store, convincing the reluctant company to expand from its very lucrative catalog business. This was directly driven by Sear’s foundation as a mail order business. In essence, Woods was hedging his bet. He built his stores far from downtown business centers, where land was cheap. And, if they failed as retail destinations, they could always be repurposed as mail order distribution and fulfillment centers. But Wood got lucky. Just about the time he made this call, America fell in love with the automobile. They didn’t mind driving a little bit to get to a store where they could save some money. This was followed by the suburbanization of America. When America moved to the suburbs, Sears was already there.

So, you could say Sears was amazingly smart with its strategy, presciently predicting two massive disruptions in the history of consumerism in America. Or you could also say that Sears got lucky and the market happened to reward them – twice. In the language of evolution, two fortuitous mutations of Sears led to them being naturally selected by the marketplace. But, as Longstreth showed, their luck ran out on the third disruption, the move to online shopping.

A recent article looking back at Longstreth’s paper is titled “Could Sears Have Avoided Becoming Obsolete?”

I believe the answer is no. The article points to one critical strategic flaw as the reason for Sear’s non-relevance: doubling down on their mall anchor strategy as the world stopped going to malls. In hindsight, this seems correct, but the fact is, it was no longer in Sears DNA to pivot into new retail opportunities. They couldn’t have jumped on the e-com bandwagon, just as a whale can’t learn how to fly. It’s easy for historians to cast a gaze backwards and find reasons for organizational failure, just as it’s easy to ascribe past business success to a brilliant strategy or a visionary CEO. But the fact is, as business academic Phil Rosenzweig shows in his masterful book The Halo Effect, we’re just trying to jam history into a satisfying narrative. And narratives crave cause and effect. We look for mistakes that lead to obsolescence. This gives us the illusion that we could avoid the same fate, if only we are smarter. But it’s not that simple. There are bigger forces at play here. And they can be found at the Edge of Chaos.

Edge of Chaos Theory

In his book, Complexity: Life at the Edge of Chaos, Roger Lewin chronicles the growth of the Santa Fe Institute, an academic think tank that has been dedicated to exploring complexity for the last 33 years now. But the “big idea” in Lewin’s book is the Edge of Chaos Theory, a term coined by mathematician Doyne Farmer to describe a discovery by computer scientist Christopher Langton.

The theory, in its simplest form, is this: On one side you have chaos, where there is just too much dynamic activity and instability for anything sustainable to emerge. On the other side you have order, where rules and processes are locked in and things become frozen solid. These are two very different states that can apply to biology, sociology, chemistry, physics, economics – pretty much any field you can think of.

To go from one state – in either direction – is a phase transition. Everything changes when you move from one to the other. On one side, turmoil crushes survivability. One the other, inertia smothers change. But in between there is a razor thin interface, balanced precipitously on the edge of chaos. Theorists believe that it’s in this delicate interface where life forms, where creativity happens and where new orders are born.

For any single player, it’s almost impossible to maintain this delicate balance. As organizations grow, I think they naturally move from chaos to order, at some point moving through this exceptional interface where the magic happens. Some companies manage to move through this space a few times. Apple is such a company. Sears probably moved through the space twice, once is setting their mail order business up and once with their move to suburban retail. But sooner or later, organizations go through their typical life cycle and inevitably choose order over chaos. At this point, their DNA solidifies to the point where they can no longer rediscover the delicate interface between the two.

It’s at the market level where we truly see the Edge of Chaos theory play out. The theory contests that adaptive systems in which there is feedback continually adapt to the Edge of Chaos. But, as in any balancing act, it’s a very dynamic process. In the case of sociological evolution, it’s often a force (or convergence of forces) of technology that catalyzes the phase transition from order back to chaos. This is especially true when we look at markets. But this is an oscillation between order and chaos, with the market switching from phases of consolidation and verticalization to phases of chaos and sweeping horizontal activation. Markets will swing back and forth but will constantly be rewarding winners that live closest to the edge between the two states.

We all love to believe that immortality can be captured in our corporate form, whether it be our company or our own body. But history shows that we all have a natural life cycle. We may be lucky enough to extend our duration in that interface on the edge of chaos, but sooner or later our time there will end. Just as it did with Sears.




Our Brain on Reviews

There’s an interesting new study that was just published about how our brain mathematically handles online reviews that I wanted to talk about today. But before I get to that, I wanted to talk about foraging a bit.

The story of how science discovered our foraging behaviors serves as a mini lesson in how humans tick. The economists of the 1940’s and 50’s discovered the world of micro-economics, based on the foundation that humans were perfectly rational – we were homo economicus. When making personal economic choices in a world of limited resources, we maximized utility. The economists of the time assumed this was a uniquely human property, bequeathed on us by virtue of the reasoning power of our superior brains.

In the 60’s, behavior ecologists knocked our egos down a peg or two. It wasn’t just humans that could do this. Foxes could do it. Starlings could do it. Pretty much any species had the same ability to seemingly make optimal choices when faced with scarcity. It was how animals kept from starving to death. This was the birth of foraging theory. This wasn’t some homo-sapien-exclusive behavior that was directed from the heights of rationality downwards. It was an evolved behavior that was built from the ground up. It’s just that humans had learned how to apply it to our abstract notion of economic utility.

Three decades later, two researchers at Xerox’s Palo Alto Research Center found another twist. Not only had our ability to forage been evolved all the way through our extensive family tree, but we seemed to borrow this strategy and apply it to entirely new situations. Peter Pirolli and Stuart Card found that when humans navigate content in online environments, the exact same patterns could be found. We foraged for information. Those same calculations determined whether we would stay in an information “patch” or move on to more promising territory.

This seemed to indicate three surprising discoveries about our behavior:

  • Much of what we think is rational behavior is actually driven by instincts that have evolved over millions of years
  • We borrow strategies from one context and apply them in another. We use the same basic instincts to find the FAQ section of a website that we used to find sustenance on the savannah.
  • Our brains seem to use Bayesian logic to continuously calculate and update a model of the world. We rely on this model to survive in our environment, whatever and wherever that environment might be.

So that brings us to the study I mentioned at the beginning of this column. If we take the above into consideration, it should come as no surprise that our brain uses similar evolutionary strategies to process things like online reviews. But the way it does it is fascinating.

The amazing thing about the brain is how it seamlessly integrates and subconsciously synthesizes information and activity from different regions. For example, in foraging, the brain integrates information from the regions responsible for wayfinding – knowing our place in the world – with signals from the dorsal anterior cingulate cortex – an area responsible for reward monitoring and executive control. Essentially, the brain is constantly updating an algorithm about whether the effort required to travel to a new “patch” will be balanced by the reward we’ll find when we get there. You don’t consciously marshal the cognitive resources required to do this. The brain does it automatically. What’s more – the brain uses many of the same resources and algorithm whether we’re considering going to McDonald’s for a large order of fries or deciding what online destination would be the best bet for researching our upcoming trip to Portugal.

In evaluating online reviews, we have a different challenge: how reliable are the reviews? The context may be new – our ancestors didn’t have TripAdvisor or AirBNB ratings for choosing the right cave to sleep in tonight – but the problem isn’t. What criteria should we use when we decide to integrate social information into our decision making process? If Thorlak the bear hunter tells me there’s a great cave a half-day’s march to the south, should I trust him? Experience has taught us a few handy rules of thumb when evaluating sources of social information: reliability of the source and the consensus of crowds. Has Thorlak ever lied to us before? Do others in the tribe agree with him? These are hardwired social heuristics. We apply them instantly and instinctively to new sources of information that come from our social network. We’ve been doing it for thousands of years. So it should come as no surprise that we borrow these strategies when dealing with online reviews.

In a neuro-scanning study from the University College of London, researchers found that reliability plays a significant role in how our brains treat social information. Once again, a well-evolved capability of the brain is recruited to help us in a new situation. The dorsomedial prefrontal cortex is the area of the brain that keeps track of our social connections. This “social monitoring” ability of the brain worked in concert with ventromedial prefrontal cortex, an area that processes value estimates.

The researchers found that this part of our brain works like a Bayesian computer when considering incoming information. First we establish a “prior” that represents a model of what we believe to be true. Then we subject this prior to possible statistical updating based on new information – in this case, online reviews. If our confidence is high in this “prior” and the incoming information is weak, we tend to stick with our initial belief. But if our confidence is low and the incoming information is strong – i.e. a lot of positive reviews – then the brain overrides the prior and establishes a new belief, based primarily on the new information.

While this seems like common sense, the mechanisms at play are interesting. The brain effortlessly pattern matches new types of information and recruits the region that is most likely to have evolved to successfully interpret that information. In this case, the brain had decided that online reviews are most like information that comes from social sources. It combines the interpretation of this data with an algorithmic function that assigns value to the new information and calculates a new model – a new understanding of what we believe to be true. And it does all this “under the hood” – sitting just below the level of conscious thought.

Flow and the Machine

“In the future, either you’re going to be telling a machine what to do, or the machine is going to be telling you.”

Christopher Penn – VP of Marketing Technology, Shift Communications.

I often talk about the fallibility of the human brain – those irrational, cognitive biases that can cause us to miss the reality that’s right in front of our face. But there’s another side to the human brain – the intuitive, almost mystical machinations that happen when we’re on a cognitive roll, balancing gloriously on the edge between consciousness and subconciousness. Malcolm Gladwell took a glancing shot at this in his mega-bestseller: Blink. But I would recommend going right to the master of “Flow” – Mihaly Csikszentmihalyi (pronounced, if you’re interested – me-hi Chick-sent-me-hi). The Hungarian psychologist coined the term “flow” – referring to a highly engaged mental state where we’re completely absorbed with the work at hand. Csikszentmihalyi calls it the “psychology of optimal experience.”

It turns out there’s a pretty complicated neuroscience behind flow. In a blog post from gamer Adam Sinicki, he describes a state where the brain finds an ideal balance between instinctive behavior and total focus on one task. The state is called Transient Hypofrontality. It can sometimes be brought on by physical exercise. It’s why some people can think better while walking, or even jogging. The brain juggles resources required and this can force a stepping down of the prefrontal cortex, the part of the brain that causes us to question ourselves. This part of the brain is required in unfamiliar circumstances but in a situation where we’ve thoroughly rehearsed the actions required it’s actually better if it takes a break. This allows other – more intuitive – parts of the brain to come to the fore. And that may be the secret of “Flow.” It may also be the one thing that machines can’t replicate – yet.

The Rational Machine

If we were to compare the computer to a part of the brain, it would probably be the Prefrontal Cortex (PFC). When we talk about cognitive computing, what we’re really talking about is building a machine that can mimic – or exceed – the capabilities of the PFC. This is the home of our “executive function” – complex decision making, planning, rationalization and our own sense of self. It’s probably not a coincidence that the part of our brain we rely on to reason through complex challenges like designing artificial intelligence would build a machine in it’s own image. And in this instance, we’re damned close to surpassing ourselves. The PFC is an impressive chunk of neurobiology in its flexibility and power, but speedy it’s not. In fact, we’ve found that if we happen to make a mistake, the brain slows almost to a stand still. It shakes our confidence and kills any “flow” that might be happening in it’s tracks. This is what happens to athletes when they choke. With artificial intelligence, we are probably on the cusp of creating machines that can do most of what the PFC can do, only faster, more reliably and with the ability to process much more information.

But there’s a lot more to the brain than just the PFC. And it’s this ethereal intersection between ration and intuition where the essence of being human might be hiding.

The Future of Flow

What if we could harness “flow” at will? If we work in partnership with a machine that can crunch data in real time and present us with the inputs required to continue our flow-fueled exploration without the fear of making a mistake? It’s not so much a machine telling us what to do – or the reverse – as it is a partnership between human intuition and machine based rationalization. It’s analogous to driving a modern car, where the intelligent safety and navigation features backstop our ability to drive.

Of course, it may just be a matter of time before machines best us in this area as well. Perhaps machines already have mastered flow because they don’t have to worry about the consequences of making a mistake. But it seems to me that if humans have a future, it’s not going to be in our ability to crunch data and rationalize. We’ll have to find something a little more magical to stake our claim with.



How I Cleared a Room Full of Marketing Techies

Was it me?

Was it something I said?

I don’t think so. I think it was just that I was talking about B2B.

Let me explain.

Last week, I was in San Francisco talking at a marketing technology conference. My session, in which I was a co presenter, was going to be about psychographic profiling and A.I. – in B2B marketing. It was supposed to start immediately after another session on “cognitive marketing”. During this prior session, I decided to stand at the back at the room so I didn’t take up a seat.

That proved to be a mistake. During the session, which was in one of three tracks running at the time, the medium sized room filled to standing room only capacity. The presenter talked about how machine learning – delivered via IBM’s Watson, Google’s DeepMind or Amazon’s Cloud AI solution – is going to change marketing and, along with it, the job of a human marketer.

I found it interesting. The audience seemed to think so as well. The presenter wrapped up – the moderator got up to thank him and introduce me as the next presenter – and about 60% of the room stood as one and headed for the exit door, creating a solid human wall between myself and the stage. It took me – the fish – about 5 minutes of proverbially and physically swimming upstream before I could get to the stage. It wasn’t the smoothest of transitions.

I tend to take these things personally. But I honestly don’t think it was me. I think it was the fact that “B2B” was in the title of my presentation. I have found that as soon as you slap that label on anything, marketers tend to swarm in the opposite direction. If there is a B2B track at a general marketing show, you can bet your authentic Adam West Batman action figure (not that I would have any such thing) that it’s tucked away in some far-off corner of the conference center, down three flights of escalators, where you turn right and head towards the parking garage. My experience at this past show was analogous to the lot of B2B marketing in general. Whenever we start talking about it, people start heading for the door.

I don’t get it.

It’s not a question of budget. Even in terms of marketing dollars, a lot of budget gets allocated for B2B. An Outsell report for 2016 pegged the total US B2B marketing spend at about $151 billion. That compares respectfully with the total consumer Ad Spend of $192 billion, according to eMarketer.

And it’s definitely not a question of market size. It’s very difficult to size the entire B2B market, but there’s no doubt that it’s huge. A Forrester report estimates that $8 trillion was sold in the US B2B retail space in 2014. That’s almost half of the US gross domestic product that year. And a huge swath of the business is happening online. The worldwide B2B eCommerce market is projected to be $6.7 trillion by 2020. That’s twice as big as the projected online B2C market ($3.2 trillion).

So what gives? B2B is showing us the money. Why are we not showing it any love? Just digging up the background research for this column proved to be painful. Consumer spend and marketing dollar numbers come gushing off the page of even a half-assed Google search. But B2B stats? Cue the crickets.

I have come to the conclusion that it’s just lack of attention, which probably comes from a lack of sex appeal. B2B is like the debate club in high school. While everyone goes gaga during school assemblies over the cheerleading squad and the football team, the people who will one day rule the world quietly gather after class with Mr. Tilman in the biology lab to plot their debate strategy for next week’s match up against J.R. Matheson Senior High. It goes without saying that parents will be the only ones who actually show up. And even some of them will probably have to stay home to cut the grass.

Those debaters will probably all grow up to be B2B marketers.

It may also be that B2B marketing is hard. Like – juggling Rubik’s Cubes while simultaneously solving them – hard. At least, it’s hard if you dare to go past the “get a lead and hound them mercilessly until they either move to another country or give in and buy something to get you off their back” school of marketing. If you try to do something as silly as try to predict purchase behaviors you have the problem of compound complexity. We have been trying for some time, with limited success, to predict a single consumer’s behavior. In B2B, you have to predict what might happen when you assemble a team of potential buyers – each with their own agenda, emotions and varying degrees of input – and ask them to come to a consensus on an organizational buying decision.

That can make your brain hurt. It’s a wicked problem to the power of 5.4 (the average number of buyers involved in a B2B buying decision- according to CEB’s research). It’s the Inconvenient Truth of Marketing.

That, I keep telling myself, is why everyone was rushing for the door the minute I started walking to the stage. I shouldn’t take it personally.

Shopping is Dead. Long Live Shopping!

Last week, a delivery truck pulled up in my driveway. As the rear door rolled up, I saw the truck was full of Amazon parcels, including one for me. Between the four of us that live in our house, we have at least one online purchase delivered each week. When compared to the total retail spending we do, perhaps that’s not all that significant, but it’s a heck of a lot more than we used to spend.

We are a microcosm of a much bigger behavioral trend. A recent Mediapost article by Jack Loechner reported that online retail grew by 15.6 percent last year and represents 11.7 percent of total retail sales. An IRI report shows similar trends in consumer packaged goods. In 2015, ecommerce represented just 1.5% of all consumer packaged good sales, but they project that to climb to 10% in 2022. In fueling that increase, Amazon is not only leading the pack, but also dominating it to an awe-inspiring extent. Between 2010 and last year, Amazon’s sales in North America quintupled from $16 billion to $80 billion. Hence all those packages in the back of the afore-mentioned truck.

Now, maybe all this still represents “small potatoes” in the total world of retail, but I think we’re getting close to an inflection point. We are fundamentally changing how we think of shopping, and once we let that demon out of the box (or bubble wrapped envelope) there is no stuffing it back.

In the nascent days of online shopping, way back in 2001, an academic study looked at the experience of shopping online. The authors, Childers, Carr, Peck and Carson, divided the experience into two aspects: hedonic and utilitarian. I’ll deal with both in that order.

First of all, the hedonic side of shopping – the touchy, feely joy of buying stuff. It’s mainly the hedonic aspects that purportedly hold up the shaky foundations of all those bricks and mortar stores. And I wonder – is that a generational thing? People of my generation and older still seem to like a little retail therapy now and again. But for my daughters, the act of physically shopping is generally a pain in the ass. If they can get what they want online, they’ll do so in the click of an OneClick button. They’ll visit a mall only if they have to.

In an article early this year in The Atlantic, Derek Thompson detailed the decimation of traditional retail. Mall visits declined 50 percent between 2010 and 2013, according to the real-estate research firm Cushman and Wakefield, and they’ve kept falling every year since. Retailers are declaring bankruptcy at alarming rates. Thompson points the finger at online shopping, but adds a little more context. Maybe the reason bricks and mortar retail is bleeding so badly is that it represents an experience that is no longer appealing. A quote from that article raises an interesting point:

“ ‘What experience will reliably deliver the most popular Instagram post?’—really drive the behavior of people ages 13 and up. This is a big deal for malls, says Barbara Byrne Denham, a senior economist at Reis, a real-estate analytics firm”

Malls were designed to provide an experience – to the point of ludicrous overkill in mega-malls like Canada’s West Edmonton Mall or Minnesota’s Mall of America. But increasingly, those aren’t the experiences we’re looking for. We’re still hedonistic, but our hedonism has developed different tastes. Things like travel and dining out with friends are booming, especially with younger generations. As Denham points out, our social barometers are not determined so much but what we have as by what we’re doing and whom we’re doing it with. Social proof of such things is just one quick post away.

Now let’s deal with the utilitarian aspects of shopping. According to a recent Harris Poll, the three most popular categories for online shopping are:

  1. Clothing and Shoes
  2. Beauty and Personal Care Products
  3. Food Items

Personally, when I look at the things I’ve recently ordered online, they include:

  • A barbecue
  • Storage shelves
  • Water filters for my refrigerator
  • A pair of sports headphones
  • Cycling accessories

I ordered these things online because (respectively):

  • They were heavy and I didn’t want the hassle of dragging them home from the store; and/or,
  • They probably wouldn’t have what I was looking for at any stores in my area.

But even if we look beyond these two very good reasons to buy online, “etail” is just that much easier. It’s generally cheaper, faster and more convenient. We have a long, long tail of things to look for, the advantage of objective reviews to help filter our buying and an average shopping trip duration of just a few minutes – start to finish – as opposed to a few hours or half a day. Finally, we don’t have to contend with assholes in the parking lot.

Online already wins on almost every aspect and the delta of “surprise and delight” is just going to keep getting bigger. Mobile devices untether buying from the desktop, so we can do it any place, any time. Voice commands can save our tender fingertips from unnecessary typing and clicking. Storefronts continue to get better as online retailers run bushels of UX tests to continually tweak the buying journey.

But what’s that you say? “There are just some things that you have to see and touch before you buy?” Perhaps, although I personally remain unconvinced about the need for tactile feedback when shopping. People are buying cars online and if ever there was a candidate for hedonism, it’s an automobile. But let’s say you’re right. I already wrote about how Amazon is changing the bricks and mortar retail game. But Derek Thompson casts his crystal ball gazing even further in the future when he speculates on what autonomous vehicles might do for retail:

“Once autonomous vehicles are cheap, safe, and plentiful, retail and logistics companies could buy up millions, seeing that cars can be stores and streets are the ultimate real estate. In fact, self-driving cars could make shopping space nearly obsolete in some areas.”

Maybe you should buy some shares in Amazon, if you haven’t already. P.S. You can buy them online.


The Status Quo Bias – Why Every B2B Vendor has to Understand It

It’s probably the biggest hurdle any B2B vendor has to get over. It’s called the Status Quo bias and it’s deadly in any high-risk purchase scenario. According to Wikipedia, the bias occurs when the current baseline (or status quo) is taken as a reference point, and any change from that baseline is perceived as a loss. In other words, if it ain’t broke don’t fix it. We believe that simply because something exists, it must have merit. The burden of proof then falls on the vendor to overcome this level of complacency

The Status Quo Bias is actually a bundle of other common biases, including the Endowment Effect, the Loss Aversion Bias, The Existence Bias, Mere Exposure effect and other psychological factors that tend to continually jam the cogs of B2B commerce. Why B2B? The Status Quo Bias is common in any scenario where risk is high and reward is low, but B2B in particular is subject to it because these are group-buying decisions. And, as I’ll soon explain, groups tend to default to Status Quo bias with irritating regularity. The new book from CEB (recently acquired by Gartner) – The Challenger Customer – is all about the status quo bias.

So why is the bias particularly common with groups? Think of the dynamics at play here. Generally speaking, most people have some level of the Status Quo Bias. Some will have it more than others, depending on their level of risk tolerance. But let’s look at what happens when we lump all those people together in a group and force them to come to a consensus. Generally, you’re going to have a one or two people in the group that are driving for change. Typically, these will be the ones that have the most to gain and have a risk tolerance threshold that allows the deal to go forward. On the other end of the spectrum you have some people who have low risk tolerance levels and nothing to gain. They may even stand to lose if the deal goes forward (think IT people who have to implement a new technology). In between you have the moderates. The gain factor and their risk tolerance levels net out to close to zero. Given that those that have something to gain will say yes and those who have nothing to gain will say no, it’s this middle group that will decide whether the deal will live or die.

Without the Status Quo bias, the deal might have a 50/50 chance. But the status quo bias stacks the deck towards negative outcomes for the vendor. Even if it tips the balance just a little bit towards “no” – that’s all that’s required to stop a deal dead in its tracks. The more disruptive the deal, the greater the Status Quo Bias. Let’s remember – this is B2B. There are no emotional rewards that can introduce a counter acting bias. It’s been shown in at least one study (Baker, Laury, Williams – 2008) that groups tend to be more risk averse than the individuals that make up that group. When the groups start discussing and – inevitably – disagreeing, it’s typically easier to do nothing.

So, how do we stick handle past this bias? The common approach is to divide and conquer – identifying the players and tailoring messages to speak directly to them. The counter intuitive finding of the CEB Challenger Customer research was that dividing and conquering is absolutely the wrong thing to do. It actually lessens the possibility of making a sale. While this sounds like it’s just plain wrong, it makes sense if we shift our perspective from the selling side to the buying side.

With our vendor goggles on, we believe that if we tailor messaging to appeal to every individual’s own value proposition, that would be a way to build consensus and drive the deal forward. And that would be true, if every member of our buying committee was acting rationally. But as we soon see when we put on the buying googles, they’re not. Their irrational biases are firmly stacked up on the “do nothing” side of the ledger. And by tailoring messaging in different directions, we’re actually just giving them more things to disagree about. We’re creating dysfunction rather than eliminating it. Disagreements almost always default back to the status quo, because it’s the least risky option. The group may not agree about much, but they can agree that the incumbent solution creates the least disruption.

So what do you do? Well, I won’t steal the CEB’s thunder here, because the Challenger Customer is absolutely worth a read if you’re a B2B vendor. The authors, Brent Adamson, Matthew Dixon, Pat Spenner and Nick Toman, lay out step by step strategy to get around the Status Quo bias. The trick is to create a common psychological frame where everyone can agree that doing nothing is the riskiest alternative. But biases are notoriously sticky things. Setting up a commonly understood frame requires a deep understanding of the group dynamics at play. The one thing I really appreciate about CEB’s approach is that it’s “psychologically sound.” They make no assumptions about buyer rationality. They know that emotions ultimately drive all human behavior and B2B purchases are no exception.