Together We Lie

Humans are social animals. We’ve become this way because – evolutionarily speaking – we do better as a group than individually. But there’s a caveat here. If you get a group of usually honest people together, they’re more likely to lie. Why is this?

Martin Kocher and his colleagues from LMU in Munich set up a study where participants had to watch a video of a single roll of a die and then report on the number that came up. Depending on what they reported, there was a payoff. Researchers asked both individuals and small groups who had the opportunity to chat anonymously with each other before reporting. The result,

“Our findings are unequivocal: People are less likely to lie if they decide on their own.”

Even individuals who answered honestly independently started lying when they got in a group.

The researchers called this a “dishonesty shift.” They blame it on a shifting weight placed on the norm of honesty. Norms are those patterns we have that guide us in our behaviors and beliefs. But those norms may be different individually than they are when we’re part of a group.

“Feedback is the decisive factor. Group-based decision-making involves an exchange of views that may alter the relative weight assigned to the relevant norm.”

Let’s look at how this may play out. Individually, we may default to honesty. We do so because we’re unsure of the consequences of not being honest. But when we get in a group, we start talking to others and it’s easier to rationalize not being honest – “Well, if everyone’s going to lie, I might as well too.”

Why is this important? Because marketing is done in groups, by groups, to groups. The dynamics of group-based ethics are important for us to understand. It could help to explain the most egregious breaches of ethics we see becoming more and more commonplace, either in corporations or in governments.

Four of the seminal studies in psychology and sociology shed further light on why groups tend to shift towards dishonesty. Let’s look at them individually.

In 1955, Solomon Asch showed that even if individually we believe something to be incorrect, if enough people around us have a different option, we’ll go with the group consensus rather than risk being the odd person out. In his famous study, he would surround a subject with “plants” who, when shown cards with three black lines of obviously differing lengths on it, would insist that three lines were equal. The subjects were then asked their opinion. In 75% of the cases, they’d go with the group rather than risk disagreement. As Asch said in his paper – quoting sociologist Gabriel Tarde – “Social man in a somnambulist.” We have about as much independent will as your average sleepwalker.

Now, let’s continue with Stanley Milgram’s Obedience to Authority study, perhaps the most controversial and frightening of the group. When confronted with an authoritative demeanor, a white coat and a clipboard, 63% of the subjects meekly followed directions and delivered what were supposed to be lethal levels of electrical shock to a hapless individual. The results were so disheartening that we’ve been trying to debunk them ever since. But a follow up study by Stanford psychology professor Philip Zimbardo – where subjects were arbitrarily assigned roles as guards and inmates in a mock prison scenario – was even more shocking. We’re more likely to become monsters and abandon our personal ethics when we’re in a group than when we act alone. Whether it’s obedience to authority – as Milgram was trying to prove – or whether it’s social conformity taken to the extreme, we tend to do very bad things when we’re in bad company.

But how do we slip so far so quickly from our own personal ethical baseline? Here’s where the last study I’ll cite can shed a little light. Sociologist Mark Granovetter – famous for his Strength of Weak Ties study – also looked at the viral spreading of behaviors in groups. I’ve talked about this in a previous column, but here’s the short version: If we have the choice between two options, with accompanying social consequences, which option we choose may be driven by social conformity. If we see enough other people around us picking the more disruptive option (i.e. starting a riot) we may follow suit. Even if we all have different thresholds – which we do – the nature of a crowd is such that those with the lowest threshold will pick the disruption option, setting into effect a bandwagon effect that eventually tips the entire group over the threshold.

These were all studied in isolation, because that’s how science works. We study variables in isolation. But it’s when factors combine that we get the complexity that typifies the real world – and the real marketplace. And there’s where predictability goes out the window. The group dynamics in play can create behavioral patterns that make no sense to the average person with the average degree of morality. But it’s happened before, it’s happening now, and it’s sure to happen again.

 

 

To Buy or Not to Buy: The Touchy Subject of Mobile ECommerce

A recent report from Akamai indicates that users have little patience when it comes to making purchases on a mobile device. Here are just a few of the stats:

  • While almost half of all consumers browse via their phones, only 1 in 5 complete transactions on mobile
  • Optimal load times for peak conversions ranged from 1.8 to 2.7 seconds across device types
  • Just a 100-millisecond delay in load time hurt conversion rates by up to 7%
  • Bounce rates were highest among mobile shoppers and lowest among those using tablets

But there may be more behind this than just slow load times. We also have to consider what modes we’re in when we’re interacting with our mobile device.

In 2010, Microsoft did a fascinating research project that looked at how user behaviors varied from desktop to tablet to smart phone. The research was headed by Jacquelyn Krones, who was a Search Product Manager at the time. Search was the primary activity examined, but there was a larger behavioral context that was explored. While the study is 7 years old, I think the core findings are still relevant. The researchers found that we tend to have three large buckets of behaviors: missions, explorations and excavations. Missions were focused tasks that were usually looking for a specific piece of information – i.e. looking for an address or phone number. Explorations where more open ended and less focused on a given destination – i.e. seeing if there was any thing you wanted to do this Friday night. Excavations typically involved multiple tasks within an overarching master task – i.e. researching an article. In an interview with me, Krones outlined their findings:

“There’s clearly a different profile of these activities on the different platforms. On desktops and laptops, people do all three of the activities – they conduct missions and excavations and explorations.

“On their phones we expected to see lots of missions – usually when you use your mobile phone and you’re conducting a search, whatever you’re doing in terms of searching is less important than what’s going on with you in the real world – you’re trying to get somewhere, you’re having a discussion with somebody and you want to look something up quick or you’re trying to make a decision about where to go for dinner.

“But we were surprised to find that people are using their mobile phones for exploration. But once we saw the context, it made sense – people have a low tolerance for boredom. Their phone is actually pretty entertaining, much more entertaining than just looking at the head in front of you while you’re waiting in line. You can go check a sports score, read a story, or look at some viral video and have a more engaged experience.

“On tablets, we found that people are pretty much only using them for exploration today. I had expected to see more missions on tablets, and I think that that will happen in the future, but today people perceive their mobile phone as always with them, very personal, always on, and incredibly efficient for getting information when they’re in mission mode.”

Another study, coming out The University of British Columbia Okanagan, also saw a significant difference in behavioral modality when it came to interacting with touch screens. Assistant Professor Ying Zhu was the principal author:

“The playful and fun nature of the touchscreen enhances consumers’ favour of hedonic products; while the logical and functional nature of a desktop endorses the consumers’ preference for utilitarian products,” explains Zhu.

“Zhu’s study also found that participants using touchscreen technology scored significantly higher on experiential thinking than those using desktop computers. However, those on desktops scored significantly higher on rational thinking.”

I think what we have here is an example of thinking: fast and slow. I suspect we’re compartmentalizing our activities, subconsciously setting some aside for completion on the desktop. I would suspect utilitarian type purchasing would fall into this category. I know that’s certainly true in my case. As Dr. Zhu noted, we have a very right brain relationship with touchscreens, while desktops tend to bring out our left-brain. I have always been amazed at how our brains subconsciously prime us based on anticipating an operating environment. Chances are, we don’t even realize how much our behaviors change when we move from a smart phone to a tablet to a desktop. But I’d be willing to place a significant wager that it’s this subconscious techno-priming that’s causing some of these behavioural divides between devices.

Slow load times are never a good thing, on any device, but while they certainly don’t help with conversions, they may not be the only culprit sitting between a user and a purchase. The device itself could also be to blame.

Is Busy the New Alpha?

Imagine you’ve just been introduced into a new social situation. Your brain immediately starts creating a social hierarchy. That’s what we do. We try to identify the power players. The process by which we do this is interesting. The first thing we do is look for obvious cues. In a new job, that would be titles and positions. Then, the process becomes very Bayesian – we form a base understanding of the hierarchy almost immediately and then constantly update it as we gain more knowledge. We watch power struggles and update our hierarchy based on the winners and losers. We start assigning values to the people in this particular social network and; more importantly, start assessing our place in the network and our odds for ascending in the hierarchy.

All of that probably makes sense to you as you read it. There’s nothing really earth shaking or counter intuitive. But what is interesting is that the cues we use to assign standings are context dependent. They can also change over time. What’s more, they can vary from person to person or generation to generation.

In other words, like most things, our understanding of social hierarchy is in the midst of disruption.

An understanding of hierarchy appears to be hardwired into us. A recent study found that humans can determine social standing and the accumulation of power pretty much as soon as they can walk. Toddlers as young as 17 months could identify the alphas in a group. One of the authors of the study, University of Washington psychology professor Jessica Sommerville , said that even the very young can “see that someone who is more dominant gets more stuff.” That certainly squares with our understanding of how the world works. “More stuff” has been how we’ve determined social status for hundreds of years. In sociology, it’s called conspicuous consumption, a term coined by sociologist Thorstein Veblen. And it’s a signaling strategy that evolved in humans over our recorded history. The more stuff we had, and the less we had to do to get that stuff, the more status we had. Just over a hundred years ago, Veblen called this the Leisure Class.

But today that appears to be changing. A recent study seems to indicate that we now associate busyness with status. Here, it’s time – not stuff – that is the scarce commodity. Social status signaling is more apt to involve complaining about how we never go on a vacation than about our “summer on the continent”.

At least, this seems to be true in the U.S. The researchers also ran their study in Italy and there the situation was reversed. Italians still love their lives of leisure. The U.S. is the only developed country in the world without a single legally required paid vacation day or holiday. In Italy, every employee is entitled to at least 32 paid days off per year.

In our world of marketing – which is acutely aware of social signaling – this could create some interesting shifts in messaging. I think we’re already seeing this. Campaigns aimed at busy people seem to equate scarcity of time with success. The one thing missing in all this social scrambling – whether it be conspicuous consumption or working yourself to death – might be happiness. Last year a study out of the University of British Columbia found a strong link between those who value their time more than money and happiness.

Maybe those Italians are on to something.

Curmudgeon, Chicken Little or Cognoscenti?

Apparently I’m old and out of step. Curmudgeonly, even. And this is from people of my own generation. My previous column about the potential shallowness encouraged by social media drew a few comments that indicated I was just being a grumpy old man. One was from an old industry friend – Brett Tabke:

“The rest of the article is like out of the 70’s in that it is devoid of the reality that is the uber-me generation. The selfie is only a reflection of their inward focus.”

The other was from Monica Emrich, whom I’ve never had the pleasure of meeting:

” ’Social Media Is Barely Skin-Deep.’ ho hum. History shows: when new medium hits, civilization as we know it is over.”

These comments seem to telling me, “Relax. You just don’t understand because you’re too old. Everything will be great.” And, if that’s true, I’d be okay with that. I’m more than willing to be proven a doddering old fool if it means technology is ushering us into a new era of human greatness.

But what if this time is different? What if Monica’s facetious comment actually nailed it? Maybe civilization as we know it will be over. The important part of this is “as we know it.” Every technological disruption unleashes a wave of creative destruction that pushes civilization in a new direction. We seem to blindly assume it will always go in the right direction. And it is true that technology has generally elevated the human race. But not uniformly – and not consistently. What if this shift is different? What if we become less than what we were? It can happen. Brexit – Xenophobia – Trump – Populism, all these things are surfing on the tides of new technology.

Here’s the problem. There are some aspects of technology that we’ve never had to deal with before – at least, not at this scale. One these aspects (other aspects will no doubt be the topic of a future Media Insider) is that technology is now immersive and ubiquitous. It creates an alternate reality for us, and it has done in it in a few short decades. Why is this dangerous? It’s dangerous because evolution has not equipped us to deal with this new reality. In the past, when there has been a shift in our physical reality, it has taken place over several generations. Natural selection had the time to reshape the human genome to survive and eventually thrive in this new reality. Along the way, we acquired checks and balances that would allow us to deal with the potentially negative impacts of the environment.

But our new reality is different. It’s happen in the space of a single generation. There is no way we could have acquired natural defenses against it. We are operating in an environment we have been untested for. The consequences are yet to be discovered.

No, your response might be to say that, “Yes, evolution doesn’t move this quickly, but out brains can. They are elastic and malleable.” This is true, but there’s a big “but” that lies hidden in this approach. Our brains rewire to be a better match their environment. This is one of the things that humans excel at. But this rewiring happens on top of a primitive platform with some built in limitations. The assumption is that a better match with our environment provides a better chance for survival of the species.

But what if technology is throwing us a curve ball in this case? No matter what the environment we have adapted to, there has been one constant: The history of humans depends on our success in living together. We have evolved to be social animals but that evolution is predicated on the assumption that our socializing would take place face-to-face. Technology is artificially decoupling our social interactions from the very definition of society that we have evolved to be able to handle. A recent Wharton interview with Eden Collinsworth sounds the same alarm bells.

“The frontal lobes, which are the part of the brain that puts things in perspective and allows you to be empathetic, are constantly evolving. But it is less likely to evolve and develop those skills if you are in front of a screen. In other words, those skills come into play when you have a face-to-face interaction with someone. You can observe facial gestures. You can hear the intonation of a voice. You’re more likely to behave moderately in that exchange, unless it’s a just a knock-down, drag-out fight.”

Collinsworth’s premise – which is covered in her new book, Behaving Badly – is that this artificial reality is changing our concepts of morality and ethics. She reminds us the two are interlinked, but they are not the same thing. Morality is our own personal code of conduct. Ethics are a shared code that society depends on to instill a general sense of fairness. Collinsworth believes both are largely learned from the context of our culture. And she worries that a culture that is decoupled from the physical reality we have evolved to operate in may have dire consequences.

The fact is that if our morality and ethics are intended to keep us socially more cohesive, this works best in a face-to-face context. In an extreme example of this, Lt. Col. Dave Grossman, a former paratrooper and professor of psychology at West Point, showed how our resistance to killing another human in combat is inversely related to our physical distance from them. The closer we are to them, the more resistant we are to the idea of killing them. This makes sense in an evolutionary environment where all combat was hand-to-hand. But today, the killer could be in a drone flight control center thousands of miles from his or her intended target.

This evolved constraint on unethical behavior – the social check and balance of being physically close to the people we’re engaging with – is important. And while the application of the two examples I’ve cited; One – the self-absorbed behavior on social networks – and Two – the moral landscape of a drone strike operator, may seem magnitudes apart in terms of culpability, the underlying neural machinery is related. What we believe is right and wrong is determined by a moral compass set to the bearings of our environment. The fundamental workings of that compass assumed we would be face-to-face with the people we have to deal with. But thanks to technology, that’s no longer the case.

Maybe Brett and Monica are right. Maybe I’m just being alarmist. But if not, we’d better start paying more attention. Because civilization “as we know it” may be ending.

 

Social Media is Barely Skin Deep

Here’s a troubling fact. According to a study from the Georgia Institute of Tech, half of all selfies taken have one purpose, to show how good the subject looks. They are intended to show the world how attractive we are: our makeup, our clothes, our shoes, our lips, our hair. The category accounts for more selfies than all other categories combined. More than selfies taken with people or pets we love, more than us doing the things we love, more than being in the places we love, more than eating the food we love. It appears that the one thing we love the most is ourselves. The selfies have spoken

In this study, the authors reference a 1956 work from sociologist Erving Goffman– The Presentation of Self in Everyday Life. Goffman took Shakespeare’s line – “All the World is a Stage and all the men and women merely players” – quite literally. His theory was that we are all playing the part of whom we want to be perceived as. Our lives are divided up into two parts – the front, when we’re “on stage” and playing our part, and the “back” – when we prepare for our role. The roles we play depend on the context we’re in.

 

Goffman’s theory introduces an interesting variable into consideration. The way we play these roles and the importance we place on them will vary with the individual. For some of us, it will be all about the role and less about the actual person who inhabits that role. These people are obsessed about how they are perceived by others. They’re the ones snapping selfies of themselves to show the world just how marvelous they look.

For others, they care little about what the world thinks of them. They are internally centered and are focused on living their lives, rather than acting their way through their lives for the entertainment of – and validation from – others. In between the two extremes is the ubiquitous bell curve of normal distribution. Most of us live somewhere on that curve.

Goffman’s theory was created specifically to provide insight into face-to-face encounters. Technology has again throw a gigantic wrinkle into things – and that wrinkle may explain why we keep taking those narcissistic selfies.

Humans are pretty damned good at judging authenticity in a face-to-face setting. We pick up subtle cues from across a wide swath of interpersonal communication channels: vocal intonations, body language, eye-to-eye contact, micro-expressions. Together, these inputs give us a pretty accurate “bullshit detector.” If someone comes across as an inauthentic “phony” the majority of us will just roll our eyes and simply start avoiding the person. In face-to-face encounters there is a social feedback mechanism that keeps the “actors” amongst us at least somewhat honest in order to remain part of the social network that forms their audience.

But social media platforms provide the idea incubator for inauthentic presentation of our own personas. There are three factors in particular that allow shallow “actors” to flourish – even to the point of going viral.

False Intimacy and Social Distance

In his blog on Psychology Today, counselor Michael Formica talks about two of these factors – social distance and false intimacy. I’ve talked about false intimacy before in another context – the “labelability” of celebrities. Social media removes the transactional costs of retaining a relationship. This has the unfortunate side effect of screwing up the brain’s natural defenses against inauthentic relationships. When we’re physically close to a person, there are no filters for the bad stuff. We get it all. Our brains have evolved to do a cost/benefit analysis of each relationship we have and decide whether it’s worth the effort to maintain it. This works well when we depend on physically proximate relationships for our own well-being.

But social media introduces a whole new context for maintaining social relationships. When the transactional costs are reduced to a scanning of a newsfeed and hitting the “Like” button, the brain says “What the hell, let’s add them to our mental friends list. It’s not costing me anything.” In evolutionary terms, intimacy is the highest status we can give to a relationship and it typically only comes with a thorough understanding of the good and the bad involved in that relationship by being close to the person – both physically and figuratively. With zero relational friction, we’re more apt to afford intimacy, whether or not it’s been earned.

The Illusion of Acceptance

The previous two factors perfectly set the “stage” for false personas to flourish, but it’s the third factor that allows them to go viral. Every actor craves acceptance from his or her audience. Social exclusion is the worst fate imaginable for them. In a face-to-face world, our mental cost/benefit algorithm quickly weeds out false relationships that are not worth the investment of our social resources. But that’s not true online. If it costs us nothing, we may be rolling our eyes – safely removed behind our screen – as we’re also hitting the “Like” button. And shallow people are quite content with shallow forms of acceptance. A Facebook like is more than sufficient to encourage them to continue their act. To make it even more seductive, social acceptance is now measurable – there are hard numbers assigned to popularity.

This is pure cat-nip to the socially needy. Their need to craft a popular – but entirely inauthentic – persona goes into overdrive. Their lives are not lived so much as manufactured to create a veneer just thick enough to capture a quick click of approval. Increasingly, they retreat to an online world that follows the script they’ve written for themselves.

Suddenly it makes sense why we keep taking all those selfies of ourselves. When all the world’s a stage, you need a good head shot.

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.

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.