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.

We’re Becoming Intellectually “Obese”

Humans are defined by scarcity. All our evolutionary adaptations tend to be built to ensure survival in harsh environments. This can sometimes backfire on us in times of abundance.

For example, humans are great at foraging. We have built-in algorithms that tell us which patches are most promising and when we should give up on the patch we’re in and move to another patch.

We’re also good at borrowing strategies that evolution designed for one purpose and applying them for another purpose. This is called exaptation. For example, we’ve exapted our food foraging strategies and applied them to searching for information in an online environment. We use these skills when we look at a website, conduct an online search or scan our email inbox. But as we forage for information – or food – we have to remember, this same strategy assumes scarcity, not abundance.

Take food for example. Nutritionally we have been hardwired by evolution to prefer high fat, high calorie foods. That’s because this wiring took place in an environment of scarcity, where you didn’t know where your next meal was coming from. High fat, high calorie and high salt foods were all “jackpots” if food was scarce. Eating these foods could mean the difference between life and death. So our brains evolved to send us a reward signal when we ate these foods. Subsequently, we naturally started to forage for these things.

This was all good when our home was the African savannah. Not so good when it’s Redondo Beach, there’s a fast food joint on every corner and the local Wal-Mart’s shelves are filled to overflowing with highly processed pre-made meals. We have “refined” food production to continually push our evolutionary buttons, gorging ourselves to the point of obesity. Foraging isn’t a problem here. Limiting ourselves is.

So, evolution has made humans good at foraging when things are scarce, but not so good at filtering in an environment of abundance. I suspect the same thing that happened with food is today happening with information.

Just like we are predisposed to look for food that is high in fats, salt and calories, we are drawn to information that:

  1. Leads to us having sex
  2. Leads to us having more than our neighbors
  3. Leads to us improving our position in the social hierarchy

All those things make sense in an evolutionary environment where there’s not enough to go around. But, in a society of abundance, they can cause big problems.

Just like food, for most of our history information was in short supply. We had to make decisions based on too little information, rather than too much. So most of our cognitive biases were developed to allow us to function in a setting where knowledge was in short supply and decisions had to be made quickly. In such an environment, these heuristic short cuts would usually end up working in our favor, giving us a higher probability of survival.

These evolutionary biases become dangerous as our information environment becomes more abundant. We weren’t built to rationally seek out and judiciously evaluate information. We were built to make decisions based on little or no knowledge. There is an override switch we can use if we wish, but it’s important to know that just like we’re inherently drawn to crappy food, we’re also subconsciously drawn to crappy information.

Whether or not you agree with the mainstream news sources, the fact is that there was a thoughtful editorial process, which was intended to improve the quality of information we were provided. Entire teams of people were employed to spend their days rationally thinking about gathering, presenting and validating the information that would be passed along to the public. In Nobel laureate Daniel Kahneman’s terminology, they were “thinking slow” about it. And because the transactional costs of getting that information to us was so high, there was a relatively strong signal to noise ratio.

That is no longer the case. Transactional costs have dropped to the point that it costs almost nothing to get information to us. This allows information providers to completely bypass any editorial loop and get it in front of us. Foraging for that information is not the problem. Filtering it is. As we forage through potential information “patches” – whether they be on Google, Facebook or Twitter – we tend to “think fast” – clicking on the links that are most tantalizing.

I would have never dreamed that having too much information could be a bad thing. But most of the cautionary columns that I’ve written about in the last few years all seem to have the same root cause – we’re becoming intellectually “obese.” We’ve developed an insatiable appetite for fast, fried, sugar-frosted information.

 

Damn You Technology…

Quit batting your seductive visual sensors at me. You know I can’t resist. But I often wonder what I’m giving up when I give in to your temptations. That’s why I was interested in reading Tom Goodwin’s take on the major theme at SXSW – the Battle for Humanity. He broke this down into three sub themes. I agree with them. In fact, I’ve written on all of them in the past. They were:

Data Trading – We’re creating a market for data. But when you’re the one that generated that data, who should own it?

Shift to No Screens – an increasing number of connected devices will change of concept of what it means to be online.

Content Tunnel Vision – As the content we see is increasingly filtered based on our preferences, what does that do for our perception of what is real?

But while we’re talking about our imminent surrender to the machines, I feel there are some other themes that also merit some discussion. Let’s limit it to two today.

A New Definition of Connection and Community

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Robert Sapolsky

A few weeks ago I read an article that I found fascinating by neuroendocrinologist and author Robert Sapolsky. In it, he posits that understanding Capgras Syndrome is the key to understanding the Facebook society. Capgras, first identified by French psychiatrist Joseph Capgras, is a disorder where we can recognize a face of a person but we can’t retrieve feelings of familiarity. Those afflicted can identify the face of a loved one but swear that it’s actually an identical imposter. Recognition of a person and retrieval of emotions attached to that person are handled by two different parts of the brain. When the connection is broken, Capgras Syndrome is the result.

This bifurcation of how we identify people is interesting. There is the yin and yang of cognition and emotion. The fusiform gyrus cognitively “parses” the face and then the brain retrieves the emotions and memories that are associated with it. To a normally functioning brain, it seems seamless and connected, but because two different regions (or, in the case of emotion, a network of regions) are involved, they can neurologically evolve independently of each other. And in the age of Facebook, that could mean a significant shift in the way we recognize connections and create “cognitive communities.” Sapolsky elaborates:

Through history, Capgras syndrome has been a cultural mirror of a dissociative mind, where thoughts of recognition and feelings of intimacy have been sundered. It is still that mirror. Today we think that what is false and artificial in the world around us is substantive and meaningful. It’s not that loved ones and friends are mistaken for simulations, but that simulations are mistaken for them.

As I said in a column a few months back, we are substituting surface cues for familiarity. We are rushing into intimacy without all the messy, time consuming process of understanding and shared experience that generally accompanies it.

Brains do love to take short cuts. They’re not big on heavy lifting. Here’s another example of that…

Free Will is Replaced with An Algorithm

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Yuval Harari

In a conversation with historian Yuval Harari, author of the best seller Sapiens, Derek Thompson from the Atlantic explored “The Post Human World.” One of the topics they discussed was the End of Individualism.

Humans (or, at least, most humans) have believed our decisions come from a mystical soul – a transcendental something that lives above our base biology and is in control of our will. Wrapped up in this is the concept of us as an individual and our importance in the world as free thinking agents.

In the past few decades, there is a growing realization that our notion of “free will” is just the result of a cascade of biochemical processes. There is nothing magical here; there is just a chain of synaptic switches being thrown. And that being the case – if a computer can process things faster than our brains, should we simply relegate our thinking to a machine?

In many ways, this is already happening. We trust Google Maps or our GPS device more than we trust our ability to find our own way. We trust Google Search more than our own memory. We’re on the verge of trusting our wearable fitness tracking devices more than our own body’s feedback. And in all these cases, our trust in tech is justified. These things are usually right more often than we are. But when it comes to humans vs, machines, they represent a slippery slope that we’re already well down. Harari speculates what might be at the bottom:

What really happens is that the self disintegrates. It’s not that you understand your true self better, but you come to realize there is no true self. There is just a complicated connection of biochemical connections, without a core. There is no authentic voice that lives inside you.

When I lay awake worrying about technology, these are the types of things that I think about. The big question is – is humanity an outmoded model? The fact is that we evolved to be successful in a certain environment. But here’s the irony in that: we were so successful that we changed that environment to one where it was the tools we’ve created, not the creators, which are the most successful adaptation. We may have made ourselves obsolete. And that’s why really smart humans, like Bill Gates, Elon Musk and Stephen Hawking are so worried about artificial intelligence.

“It would take off on its own, and re-design itself at an ever increasing rate,” said Hawking in a recent interview with BBC. “Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.”

Worried about a machine taking your job? That may be the least of your worries.

 

 

You’ve got a Friend in Me – Our Changing Relationship with A.I.

Since Siri first stepped into our lives in 2011, we’re being introduced to more and more digital assistants. We’ve met Amazon’s Alexa, Microsoft’s Cortana and Google’s Google Now. We know them, but do we love them?

Apparently, it’s important that we bond with said digital assistants and snappy comebacks appear to be the surest path to our hearts. So, if you ask Siri if she has a boyfriend, she might respond with, “Why? So we can get ice cream together, and listen to music, and travel across galaxies, only to have it end in slammed doors, heartbreak and loneliness? Sure, where do I sign up?” It seems to know a smart-assed digital assistant is to love her – but just be prepared for that love to be unrequited.

Not to be outdone, Google is also brushing up on its witty repartee for it’s new Digital Assistant – thanks to some recruits from the Onion and Pixar. A recent Mediapost article said that Google had just assembled a team of writers from those two sources – tapping the Onion for caustic sarcasm and Pixar for a gentler, more human touch.

But can we really be friends with a machine, even if it is funny?

Microsoft thinks so. They’ve unveiled a new chatbot in China called Xiaoice (pronounced Shao-ice). Xiaoice takes on the persona of a 17 year old girl that responds to questions like “How would you like others to comment on you when you die one day?” with the plaintiff “The world would not be much different without me.” Perhaps this isn’t as clever as Siri’s comebacks, but there’s an important difference: Siri’s responses were specifically scripted to respond to anticipated question; while Xiaoice actually talks with you by using true artificial intelligence and linguistic processing.

In a public test on WeChat, Xiaoice received 1.5 million chat group invitations in just 72 hours. As of earlier this year, she had had more than 10 billion conversations. In a blog post, Xiaoice’s “father”, Yongdong Wang, head of the Microsoft Application and Services Group East Asia, said, “Many see Xiaoice as a partner and friend, and are willing to confide in her just as they do with their human friends. Xiaoice is teaching us what makes a relationship feel human, and hinting at a new goal for artificial intelligence: not just analyzing databases and driving cars, but making people happier.”

When we think of digital assistants, we naturally think of the advantages that machines have over humans: unlimited memory, access to the entire web, vastly superior number crunching skills and much faster processing speeds. This has led to “cognitive offloading” – humans transferring certain mental processing tasks to machines. We now trust Google more than our own memory for retrieving information – just as we trust calculators more than our own limited mathematical abilities. But there should be some things that humans are just better at. Being human, for instance. We should be more empathetic – better able to connect with other people. A machine shouldn’t “get us” better than our spouse or best friend.

For now, that’s probably still true. But what if you don’t have a spouse, or even a best friend? Is having a virtual friend better than nothing at all? Recent studies have shown that robotic pets seem to ease loneliness with isolated seniors. More research is needed, but it’s not really surprising to learn that a warm, affectionate robot is better than nothing at all. What was surprising was that in one study, seniors preferred a robotic dog to the real thing.

The question remains, however: Can we truly have a relationship with a machine? Can we feel friendship – or even love – when we know that the machine can’t do the same? This goes beyond the high-tech flirtation of discovering Siri’s or Google’s “easter egg” responses to something more fundamental. It’s touching on what appears to be happening in China, where millions are making a chatbot their personal confident. I suspect there are more than a few lonely Chinese who would consider Xiaoice their best friend.

And – on many levels – that scares the hell out of me.

 

Why Millennials are so Fascinating

When I was growing up, there was a lot of talk about the Generation Gap. This referred to the ideological gap between my generation – the Baby Boomers, and our parent’s generation – The Silent Generation (1923 – 1944).

But in terms of behavior, there was a significant gap even amongst early Baby Boomers and those that came at the tail end of the boom – like myself. Generations are products of their environment and there was a significant change in our environment in the 20-year run of the Baby Boomers – from 1945 to 1964. During that time, TV came into most of our homes. For the later boomers, like myself, we were raised with TV. And I believe the adoption of that one technology created an unbridgeable ideological gap that is still impacting our society.

The adoption of ubiquitous technologies – like TV and, more recently, connective platforms like mobile phones and the Internet – inevitable trigger massive environmental shifts. This is especially true for generations that grow up with this technology. Our brain goes through two phases where it literally rewires itself to adapt to its environment. One of those phases happens from birth to about 2 to 3 years of age and the other happens during puberty – from 14 to 20 years of age. A generation that goes through both of those phases while exposed to a new technology will inevitably be quite different from the generation that preceded it.

The two phases of our brain’s restructuring – also called neuroplasticity – are quite different in their goals. The first period – right after birth – rewires the brain to adapt to its physical environment. We learn to adapt to external stimuli and to interact with our surroundings. The second phase is perhaps even more influential in terms of who we will eventually be. This is when our brain creates its social connections. It’s also when we set our ideological compasses. Technologies we spend a huge amount of time with will inevitably impact both those processes.

That’s what makes Millennials so fascinating. It’s probably the first generation since my own that bridges that adoption of a massively influential technological change. Most definitions of this generation have it starting in the early 80’s and extend it to 1996 or 97.   This means the early Millennials grew up in an environment that was not all that different than the generation that preceded it. The technologies that were undergoing massive adoption in the early 80’s were VCRs and microwaves – hardly earth shaking in terms of environmental change. But late Millennials, like my daughters, grew up during the rapid adoption of three massively disruptive technologies: mobile phones, computers and the Internet. So we have a completely different environment for which the brain must adapt not only from generation to generation, but within the generation itself. This makes Millennials a very complex generation to pin down.

In terms of trying to understand this, let’s go back to my generation – the Baby Boomers – to see how environment adaptation can alter the face of society. Boomers that grew up in the late 40’s and early 50’s were much different than boomers that grew up just a few years later. Early boomers probably didn’t have a TV. Only the wealthiest families would have been able to afford them. In 1951, only 24% of American homes had a TV. But by 1960, almost 90% of Americans had a TV.

Whether we like to admit it or not, the values of my generation where shaped by TV. But this was not a universal process. The impact of TV was dependent on household income, which would have been correlated with education. So TV impacted the societal elite first and then trickled down. This elite segment would have also been those most likely to attend college. So, in the mid-60’s, you had a segment of a generation who’s values and world view were at least partially shaped by TV – and it’s creation of a “global village” – and who suddenly came together during a time and place (college) when we build the persona foundations we will inhabit for the rest of our lives. You had another segment of a generation that didn’t have this same exposure and who didn’t pursue a post-secondary education. The Vietnam War didn’t create the Counter-Cultural revolution. It just gave it a handy focal point that highlighted the ideological rift not only between two generations but also within the Baby Boomers themselves. At that point in history, part of our society turned right and part turned left.

Is the same thing happening with Millennials now? Certainly the worldview of at least the younger Millennials has been shaped through exposure to connected media. When polled, they inevitably have dramatically different opinions about things like religion, politics, science – well – pretty much everything. But even within the Millennial camp, their views often seem incoherent and confusing. Perhaps another intra-generational divide is forming. The fact is it’s probably too early to tell. These things take time to play out. But if it plays out like it did last time this happened, the impact will still be felt a half century from now.

Prospect Theory, Back Burners and Relationship Risk

What does relationship infidelity and consumer behavior have in common? Both are changing, thanks to technology – or, more specifically – the intersection between technology and our brains. And for you regular readers, you know that stuff is right in my wheelhouse.

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Dr. Michelle Drouin

So I was fascinated by a recent presentation given by Dr. Michelle Drouin from Purdue University. She talked about how connected technologies are impacting the way we think about relationship investment.

The idea of “investing” in a relationship probably paints in a less romantic light then we typically think of, but it’s an accurate description. We calculate odds and evaluate risk. It’s what we do. Now, in the case of love, an admittedly heuristic process becomes even less rational. Our subliminal risk appraisal system is subjugated by a volatile cocktail of hormones and neurotransmitters. But – at the end of the day – we calculate odds.

If you take all this into account, Dr. Drouin’s research into “back burners” becomes fascinating, if not all that surprising. In the paper, back burners are defined as “a desired potential or continuing romantic/sexual partner with whom one communicates, but to whom one is not exclusively committed.” “Back burners” are our fall back bets when it comes to relationships or sexual liaisons. And they’re not exclusive to single people. People in committed relationships also keep a stable of “back burners.” Women keep an average of 4 potential “relationship” candidates from their entire list of contacts and 8 potential “liaison” candidates. Men, predictably, keep more options open. Male participants in the study reported an average of over 8 “relationship” options and 26 liaison “back burners.” Drouin’s hypothesis is that this number has recently jumped thanks to technology, especially with the connectivity offered through social media. We’re keeping more “back burners” because we can.

What does this have to do with advertising? The point I’m making is that this behavior is not unique. Humans treat pretty much everything like an open marketplace. We are constantly balancing risk and reward amongst all the options that are open to us, subconsciously calculating the odds. It’s called Prospect Theory. And, thanks to technology, that market is much larger than it’s ever been before. In this new world, our brain has become a Vegas odds maker on steroids.

In Drouin’s research, it appears that new technologies like Tinder, What’sapp and Facebook have had a huge impact on how we view relationships. Our fidelity balance has been tipped to the negative. Because we have more alternatives – and it’s easier to stay connected with those alternatives and keep them on the “back burner” – the odds are worth keeping our options open. Monogamy may not be our best bet anymore. Facebook is cited in one-third of all divorce cases in the U.K. And in Italy, evidence from the social messaging app What’sapp shows up in nearly half of the divorce proceedings.

So, it appears that humans are loyal – until a better offer with a degree of risk we can live with comes along.

This brings us back to our behaviors in the consumer world. It’s the same mental process, applied in a different environment. In this environment, relationships are defined as brand loyalty. And, as Emanuel Rosen and Itamar Simonson show in their book Absolute Value, we are increasingly keeping our options open in more and more consumer decisions. When it comes to buying stuff – even if we have brand loyalty – we are increasingly aware of the “back burners” available to us.

 

 

 

Why Our Brains are Blocking Ads

On Mediapost alone in the last three months, there have been 172 articles written that have included the words “ad blockers” or “ad blocking.” That’s not really surprising, given that Mediapost covers the advertising biz and ad blocking is killing that particular biz, to the tune of an estimated loss of $41 billion in 2016. eMarketer estimates 70 million Americans, or 1 out of every 4 people online, uses ad blockers.

Paul Verna, an eMarketer Senior Analyst said “Ad blocking is a detriment to the entire advertising ecosystem, affecting mostly publishers, but also marketers, agencies and others whose businesses depend on ad revenue.” The UK’s culture Secretary, John Whittingdale, went even further, saying that ad blocking is a “modern-day protection racket.”

Here’s the problem with all this finger pointing. If you’re looking for a culprit to blame, don’t look at the technology or the companies deploying that technology. New technologies don’t cause us to change our behaviors – they enable behaviors that weren’t an option before. To get to the bottom of the growth of ad blocking, we have to go to the common denominator – the people those ads are aimed at. More specifically, we have to look at what’s happening in the brains of those people.

In the past, the majority of our interaction with advertising was done while our brain was idling, with no specific task in mind. I refer to this as bottom up environmental scanning. Essentially, we’re looking for something to capture our attention: a TV show, a book, a magazine article, a newspaper column. We were open to being engaged by stimuli from our environment (in other words, being activated from the “bottom up”).

In this mode, the brain is in a very accepting state. We match signals from our environment with concepts and beliefs we hold in our mind. We’re relatively open to input and if the mental association is a positive or intriguing one – we’re willing to spend some time to engage.

We also have to consider the effect of priming in this state. Priming sets a subconscious framework for the brain that then affects any subsequent mental processing. The traditional prime that was in place when we were exposed to advertising was a fairly benign one: we were looking to be entertained or informed, often the advertising content was delivered wrapped in a content package that we had an affinity for (our favorite show, a preferred newspaper, etc), and advertising was delivered in discrete chunks that our brain had been trained to identify and process accordingly.

All this means that in traditional exposures to ads, our brain was probably in the most accepting state possible. We were looking for something interesting, we were primed to be in a positive frame of mind and our brains could easily handle the contextual switches required to consider an ad and it’s message.

We also have to remember that we had a relatively static ad consumption environment that usually matched our expectations of how ads would be delivered. We expected commercial breaks in TV shows. We didn’t expect ads in the middle of a movie or book, two formats that required extended focusing of attention and didn’t lend themselves to mental contextual task switches. Each task switch brings with it a refocusing of attention and a brief burst of heightened awareness as our brains are forced to reassess its environment. These are fine in some environments – not in others.

Now, let’s look at the difference in cognitive contexts that accompany the deliver of most digital ads. First of all, when we’re online on our desktop or engaged with a mobile device, it’s generally in what I’ll call a “top down foraging” mode. We’re looking for something specific and we have intent in mind. This means there’s already a task lodged in our working memory (hence “top down”) and our attentional spotlight is on and focused on that task. This creates a very different environment for ad consumption.

When we’re in foraging mode, we suddenly are driven by an instinct that is as old as the human race (actually, much older than that): Optimal Foraging Theory. In this mode, we are constantly filtering the stimuli of our environment to see what is relevant to our intent. It’s this filtering that causes attentional blindness to non-relevant factors – whether they be advertising banners or people dressed up like gorillas. This filtering happens on a subconscious basis and the brain uses a primal engine to drive it – the promise of reward or the frustration of failure. When it comes to foraging – for food or for information – frustration is a feature, not a bug.

Our brains have a two loop learning process. It starts with a prediction – what psychologists and economists call “expected utility.” We mentally place bets on possible outcomes and go with the one that promises the best reward. If we’re right, the reward system of the brain gives us a shot of dopamine. Things are good. But if we bet wrong, a different part of the brain kicks in: the right anterior insula, the adjacent right ventral prefrontal cortex and the anterior cingulate cortex. Those are the centers of the brain that regulate pain. Nature is not subtle about these things – especially when the survival of the species depends on it. If we find what we’re looking for, we get a natural high. If we don’t, it’s actually causes us pain – but not in a physical way. We know it as frustration. Its purpose is to encourage us to not make the same mistake twice

The reason we’re blocking ads is that in the context those ads are being delivered, irrelevant ads are – quite literally – painful. Even relevant ads have a very high threshold to get over. Ad blocking has little to do with technology or “protection rackets” or predatory business practices. It has to do with the hardwiring of our brains. So if the media or the ad industry want to blame something or someone, let’s start there.