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.

Don’t Be Evil – Revisited

I have to confess, I was actually a fan of Google’s “Don’t Be Evil” philosophy. Predictably, once they went public with it, the cynics were quick to tear it apart. Was it naïve? Of course it was. The minute Google did anything that smacked of ethical transgression; there were scads of people willing to point fingers. But the fact was, at least Google was trying. It gave those inside the Googleplex a common code of conduct. More than one planning meeting’s blue sky postulation ran up against the “Don’t be Evil” mantra which caused the conversation to veer in another – hopefully less evil – direction.

Some columns back, I talked about the corporate rush to embrace morality and voiced my own skepticism about this born again fervor. I’m skeptical because I don’t believe that capitalism and morality play very nice together. It’s tough to make a profit and make the world a kinder place at the same time. I think you can certainly set your sights in that direction, but as Google found out, if you wear your morality on your sleeve there are many who look for every opportunity to call “bullshit” on you. That’s likely why they downplayed the whole “Don’t Be Evil” thing in 2015 when Alphabet was formed.

But I still think that Google generally tries to be good. And, perhaps not coincidentally, Google is now most valuable brand in the world, according to Brand Finance When you’re a huge company you have your finger in a lot of pies and some of them, inevitably, will upset someone somewhere. The trick here is that what is evil is in the eye of the beholder. Is AirBNB good because they have enabled a new option for travellers to connect with property owners and find better value accommodation, or are they evil because they’re disrupting an established industry and putting thousands of people out of work?

It’s hard to combine the church of morality and the state of profitability. That’s why most corporations elect to keep the two separate. Microsoft is a good example. Under the reign of Bill Gates, Microsoft was even called the “Evil Empire” because of their predatory and monopolistic business practices. Yet Forbes recently tagged Microsoft as having the second best corporate social responsibility program in the world, right behind –you guessed it – Google. How do you reconcile the two? Thanks to the Bill and Melinda Gates Foundation, Bill Gates is one of the world’s most generous philanthropists. He really, really, really wants to make the planet a better place. But as head of Microsoft, he also made a shit load of money (some of which he is currently giving away) by being an asshole. He, perhaps more than anyone, personifies the dynamic tension we talk about when we refer to corporate ethics.

Let’s go back to the value of corporate brands on the Brand Finance list and the role ethics might play. It’s a timely discussion, especially right now. United Airlines was heading in the right direction, 81 on the list, up a whopping 53 spots from 2016. But then they gave the thumbs up to drag Dr. Dao down the aisle in front of an entire plane full of smart phone equipped passengers. Pepsi was number 33 on the list. But that was before the Pepsi marketing execs gave the green light to the Kylie Jenner abomination masquerading as an ad.

There’s evilness, and then there’s just bone-headed, tone deaf, shake your head in bewilderment stupidity. How the hell do these things happen? Even taking into account the “two sides to every story” factor, how did the multiple United staff members who must have had a part in the Dao debacle think that this could possibly be the way to treat a paying customer flying the “Friendly Skies”? How did the Jenner ad pass through what must have been multiple rounds of approval at Pepsi with no one whispering “WTF”?

Here, it’s an issue of culture. Culture is defined by Merriam-Webster as: the set of shared attitudes, values, goals, and practices that characterizes an institution or organization. And the tone of the culture is generally set from the top down. Corporate ethics depend on the ethics of the founders, CEO and executive management. While having a moral CEO might not be enough to guarantee consistent corporate ethics, it’s a lead pipe cinch that if you have a scum-bag in the CEO role, the company is probably going to be a pretty sleazy operation.

Culture depends on clearly understood values and practices that adhere to those values. If this is in place, it gives the rank and file the confidence to hold up their hand when “off-culture” things occur. It would give the United flight attendant the moral obligation to say, “What a minute. Maybe we shouldn’t drag a paying customer who had already been seated forcefully off the plane like a common criminal. That just doesn’t seem right to me.”

Things like Google’s “Don’t Be Evil” dictate may seem naïve in the corporate world, but it was a value that helped define the culture. Perhaps we shouldn’t be so quick to criticize it. Maybe we need more of that particular type of naiveté.

Want to be Innovative? Immerse Yourself!

In a great post earlier this year, VC Pascal Bouvier (along with Aldo de Jong and Harry Wilson) deconstructed the idea that starts ups always equate with successful innovation. Before you jump on the Lean Start Up bandwagon, realize the success rate of a start up taking ideas to market is about 0.2%. Those slow-moving, monolithic corporations that don’t realize they’re the walking dead? Well, they’re notching a 12.5% hit rate. Sure, they’re not disrupting the universe, but they are protecting their profit margin, and that’s the whole point.

The problem, Bouvier states, is one of context. Start-ups serve a purpose. So do big corporations. But it’s important to realize the context in which they both belong. We are usually too quick to adopt something that appears to be working without understanding why. We then try to hammer it into a place it doesn’t belong.

Start-ups are agents in an ecosystem. Think of them like amino acids in a primordial soup from which we hope, given the right circumstances, life might emerge. The advantage in this market-based ecosystem is that things move freely – without friction. Agents can bump up against each other quickly and catalysts can take their shot at sparking life. It is a dynamic, emergent system. Start-ups are lean and fast-moving because they have to be. It is the blueprint for their survival. It is also why the success rate of any individual start-up is so low. The market is a Darwinian beast – red of tooth and claw. Losers are ruthlessly weeded out.

A corporation is a different beast that occupies a different niche on the evolutionary timeline. It is a hierarchy of components that has already been tested by the market and has assembled itself into a replicable, successful entity. It is a complex organism and has discovered rules that allow it to compete in its ecosystem as a self-organized, vertically integrated, hopefully sustainable entity. In this way, it bears almost no resemblance to a start up. Nor should it.

This is why it’s such a daunting proposition for a start up to transition into a successful corporation. Think of the feat of self-transformation that is required here. Not only do you have to change your way of doing things – you have to change your very DNA. You have to redefine every aspect of who you are, what you do and how you do it.

If you pull out your perspective dramatically here, you see that this is a wave. Call it Schumpeterian Gale of Creative Destruction, call it a Kontdratiev Wave, call it whatever you like – this is not simply a market adaptation – this is a phase transition. The rules on one side of the wave are completely different than on the other side – just as the rules of physics are different for liquids and gases. And that applies to everything, including how you think about innovation.

We commonly believe start-ups are more innovative than corporations. But that’s not actually true. It’s the market that is more innovative. And that innovation has a very distinct characteristic. It comes from agents who are immersed in a particular part of the market. As Bouvier points out in his post, start up CEO’s solve a problem that’s “right in front of their nose.” Think of the typical start up founder. They are ear lobe deep in whatever they are doing. From this perspective, they see something they believe to be a need. They then set out to create a new solution to that need. This is the sense making cycle I keep talking about.

For a lot of start ups, sense making is ingrained. The entrepreneur is embedded in a context where it allows them to make sense of a need that has been overlooked. The magic happens when the switch clicks and the need is matched with a solution. Entrepreneurs are the synaptic connections of the market, but this requires deep immersion in the market.

There’s something else about this immersion that’s important to consider – there is nothing quantitative about it. It’s organic and natural. It’s messy and often chaotic. It’s what I call “steeping in it.” I believe this is also important to innovation. And it’s not just me. A recent study from the University of Toronto shows that creativity thrives in environments free of too much structured knowledge. The authors note, “A hierarchical information structure, compared to a flat information structure, will reduce creativity because it reduces cognitive flexibility.”

Innovation requires insight, and insight comes from being intimately immersed in something. There is a place for data analysis and number crunching, but like most things, that’s the other side of the quant/qual wave. You need both to be innovative.

 

The Chaos Theory of Marketing

Last week, I wrote why marketers are struggling with job security. In an effort to provide career counseling to an industry, I would offer this suggestion: start learning about the behaviors of non-linear dynamic systems. You’re going to have to get comfortable with the special conditions that accompany complexity.

Markets are always complex, but there’s a phenomenon that gives them the illusion of predictability. This phenomenon is potential. Potential, in this instance, means the gap between the current market state and a possible future state. The presence of potential creates market demand. Every time a new product is introduced, a new potential gap is created. Supply and demand are knocked out of balance. Until balance is regained, the market becomes more predictable.

Here’s an analogy that makes it a little easier to understand how this potential can impact the behaviors of a complex market. A model that’s often used to explain complexity is to imagine a pool table filled with balls. The twist is that each of these balls is self propelled and can move in any direction at random. Imagine how difficult it would be to predict where any single ball might go.

Now, imagine taking this same pool table and lifting one of the corner legs up 6 inches, introducing the force of gravity as a variable. Individual predictions are still difficult, but you’d be pretty safe in saying that the pocket that was diagonally opposite to the raised leg would eventually collect more than it’s fair share of balls. In this example, gravity plays the role of market potential. The market still behaves in a complex manner but there is a consistent force – the force of gravity – that exerts its influence on that complexity and makes it more predictable.

Marketing is built on exploiting potential – on capitalizing on (or creating) gaps between what we have and what we want. These gaps have always been around, but the nature of them has changed. While this potential was aimed further down Maslow’s hierarchy, it was pretty easy to predict purchasing behaviors. When it comes to the basics – meeting our need of food, water, shelter, safety – humans are all pretty much alike. But when it comes to purchases higher up the hierarchy – at the levels of self-esteem or self-actualization – things become tougher to predict.

Collectively, the western world has moved up Maslow’s hierarchy. A 2011 study from Heritage.org showed that even those living below the poverty line have a standard of life that exceeds those at all but the highest income levels just a few decades before. In 2005, 98.7% of homes had a TV, 84% had air conditioning, 79% has satellite or cable TV and 68% had a personal computer.

But it’s not only the diversification of consumer demand that’s increasing the complexity of markets. The more connected that markets become, the more unpredictable they become. Let’s go back to our overly simplified pool ball analogy. Let’s imagine that not only are our pool balls self-propelled, but they also tend to randomly change direction every time they collide with another ball. The more connected the market, the greater the number of collisions and subsequent direction changes. In marketing, those “collisions” could be a tweet, a review, a Facebook post, a Google search – well – you get the idea. It’s complex.

These two factors; the fragmentation of consumer demand and the complexity of a highly interconnected market, makes predicting consumer behavior a mug’s game. The challenge here is that marketing – in a laudable attempt to become more scientific – is following in science’s footsteps by taking a reductionist path. Our marketing mantra is to reduce everything down to testable variables and there’s certainly nothing wrong with that. I’ve said it myself on many occasions. But, as with science, we must realize that when we’re dealing with dynamic complexity, the whole can be much greater than the sum of its testable parts. There are patterns that can be perceived only at a macro scale. Here there be “black swans.” It’s the old issue of ignoring the global maxima or minima by focusing too closely on the local.

Reduction and testing tends to lead to a feeling of control and predictability. And, in some cases (such as a market that has a common potential) things seem to go pretty much according to plan. But sooner or later, complexity rears its head and those best laid plans blow up in your face.

 

 

How Vision and Strategy Can Kill a Marketer’s Job Security

“Apparently, marketers today are losing confidence in their ability to meet key goals, like reaching the right customers with their marketing efforts, or being able to understand or evaluate the ROI of their marketing plans.”

Dave Morgan – Why Are Marketing Losing Confidence in Their Ability to Do Their Jobs?

“I think marketing is going to be getting much, much easier over the next couple of years.”

Cory Treffiletti – CMOs’ Vision Crucial to their Success

A couple of weeks ago, my fellow Spinners offered these two seemingly contradictory prognoses of the future of marketing. The contradiction, I believe, is in the conflation of the ideas of media buying and marketing. Yes, media buying is going to get easier (or, at least, more automated). And I agree with Cory’s prediction of consolidation in the industry. But that doesn’t do much to ease the crisis of confidence mentioned by Dave Morgan. That’s still very real.

The problem here is one of complexity. Markets are now complex. Actually, they’ve always been complex, but now they’re even more complex and we marketers can no longer pretend that they’re otherwise. When things get complex, our ability to predict outcomes takes a nosedive.

At the same time, an avalanche of available data makes marketers more accountable than ever. This data, along with faster, smarter machines, offers the promise of predictability, but it’s a dangerous illusion. If anything, the data and AI is just revealing more of the complexity that lurks within those markets.

And here is the crux of the dilemma that lives between the two quotes above. Yes, marketing is becoming more powerful, but the markets themselves are becoming more unpredictable. And marketers are squarely caught on the horns of that dilemma. We sign on to deliver results and when those results are no longer predictable, we feel our job security rapidly slipping away.

Cory Treffiletti talks about vision – which also goes by the name of strategy. It sounds good, but here’s the potential problem with that. In massively complex environments, strategy in the wrong hands can become a liability. It leads to an illusion of control, which is part of a largely disproven and outdated corporate mindset. You can blindly follow a strategy right into a dead end because strategies depend on beliefs and beliefs can dramatically alter your perception of what’s real. No one can control a complex environment. The best you can do is monitor and react to that environment. Of course, those two things can – and should – become a strategy in and of themselves.

Strategy is not dead. It can still make a difference. But it needs to be balanced with two other “S’s” – Sense making and Synthesis. These are the things that make a difference in a world of complexity.

You have to make sense of the market. And this is more difficult than it sounds. This is where the “Strategy” paradox can creep up and kill you. If your “Vision” – to use Cory Treffiletti’s term – becomes more important to you than reality, you’ll simply look for things that confirm that vision and plunge ahead, unaware of the true situation. You’ll ignore the cues that are telling you a change of direction may be required. The Sense Making cycle starts with a “frame” of the world (a.k.a. “Vision”) and then looks for external data to either confirm and elaborate or refute that frame/vision. But the data we collect and the way we analyze that data depends on the frame we begin with. Belief tends to make this process a self-reinforcing loop that often leads to disaster. The stronger the “vision,” the greater the tendency for us to delude ourselves.

sensemaking2

Sensemaking: Klein, Moon and Hoffman

If you can remain objective as possible during the sense making cycle you then end up with a reasonably accurate “frame” of your market. This is when the Synthesis part of the equation takes over. Here, you look at your strategy and see how it lines up with the market. You look for new opportunities and threats. Knowing the market is unpredictable, you take the advice of Antifragile author Nassim Nicholas Taleb, minimizing your downside and maximizing your upside. You pull this together into a new iteration of strategy and execute like hell against it. Then you start all over again.

By going through this cycle, you’ll find that you create a wave-like approach to strategy, oscillating through phases of sense making, synthesis and strategic execution. The behavior and mindsets required in each of these phases are significantly – and often diametrically – different. It’s a tough act to pull off.

No wonder marketers are having a tough time right now.

 

 

 

 

 

 

 

Drowning in a Sea of Tech

The world is becoming a pretty technical place. The Internet of Things is surrounding us. Which sounds exciting. Until the Internet of Things doesn’t work.

Then what?

I know all these tech companies have scores of really smart people who work to make their own individual tech as trouble free as possible. Although the term has lost its contextual meaning, we’re all still aiming for “plug and play”. For people of a certain age – me, for example – this used to refer to a physical context; being able to plug stuff into a computer and have it simply started working. Now, we plug technology into our lives and hopes it plays well with all the other technology that it finds there.

But that isn’t always the case – is it? Sometimes, as Mediapost IoT Daily editor Chuck Martin recently related, technology refuses to play nice together. And because we now have so much technology interacting in so many hidden ways, it becomes very difficult to root out the culprit when something goes wrong.

Let me give you an example. My wife has been complaining for some time that her iPhone has been unable to take a picture because it has no storage available, even though it’s supposed to magically transport stuff off to the “Cloud”. This past weekend, I finally dug in to see what the problem was. The problem, as it turned out, was that the phone was bloated with thousands of emails and Messenger chats that were hidden and couldn’t be deleted. They were sucking up all the available storage. After more than an hour of investigation, I managed to clear up the Messenger cache but the email problem – which I’ve traced back to some issues with configuration of the account at her email provider – is still “in progress.”

We – and by “we” I include me and all you readers – are a fairly tech savvy group. With enough time and enough Google searches, we can probably hunt down and eliminate most bugs that might pop up. But that’s us. There are many more people who are like my wife. She doesn’t care about incorrectly configured email accounts or hidden caches. She just wants shit to work. She wants to be able to take a picture of my nephew on his 6th birthday. And when she can’t do that, the quality of my life takes a sudden downturn.

The more that tech becomes interconnected, the more likely it is that stuff can stop working for some arcane reason that only a network or software engineer can figure out. It’s getting to the point where all of us are going to need a full-time IT tech just to keep our households running. And I don’t know about you, but I don’t know where they’re going to sleep. Our guest room is full of broken down computers and printers right now.

For most of us, there is a triage sequence of responses to tech-related pains in the ass:

  1. First, we ignore the problem, hoping it will go away.
  2. Second, we reboot every piece of tech related to the problem, hoping it will go away.
  3. If neither of the above work, we marginalize the problem, working around it and hoping that eventually it will go away.
  4. If none of this works, we try to upgrade our way out of the problem, buying newer tech hoping that by tossing our old tech baby out the window, the problem will be flushed out along with the bath water.
  5. Finally, in rare cases (with the right people) – we actually dig into the problem, trying to resolve it

By the way, it hasn’t escaped my notice that there’s a pretty significant profit motive in point number 4 above. A conspiracy, perchance? Apple, Microsoft and Google wouldn’t do that to us, would they?

I’m all for the Internet of Things. I’m ready for self-driving cars, smart houses and bio-tech enhanced humans. But my “when you get a chance could you check…” list is getting unmanageably long. I’d be more than happy to live the rest of my life without having to “go into settings” or “check my preferences.”

Just last night I dreamt that I was trying to swim to a deserted tropical island but I kept drowning in a sea of Apple Watches. I called for help but the only person that could hear me was Siri. And she just kept saying, “I’m really sorry about this but I cannot take any requests right now. Please try again later…”

Do you think it means anything?

 

Too Many Fish in the Sea: The Search for Brand Love

I still see – in a number of MediaPost articles and in other places – a lot of talk about “brand-love.” So let’s talk about that.

My grandfather Jack, who farmed on the Canadian Prairies for most of his life, loved John Deere tractors.

And I mean L-O-V-E-D. Deep love. A love that lasted 50 some years and never – not once – did he ever consider a rival for his affection. You could have given him a brand new shiny red Massey Ferguson and it would have sat untouched behind the barn. The man bled green and yellow. He wore a John Deere ball cap everywhere. He had his grime encrusted one for every day wear and a clean one for formal occasions – things like the christening of new grandchildren and 50th wedding anniversaries. He wasn’t buried with one, but if he had his way, he would have been.

My grandpa Jack loved John Deere tractors because he loved one tractor – his tractor. And there was absolutely no logic to this love.

I’ve heard stories of Jack’s rocky road to farm equipment romance. His tractor was a mythically cantankerous beast. It often had to be patiently cajoled into turning over. It was literally held together with twine and bailing wire. At the end of its life, there was little of it that originally issued from the John Deere factory floor in Welland, Ontario. Most of it was vintage Jury-rigged Jack.

But Jack didn’t love this tractor in spite of all that. He loved it because of it. Were there better tractors than the ones John Deere made? Perhaps. Were there better tractors than this particular John Deere? Guaranteed. But that wasn’t the point. Over the years there was a lot of Jack in that tractor. It got to the point where he was the only one who was sufficiently patient to get it to run. But there was also a lot of that tractor in Jack. It made him a more patient man, more resourceful and – much to my grandmother’s never ending frustration – much more stubborn.

This is the stuff that love is made of. The tough stuff. The maddening stuff. The stuff that ain’t so pretty. A lot of times, love happens because you don’t have an alternative. I suspect love – true love – may be inversely correlated to choice. Jack couldn’t afford a new tractor. And by the time he could, he was too deeply in love to consider it.

This may be the dilemma for brands looking for love in today’s world. We may be attracted to a brand, we may even become infatuated with it, but will we fall in true love? What I call “Jack-love?”

Let me lay out some more evidence of this Love/Choice paradox.

If you believe the claims of online dating sites like Match.com and eHarmony, your odds of ending up in a happy relationship have never been better than when you put yourselves in the hands of their matching algorithm. This just makes sense. If you increase the prospects going in the front end and are much smarter about filtering your options, you should come out the winner in the end. But according to an article from the Association for Psychological Science, this claim doesn’t really stand up when subjected to academic rigor. “Regarding matching, no compelling evidence supports matching sites’ claims that mathematical algorithms work— that they foster romantic outcomes that are superior to those fostered by other means of pairing partners.”

A study, by Dr. Aditi Paul, found that couples that meet through online dating sites are less likely to enter marriage than those that meet through offline channels and; if they do wed, are more likely to split up down the road. Another study (D’Angelo and Toma) showed that the greater the number of options at the beginning, the more likely it was that online daters would question and probably reverse their choice.

What dating sites have done have turned looking for love into an exercise in foraging. And the rule of thumb in foraging is: The more we believe there are options that may be better, the less time we will be willing to invest in the current choice. It may seem sacrilegious to apply something so mundane as foraging theory to romance, but the evidence is starting to mount up. And if the search for a soul mate has become an exercise in efficient foraging, it’s not a great leap to conclude that everything else that can be determined by a search and matching algorithm has suffered the same fate. This may not be a bad thing, but I’m placing a fairly large bet that we’re looking at a very different cognitive processing path here. The brain simply wouldn’t use the same mechanisms or strategies to juggle a large number of promising alternatives as it would do fall deeply in love, like Jack and his John Deere (or my grandmother, for that matter).

The point is this. Infatuation happens quickly and can fade just as quickly. Love develops over time and it requires shared experiences. That’s something that’s pretty tough for an algorithm to predict. As the authors of the APS article said, “these sites are in a poor position to know how the two partners will grow and mature over time, what life circumstances they will confront and coping responses they will exhibit in the future, and how the dynamics of their interaction will ultimately promote or undermine romantic attraction and long-term relationship well-being.”

I’ve always felt uncomfortable with the phrase “brand-love” but I think it did provide a convenient and mostly accurate label for some brand relationships. I’m not so sure this is still true today. As I said in a previous column, branding is still aiming to engender love by latching on to our emotions but I suspect they may just be sparking infatuation.