Category Archives: Behavior & Psychology

Decoupling Our Hunch Making Mechanism

Humans are hunch-making machines. We’re gloriously good at it. In fact, no one and no thing is better at coming up with a hunch. It’s what sets up apart on our planet and, thus far, nothing we’ve invented has proven to be better suited to strike the spark of intuition.

We can seemingly draw speculative guesses out of thin air – literally. From all the noise that surrounds us, we recognize potential patterns and infer significance. Scientists call them hypotheses. Artists call them artistic inspirations. Entrepreneurs call them innovations.

Whatever the label, we’re not exactly sure what happens. Mihaly Czikszentmihaly (which, in case you’re wondering, is pronounced Me-high Cheek-sent-me-high) explored where these hunches come from in his fascinating book, Creativity, The Psychology of Discovery and Invention. But despite the collective curiosity about the source of human creativity – the jury remains out. The mechanism that turns these very human gears and sparks the required connections between our synapses remains a mystery.

We’re good at making hunches. But we suck at qualifying those hunches. The reason is that we rush a hunch straight into becoming a belief. And that’s where things go off the rails. A hunch is a guess about what might be true. A belief is what we deem to be true. We go straight from what is one of many possible scenarios to the only scenario we execute against. The entire scientific method was created to counteract this very human tendency – forcing rational analysis of the hunches we churn out.

Philip Tetlock’s work on expertise in prediction shows how fragile this tendency to go from hunch to belief can make us. After all, a prediction is nothing more than a hunch of what might be. He referred to Isaiah Berlin’s 1950 essay, “The Hedgehog and the Fox.” In the essay, Berlin quotes the ancient Greek poet Archilochus, “”a fox knows many things, but a hedgehog one important thing.” Taking some poetic license, you could said that a hedgehog is more prone to moving straight from hunch to belief, where a fox tends to evaluate her hunches against multiple sources. Tetlock found that when it came to the accuracy of predictions, it was better to be a fox than a hedgehog. In some cases, much better.

But Tetlock also found that when it comes down to “crunching hunches”, machines tend to bet man hands down. It’s because humans have been programmed for thousands of generations to trust our hunches and no matter how much we fight it, we are born to treat our hunches as fact. Machines bear no such baggage.

This is an example of Moravec’s Paradox – the things that seem simple for humans are amazingly complex for machines. And vice versa. As artificial intelligence pioneer Marvin Minsky once recognized, it’s the things we do unconsciously that represent the biggest challenges for artificial intelligence, “In general, we’re least aware of what our minds do best.” Machines may never be as good as humans at creating a hunch – or, at least – we’re certainly not there yet. But machines have already outstripped humans in the ability to empirically analyze and validate multiple options.

Fellow Online Spin columnist Kaila Colbin posited this in her last column, “When Watson Comes for Your Job, Give it to Him.” As she points out, IBM’s Watson can kick any human ass when it comes to reviewing case law – or plowing through the details required for an accurate medical diagnosis – or assisting students prepare for an upcoming exam. But Watson isn’t very good at coming up with hunches. It’s because hunches aren’t rational. They’re inspirational. And machines aren’t fluent in inspiration. Not yet, anyway.

Maybe that’s why – even in something as logical as chess – the current champion isn’t a machine, or a human. It’s a combination of both. As American economist and author (Average is Over) Tyler explained in a blog post, a “striking percentage of the best or most accurate chess games of all time have been played by man-machine pairs.” Cowen shows four ways a man-machine team can outperform and they all have to do with leveraging the respective strengths of each. Humans use intuition to create hunches, and then harness the power of the machine to analyze relevant options.

Hunches have served humans very well. They will continue to do so. The trick is to decouple those hunches from the belief making mechanism that has historically accompanied it. That’s where we should let machines take over.

 

 

How We Might Search (On the Go)

As I mentioned in last week’s column – Mediative has just released a new eyetracking study on mobile devices. And it appears that we’re still conditioned to look for the number one organic result before clicking on our preferred destination.

But…

It appears that things might be in the process of changing. This makes sense. Searching on a mobile device is – and should be – significantly different from searching on a desktop. We have different intents. We are interacting with a different platform. Even the way we search is different.

Searching on a desktop is all about consideration. It’s about filtering and shortlisting multiple options to find the best one. Our search strategies are still carrying a significant amount of baggage from what search was – an often imperfect way to find the best place to get more information about something. That’s why we still look for the top organic listing. For some reason we still subconsciously consider this the gold standard of informational relevancy. We measure all other results against it. That’s why we make sure we reserve one slot from the three to five available in our working memory (I have found that the average person considers about 4 results at a time) for its evaluation.

But searching on a mobile device isn’t about filtering content. For one thing, it’s absolutely the wrong platform to do this with. The real estate is too limited. For another, it’s probably not what we want to spend our time doing. We’re on the go and trying to get stuff done. This is not the time for pausing and reflecting. This is the time to find what I’m looking for and use it to take action.

This all makes sense but the fact remains that the way we search is a product of habit. It’s a conditioned subconscious strategy that was largely formed on the desktop. Most of us haven’t done enough searching on mobile devices yet to abandon our desktop-derived strategies and create new mobile specific ones. So, our subconscious starts playing out the desktop script and only varies from it when it looks like it’s not going to deliver acceptable results. That’s why we’re still looking for that number one organic listing to benchmark against

There were a few findings in the Mediative study that indicate that our desktop habits may be starting to slip on mobile devices. But before we review them, let’s do a quick review of how habits play out. Habits are the brains way of cutting down on thinking. If we do something over and over again and get acceptable results, we store that behavior as a habit. The brain goes on autopilot so we don’t have to think our way through a task with predictable outcomes.

If, however, things change, either in the way the task plays out or in the outcomes we get, the brain reluctantly takes control again and starts thinking its way through the task. I believe this is exactly what’s happening with our mobile searches. The brain desperately wants to use its desktop habits, but the results are falling below our threshold of acceptability. That means we’re all somewhere in the process of rebuilding a search strategy more suitable for a mobile device.

Mediative’s study shows me a brain that’s caught between the desktop searches we’ve always done and the mobile searches we’d like to do. We still feel we should scroll to see at least the top organic result, but as mobile search results become more aligned with our intent, which is typically to take action right away, we are being side tracked from our habitual behaviors and kicking our brains into gear to take control. The result is that when Google shows search elements that are probably more aligned with our intent – either local results, knowledge graphs or even highly relevant ads with logical ad extensions (such as a “call” link) – we lose confidence in our habits. We still scroll down to check out the organic result but we probably scroll back up and click on the more relevant result.

All this switching back and forth from habitual to engaged interaction with the results ends up exacting a cost in terms of efficiency. We take longer to conduct searches on a mobile device, especially if that search shows other types of results near the top. In the study, participants spent an extra 2 seconds or so scrolling between the presented results (7.15 seconds for varied results vs. 4.95 seconds for organic only results). And even though they spent more time scrolling, more participants ended up clicking on the mobile relevant results they saw right at the top.

The trends I’m describing here are subtle – often playing out in a couple seconds or less. And you might say that it’s no big deal. But habits are always a big deal. The fact that we’re still relying on desktop habits that were laid down over the past two decades show how persistent then can be. If I’m right and we’re finally building new habits specific to mobile devices, those habits could dictate our search behaviors for a long time to come.

In Search- Even in Mobile – Organic Still Matters

I told someone recently that I feel like Rick Astley. You know, the guy that had the monster hit “Never Gonna Give You Up” in 1987 and is still trading on it almost 30 years later? He even enjoyed a brief resurgence of viral fame in 2007 when the world discovered what it meant to be “Rickrolled”

google-golden-triangle-eye-trackingFor me, my “Never Gonna Give You Up” is the Golden Triangle eye tracking study we released in 2005. It’s my one hit wonder (to be fair to Astley, he did have a couple other hits, but you get the idea). And yes, I’m still talking about it.

The Golden Triangle as we identified it existed because people were drawn to look at the number one organic listing. That’s an important thing to keep in mind. In today’s world of ad blockers and teeth gnashing about the future of advertising, there is probably no purer or more controllable environment than the search results page. Creativity is stripped to the bare minimum. Ads have to be highly relevant and non-promotional in nature. Interaction is restricted to the few seconds required to scan and click. If there was anywhere where ads might be tolerated, its on the search results page

But…

If we fully trusted ads – especially those as benign as those that show up on search results – there would have be no Golden Triangle. It only existed because we needed to see that top Organic result and dragging our eyes down to it formed one side of the triangle.

eyetracking2014Fast forward almost 10 years. Mediative, which is the current incarnation of my old company, released a follow up two years ago. While the Golden Triangle had definitely morphed into a more linear scan, the motivation remained – people wanted to scan down to see at least one organic listing. They didn’t trust ads then. They don’t trust ads now.

Google has used this need to anchor our scanning with the top organic listing to introduce a greater variety of results into the top “hot zone” – where scanning is the greatest. Now, depending on the search, there is likely to be at least a full screen of various results – including ads, local listings, reviews or news items – before your eyes hit that top organic web result. Yet, we seem to be persistent in our need to see it. Most people still make the effort to scroll down, find it and assess its relevance.

It should be noted that all of the above refers to desktop search. But almost a year ago, Google announced that – for the first time ever – more searches happened on a mobile device than on a desktop.

eyetracking mobile.pngMediative just released a new eye-tracking study (Note: I was not involved at all with this one). This time, they dove into scan patterns on mobile devices. Given the limited real estate and the fact that for many popular searches, you would have to consciously scroll down at least a couple times to see the first organic result, did users become more accepting of ads?

Nope. They just scanned further down!

The study’s first finding was that the #1 organic listing still captures the most click activity, but it takes users almost twice as long to find it compared to a desktop.

The study’s second finding was that even though organic is still important, position matters more than ever. Users will make the effort to find the top organic result and, once they do, they’ll generally scan the top 4 results, but if they find nothing relevant, they probably won’t scan much further. In the study, 92.6% of the clicks happened above the 4th organic listing. On a desktop, 84% of the clicks happened above the number 4 listing.

The third listing shows an interesting paradox that’s emerging on mobile devices: we’re carrying our search habits from the desktop over with us – especially our need to see at least one organic listing. The average time to scan the top sponsored listing was only 0.36 seconds, meaning that people checked it out immediately after orienting themselves to the mobile results page, but for those that clicked the listing, the average time to click was 5.95 seconds. That’s almost 50% longer than the average time to click on a desktop search. When organic results are pushed down the page because of other content, it’s taking us longer before we feel confident enough to make our choice. We still need to anchor our relevancy assessment with that top organic result and that’s causing us to be less efficient in our mobile searches than we are on the desktop.

The study also indicated that these behaviors could be in flux. We may be adapted our search strategies for mobile devices, but we’re just not quite there yet. I’ll touch on this in next week’s column.

 

 

 

 

 

 

 

 

The World in Bite Sized Pieces

It’s hard to see the big picture when your perspective is limited to 160 characters.

Or when we keep getting distracted from said big picture by that other picture that always seems to be lurking over there on the right side of our screen – the one of Kate Upton tilting forward wearing a wet bikini.

Two things are at work here obscuring our view of the whole: Our preoccupation with the attention economy and a frantic scrambling for a new revenue model. The net result is that we’re being spoon-fed stuff that’s way too easy to digest. We’re being pandered to in the worst possible way. The world is becoming a staircase of really small steps, each of which has a bright shiny object on it urging us to scale just a little bit higher. And we, like idiots, stumble our way up the stairs.

This cannot be good for us. We become better people when we have to chew through some gristle. Or when we’re forced to eat our broccoli. The world should not be the cognitive equivalent of Captain Crunch cereal.

It’s here where human nature gets the best of us. We’re wired to prefer scintillation to substance. Our intellectual laziness and willingness to follow whatever herd seems to be heading in our direction have conspired to create a world where Donald Trump can be a viable candidate for president of the United States – where our attention span is measured in fractions of a second – where the content we consume is dictated by a popularity contest.

Our news is increasingly coming to us in smaller and smaller chunks. The exploding complexity of our world, which begs to be understood in depth, is increasingly parceled out to us in pre-digested little tidbits, pushed to our smartphone. We spend scant seconds scanning headlines to stay “up to date.” And an algorithm that is trying to understand where our interests lie usually determines the stories we see.

This algorithmic curation creates both “Filter” and “Agreement” Bubbles. The homogeneity of our social network leads to a homogeneity of content. But if we spend our entire time with others that think like us, we end up with an intellectually polarized society in which the factions that sit at opposite ends of any given spectrum are openly hostile to each other. The gaps between our respective ideas of what is right are simply too big and no one has any interest in building a bridge across them. We’re losing our ideological interface areas, those opportunities to encounter ideas that force us to rethink and reframe, broadening our worldview in the process. We sacrifice empathy and we look for news that “sounds right” to us, not matter what “right” might be.

This is a crying shame, because there is more thought provoking, intellectually rich content than ever before being produced. But there is also more sugar coated crap who’s sole purpose is to get us to click.

I’ve often talked about the elimination of friction. Usually, I think this is a good thing. Bob Garfield, in a column a few months ago, called for a whoop-ass can of WD 40 to remove all transactional friction. But if we make things too easy to access, will we also remove those cognitive barriers that force us to slow down and think, giving our rationality a change to catch up with impulse? And it’s not just on the consumption side where a little bit of friction might bring benefits. The upside of production friction was that it did slow down streams of content just long enough to introduce an editorial voice. Someone somewhere had to give some thought as to what might actually be good for us.

In other words, it was someone’s job to make sure we ate our vegetables.

The Future of the Workplace

I noticed a post a few weeks back that said many companies are abandoning their sprawling suburban campuses and are moving back to the city. I found this interesting, because where we work, like so many things in our lives, seems to be in the midst of disruption.

Frederick_Winslow_Taylor_crop

Frederick Winslow Taylor

 

The psychology of the workplace is now a thing. It never used to be. In fact, my youngest daughter is focusing on exactly that as she pursues her post-grad thesis. In the Frederick Winslow Taylor induced hangover that most of corporate America has been trying to get over in the past several decades, workers were considered machinery. Which was a step forward. Prior to that, they were considered grist for the mill. At least Taylor recognized that well maintained machinery worked better than neglected machinery.

But there have been a significant number of studies looking at how the psychology of the individual contributes to the corporate bottom line. And some interesting paradoxes are emerging. Many of these deal with the nature of the workplace.

We used to think of all workplaces as factories. They were built where land was relatively cheap. This led to the whole concept of the suburban campus. But we spend a lot of time at work. We should be happy there. And our work life should not be out of sync with the rest of our lives. So being exiled to the corporate hinterlands of Blandeville, Connecticut or Nondescript, New Jersey may not fit very well with our life plans anymore. We want workplaces that are close to where we choose to live. We want an integrated work-life balance, not an artificially divided one.

The location of our office isn’t the only thing being disrupted. Should we even go to the office at all? Telecommuting has been explored as a viable option by a number of companies.

When I was CEO of my own company we tried our own telecommuting experiment. The rationale is pretty compelling: if you just need a computer and a connection to work, why bear the expense of all the trappings of a formal office? Additionally, it allowed us to recruit in cities where we didn’t have an office. Finally, there was little doubt the majority of our telecommuting employees were happier with the new arrangement.

For us as employers, however, the results were mixed. When our company was acquired, the new owners ended the telecommuting experiment. It was not a popular decision with our employees. I initially fought against it, but eventually, I came around and supported the requirement to share a physical space. This was a few years before Marissa Mayer brought the same hammer down on the telecommuting employees of Yahoo. The infamous memo was sent at Mayer’s behest by Yahoo’s Head of HR, Jackie Reses on February 22, 2013. Here is an excerpt that provides context for the decision:

“That is why it is critical that we are all present in our offices. Some of the best decisions and insights come from hallway and cafeteria discussions, meeting new people, and impromptu team meetings. Speed and quality are often sacrificed when we work from home.”

We found the same thing. While employees loved telecommuting and were generally disciplined in ensuring we got full value from them, we missed the collaboration and creativity that comes from chance encounters and serendipitous discussions. One could make a strong argument that telecommuting might be more efficient in terms of productivity, but an increasing number of studies show that effectiveness is often sacrificed.

Like most things in the sphere of human behavior, I think the disruption of the workplace is subject to the pendulum effect. The starting point was the faceless beige cubicle satirized in Dilbert. As this started to change, we swung too far over to the other side, embracing the geographically unlimited possibilities of a connected workplace. But we found that something was sacrificed in the transition. The best answer likely falls somewhere between these two extremes.

I have talked before about the research done by MIT’s Alex “Sandy” Pentland. He found that the most effective teams have two distinct phases they go through – exploration and engagement. Innovation and creativity comes from exploration. Productivity comes from engagement. I suspect that telecommuting might work well for engagement. But exploration requires some type of common ground – literally. For example, Pentland found something as simple as all employees taking coffee breaks at the same time lead to a significant increase in team effectiveness.

However the workplace may evolve in the future, I believe we’re learning that some essential element of teamwork still requires us being in the same place at the same time, or, as John F. Kennedy once said, “breathing the same air.”

 

 

 

Disruption 101

We Online Spinners are talking a lot about disruption. Dave Morgan has been talking about disruption in the Advertising and Marketing Technology space. I’ve been looking at disruption in other areas, including academia. Cory Treffiletti, Kaila Colbin, Maarten Albarda have all looked at various aspects of disruption. A quick look back at the past few months’ Spin columns show that well over half of them deal with disruption in one way or another.

Maybe it’s time we did a primer on the idea of disruption.

Disruption is what happens when something stable becomes unstable. That’s kind of a “duh..obviously” statement, but there are some very important concepts lurking in there.

When an environment is stable, it allows for the development of extensive but fragile ecosystems. In a corporate sense, this allows for the development of very complicated supply chains, with several “value niches” emerging along that chain. The more complicated the chain, the higher the potential for profit. Each link adds another level of complication, allowing for someone to be squeezing a little more profit from the end consumer.

In addition to extensive ecosystems, stable environments also allow some members of those ecosystems to achieve significant scale. Things are predictable and this allows organizations to grow, embed processes and systems, thereby improving efficiency and profitability. Often, one organization can establish itself at several levels along the supply chain, maximizing its profit potential.

In our physical world, stability is generally a by-product of friction. The higher the degree of friction – or what economist Ronald Coase called “transactional costs” – the more stable the market becomes. Barriers to entry are higher. Competitive factors are dampened. Capital becomes the main predictor of success.

Then – everything changes. We get hit with instability.

In our current case, we got hit with a double whammy: The disruption we’re experiencing is caused by the removal of friction. Technology is reducing transactional costs in a huge swath of industries.

Technology is an interesting catalyst. We think that technology changes behaviors. I don’t believe so. I think technology enables behaviors to change, in that it allows its users to do something they already wanted to do, but couldn’t because of some obstacle. It allows for an attractive alternative that didn’t previously exist. That technology is usually offered to the broadest base of users available and this triggers the disruption, which starts from the ground up. Typically, technology also removes the friction that enables those delicate hierarchal supply chains to form and flourish.

When the disruption begins and the incumbent ecosystem is threatened, the first casualties are the most fragile members of that ecosystem. These are usually the smaller niche players that rely on the bigger hosts that make up the ecosystem. The bigger hosts can survive longer and often swallow up the first casualties in an attempt to shore up their defenses. They will also often make a half-hearted attempt to respond to the disruption by adopting the technology and going after the disruptors. This never works. Disruption is not in their genetic make up. Their priority is always protecting the status quo, because that’s where their profit lies.

As disruption forever alters the environment, eventually the previous ecosystem withers and dies. A new (temporary) stability emerges – along with a new ecosystem – built on the foundation of the previous disruption and the entire cycle starts again.

The Collateral Damage of Disruption

Not all the stories of disruption are of the “David vs. Goliath” variety. Sometimes they are more of the “David vs. Goliath vs. Innocent Bystanders” ilk.

Stewart Wills reminded me of this last week when I was writing about Alexandra Elbakyan and the Elsevier vs. Sci-Hub case. It’s easy to take aim at Elsevier. After all, they’re a very big 4.2 billion dollar target. It’s just too easy to demonize them. But they’re not the only academic publisher in the world.

“Siding with this particular self-styled “Robin Hood” may seem like a no-brainer (and a good, easy-to-tell story), but everyone seems so interested in focusing on big bad Elsevier that they miss a lot of important other affected parties in the picture.”

Wills pointed me to a posting from Caldera Publishing Solutions, a consulting firm that caters to smaller academic publishers. This post refutes my statement of last week that Elsevier is the only one being harmed by the actions of pirates like Elbakyan. In fact, there is an extended chain of bystanders that threaten to be washed away by the tsunami of disruption that’s bearing down on the academic world. For example, there are “dozens and dozens” of society journals who use huge publishers like Elsevier as a clearinghouse. Behind much of the research in the Sci-Hub library, you’ll find non-profit societies, which means that this is “less of a story of Robin Hood robbing from the town’s greedy sheriff, and more a story of Robin Hood stealing from the town’s hospitals and charities.”

The post draws an analogy to a disruptive wave that first broke 17 years ago now: Napster and illegal file sharing. Given that we now have close to two decades of hindsight in this particular case, it might be useful to do a post-mortem on Napster’s impact on the music industry.

I’m not sure if you happened to watch the Grammys, but if you did, you saw Neil Portnow, president of the National Academy of Recording Arts and Sciences, deliver a plea against streaming music services. The problem, said Mr. Portnow, is these services have commoditized music to the degree that royalties amount to fractions of a cent for each play of a song. That may be fine if you’re Rihanna or Sam Smith, but not great if you’re a struggling independent artist.

The problem with the plea is the same tactical error the Academy has made since the first such sermon, delivered by then president Michael Greene at the 2002 Grammies – it was delivered in the wrong church. It’s very hard to feel sorry for the music industry when the most obvious examples – the artists in the audience – are all multi-millionaires drowning under the weight of their own bling. Portnow might be right when he says music may no longer be a viable career, but it’s hard to swallow that message when delivered in the midst of such excess.

But did Napster, and the subsequent removal of friction from the music industry, truly wreak the damage that NARAS keeps warning us about? The fact is, we now have access to far more music than we did in 1990. We can discover new music more readily. Artists can now self produce and distribute. They can even use Songkick to launch their own tours, or Kickstarter to fund a new album. Will they all get rich? No. But they have a better chance than they did two decades ago, when the only path to stardom led directly through the big (and cutthroat) business of music publishing. Napster, and its technological descendants, did what disruption is supposed to do. They cleaned up the market, creating direction connections between the producers and the consumers.

As Stewart Wills reminded me, there are unintended consequences of disruption. One of them is that when the supply chain begins to be violently shaken from below, as was the case with the music industry, the earliest victims are typically small and fragile members of the ecosystem that depend on a bigger host. These tend to either fall of or become absorbed into the more robust survivors. That’s why you don’t find many corner record stores any more.

But then again, good blacksmiths or door-to-door milkmen are also damned hard to find.

 

 

 

Is Amazon Creating a Personalized Store?

There was a brief Amazon-related flurry of speculation last week. Apparently, according to a podcast posted by Wharton, Amazon is planning on opening 300 to 400 bricks and mortar stores.

That’s right. Stores – actual buildings – with stuff in them.

What’s more, this has been “on the books” at Amazon for a while. Amazon CEO Jeff Bezos was asked by Charlie Rose in 2012 if they would every open physical stores. Bezos replied, ““We would love to, but only if we can have a truly differentiated idea,” he said. “We want to do something that is uniquely Amazon. We haven’t found it yet, but if we can find that idea … we would love to open physical stores.”

With that background, the speculation makes sense. If Amazon is pulling the trigger, they must have “found the idea.” So what might that idea be?

Amazon does have a test store in their own backyard of Seattle. What they have chosen to do there, in a footprint about the tenth of the size of the former Barnes and Noble store that was there, is present a “highly curated” store that caters to “local interests.”

Most of the speculation about the new Amazon experiment in “back-to-the-future” retail centers around potential new supply chain management technology or payment methods. But there was one quote from Amanda Nicholson, professor of retail practice at Syracuse University’s Whitman School of Management, that caught my attention; “she said that space represents ‘a test’ to see if Amazon can create ‘a new kind of experience’ using data analytics about customers’ preferences.”

This becomes interesting if we spend some time thinking about the purchase journey we typically take. What Amazon had done online brilliantly is remove friction from two steps in that journey: filtering options and conducting the actual transaction. For certain kinds of purchases, this is all we need. If we’re buying a product that doesn’t rely on tactile feedback, like a digital file or a book, Amazon has connected all the dots required to take us from awareness to purchase.

But that certainly doesn’t represent all potential purchases. That could be the reason that online purchases only represent 9% of all retail. There are many products that require an “experience” between the filtering of options available to us and the actual purchase. These things still require the human “touch” – literally. Up to now, Amazon has remained emotionally distant from these types of purchases. But perhaps a new type of retail location could change that.

Let me give you an example. If you’re a cyclist (like me) you probably have a favorite bike shop. Bike stores are not simply retail outlets. They are temples of bike worship. Bike shops are usually an independent business run by people who love to talk about their favorite rides, the latest bikes or pretty much anything to do with cycling. Going to a bike store is an experience.

But Trek, one of the largest bike manufacturers in the world, also recognized the efficiency of the online model. In 2015, they announced the introduction of Trek Connect, their attempt to find a happy middle ground between practical efficiency and emotional experience. Through Trek Connect, you can configure and order your bike online, but pick it up and have it serviced at your local bike shop.

However, what Amazon may be proposing is not simply about the tactile requirements of certain types of purchases. What if Amazon could create a personalized real world shopping experience?

Right now, there is a gap between our online research and filtering activity and our real world experiential activity. Typically, we shortlist our candidates, gather required information, often in the form of a page printed off from a website, and head down to the nearest retail location. There, the hand off typically leaves a lot to be desired. We have to navigate a store layout that was certainly not designed with our immediate needs in mind. We have to explain what we want to a floor clerk who seems to have at least a thousand other things they’d rather be doing. And we are not guaranteed that what we’re looking for will even be in stock.

But what if Amazon could make the transition seamless? What if they could pick up all the signals from our online activity and create a physical “experiential bubble” for us when we visited the nearest Amazon retail outlet?

Let me go back to my bike purchasing analogy in way of an example. Let’s say I need a new bike because I’m taking up triathlons. Amazon knows this because my online activity has flagged me as an aspiring triathlete. They know where I live and they have a rich data set on my other interests, which includes my favored travel destinations. Amazon could take this data and, under the pretext of my picking up my bike, create a personalized in store experience for me, including a rich selection of potential add-on sales. With Amazon’s inventory and fulfillment prowess, it would be possible to merchandise a store especially for me.

I have no idea if this is what Amazon has “in store” for the future, but the possibility is tantalizing.

It may even make me like shopping.

 

 

 

A New Way to Determine Corporate Value

Last week, I talked about the trend of “hyper” expectations and corporate valuations. Peter Fader, a marketing professor at the Wharton School, commented, “This is why we need to replace the guesswork of tech valuation with the more rigorous, valid, and operational notion of “customer-based corporate valuation.”

I had a chance to look at Professor Fader’s paper. Essentially, he proposes a new model for the valuation of subscription-based businesses based on a calculation of customer lifetime value that uses publicly available information. While interesting in it’s own right, there is a fundamental shift of thinking here that I believe should be explored further.

There are a few standard equations that are used to calculate the value of a firm. If the firm is public, essentially its value is determined by its share price. And that share price is determined by activity in the market – the activity of shareholders. And that activity is dependent on analysts who pass judgment on companies based on projected return to shareholders. At every turn, our entire system of business finance is very heavily weighted towards ownership, which makes sense in a market-based economy. Buyers and sellers determine value.

But what Fader et al are proposing brings another essential stakeholder into the equation – the customer. It’s amazing to me that all the valuation equations we use to determine the value of a corporation don’t involve any direct measure of that corporation’s customer. Sure, we include things like profit, revenue, free cash flow and none of these things would exist without customers, but we never actually attempt to determine the value of a customer. Fader starts the process with the estimation of that value. That simple paradigmatic shift yields a very different view of the world.

For example, if we are to determine the value of a company through the lifetime value of its customers; we have to look at that company in a much different way than the typical financial analyst. We have to look at things like customer loyalty, brand affinity and the likelihood that a company will gain new market share through the disruption of markets. Last week, I used Amazon as an example. Here is a company that has been tremendously disruptive. It has essentially created a new marketplace and, in the process, upended retail as we know it. One would expect this to be taken into account when trying to determine the value of Amazon.

The problem is that things like customer loyalty and brand affinity are emotions. Emotions are not things that are easily quantified. It’s much easier to measure things like quarterly earnings and discounted free cash flow. Most of these things depend on using the past to predict the future. They also rely on the firm’s ability to prognosticate. Typically, all the heavy lifting of factoring in the fuzziness of things like future customer value is left to the company. If a company misses its projections, it is penalized by the analysts, resulting in a decrease of share price.

Ultimately, the gap between how we have historically determined the value of companies and how we might in the future comes down to a matter of our ability to determine what may come to pass. We strive for perfect predictability. We want to place our bets based on solid information and analysis. But, in a disruptive marketplace, this desire for predictability may ultimately sink us. Customers will always determine the value of a company and in a marketplace where transactional and switching costs are both plunging, those customers have the ability to switch buying behaviors instantly. The old saying, “No one ever got fired for buying IBM” has not been true for at least three decades.

Like it or not, if we want to get a true picture of the value of a company, we’re going to have to use some guesswork. And, most importantly, we’re going to have to make sure we include customers in whatever equation we’re using.

 

Living in the Age of “Hyper”

Amazon is a disappointment.

In the fourth quarter of 2015, it made a measly $482 million profit on sales of $35.7 billion. That’s a 22% gain in revenue from a year ago, and over a 100% gain in profit. In that year, Amazon also doubled its market value to over $300 billion.

Bunch of deadbeats…

Last week, Amazon’s share price took a beating in after hours trading, dropping 15%

Serves you right, slackers…

And this all happened because despite Amazon’s healthy performance, it “didn’t meet analyst’s expectations.”

Maybe it’s time to look at those expectations.

Amazon is what those analysts call a “growth” stock. If you compare it against the rest of the Fortune 500, it might even be called a “hyper-growth” stock. It’s doubling of market value outperformed other growth stocks like Apple, which has had it’s own history of disappointment. We expect great things from anything prefaced with “hyper.

You all know what hyper means. It means “above” – as in “above” normal. In terms of growth of revenue and market value, Amazon would certainly qualify. It’s in the top few percent of all companies of the Fortune 500 in both categories.

But we expect more. We expect “hyper” performance. And it you don’t measure up, you disappoint us. It’s like kicking your kid out of the house when they come home with a straight A report card in grade 10 because they didn’t qualify for early admission to Harvard.

Here’s the thing about “hyper.” Not everything can be “hyper.” Something needs to be the opposite of hyper. Do you know what the opposite of “hyper” is? It’s “hypo.” Everyone knows what hyper means, but I bet it’s been a long time since you used “hypo” in a sentence.

hypo hyper

That’s because we’re fixated on “hyper”. But the way we use “hyper” makes it an outlier. It’s a statistical anomaly on the far right of the normal distribution curve. It doesn’t represent reality. But we think it does. We expect everything to measure up to some unrealistic measure of performance. When we start a business, we expect to be as successful as Google. When we look at our bank account, we expect it to be as big as Kanye West’s. When we buy a stock, we want it to outperform every other stock in the market.

We have over-hyped “hyper.”

This tendency is starting to impact other aspects of our lives. As we quantify more of who we are, we tend to measure ourselves against the “hyper” end of the yardstick. It’s becoming a real problem. Even our friendships are now quantified, thanks to Facebook, Twitter and Instagram. The result is that it’s now almost impossible to measure up to expectations.

We, like Amazon, are disappointing. The difference is that Amazon disappoints analysts. We disappoint ourselves.

This can be a real bummer. Tom Magliozzi, co-host of NPR’s Car Talk show, summarized the problem in five words:

“Happiness Equals Reality Minus Expectations.”

If our expectations keep moving to the “hyper” end of the scale, it will never match up to reality. We’ll never be happy. According to this blog post by Tim Urban, it’s a big problem for Generation Y. And Tim should know. He’s a 31-year-old Harvard grad who owns a couple of tutoring businesses and has started a blog that grew virally to over 300,000 subscribers.

Slacker.