Category Archives: Consumer Psychology

The Rise of the Audience Marketplace

Far be it from me to let a theme go before it has been thoroughly beaten to the ground. This column has hosted a lot of speculation on the future of advertising and media buying and today, I’ll continue in that theme.

First, let’s return to a column I wrote almost a month ago about the future of advertising. This was a spin-off on a column penned by Gary Milner – The End of Advertising as We Know It. In it, Gary made a prediction: “I see the rise of a global media hub, like a stock exchange, which will become responsible for transacting all digital programmatic buys.”

Gary talked about the possible reversal of fragmentation of markets by channel and geographic area due to the potential centralization of digital media purchasing. But I see it a little differently than Gary. I don’t see the creation of a media hub – or, at least – that wouldn’t be the end goal. Media would simply be the means to the end. I do see the creation of an audience market based on available data. Actually, even an audience would only be the means to an end. Ultimately, we’re buying one thing – attention. Then it’s our job to create engagement.

The Advertising Research Foundation has been struggling with measuring engagement for a long time now. But it’s because they were trying to measure engagement on a channel-by-channel basis and that’s just not how the world works anymore. Take search, for example. Search is highly effective at advertising, but it’s not engaging. It’s a connecting medium. It enables engagement, but it doesn’t deliver it.

We talk multi-channel a lot, but we talk about it like the holy grail. The grail in this cause is an audience that is likely to give us their attention and once they do that – is likely to become engaged with our message. The multi-channel path to this audience is really inconsequential. We only talk about multi-channel now because we’re stopping short of the real goal, connecting with that audience. What advertising needs to do is give us accurate indicators of those two likelihoods: how likely are they to give us their attention and what is their potential proclivity towards our offer. The future of advertising is in assembling audiences – no matter what the channel – that are at a point where they are interested in the message we have to deliver.

This is where the digitization of media becomes interesting. It’s not because it’s aggregating into a single potential buying point – it’s because it’s allowing us to parallel a single prospect along a path of persuasion, getting important feedback data along the way. In this definition, audience isn’t a static snapshot in time. It becomes an evolving, iterative entity. We have always looked at advertising on an exposure-by-exposure basis. But if we start thinking about persuading an audience that paradigm needs to be shifted. We have to think about having the right conversation, regardless of the channel that happens to be in use at the time.

Our concept of media happens to carry a lot of baggage. In our minds, media is inextricably linked to channel. So when we think media, we are really thinking channels. And, if we believe Marshall McLuhan, the medium dictates the message. But while media has undergone intense fragmentation they’ve also become much more measurable and – thereby – more accountable. We know more than ever about who lies on the other side of a digital medium thanks to an ever increasing amount of shared data. That data is what will drive the advertising marketplace of the future. It’s not about media – it’s about audience.

In the market I envision, you would specify your audience requirements. The criteria used would not be so much our typical segmentations – demography or geography for example. These have always just been proxies for what we really care about; their beliefs about our product and predicted buying behaviors. I believe that thanks to ever increasing amounts of data we’re going to make great strides in understanding the psychology of consumerism. These  will be foundational in the audience marketplace of the future. Predictive marketing will become more and more accurate and allow for increasingly precise targeting on a number of behavioral criteria.

Individual channels will become as irrelevant as the manufacturer that supplies the shock absorbers and tie rods in your new BMW. They will simply be grist for the mill in the audience marketplace. Mar-tech and ever smarter algorithms will do the channel selection and media buying in the background. All you’ll care about is the audience you’re targeting, the recommended creative (again, based on the mar-tech running in the background) and the resulting behaviors. Once your audience has been targeted and engaged, the predicted path of persuasion is continually updated and new channels are engaged as required. You won’t care what channels they are – you’ll simply monitor the progression of persuasion.

 

Media Buying is Just the Tip of Advertising’s Disruptive Iceberg

Two weeks ago, Gary Milner wrote a lucid prediction of what advertising might become. He rightly stated that advertising has been in a 40-year period of disruption. Bingo. He went on to say that he sees a consolidation of media buying into a centralized hub. Again, I don’t question the clarity of Milner’s crystal ball. It makes sense to me.

What is missing from Milner’s column, however, is the truly disruptive iceberg that is threatening to founder advertising as we know it – the total disruption of the relationship between the advertiser and the marketplace. Milner deals primarily with the media buying aspect of advertising but there’s a much bigger question to tackle. He touched on it in one sentence: “The fact is that a vast majority of advertising is increasingly being ignored.”

Yes! Exactly. But why?

I’ll tell you why. It’s because of a disagreement about what advertising should be. We (the buyers) believe advertising’s sole purpose is to inform. But the sellers believe advertising is there to influence buyers. And increasingly, we’re rejecting that definition.

I know. That’s a tough pill to swallow. But let’s apply a little logic to the premise. Bear with me.

Advertising was built on a premise of scarcity. Market places can’t exist without scarcity. There needs to be an imbalance to make an exchange of value worthwhile. Advertising exists because there once was a scarcity of information. We (the buyers) lacked information about products and services. This was primarily because of the inefficiencies inherent in a physical market. So, in return for the information, we traded something of value – our attention. We allowed ourselves to be influenced. We tolerated advertising because we needed it. It was the primary way we gained information about the marketplace.

In Milner’s column, he talks about Peter Diamandis’ 6 stages that drive the destruction of industries: digitalization, deception, disruption, demonetization, dematerialization, and democratization. Milner applied it to the digitization of media. But these same forces are also being applied to information and rather than driving advertising from disruption to a renaissance period, as Milner predicts, I believe we’ve barely scratched the surface of disruption. The ride will only get bumpier from here on.

The digitization of information enables completely new types of marketplaces. Consider the emergence of the two-sided markets that both AirBNB and Uber exemplify. Thanks to the digitization of information, entirely new markets have emerged that allow the flow of information between buyers and suppliers. Because AirBNB and Uber have built their business models astride these flows, they can get a cut of the action.

But the premise of the model is important to understand. AirBNB and Uber are built on the twin platforms of information and enablement. There is no attempt to persuade by the providers of the platforms – because they know those attempts will erode the value of the market they’re enabling. We are not receptive to persuasion (in the form of advertising) because we have access to information that we believe to be more reliable – user reviews and ratings.

The basic premise of advertising has changed. Information is no longer scarce. In fact, through digitization, we have the opposite problem. We have too much information and too little attention to allocate to it. We now need to filter information and increasingly, the filters we apply are objectivity and reliability. That turns the historical value exchange of advertising on its head. This has allowed participatory information marketplaces such as Uber, AirBNB and Google to flourish. In these markets, where information flows freely, advertising that attempts to influence feels awkward, forced and disingenuous. Rather than building trust, advertising erodes it.

This disruption has also driven another trend with dire consequences for advertising as we know it – the “Maker” revolution and the atomization of industries. There are some industries where any of us could participate as producers and vendors. The hospitality industry is one of these. The needs of a traveller are pretty minimal – a bed, a roof, a bathroom. Most of us could provide these if we were so inclined. We don’t need to be Conrad Hilton. These are industries susceptible to atomization – breaking the market down to the individual unit. And it’s in these industries where disruptive information marketplaces will emerge first. But I can’t build a refrigerator. Or a car (yet). In these industries, scale is still required. And these will be the last strongholds of mass advertising.

Milner talked about the digitization of media and the impact on advertising. But there’s a bigger change afoot – the digitization of information in marketplaces that previously relied on scarcity of information to prop up business models. As information goes from scarcity to abundance, these business models will inevitably fall.

Where Context Comes From

Fellow Spinner Cory Treffiletti told you last week that data without context is noise.

Absolutely right.

I want to continue that conversation, because it’s an important one. It’s all about context. So let’s talk a little more about context. And specifically how we decide what makes up that context.

You might have seen or heard the hubbub that emerged around a tweet from Neil Degrasse Tyson a month ago: “Earth needs a virtual country: #Rationalia, with a one-line Constitution: All policy shall be based on the weight of evidence”

Nice thought, but it ignited a social media shit-storm. Which was entirely predictable. Because we don’t want to be rational. We want to be human. Did 79 episodes of Star Trek teach us nothing?

The biggest beef against #Rationalia was that evidence is typically in the eyes of the beholder. It’s all a matter of context. I’m guessing that the policies that come from evidence in the hands of Republicans will not bear much resemblance to policies that come from the evidence of Democrats. The evidence could be the same but the context is different, because Democrats and Republicans think differently.

Like Treffiletti said – evidence without context is just noise. And our context is only marginally based on evidence. And that’s why #Rationalia – as intellectually attractive as it might be – won’t work.

We as humans understand the world through something called sense making. This is the process we use to build context. In 2006, psychologist Gary Klein shed new light on how we make sense of the world. We start with a frame that captures our current understanding of the situation and depending on the evidence presented to us, we decide whether to elaborate our frame or discard it and create a new frame. So, sensemaking is really an iterative loop that is constantly using our current frame as a reference point.

But here’s the thing. What we consider as evidence depends on the frame we already have in place. It’s the filter that determines what data we pay attention to. And much as Neil Degrasse Tyson would like the governments of the world to be totally unbiased in the filtering of evidence, “that dog just won’t hunt.” It can’t – because we can’t consider data without some context to put it in.

Perhaps someday artificial intelligence will advance to the point where it can pull unbiased context out of random data. Maybe computers will be able to do what we’re unable to – make sense of the noise without assuming a pre-existing frame. But we’re not there yet. And even if we were, we would simply look at the conclusions of the computer and decide whether we agree with them or not. As long as humans are in charge, there will always be a biased filter in place.

So back to Cory’s column. If context is so important, think about where that context is coming from. Who is defining the context and what frame are they operating from? That in turn will define what data you consider and how you consider it.

Perhaps the most important decision before considering data is to be totally clear about what the goal is. Goals, together with experience, form the underpinning of beliefs. Frames are then built on those beliefs. Context comes from those frames. And context is the filter we apply to evidence.

Can Stories Make Us Better?

In writing this column, I often put ideas on the shelf for a while. Sometimes, world events conspire to make one of these shelved ideas suddenly relevant. This happened this past weekend.

The idea that caught my eye some months ago was an article that explored whether robots could learn morality by reading stories. On the face of it, it was mildly intriguing. But early Sunday morning as the heartbreaking news filtered to me from Orlando, a deeper connection emerged.

When we speak of unintended consequence, which we have before, the media amplification of acts of terror are one of them. The staggeringly sad fact is that shocking casualty numbers have their own media value. And that, said one analyst who was commenting on ways to deal with terrorism, is a new reality we have to come to terms with. When we in the media business make stories news worthy we assign worth not just for news consumers but also to newsmakers – those troubled individuals who have the motivation and the means to blow apart the daily news cycle.

This same analyst, when asked how we deal with terrorism, made the point you can’t prevent lone acts of terrorism. The only answer is to use that same network of cultural connections we use to amplify catastrophic events to create an environment that dampens rather than intensifies violent impulse. We in the media and advertising industries have to use our considerable skills in setting cultural contexts to create an environment that reduces the odds of a violent outcome. And sadly, this is a game of odds. There are no absolute answers here – there is just a statistical lowering of the curve. Sometimes, despite your best efforts, the unimaginable still happens.

But how do you use the tools at our disposal to amplify morality? Here, perhaps the story I shelved some months ago can provide some clues.

In the study from Georgia Tech, Mark Riedl and Brent Harrison used stories as models of acceptable morality. For most of human history, popular culture included at least an element of moral code. We encoded the values we held most dear into our stories. It provided a base for acceptable behavior, either through positive reinforcement of commonly understood virtues (prudence, justice, temperance, courage, faith, hope and charity) or warnings about universal vices (lust, gluttony, greed, sloth, wrath, envy and pride). Sometimes these stories had religious foundations, sometimes they were secular morality fables but they all served the same purpose. They taught us what was acceptable behavior.

Stories were never originally intended to entertain. They were created to pass along knowledge and cultural wisdom. Entertainment came after when we discovered the more entertaining the story, the more effective it was at its primary purpose: education. And this is how the researchers used stories. Robots can’t be entertained, but they can be educated.

At some point in the last century, we focused on the entertainment value of stories over education and, in doing so, rotated our moral compass 180 degrees. If you look at what is most likely to titillate, sin almost always trumps sainthood. Review that list of virtues and vices and you’ll see that the stories of our current popular culture focus on vice – that list could be the programming handbook for any Hollywood producer. I don’t intend this a sermon – I enjoy Game of Thrones as much as the next person. I simply state it as a fact. Our popular culture – and the amplification that comes from it – is focused almost exclusively on the worst aspects of human nature. If robots were receiving their behavioral instruction through these stories, they would be programmed to be psychopathic moral degenerates.

For most of us, we can absorb this continual stream of anti-social programming and not be affected by it. We still know what is right and what is wrong. But in a world where it’s the “black swan” outliers that grab the news headlines, we have to think about the consequences that reach beyond the mainstream. When we abandon the moral purpose of stories and focus on their entertainment aspect, are we also abandoning a commonly understood value landscape?

If you’re looking for absolute answers here, you won’t find them. That’s just not the world we live in. And am I naïve when I say the stories we chose to tell may have an influence on isolated violent events such as happened in Orlando? Perhaps. Despite all our best intentions, Omar Mateen might still have gone horribly offside.

But all things and all people are, to some extent, products of their environment. And because we in media and advertising are storytellers, we set that cultural environment. That’s our job. Because of this, I belief we have a moral obligation. We have to start paying more attention to the stories we tell.

 

 

 

 

Ex Machina’s Script for Our Future

One of the more interesting movies I’ve watched in the past year has been Ex Machina. Unlike the abysmally disappointing Transcendence (how can you screw up Kurzweil – for God’s sake), Ex Machina is a tightly directed, frighteningly claustrophobic sci-fi thriller that peels back the moral layers of artificial intelligence one by one.

If you haven’t seen it, do so. But until you do, here’s the basic set up. Caleb Smith (Domhnall Gleeson) is a programmer at a huge Internet search company called Blue Book (think Google). He wins a contest where the prize is a week spent with the CEO, Nathan Bateman (Oscar Isaac) at his private retreat. Bateman’s character is best described as Larry Page meets Steve Jobs meets Larry Ellison meets Charlie Sheen – brilliant as hell but one messed up dude. It soon becomes apparent that the contest is a ruse and Smith is there to play the human in an elaborate Turing Test to determine if the robot Ava (Alicia Vikander) is capable of consciousness.

About half way through the movie, Bateman confesses to Smith the source of Ava’s intelligence “software.” It came from Blue Book’s own search data:

‘It was the weird thing about search engines. They were like striking oil in a world that hadn’t invented internal combustion. They gave too much raw material. No one knew what to do with it. My competitors were fixated on sucking it up, and trying to monetize via shopping and social media. They thought engines were a map of what people were thinking. But actually, they were a map of how people were thinking. Impulse, response. Fluid, imperfect. Patterned, chaotic.”

As a search behaviour guy – that sounded like more fact than fiction. I’ve always thought search data could reveal much about how we think. That’s why John Motavalli’s recent column, Google Looks Into Your Brain And Figures You Out, caught my eye. Here, it seemed, fiction was indeed becoming fact. And that fact is, when we use one source for a significant chunk of our online lives, we give that source the ability to capture a representative view of our related thinking. Google and our searching behaviors or Facebook and our social behaviors both come immediately to mind.

Motavalli’s reference to Dan Ariely’s post about micro-moments is just one example of how Google can peak under the hood of our noggins and start to suss out what’s happening in there. What makes this either interesting or scary as hell, depending on your philosophic bent, is that Ariely’s area of study is not our logical, carefully processed thoughts but our subconscious, irrational behaviors. And when we’re talking artificial intelligence, it’s that murky underbelly of cognition that is the toughest nut to crack.

I think Ex Machina’s writer/director Alex Garland may have tapped something fundamental in the little bit of dialogue quoted above. If the data we willingly give up in return for online functionality provides a blue print for understanding human thought, that’s a big deal. A very big deal. Ariely’s blog post talks about how a better understanding of micro-moments can lead to better ad targeting. To me, that’s kind of like using your new Maserati to drive across the street and visit your neighbor – it seems a total waste of horsepower. I’m sure there are higher things we can aspire to than figuring out a better way to deliver a hotels.com ad. Both Google and Facebook are full of really smart people. I’m pretty sure someone there is capable of connecting the dots between true artificial intelligence and their own brand of world domination.

At the very least, they could probably whip up a really sexy robot.

 

 

 

 

 

 

 

 

 

 

 

 

Why Marketers Love Malcolm Gladwell … and Why They Shouldn’t

Marketers love Malcolm Gladwell. They love his pithy, reductionist approach to popular science – his tendency to sacrifice verity for the sake of a good “Just-so” story. And in doing this, what is Malcolm Gladwell but a marketer at heart? No wonder our industry is ga-ga over him. We love anyone who can oversimplify complexity down to the point where it can be appropriated as yet another marketing “angle”.

Take the entire influencer advertising business, for instance. Earlier this year, I saw an article saying more and more brands are expanding their influencer marketing programs. We are desperately searching for that holy nexus where social media and those super-connected “mavens” meet. While the idea of influencer marketing has been around for a while, it really gained steam with the release of Gladwell’s “The Tipping Point.” And that head of steam seems to have been building since the release of the book in 2000.

As others have pointed out, Gladwell has made a habit of taking one narrow perspective that promises to “play well” with the masses, supporting it with just enough science to make it seem plausible and then enshrining it as a “Law.”

Take “The Law of the Few”, for instance, from The Tipping Point: “The success of any kind of social epidemic is heavily dependent on the involvement of people with a particular and rare set of social gifts.” You could literally hear the millions of ears attached to marketing heads “perk up” when they heard this. “All we have to do,” the reasoning went, “is reach these people, plant a favorable opinion of our product and give them the tools to spread the word. Then we just sit back and wait for the inevitable epidemic to sweep us to new heights of profitability.”

Certainly commercial viral cascades do happen. They happen all the time. And, in hindsight, if you look long and hard enough, you’ll probably find what appears to be a “maven” near ground-zero. From this perspective, Gladwell’s “Law of the Few” seems to hold water. But that’s exactly the type of seductive reasoning that makes “Just So” stories so misleading. You mistakenly believe that because it happened once, you can predict when it’s going to happen again. Gladwell’s indiscriminate use of the term “Law” contributes to this common deceit. A law is something that is universally applicable and constant. When a law governs something, it plays out the same way, every time. And this is certainly not the case in social epidemics.

duncan-watts

Duncan Watts

If Malcolm Gladwell’s books have become marketing and pop-culture bibles, the same, sadly, cannot be said for Duncan Watts’ books. I’m guessing almost everyone reading this column has heard of Malcolm Gladwell. I further guess that almost none of you have heard of Duncan Watts. And that’s a shame. But it’s completely understandable.

Duncan Watts describes his work as determining the “role that network structure plays in determining or constraining system behavior, focusing on a few broad problem areas in social science such as information contagion, financial risk management, and organizational design.”

You started nodding off halfway through that sentence, didn’t you?

As Watts shows in his books, “Firms spent great effort trying to find “connectors” and “mavens” and to buy the influence of the biggest influencers, even though there was never causal evidence that this would work.” But the work required to get to this point is not trivial. While he certainly aims at a broad audience, Watts does not read like Gladwell. His answers are not self-evident. There is no pithy “bon mot” that causes our neural tumblers to satisfyingly click into place. Watts’ explanations are complex, counter-intuitive, occasionally ambiguous and often non-conclusive – just like the world around us. As he explains his book “Everything is Obvious: *Once You Know the Answer”, it’s easy to look backwards to find causality. But it’s not always right.

Marketers love simplicity. We love laws. We love predictability. That’s why we love Gladwell. But in following this path of least resistance, we’re straying further and further from the real world.

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.

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.

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.