The Cathedral and Bazaar Cycle of Mar -Tech Innovation

Each year my friend Scott Brinker sits down to update his marketing technology landscape and each year he is amazed by the explosion of vendors he has to fit on a single slide. Last year’s version clocked in at 3874 Mar Tech solutions – almost twice as many as 2015. He started in 2011 with about 150 and it has effectively doubled with each iteration. While everyone has expected eventual consolidation this hasn’t happened to date.

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Scott’s Marketing Technology Landscape – 2016

Why?

For a possible answer, we can look at a fascinating study conducted by a UCLA team looking at the fossil record of cars. Since 1896, there is a reliable record of the introduction of new automobile makes and models. In essence, this creates a “fossil” record, similar to biology, where we can look at the evolution of a technology over an extended time period. In this case, the researchers were looking to isolate the factors that led to the greatest introduction of new models and the discontinuation of old models. When many new models were being introduced, the evolution of the automotive technology accelerated. The researchers wanted to see if this pace of evolution was tied to strength of the economy, changes in oil prices or the number of other cards on the market. What they found was that competition in the marketplace played a bigger role in the variety of car models than either economic growth or oil prices.

However, these periods of rapid innovation didn’t last forever. Inevitably, there was a period of consolidation, where the major manufacturers focused on a few models to increase profitability. It’s a lot more profitable to produce a popular model with relatively few changes over a long period of time.

Once again, we have an oscillation or wave happening.

What is interesting about this is that these periods of rapid innovation always come from an open market with many competitors – exactly what is happening in marketing technology right now. That is because open markets always drive more innovation than can be achieved within hierarchal organizations. As Eric Raymond showed in his brilliant essay on the open source movement – The Cathedral and the Bazaar – the evolutionary forces of a distributed open market (or “Bazaar”) always trump vertical integration (“Cathedrals”) when it comes to spinning off fresh ideas.

In their book “Creative Destruction,” authors Richard Foster and Sarah Kaplan show that organizations (cathedrals) tend to favor incremental innovation with occasional forays into substantial innovation. But markets (bazaars) unleash transformational innovation. The unpredictability and risk increases by a factor of ten as you go from one version of innovation to the other, but so do the rewards. Innovation in markets grow on a logarithmic scale. It’s why some players – like Tesla and Google – have espoused the open-source “Bazaar” approach in areas like sustainable transportation and artificial intelligence where rapid innovation is essential.

There is another critical factor at play here as well. The market/bazaar, being ruthless, quickly culls the competitors down to those that have the best market potential. This explosion of innovation and the subsequent winnowing need a brutally competitive market environment – a rugged landscape in evolutionary terms. Organizations/Cathedrals are reluctant to pull the plug on losers as they fall victim to the sunk cost fallacy and loss aversion. Markets/bazaars operate like nature – “red in tooth and claw” – with a brutal efficiency in dispatching the less fit.

After this explosion of innovation and the subsequent purge, there is a period of consolidation where the biggest players benefit. Let’s call this the Cathedral phase. Here, operational efficiency takes over, looking for greater profitability. Here, market tested innovation is acquired by the largest organizations and systematically incorporated into a replicable template that allows for scalability. Here, the Cathedral model does what it excels at, maximizing profits. Of course, there is a trade off. Innovation withers and dies in this environment, leading to eventual stagnation, which triggers the need for break out innovation all over again.

Will marketing technology follow the Cathedral/Bazaar pattern? In his last landscape, Scott mentioned that rather than coalescing around an “a small oligopoly of platform providers competing for that starring role” the Mar-Tech ecosystem seems to be embedding plug and play compatibility allowing for a longer “Bazaar” phase. Perhaps, with the elimination of market friction, we’re getting to a point where profitability can be uncoupled from the need for scale. I guess we’ll have to wait and see how many mar-tech vendors end up on the 2017 version of Scott’s slide.

 

 

 

 

Prospect Theory, Back Burners and Relationship Risk

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

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Dr. Michelle Drouin

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

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

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

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

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

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

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

 

 

 

Why Our Brains are Blocking Ads

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

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

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

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

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

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

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

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

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

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

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

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

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.

A Possibly Premature Post-Mortem on Yahoo

Last Thursday, Yahoo held it ‘s annual shareholder meeting. At that meeting, CEO Marissa Mayer dealt the company a doubled down kiss of death. She stated the goals of the board are fully aligned with one clear priority: “delivering shareholder value to all of you.” She further mentioned, when dealing with the divesture of all that once was Yahoo, that she’s “been very heartened by the level of interest in Yahoo. It validates our business processes as well as our achievements to date.”

It’s fancier language, but it’s basically the same as the butcher saying, “This cow is no longer viable as a cow, so I’m looking at it as a collection of rump roasts, T-Bones and hamburger. I’m hoping we have more of the former and less of the later.”

Yahoo_1996I first encountered Yahoo in 1995, shortly after it’s brief life as Jerry and David’s Guide to the World Wide Web. I think it was probably still parked on Stanford’s servers at the time. At the time, the Internet was like the world’s biggest second-hand store – a huge collection that was 95% junk/5 % useful stuff with no overarching order or organization. David Filo and Jerry Yang’s site was one of the very first to try to provide that order.

As an early search marketer in the run up to the dot-com bubble, you couldn’t ignore the Yahoo directory. The Yahooligans walked with typical Valley swagger. Hubris was never in short supply. They were the cocks of the walk and they knew it.

It was a much-humbled post-bubble Yahoo that I visited in 2004. They had got their search asses soundly kicked by Google, who was now powering their non-directory results. The age of the curated directory was gone, replaced by the scalability of algorithmic search.

As a culture, the Yahooligans were struggling with the mixed management signals that came from then CEO Terry Semel and his team. Sunnyvale was clouded in a purple haze. The Yahooligans didn’t know who the hell they were or what they were supposed to do. Where they a tech company or an entertainment company? The answer, as it turned out, was neither.

I met with the remnants of the once mighty search team to talk about user behaviors. I didn’t know it at the time, but Yahoo was gearing up to relaunch their search service. A much vilified paid inclusion program would also be debuted. It was one of many ill-fated attempts to find the next “Big Thing.”

Marissa Mayer continues to put a brave face on it, but the Yahoo engine ran out of steam at least a decade and a half ago. What amazes me is how long the ride has been. There is a message here for tech-based companies.

If you dig down to the critical incubation period of any tech company, you find a recurring pattern. Some technologically mediated connection allows people to do something they were previously unable to do. This releases pent up market demand. It’s like a thin sliver trying to poke through a water balloon. If successful, this released market demand creates an immediate and sizable audience for whomever introduced the innovation. Yahoo’s directory, Google’s PageRank, Facebook’s “Facemash”, AirBnB’s accommodation directory, Uber’s ridesharing app – they all share the same modus operandi – a tech-step forward creates a new audience and market opportunity.

In hindsight, once you strip away all the hype, it’s amazing how tenuous and unimpressive these technological advances are. Luck and timing typically play a huge part. If the conditions are right, the sliver eases through the balloon’s membrane and for a time, there is a steady stream of opportunity.

The problem is that is that as easily as these markets form, they can just as easily evaporate. When the technological advantage passes to the next competitor, as it did when Yahoo gave way to Google, all that’s left is the audience. When you consider that Yahoo has been coasting on this audience for close to two decades, it’s rather amazing that Mayer still has any assets at all to sell.