This is Why We Can’t Have Nice Things

Relevance is the new gold standard in marketing. In an  article in the Harvard Business Review written last year, John Zealley, Robert Wollan and Joshua Bellin — three senior execs at Accenture — outline five stages of marketing (paraphrased courtesy of a post from Phillip Nones):

  1. Mass marketing (up through the 1970s) – The era of mass production, scale and distribution.Marketing segmentation (1980s) – More sophisticated research enabling marketers to target customers in niche segments.
  2. Customer-level marketing (1990s and 2000s) – Advances in enterprise IT make it possible to target individuals and aim to maximize customer lifetime value.
  3. Loyalty marketing (2010s) – The era of CRM, tailored incentives and advanced customer retention.
  4. Relevance marketing (emerging) – Mass communication to the previously unattainable “Segment of One.”

This last stage – according to marketers past and present – should be the golden era of marketing:

“The perfect advertisement is one of which the reader can say, ‘This is for me, and me alone.” 

— Peter Drucker

“Audiences crave tailored messages that cater to them specifically and they are willing to offer information that enables marketers to do so.”

 Kevin Tash, CEO of Tack Media, a digital marketing agency in Los Angeles.

Umm…no! In fact, hell, no!

I agree that relevance is an important thing. And in an ethical world, the exchange Tash talks about would be a good thing, for both consumers and marketers. But we don’t live in such a world. The world we live in has companies like Facebook and Cambridge Analytica.

Stop Thinking Like a Marketer!

There is a cognitive whiplash that happens when our perspective changes from that of marketer to that of a consumer. I’ve seen it many times. I’ve even prompted it on occasion. But to watch it in 113 minutes of excruciating detail, you should catch “The Great Hack” on Netflix. 

The documentary is a journalistic peeling of the onion that is the Cambridge Analytica scandal. It was kicked off by the whistle blowing of Christopher Wylie, a contract programmer who enjoyed his 15 minutes of fame. But to me, the far more interesting story is that of Brittany Kaiser, the director of business Development of SCL Group, the parent company of Cambridge Analytica. The documentary digs into the tortured shift of perspective as she transitions from thinking like a marketer to a citizen who has just had her private data violated. It makes for compelling viewing.

Kaiser shifted her ideological compass about as far as one could possibly do, from her beginnings as an idealistic intern for Barack Obama and a lobbyist for Amnesty International to one of the chief architects of the campaigns supporting Trump’s presidential run, Brexit and other far right persuasion blitzkriegs. At one point, she justifies her shift to the right by revealing her family’s financial struggle and the fact that you don’t get paid much as an underling for Democrats or as a moral lobbyist. The big bucks are found in the ethically grey areas.  Throughout the documentary, she vacillates between the outrage of a private citizen and the rationalization of a marketer. She is a woman torn between two conflicting perspectives.

We marketers have to stop kidding ourselves and justifying misuse of personal data with statements like the one previously quoted from Kevin Tash. As people, we’re okay. I like most of the marketers I know. But as professional marketers, we have a pretty shitty track record. We trample privacy, we pry into places we shouldn’t and we gleefully high-five ourselves when we deliver the goods on a campaign — no matter who that campaign might be for and what its goals might be. We are very different people when we’re on the clock.

We are now faced with what may be the most important questions of our lives: How do we manage our personal data? Who owns it? Who stores it? Who has the right to use it? When we answer those questions, let’s do it as people, and not marketers. Because there is a lot more at stake here than the ROI rates on a marketing campaign.

Data does NOT Equal People

We marketers love data. We treat it like a holy grail: a thing to be worshipped. But we’re praying at the wrong altar. Or, at the very least, we’re praying at a misleading altar.

Data is the digital residue of behavior. It is the contrails of customer intent — a thin, wispy proxy for the rich bandwidth of the real world. It does have a purpose, but it should be just one tool in a marketer’s toolbox. Unfortunately, we tend to use it as a Swiss army knife, thinking it’s the only tool we need.

The problem is that data is seductive. It’s pliable and reliable, luring us into manipulation because it’s so easy to do. It can be twisted and molded with algorithms and spreadsheets.

But it’s also sterile. There is a reason people don’t fit nicely into spreadsheets. There are simply not enough dimensions and nuances to accommodate real human behavior.

Data is great for answering the questions “what,” “who,” “when” and “where.” But they are all glimpses of what has happened. Stopping here is like navigating through the rear-view mirror.

Data seldom yields the answer to “why.” But it’s why that makes the magic happen, that gives us an empathetic understanding that helps us reliably predict future behaviors.

Uncovering the what, who, when and where makes us good marketers. But it’s “why” that makes us great. It’s knowing why that allows us to connect the distal dots, hacking out the hypotheses that can take us forward in the leaps required by truly great marketing. As Tom Goodwin, the author of “Digital Darwinism,” said in a recent post, “What digital has done well is have enough of a data trail to claim, not create, success.”

We as marketers have to resist stopping at the data. We have to keep pursuing why.

Here’s one example from my own experience. Some years ago, my agency did an eye-tracking study that looked at gender differences in how we navigate websites.

For me, the most interesting finding to fall out of the data was that females spent a lot more time than males looking at a website’s “hero” shot, especially if it was a picture that had faces in it. Males quickly scanned the picture, but then immediately moved their eyes up to the navigation menu and started scanning the options there. Females lingered on the graphic and then moved on to scan text immediately adjacent to it.

Now, I could have stopped at “who” and “what,” which in itself would have been a pretty interesting finding. But I wanted to know “why.” And that’s where things started to get messy.

To start to understand why, you have to rely on feelings and intuition. You also have to accept that you probably won’t arrive at a definitive answer. “Why” lives in the realm of “wicked” problems, which I defined in a previous column as “questions that can’t be answered by yes or no — the answer always seems to be maybe.  There is no linear path to solve them. You just keep going in loops, hopefully getting closer to an answer but never quite arriving at one. Usually, the optimal solution to a wicked problem is ‘good enough – for now.’”

The answer to why males scan a website differently than females is buried in a maze of evolutionary biology, social norms and cognitive heuristics. It probably has something to do with wayfinding strategies and hardwired biases. It won’t just “fall out” of data because it’s not in the data to begin with.

Even half-right “why” answers often take months or even years of diligent pursuit to reveal themselves. Given that, I understand why it’s easier to just focus on the data. It will get you to “good,” and maybe that’s enough.

Unless, of course, you’re aiming to “put a ding in the universe,” as Steve Jobs said in an inspirational commencement speech at Stanford University. Then you have to shoot for great.

The Gap Between People and Platforms

I read with interest fellow Spinner Dave Morgan’s column about how software is destroying advertising agencies, but not the need for them. I do want to chime in on what’s happening in advertising, but I need a little more time to think about it.

What did catch my eye was a comment at the end by Harvard Business School professor Alvin Silk: “You can eliminate the middleman, but not his/her function.”

I think Dave and Alvin have put their collective thumbs on something that extends beyond our industry: the growing gap between people and platforms. I’ll use my current industry as an example – travel. It’s something we all do so we can all relate to it.

Platforms and software have definitely eaten this industry. In terms of travel destination planning, the 800-pound Gorilla is TripAdvisor. It’s impossible to overstate its importance to operators and business owners.  TripAdvisor almost single-handedly ushered in an era of do-it-yourself travel planning. For any destination in the world, we can now find the restaurants, accommodations, tours and attractions that are the favorites of other travellers. It allows us to both discover and filter while planning our next trip, something that was impossible 20 years ago, before TripAdvisor came along.

But for all its benefits, TripAdvisor also leaves some gaps.

The biggest gap in travel is what I’ve heard called the “Other Five.” I live in Canada’s wine country (yes, there is such a thing). Visitors to our valley – the Okanagan – generally come with 5 wineries they have planned to visit. The chances are very good that those wineries were selected with the help of TripAdvisor. But while they’re visiting, they also visit the “other five” – 5 wineries they discovered once they got to the destination. These discoveries depend on more traditional means – either word of mouth or sheer serendipity. And it’s often one of these “other five” that provide the truly memorable and authentic experiences.

That’s the problem with platforms like TripAdvisor, which are based on general popularity and algorithms. Technically, platforms should help you discover the long tail, but they don’t. Everything automatically defaults to the head of the curve. It’s the Matthew Effect applied to travel – advantage accumulates to those already blessed. We all want to see the same things – up to a point.

But then we want to explore the “other five” and that’s where we find the gap between platforms and people. We have been trained by Google not to look beyond the first page of online results. It’s actually worse than that. We don’t typically scan beyond the top five. But – by the very nature of ratings-based algorithms – that is always where you’ll find the “other five.” They languish in the middle of the results, sometimes taking years to bump up even a few spots. It’s why there’s still a market – and a rapidly expanding one at that – for a tour guided by an actual human. Humans can think beyond an algorithm, asking questions about what you like and pulling from their own experience to make very targeted and empathetic suggestions.

The problem with platforms is their preoccupation with scale. They feel they have to be all things to all people. I’ll call it Unicornitis – the obsession with gaining a massive valuation. They approach every potential market focused on how many users they can capture. By doing so, they have to target the lowest common denominator. The web thrives on scale and popularity; the rich get richer and the poor get poorer. Yes, there are niche players out there, but they’re very hard to find. They are the “other five” of the Internet, sitting on the third page of Google results.

This has almost nothing to do with advertising, but I think it’s the same phenomenon at work. As we rely more on software, we gain a false confidence that it replaces human-powered expertise. It doesn’t. And a lot of things can slip through the gap that’s created.

 

The Pillorying of Zuckerberg

Author’s Note: When I started this column I thought I agreed with the views stated. And I still do, mostly. But by the time I finished it, there was doubt niggling at me. It’s hard when you’re an opinion columnist who’s not sure you agree with your own opinion. So here’s what I decided to do. I’m running this column as I wrote it. Then, next week, I’m going to write a second column rebutting some of it.

Let’s face it. We love it when smart asses get theirs. For example: Sir Martin Sorrell. Sorry your lordship but I always thought you were a pontificating and pretentious dickhead and I’m kind of routing for the team digging up dirt on you. Let’s see if you doth protest too much.

Or Jeff Bezos. Okay, granted Trump doesn’t know what the hell he’s talking about regarding Amazon. And we apparently love the company. But just how much sympathy do we really have for the world’s richest man? Couldn’t he stand to be taken down a few pegs?

Don’t get me started on Bill Gates.

But the capo di tutti capi of smart-asses is Mark Zuckerberg. As mad as we are about the gushing security leak that has sprung on his watch, aren’t we all a little bit schaudenfreude-ish as we watch the public flailing that is currently playing out? It’s immensely satisfying to point a finger of blame and it’s doubly so to point it at Mr. Zuckerberg.

Which finger you use I’ll leave to your discretion.

But here’s the thing. As satisfying as it is to make Mark our scapegoat, this problem is systemic. It’s not the domain of one man, or even one company. I’m not absolving Facebook and it’s founder from blame. I’m just spreading it around so it’s a little more representatively distributed. And as much as we may hate to admit it, some of that blame ends up on our plate. We enabled the system that made this happen. We made personal data the new currency of exchange. And now we’re pissed off because there were exchanges made without our knowledge. It all comes down to this basic question: Who owns our data?

This is the fundamental question that has to be resolved. Up to now, we’ve been more than happy to surrender our data in return for the online functionality we need to pursue trivial goals. We rush to play Candy Crush and damn the consequences. We have mindlessly put our data in the hands of Facebook without any clear boundaries around what was and wasn’t acceptable for us.

If we look at data as a new market currency, our relationship with Facebook is really no different than that of a bank when we deposit our money in a bank account and allowing the bank to use our money for their own purposes in return for paying us interest. This is how markets work. They are complicated and interlinked and the furthest thing possible from being proportionately equitable.

Personal Data is a big industry. And like any industry, there is a value chain emerging. We are on the bottom of that chain. We supply the raw data. It is no coincidence that terms like “mining,” “scraping” and “stripping” are used when we talk about harvesting data. The digital trails of our behaviors and private thoughts are a raw resource that has become incredibly valuable. And Facebook just happens to be strategically placed in the market to reap the greatest rewards. They add value by aggregating and structuring the data. Advertisers then buy prepackaged blocks of this data to target their messaging. The targeting that Facebook can provide – thanks to the access they have to our data – is superior to what was available before. This is a simple supply and demand equation. Facebook was connecting the supply – coming from our willingness to surrender our personal data – with the demand – advertisers insisting on more intrusive and personal targeting criteria. It was a market opportunity that emerged and Facebook jumped on it. The phrase “don’t hate the player, hate the game” comes to mind.

When new and untested markets emerge, all goes well until it doesn’t. Then all hell breaks loose. Just like it did with Cambridge Analytica. When that happens, our sense of fairness kicks in. We feel duped. We rush to point fingers. We become judgmental, but everything is done in hindsight. This is all reaction. We have to be reactive, because emerging markets are unpredictable. You can’t predict something like Cambridge Analytica. If it wasn’t them – if it wasn’t this – it would have been something else that would have been equally unpredictable. The emerging market of data exchange virtually guaranteed that hell would eventually break loose. As a recent post on Gizmodo points out,

“the kind of data acquisition at the heart of the Cambridge Analytica scandal is more or less standard practice for every other technology company, including places like Google and even Apple. Facebook simply had the misfortune of getting caught after playing fast and loose with who has control over their data.”

To truly move forward from this, we all have to ask ourselves some hard questions. This is not restricted to Mark Zuckerberg and Facebook. It’s symptomatic of a much bigger issue. And we, the ground level source of this data, will be doing ourselves a disservice in the long run by trying to isolate the blame to any one individual or company. In a very real sense, this is our problem. We are part of a market dynamic that is untested and – as we’ve seen – powerful enough to subvert democracy. Some very big changes are required in the way we treat our own data. We owe it to ourselves to be part of that process.

Why Do Cities Work?

It always amazes me how cities just seem to work. Take New York – for example. How the hell does everything a city of nine million needs to continue to exist happen? Cities are perhaps the best example I can think of how complex adaptive systems can work in the real world. They may be the answer to our future as the world becomes a more complex and connected place.

It’s not due to any centralized sense of communal collaboration. If anything, cities make us more individualistic. Small towns are much more collaborative. I feel more anonymous and autonomous in a big city than I ever do in a small town. It’s something else, more akin to Adam Smith’s Invisible Hand – but different. Millions of individual agents can all do their own thing based on their own requirements, but it works out okay for all involved.

Actually, according to Harvard economist Ed Glaeser, cities are more than just okay. He calls them mankind’s greatest invention. “So much of what humankind has achieved over the past three millennia has come out of the remarkable collaborative creations that come out of cities. We are a social species. We come out of the womb with the ability to sop up information from people around us. It’s almost our defining characteristic as creatures. And cities play to that strength. Cities enable us to learn from other people.”

Somehow, cities manage to harness the collective potential of their population without dipping into chaos. This is all the more amazing when you consider that cities aren’t natural for humans – at least – not in evolutionary terms. If you considered just that, we should all live in clusters of 150 people – otherwise known as Dunbar’s number. That’s the brain’s cognitive limit for keeping track of our own immediate social networks. It we’re looking for a magic number in terms of maximizing human cooperation and collaboration that would be it. But somehow cities allow us to far surpass that number and still deliver exponential returns.

Most of our natural defense mechanisms are based on familiarity. Trust, in it’s most basic sense, is Pavlovian. We trust strangers who happen to resemble people we know and trust. We are wary of strangers that remind us of people who have taken advantage of us. We are primed to trust or distrust in a few milliseconds, far under the time threshold of rational thought. Humans evolved to live in communities where we keep seeing the same faces over and over – yet cities are the antithesis of this.

Cities work because it’s in everyone’s best interest to make cities work. In a city, people may not trust each other, but they do trust the system. And it’s that system – or rather – thousands of complementary systems, that makes cities work. We contribute to these systems because we have a stake in them. The majority of us avoid the Tragedy of the Commons because we understand that if we screw the system, the system becomes unsustainable and we all lose. There is an “invisible network of trust” that makes cities work.

The psychology of this trust is interesting. As I mentioned before, in evolutionary terms, the mechanisms that trigger trust are fairly rudimentary: Familiarity = Trust. But system trust is a different beast. It relies on social norms and morals – on our inherent need to conform to the will of the herd. In this case, there is at least one degree of separation between trust and the instincts that govern our behaviors. Think of it as a type of “meta-trust.” We are morally obligated to contribute to the system as long as we believe the system will increase our own personal well-being.

This moral obligation requires feedback. There needs to be some type of loop that shows our that our moral behaviors are paying off for us. As long as that loop is working, it creates a virtuous cycle. Moral behaviors need to lead to easily recognized rewards, both individually and collectively. As long as we have this loop, we will continue to be governed by social norms that maintain the systems of a city.

When we look to cities to provide us clues on how to maintain stability in a more connected world, we need to understand this concept of feedback. Cities provide feedback through physical proximity. When cities start to break down, the results become obvious to all who live there. But when it’s digital bonds rather than physical ones that link our networks, feedback becomes trickier. We need to ponder other ways of connecting cause, effect and consequences. As we move from physical communities to ideological ones, we have to overcome the numbing effects of distance.

 

Tempest in a Tweet-Pot

On February 16, a Facebook VP of Ads named Rob Goldman had a bad day. That was the day the office of Special Counsel, Robert Mueller, released an indictment of 13 Russian operatives who interfered in the U.S. election. Goldman felt he had to comment via a series of tweets that appeared to question the seriousness with which the Mueller investigation had considered the ads placed by Russians on Facebook. Nothing much happened for the rest of the day. But on February 17, after the US Tweeter-in-Chief – Donald Trump – picked up the thread, Facebook realized the tweets had turned into a “shit sandwich” and to limit the damage, Goldman had to officially apologize.

It’s just one more example of a personal tweet blowing into a major news event. This is happening with increasingly irritating frequency. So today, I thought I’d explore why.

Personal Brand vs Corporate Brand

First, why did Rob Goldman feel he had to go public with his views anyway? He did because he could. We all have varying degrees of loyalty to our employer and I’m sure the same is true for Mr. Goldman. Otherwise he wouldn’t have swallowed crow a few days later with his public mea culpa. But our true loyalties go not to the brand we work for, but the brand we are. Goldman – like me, like you, like all of us – is building his personal brand. Anyone who’s says they’re not – yet posts anything online – is in denial. Goldman’s brand, according to his twitter account, is “Student, seeker, raconteur, burner. ENFP.” That is followed with the disclaimer “Views are mine.” And you know what? This whole debacle has been great for Goldman’s brand, at least in terms of audience size. Before February 16th, he had about 1500 followers. When I checked, that had swelled to almost 12,000. Brand Goldman is on a roll!

The idea of a personal brand is new – just a few decades old. It really became amplified through the use of social media. Suddenly, you could have an audience -and not just any audience, but an audience numbering in the millions.

Before that, the only people who could have been said to have personal brands were artists, authors and musicians. They made their living by sharing who they were with us.

For the rest of us, our brands were trapped in our own contexts. Only the people who knew us were exposed to our brands. But the amplification of social media suddenly exposes our brand to a much broader audience. And when things go viral, like they did on February 17, millions suddenly became aware of Rob Goldman and his tweet without knowing anything more than that he was a VP of Ads for Facebook.

It was that connection that created the second issue for Goldman. When we speak for our own personal brands, we can say, “views are mine” but the problem always comes when things blow up, as they did for Rob Goldman. None of his tweets were passed by anyone at Facebook, yet he had suddenly become a spokesperson for the corporation. And for those eager to accept his tweets as fact, they suddenly became the “truth.”

Twitter: “Truth” Without Context

Increasingly, we’re not really that interested in the truth. What we are interested in is our beliefs and our own personal truth. This is the era of “Post Truth” – the Oxford Dictionary word of the year for 2016 – defined as “relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief’.

Truth was a commonly understood base that could be supported by facts. Now, truth is in the eye of the beholder. Common understandings are increasingly difficult to come to as the world continues to fragment and become more complex. How can we possibly come to a common understanding of what is “true” when any issue worth discussing is complex? This is certainly true of the Mueller investigation. To try to distill the scope of it to 900 words – about the length of this column – would be virtually impossible. To reduce it to 280 characters – the limits of a tweet and one- twentieth the length of this column – well, there we should not tread. But, of course, we do.

This problem is exacerbated by the medium itself. Twitter is a channel that encourages “quipiness.” When we’re tweeting, we all want to be Oscar Wilde. Again, writing this column usually takes me 3 to 4 hours, including time to do some research, create a rough outline and then do the actual writing. That’s not an especially long time, but the process does allow some time for mental reflection and self-editing. The average tweet takes less than a minute to write – probably less to think about – and then it’s out there, a matter of record, irretrievable. You should find it more than a little terrifying that this is a chosen medium for the President of the United States and one that is increasingly forming our world-view.

Twitter is also not a medium that provides much support for irony, sarcasm or satire. In the Post-Truth era, we usually accept tweets as facts, especially when they come from someone who is a somewhat official position, as in the case of Rob Goldman. But at best, they’re abbreviated opinions.

In the light of all this, one has to appreciate Mr. Goldman’s Twitter handle: @robjective.

The Decentralization of Trust

Forget Bitcoin. It’s a symptom. Forget even Blockchain. It’s big – but it’s technology. That makes it a tool. Which means it’s used at our will. And that will is the real story. Our will is always the real story – why do we build the tools we do? What is revolutionary is that we’ve finally found a way to decentralize trust. That runs against the very nature of how we’ve defined trust for centuries.

And that’s the big deal.

Trust began by being very intimate – ruled by our instincts in a face-to-face context. But for the last thousand years, our history has been all about concentration and the mass of everything – including whom we trust. We have consolidated our defense, our government, our commerce and our culture. In doing so, we have also consolidated our trust in a few all-powerful institutions.

But the past 20 years have been all about decentralization and tearing down power structures, as we invent new technologies to let us do that. In that vien, Blockchain is a doozy. It will change everything. But it’s only a big deal because we’re exerting our will to make it a big deal. And the “why” behind that is what I’m focusing on.

For right or wrong, we have now decided we’d rather trust distribution than centralization. There is much evidence to support that view. Concentration of power also means concentration of risk. The opportunity for corruption skyrockets. Big things tend to rot from the inside out. This is not a new discovery on our part. We’ve known for at least a few centuries that “absolute power corrupts absolutely.”

As the world consolidated it also became more corrupt. But it was always a trade off we felt we had to make. Again, the collective will of the people is the story thread to follow here. Consolidation brought many benefits. We wouldn’t be where we are today if it wasn’t for hierarchies, in one form or another. So we willing subjugated ourselves to someone – somewhere – hoping to maintain a delicate balance where the risk of corruption was outweighed by a personal gain. I remember asking the Atlantic’s noted correspondent, James Fallows, a question when I met him once in China. I asked how the average Chinese citizen could tolerate the paradoxical mix of rampant economical entrepreneurialism and crushing ideological totalitarianism. His answer was, “As long as their lives are better today than they were yesterday, and promise to be even better tomorrow, they’ll tolerate it.”

That pretty much summarizes our attitudes towards control. We tolerated it because if we wanted our lives to continue to improve, we really didn’t have a choice. But perhaps we do now. And that possibility has pushed our collective will away from consolidated power hubs and towards decentralized networks. Blockchain gives us another way to do that. It promises a way to work around Big Money, Big Banks, Big Government and Big Business. We are eager to do so. Why? Because up to now we have had to place our trust in these centralized institutions and that trust has been consistently abused. But perhaps Blockchain technology has found a way to distribute trust in a foolproof way. It appears to offer a way to make everything better without the historic tradeoff of subjugating ourselves to anyone.

However, when we move our trust to a network we also make that trust subject to unanticipated network effects. That may be the new trade-off we have to make. Increasingly, our technology is dependent on networks, which – by their nature – are complex adaptive systems. That’s why I keep preaching the same message – we have to understand complexity. We must accept that complexity has interaction affects we could never successfully predict.

It’s an interesting swap to consider – control for complexity. Control has always offered us the faint comfort of an illusion of predictability. We hoped that someone who knew more than we did was manning the controls. This is new territory for us. Will it be better? Who can say? But we seem to building an irreversible head of steam in that direction.