Quit fracking our lives to extract data that’s none of your business and that your machines misinterpret. — New Clues, #58
That’s the blunt advice David Weinberger and I give to marketers who still make it hard to talk, sixteen years after many of them started failing to get what we meant by Markets are Conversations.
For a look at modern marketing at its wurst (pun intended),check out The Big Datastillery, by IBM and Aberdeen.
In this Linux Journal column I explain what the machine is and does:
Copy at the top describes it as “Best-in-Class Strategies to Accelerate the Return on Digital Data” and “a revolutionary new appliance to condense terabyte scale torrents of customer, transactional, campaign, clickstream and social media data down to meaningful and actionable insights that boost response rates, conversions and customer value”.
Below that is a maze of pipes pouring stuff into a hopper of “Best-in-Class companies” that are “2.8 times more likely than Laggards to incorporate unstructured data into analytical models”. The pipes are called:
- Customer Sentiment
- E-mail Metrics
- CRM
- Clickstream Data
- PPC (Pay Per Click)
- SEO Data
- Social Media
- Marketing History
- Ad Impressions
- Transactional Data
Coming out of the hopper are boxes and tanks, connected to more piping. These are accompanied by blocks of text explaining what’s going on in that part of the “datastillery”. One says “Ability to generate customer behavioral profile based on real-time analytics”. Another says “Ability to optimize marketing offers/Web experience based on buyer’s social profile”. Another says BIC (Best in Class) outfits “merge customer data from CRM with inline behavioral data to optimize digital experience”.
Customers are represented (I’m not kidding) as empty beakers moving down a conveyor belt at the bottom of this whole thing. Into the beakers pipes called “customer interaction optimization” and “marketing optimization” excrete orange and green flows of ones and zeroes. Gas farted upward by customers metabolizing goop fed by the first two pipes is collected by a third pipe called “campaign metrics” and carried to the top of the datastillery, where in liquid form it gets poured back into the hopper. Text over a departing beaker says “137% higher average marketing response rate for Best-in-Class (6.2%) vs. All Others (2.6%)”. (The 137% is expressed in type many times larger than the actual response rates.) The reciprocal numbers for those rates are 93.8% and 97.4%—meaning that nearly all the beakers are not responsive, even to Best-in-Class marketing.
New Clues again:
I also visited this in The Intention Economy. Here’s an early draft of a subchapter that was whittled down to something much tighter for the final version. I want to share it because a great Michael Ventura quote was lost in the whittling and is especially important for a point I’ll make shortly:
In The Filter Bubble: What the Internet is Hiding from You, Eli Pariser writes,
“You have one identity,” Facebook founder Mark Zuckerber told journalist David Kirkpatrick for his book The Facebook Effect. “the days of having a different image for your work friends or coworkers and for the other people you may know are probably coing to an end pretty quickly… Having two identities for yourself is an example of a lack of integrity.”
Later Zuckerberg discounted the remark as “just a sentence I said;” but to Facebook the only you that matters is the one they know. Not the one you are.
In Shadow Dancing in the USA (1985), Michael Ventura writes what he calls “a poetic description of subselves in a stepfamily.” He begins by asking, “… will we, or will we not, discover all that a man and a woman can be?” Here’s how he unpacks the challenge:
… living in this small apartment, there are, to begin with, three entirely different sets of twos: Michael and Jan, Jan and Brendan, Brendan and Michael. Each set, by itself, is very different from the other, and each is different from Jan-Brendan-Michael together. But go further:
Brendan-Jan-Michael having just gotten up ‘for breakfast is a very different body politic, with different varying tensions, depending on whether it’s a school day or not, from Brendan-Jan-Michael driving home from seeing, say, El Norte, which is different still from driving home from Ghostbusters, and all of them are different from Brendan-Jan-Michael going to examine a possible school for Brendan. The Brendan who gets up at midnight needing to talk to Michael is quite different from the Brendan who, on another night, needs suddenly to talk to Jan, and both are vastly different from the Brendan who often keeps his own counsel. The Michael writing at three in the afternoon or three in the morning, isolated in a room with three desks and two typewriters, is very different from the Michael, exasperated, figuring the bills with Jan, choosing whom not to pay; and he in turn is very different from the half-crazed, shy drunk wondering just who is this “raw-boned Okie girl” moving to Sam Taylor’s fast blues one sweltering night in the Venice of L.A. at the old Taurus Tavern. The Jan making the decision to face her own need to write, so determined and so tentative at once, is very different from the strength-in-tenderness of the Jan who is sensual, or the sure-footed abandon of Jan dancing, or the screeching of the Jan who’s had it up to here.
I can only be reasonably sure of several of these people – the several isolate Michaels, eight or fifteen of them, whom “I” pass from, day to day, night to night, dawn to almost dawn, and who at any moment in this much-too-small apartment might encounter a Jan or a Brendan whom I’ve never seen before, or whom I’ve conjectured about and can sometimes describe but am hard-pressed to know.
So in this apartment where some might see three people living a comparatively quiet life, I see a huge encampment on a firelit hillside, a tribal encampment of selves who must always be unknowable, a mystery to any brief Michael, Jan, or Brendan who happens to be trying to figure it out at any particular moment.
His narrative continues until he arrives at his main purpose behind all this:
…there may be no more important project of our time than displacing the … fiction of monopersonality. This fiction is the notion that each person has a central and unified “I” which determines his or her acts. “I” have been writing this to say that I don’t think people experience life that way. I do think they experience language that way, and hence are doomed to speak about life in structures contrary to their experience.
But what happens now, almost thirty years later, when our experience is one of Facebook chatter and Google searches, when online life and language (“poking,” “friending” and so on) soak up time formerly spent around tables, in bars or in cars, and our environment is “personalized” through guesswork by companies whose robotic filtering systems constantly customize everything to satisfy a supposedly singular you?
In the closing sentences of The Shallows: What the Internet is Doing to our Brains, Nicholas Carr writes,
In the world of 2001, people have become so machinelike that the most human character turns out to be a machine. That’s the essence of Kubrick’s dark prophecy: as we come to rely on computers to mediate our understanding of the world, it is our own intelligence that flattens into artificial intelligence.[iii]
Even if our own intelligence is not yet artificialized, what’s feeding it surely is.
Eli sums up the absurdity of all this in a subchapter titled “A Bad Theory of You.” After explaining Google’s and Facebook’s very different approaches to personalized “experience” filtration, and the assumptions behind both, he concludes, “Both are pretty poor representations of who we are, in part because there is no one set of data that describes who we are.” He says both companies have dumped us into what animators and robotics engineers call the uncanny valley: “the place where something is lifelike but not convincingly alive, and it gives people the creeps.”
I don’t know about you (nor should I, being a mere writer and not a Google or a Facebook), but I find hope in that. How long can shit this crazy last?
How long it lasts matters less than what makes it crazy.
There are three assumptions by frackers that are certifiably nuts, because they are disconnected from reality: the marketplace, which is filled with the human beings called customers. You know: us. Those assumptions are—
1) We are always in the market to buy something. We are not. (Are you shopping right now? And are you open to being distracted this very instant by an ad that thinks you are? — one placed by a machine guided by big data guesswork based on knowledge gained by following you around? Didn’t think so.)
2) We don’t mind being fracked. In fact we do, because it violates our privacy. That’s why one stain on the Web looks like this:
Source: TRUSTe 2014 US. Consumer Confidence Survey.
3) Machines can know people well — sometimes better than they know themselves. They can’t, especially when the machines are interested only in selling something.
In fact humans are terribly complex. And they are also not, as Michael Ventura says, monopersonalities. Kim Cameron, a distinguished engineer at Microsoft and its chief authority on digital identity, is only half-joking when he calls himself “the committee of the whole.”
Sanity requires that we line up many different personalities behind a single first person pronoun: I, me, mine. Also behind multiple identifiers. In my own case, I am Doc to most of those who know me, David to various government agencies (and most of the entities that bill me for stuff), Dave to many (but not all) family members, @dsearls to Twitter, and no name at all to the rest of the world, wherein I remain, like most of us, anonymous (literally, nameless), because that too is a civic grace. (And if you doubt that, ask any person who has lost their anonymity through the Faustian bargain called celebrity.)
So, where do we go with from here?
First we need to continue expanding individual agency through VRM and similar efforts. Here’s a list of developers.
Second, marketing needs to stop excusing the harms caused by personalization of advertising by frack-fed Big Data methods. For guidance from history, read Tim Walsh‘s Big Data: the New Big Tobacco.
Third, advertising needs to return to what it does best: straightforward brand messaging that is targeted at populations, and doesn’t get personal. For help with that, start reading Don Marti and don’t stop until his points sink in. Begin here and continue here.
