Toward a lexicon for advertising in both directions

We need a lexicon for the different ways buyers and sellers express their intentions to each other. Or, one might say, advertise.

On the demand side (⊂) we have what in ProjectVRM we’ve called intentcasting and (earlier) personal RFP. Scott Adams calls it broadcast shopping and John Hagel and David Siegel both (in books by that title) call it pull.

On the sell side (⊃) I can list at least six kinds of advertising alone that desperately need distinctive labels. To pull them apart, these are:

1. Brand advertising. This kind is aimed at populations. All of it is contextual, meaning placed in media, TV or radio programs, or publications, that appeal broadly or narrowly to a categorized audience. None of it is tracking-based, and none of it is personal. Little of it wants a direct response. It simply means to impress. This is also the form of advertising that burned every brand you can name into your brain. In fact the word brand itself was borrowed from the cattle industry by Procter & Gamble in the 1930s, when it also funded the golden age of radio. Today it is also what sponsors all of sports broadcasting and pays most sports stars their massive salaries.
2. Search advertising. This is what shows up with search results. There are two very different kinds here:
   1. Context-based. Not based on tracking. This is what DuckDuckGo does.
   2. Context+tracking based. This is what Google and Bing do.
3. Tracking-based advertising. I’ve called this adtech. Cory Doctorow calls it ad-tech. Others call it ad tech. Some euphemize it as behavioral, relevant, interest-based, or personalized. Shoshana Zuboff says all of them are based on surveillance, which they are. So many critics speak of it as surveillance-based advertising.
4. Advertising that’s both contextual and personal—but only in the sense that a highly characterized individual falls within a group, or a collection of overlapping groups, chosen by the advertiser. These are Facebook’s Core, Custom and Look-Alike audiences. Talk to Facebook and they’ll tell you these ads are not meant to be personal, though you should not be surprised to see ads for shoes when you have made clear to Facebook’s trackers (on the site, the apps, and wherever the company’s tentacles reach) that you might be in the market for shoes. Still, since Facebook characterizes every face in its audience in almost countless ways, it’s easy to call this form of advertising tracking-based.
5. Interactive advertising. Vaguely defined by Wikipedia here,  and sometimes called conversational advertising,  the purpose is to get an interactive response from people. The expression is not much used today, even though the Interactive Advertising Bureau (IAB) is the leading trade association in the tracking-based advertising field and its primary proponent.
6. Native advertising, also called sponsored content, is advertising made to look like ordinary editorial material.

The list is actually much longer. But the distinction that matters is between advertising that is tracking-based and the advertising that is not. As I put it in Brands need to fire adtech,

Let’s be clear about all the differences between adtech and real advertising. It’s adtech that spies on people and violates their privacy. It’s adtech that’s full of fraud and a vector for malware. It’s adtech that incentivizes publications to prioritize “content generation” over journalism. It’s adtech that gives fake news a business model, because fake news is easier to produce than the real kind, and adtech will pay anybody a bounty for hauling in eyeballs.

Real advertising doesn’t do any of those things, because it’s not personal. It is aimed at populations selected by the media they choose to watch, listen to or read. To reach those people with real ads, you buy space or time on those media. You sponsor those media because those media also have brand value.

With real advertising, you have brands supporting brands.

Brands can’t sponsor media through adtech because adtech isn’t built for that. On the contrary, adtech is built to undermine the brand value of all the media it uses, because it cares about eyeballs more than media.

Adtech is magic in this literal sense: it’s all about misdirection. You think you’re getting one thing while you’re really getting another. It’s why brands think they’re placing ads in media, while the systems they hire chase eyeballs. Since adtech systems are automated and biased toward finding the cheapest ways to hit sought-after eyeballs with ads, some ads show up on unsavory sites. And, let’s face it, even good eyeballs go to bad places.

This is why the media, the UK government, the brands, and even Google are all shocked. They all think adtech is advertising. Which makes sense: it looks like advertising and gets called advertising. But it is profoundly different in almost every other respect. I explain those differences in Separating Advertising’s Wheat and Chaff:

…advertising today is also digital. That fact makes advertising much more data-driven, tracking-based and personal. Nearly all the buzz and science in advertising today flies around the data-driven, tracking-based stuff generally called adtech. This form of digital advertising has turned into a massive industry, driven by an assumption that the best advertising is also the most targeted, the most real-time, the most data-driven, the most personal — and that old-fashioned brand advertising is hopelessly retro.

In terms of actual value to the marketplace, however, the old-fashioned stuff is wheat and the new-fashioned stuff is chaff. In fact, the chaff was only grafted on recently.

See, adtech did not spring from the loins of Madison Avenue. Instead its direct ancestor is what’s called direct response marketing. Before that, it was called direct mail, or junk mail. In metrics, methods and manners, it is little different from its closest relative, spam.

Direct response marketing has always wanted to get personal, has always been data-driven, has never attracted the creative talent for which Madison Avenue has been rightly famous. Look up best ads of all time and you’ll find nothing but wheat. No direct response or adtech postings, mailings or ad placements on phones or websites.

Yes, brand advertising has always been data-driven too, but the data that mattered was how many people were exposed to an ad, not how many clicked on one — or whether you, personally, did anything.

And yes, a lot of brand advertising is annoying. But at least we know it pays for the TV programs we watch and the publications we read. Wheat-producing advertisers are called “sponsors” for a reason.

So how did direct response marketing get to be called advertising ? By looking the same. Online it’s hard to tell the difference between a wheat ad and a chaff one.

Remember the movie “Invasion of the Body Snatchers?” (Or the remake by the same name?) Same thing here. Madison Avenue fell asleep, direct response marketing ate its brain, and it woke up as an alien replica of itself.

This whole problem wouldn’t exist if the alien replica wasn’t chasing spied-on eyeballs, and if advertisers still sponsored desirable media the old-fashioned way.

Bonus link.

I wrote that in 2017. The GDPR became enforceable in 2018 and the CCPA in 2020.  Today more laws and regulations are being instituted to fight tracking-based advertising, yet the whole advertising industry remains drunk on digital, deeply corrupt and delusional, and growing like a Stage IV cancer.

We live digital lives now, and most of the advertising we see and hear is on or through glowing digital rectangles. Most of those are personal as well. So, naturally, most advertising on those media is personal—or wishes it was. Regulations that require “consent” for the tracking that personalization requires do not make the practice less hostile to personal privacy. They just make the whole mess easier to rationalize.

So I’m trying to do two things here.

One is to make clearer the distinctions between real advertising and direct marketing.

The other is to suggest that better signaling from demand to supply, starting with intentcasting, may serve as chemo for the cancer that adtech has become. It will do that by simply making clear to sellers what buyers actually want and don’t want.

 

 

The Rise of Robot Retail

From Here Comes the Full Amazonification of Whole Foods, by Cecelia Kang (@CeceliaKang) in The New York Times:

…In less than a minute, I scanned both hands on a kiosk and linked them to my Amazon account. Then I hovered my right palm over the turnstile reader to enter the nation’s most technologically sophisticated grocery store…

Amazon designed my local grocer to be almost completely run by tracking and robotic tools for the first time.

The technology, known as Just Walk Out, consists of hundreds of cameras with a god’s-eye view of customers. Sensors are placed under each apple, carton of oatmeal and boule of multigrain bread. Behind the scenes, deep-learning software analyzes the shopping activity to detect patterns and increase the accuracy of its charges.

The technology is comparable to what’s in driverless cars. It identifies when we lift a product from a shelf, freezer or produce bin; automatically itemizes the goods; and charges us when we leave the store. Anyone with an Amazon account, not just Prime members, can shop this way and skip a cash register since the bill shows up in our Amazon account.

And this is just Amazon. Soon it will be every major vendor of everything, most likely with Amazon as the alpha sphincter among all the chokepoints controlled by robotic intermediaries between first sources and final customers—with all of them customizing your choices, your prices, and whatever else it takes to engineer demand in the marketplace—algorithmically, robotically, and most of all, personally.

Some of us will like it, because it’ll be smooth, easy and relatively cheap. It will also subordinate us utterly to machines. Or perhaps udderly, because we will be calves raised to suckle on the teats of retail’s robot cows.

This system can’t be fixed from within. Nor can it be fixed by regulation, though some of that might help. It can only be obsolesced by customers who bring more to the market’s table than cash, credit, appetites and acquiescence to systematic training.

What more?

Start with information. What do we actually want (including, crucially, to not be bothered by hype or manipulated by surveillance systems)?

Add intelligence. What do we know about products, markets, needs, and how things actually work than roboticized systems can begin to guess at?

Then add values, such as freedom, choice, agency, care for others, and the ability to collectivize in constructive and helpful ways on our own.

Then add tech. But this has to be our tech: customertech that we bring to market as independent, sovereign and capable human beings. Not just as “users” of others’ systems, or consumers (which Jerry Michalski calls “gullets with wallets and eyeballs”) of whatever producers want to feed us.

Time for solutions. Here is a list of fourteen market problems that can only be solved from the customers’ side.

And yes, we do need help from the sellers’ side. But not with promises to make their systems more “customer centric.” (We’ve been flagging that as a fail since 2008.) We need CRM that welcomes VRM. B2C that welcomes Me2B.

And money. Our startups and nonprofits have done an amazing job of keeping the VRM and Me2B embers burning. But they could do a lot more with some gas on those things.

ProjectVRM at 15

This project started in September 2006, when I became a fellow at what is now the Berkman Klein Center. Our ambitions were not small.:

1. To encourage development of tools by which individuals can take control of their relationships with organizations — especially in commercial marketplaces.
2. To encourage and conduct research on VRM-related theories, usage of VRM tools, and effects as adoption of VRM tools takes place.

The photo above is of our first workshop, at Harvard Law School, in 2008. Here is another photo with a collection of topics discussed in breakout sessions:

Zoom in on any of the topics there (more are visible on the next photo in the album), and you will find many of them still on the table, thirteen years later. Had some prophet told us then that this would still be the case, we might have been discouraged. But progress has been made on all those fronts, and the main learning in the meantime is that every highly ambitious grassroots movement takes time to bear fruit.

One example is what we discussed in the “my red dot” breakout at the May 2007 Internet Identity Workshop (the 3rd of what next week will be our 33rd ) is now finally being done with the Byway, which is about to get prototyped by our nonprofit spin-off, Customer Commons, with help from the Ostrom Workshop at Indiana University Bloomington, where Joyce and I are currently embedded as visiting scholars.

Our mailing list numbers 567 members, and is active, though it won’t hog your email flow. Check out the action at that link. And, if you like, join in.

You can also join in at our next gathering, VRM Day 2021b, which happens this coming Monday, 11 October.  We’ll visit our learnings thus far, and present progress and plans on many fronts, including

And we thank the BKC for its patience and faith in our project and its work.

Solving Subscriptions

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Count the number of companies you pay regularly for anything. Add up what you pay for all of them. Then think about the time you spend trying and failing to “manage” any of it—especially when most or all of the management tools are separately held by every outfit’s subscription system, all for their convenience rather than yours. And then think about how in most cases you also need to swim upstream against a tide of promotional BS and manipulation.

There is an industry on the corporate side of this, and won’t fix itself. That would be like asking AOL, Compuserve and Prodigy to fix the online service business in 1994.

There’s also not much help coming from the subscription management services we have on our side: Truebill, Bobby, Money Dashboard, Mint, Subscript Me, BillTracker Pro, Trim, Subby, Card Due, Sift, SubMan, and Subscript Me.

Nor from the subscription management systems offered by  Paypal, Amazon, Apple or Google (e.g. with  Google Sheets and Google Doc templates).

All of those are too narrow, too closed, too exclusive, too easily purposed for surveillance on subscribers, and too vested in the status quo. Which royally sucks. For evidence, see here, or just look up subscription hell.

So it’s long past time to unscrew it. But how?

The better question is where?

The answer is on our side: the customer’s side.

See, subscriptions are in a class of problems that can only be solved from the customers’ side. They can’t be solved from the companies’ side because they’ll all do it differently, and always in their interests before ours.

Also, most of them will want to hold you captive, just like Compuserve, AOL and Prodigy did with online services before the Internet solved that problem by obsolescing them.

A refresher: the Internet is ours. Meaning everybody’s. It doesn’t just belong to companies.

We need a similar move here. Fortunately, by subscriptions as easy as possible to make, change and cancel—in standardized ways—companies living on subscriptions will do a better job of making their goods competitive.

Now to how.

The short answer is with open standards, code and protocols. The longer answer is to start with a punch list of requirements, based on what we, as customers, need most. So, we should—

• Be able to see all our subscriptions, what they cost, and when they start and end
• Be able to cancel or renew, manually or automatically, in the simplest possible ways
• Get the best possible prices
• Be able to keep records of subscriptions and histories
• Show our actual (rather than coerced) loyalty
• Be able to provide constructive help, as loyal and experienced customers
• Join in collectives—commons—of other customers to start normalizing the way subscriptions should be offered on the corporate side and managed on the personal side

Some tech already exists for at least some of this, but we’ll leave that topic for another post. Meanwhile, give us suggestions in the comments below. Thanks!

Bonus link: From coffee to cars: how Britain became a nation of subscribers, by Tim Lewis in The Guardian. (Via John Naughton’s excellent newsletter.)

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The modified image above is a Doctor Who TARDIS console, photographed by Chris Sampson, offered under a Creative Commons Attribution-NonCommercial-ShareAlike 2.0 Generic (CC BY-NC-SA 2.0) license, published here, and obtained via Wikimedia Commons, here. We thank Chris for making it available.

Also, the original version of this post is at Customer Commons, here.

Let’s zero-base zero-party data

Forrester Research has gifted marketing with a hot buzzphrase: zero-party data, which they define as “data that a customer intentionally and proactively shares with a brand, which can include preference center data, purchase intentions, personal context, and how the individual wants the brand to recognize her.”

Salesforce, the CRM giant (that’s now famously buying Slack), is ambitious about the topic, and how it can “fuel your personalized marketing efforts.” The second person you is Salesforce’s corporate customer.

It’s important to unpack what Salesforce says about that fuel, because Salesforce is a tech giant that fully matters. So here’s text from that last link. I’ll respond to it in chunks. (Note that zero, first and third party data is about you, no matter who it’s from.)

What is zero-party data?

Before we define zero-party data, let’s back up a little and look at some of the other types of data that drive personalized experiences.

First-party data: In the context of personalization, we’re often talking about first-party behavioral data, which encompasses an individual’s site-wide, app-wide, and on-page behaviors. This also includes the person’s clicks and in-depth behavior (such as hovering, scrolling, and active time spent), session context, and how that person engages with personalized experiences. With first-party data, you glean valuable indicators into an individual’s interests and intent. Transactional data, such as purchases and downloads, is considered first-party data, too.

Third-party data: Obtained or purchased from sites and sources that aren’t your own, third-party data used in personalization typically includes demographic information, firmographic data, buying signals (e.g., in the market for a new home or new software), and additional information from CRM, POS, and call center systems.

Zero-party data, a term coined by Forrester Research, is also referred to as explicit data.

They then go on to quote Forrester’s definition, substituting “[them]” for “her.”

The first party in that definition the site harvesting “behavioral” data about the individual. (It doesn’t square with the legal profession’s understanding of the term, so if you know that one, try not to be confused.)

It continues,

why-is-zero-party-data-important

Forrester’s Fatemeh Khatibloo, VP principal analyst, notes in a video interview with Wayin (now Cheetah Digital) that zero-party data “is gold. … When a customer trusts a brand enough to provide this really meaningful data, it means that the brand doesn’t have to go off and infer what the customer wants or what [their] intentions are.”

Sure. But what if the customer has her own way to be a precious commodity to a brand—one she can use at scale with all the brands she deals with? I’ll unpack that question shortly.

There’s the privacy factor to keep in mind too, another reason why zero-party data – in enabling and encouraging individuals to willingly provide information and validate their intent – is becoming a more important part of the personalization data mix.

Two things here.

First, again, individuals need their own ways to protect their privacy and project their intentions about it.

Second, having as many ways for brands to “enable and encourage” disclosure of private information as there are brands to provide them is hugely inefficient and annoying. But that is what Salesforce is selling here.

As industry regulations such as GDPR and the CCPA put a heightened focus on safeguarding consumer privacy, and as more browsers move to phase out third-party cookies and allow users to easily opt out of being tracked, marketers are placing a greater premium and reliance on data that their audiences knowingly and voluntarily give them.

Not if the way they “knowingly and voluntarily” agree to be tracked is by clicking “AGREE” on website home page popovers. Those only give those sites ways to adhere to the letter of the GDPR and the CCPA while also violating those laws’ spirit.

Experts also agree that zero-party data is more definitive and trustworthy than other forms of data since it’s coming straight from the source. And while that’s not to say all people self-report accurately (web forms often show a large number of visitors are accountants, by profession, which is the first field in the drop-down menu), zero-party data is still considered a very timely and reliable basis for personalization.

Self-reporting will be a lot more accurate if people have real relationships with brands, rather (again) than ones that are “enabled and encouraged” in each brand’s own separate way.

Here is a framework by which that can be done. Phil Windley provides some cool detail for operationalizing the whole thing here, here, here and here.

Even if the countless separate ways are provided by one company (e.g. Salesforce),  every brand will use those ways differently, giving each brand scale across many customers, but giving those customers no scale across many companies. If we want that kind of scale, dig into the links in the paragraph above.

With great data comes great responsibility.

You’re not getting something for nothing with zero-party data. When customers and prospects give and entrust you with their data, you need to provide value right away in return. This could take the form of: “We’d love you to take this quick survey, so we can serve you with the right products and offers.”

But don’t let the data fall into the void. If you don’t listen and respond, it can be detrimental to your cause. It’s important to honor the implied promise to follow up. As a basic example, if you ask a site visitor: “Which color do you prefer – red or blue?” and they choose red, you don’t want to then say, “Ok, here’s a blue website.” Today, two weeks from now, and until they tell or show you differently, the website’s color scheme should be red for that person.

While this example is simplistic, the concept can be applied to personalizing content, product recommendations, and other aspects of digital experiences to map to individuals’ stated preferences.

This, and what follows in that Salesforce post, is a pitch for brands to play nice and use surveys and stuff like that to coax private information out of customers. It’s nice as far as it can go, but it gives no agency to customers—you and me—beyond what we can do inside each company’s CRM silo.

So here are some questions that might be helpful:

• What if the customer shows up as somebody who already likes red and is ready to say so to trusted brands? Or, better yet, if the customer arrives with a verifiable claim that she is already a customer, or that she has good credit, or that she is ready to buy something?
• What if she has her own way of expressing loyalty, and that way is far more genuine, interesting and valuable to the brand than the company’s current loyalty system, which is full of gimmicks, forms of coercion, and operational overhead?
• What if the customer carries her own privacy policy and terms of engagement (ones that actually protect the privacy of both the customer and the brand, if the brand agrees to them)?

All those scenarios yield highly valuable zero-party data. Better yet, they yield real relationships with values far above zero.

Those questions suggest just a few of the places we can go if we zero-base customer relationships outside standing CRM systems: out in the open market where customers want to be free, independent, and able to deal with many brands with tools and services of their own, through their own CRM-friendly VRM—Vendor Relationship Management—tools.

VRM reaching out to CRM implies (and will create)  a much larger middle market space than the closed and private markets isolated inside every brand’s separate CRM system.

We’re working toward that. See here.

 

Toward real market conversations

A friend pointed me to this video of a slide presentation by Bixy, because it looked to him kinda like VRM.  I thought so too…. at first. Here’s an image from the deck:

Here is what I wrote back, updated and improved a bit:

These are my notes on slides within the deck/video.

1) It looks to me like a CRM refresh rather than VRM. There have been many of these. And, while Bixy looks better than any others I can remember (partly because I can’t remember any… it’s all a blur), it’s still pitching into the CRM market. Nothing wrong with that: it’s a huge market, with side categories all around it. It’s just not VRM, which is the customer hand CRM shakes. (And no, a CRM system giving the customer a hand to shake the CRM’s with isn’t VRM. It’s just gravy on a loyalty card.)

2) The notion that customers  (I dislike the word “consumers”) want relationships with brands is a sell-side fantasy. Mostly customers are looking to buy something they’ve already searched for, or to keep what they already own working, or to replace one thing with another that won’t fail—and to get decent service when something does fail. (For more on this subject, I suggest reading the great Bob Hoffman, for example here.)

3) While it’s true that customers don’t want to be tracked, annoyed and manipulated, and that those practices have led to dislike of businesses and icky legislation (bulls eye on all of those), and that “relationships are based on trust, value, attention, respect and communication,” none of those five things mean much to the customer if all of them are locked into a company’s one-to-many system, which is what we have with 100% of all CRM, CX and XX (pick your initialism) systems—all of them different, which means  a customer needs to have as many different ways to trust, value, attend to, respect and communicate as there are company systems for providing the means.

4) Bixy’s idea here (and what the graphic above suggests, is that the customer can express likes and dislikes to many Brands’ Salesforce CRM systems. They call this “sharing for value in return.” But there is far appetite for this than than marketing thinks.  Customers share as little as they can when they are fully required to do so, and would rather share zero when they go about their ordinary surfing online or shopping anywhere. Worse, marketing in general (follow the news)—and adtech/martech in particular—continue to believe that customers “share” data gathered about them by surveillance, and that this is “exchanged” for free services, discounts and other goodies. This is one of the worst rationalizations in the history of business.

5) “B2C conversations” that are “transparent, personalized and informative” is more a marketing fantasy than a customer desire. What customers would desire, if they were available, are tools that enhance them with superpowers.  For example, the power to change their last name, email address or credit card for every company they deal with, in one move. This is real scale: customer scale.  We call these superpowers customertech:

CRM is vendortech.

6) Some percentage of Adidas customers (the example in that video) may be willing to fill out a “conversational” form to arrive at a shoe purchase, but I suspect a far larger percentage would regard the whole exercise as a privacy-risking journey down a sales funnel that they’d rather not be in. So long as the world lacks standard ways for people to prevent surveillance of their private spaces and harvesting of personal data, to make non-coercive two-way agreements with others, and ways to monitor person data use and agreement compliance, there is no way trustworthy “conversations” of the kind Bixy proposes can happen.

7) Incumbent “loyalty” programs are, on the whole, expensive and absurd.

Take Peet’s Coffee, a brand I actually do love. I’ve been a customer of Peet’s for, let’s see… 35 years. I have a high-end (like in a coffee shop) espresso machine at my house, with a high-end grinder to match. All I want from Peet’s here at home are two kinds of Peet’s beans: Garuda and Major Dickason Decaf. That’s it. I’ve sampled countless single-origin beans and blends from many sources, and those are my faves. I used to buy one-pound bags of those at Peet’s stores; but in COVID time I subscribe to have those delivered. Which isn’t easy, because Peet’s has made buying coffee online remarkably hard. Rather than just showing me all the coffees they have, they want to drag me every time through a “conversational” discovery process—and that’s after the customary (for every company) popover pitch to sign up as a member, which I already am, and to detour through a login-fail password-recovery ditch (with CAPTCHAs, over and over, clicking on busses and traffic lights and crosswalks) that show up every. damn. time. On arrival at the membership home page, “My Dashboard” all but covers the home screen, and tells me I’m 8 points away from my next reward (always a free coffee, which is not worth the trouble, and not why I’m loyal). Under the Shop menu (the only one I might care about) there are no lists of coffee types. Instead there’s “Find Your Match,” which features two kinds of coffee I don’t want and a “take your quiz” game. Below that are “signature blends” that list nothing of ingredients but require one to “Find My Coffee” through a “flavor wheel” that gives one a choice of five flavors (“herbal/earthy,” “bright/citrus”…). I have to go waaay the hell down a well of unwanted and distracting choices to get to the damn actual coffee I know I like.

My point: here is a company that is truly loved (or hell, at least liked) by its customers, mostly because it’s better than Starbucks. They’re in a seller’s market. They don’t need a loyalty program, or the high operational and cognitive overhead involved (e.g. “checking in” at stores with a QR code on a phone app). They could make shopping online a lot simpler with a nice list of products and prices. But instead they decided, typically (for marketing), that they needed all this bullshit to suck customers down sales funnels. When they don’t. If Peet’s dumped its app and made their website and subscription system simpler, they wouldn’t lose one customer and they’d save piles of money.

Now, back to the Adidas example. I am sure anybody who plays sports or runs, or does anything in athletic shoes, would rather just freaking shop for shoes than be led by a robot through a conversational maze that more than likely will lead to a product the company is eager to sell instead of one the customer would rather buy.

7) I think most customers would be creeped to reveal how much they like to run and other stuff like that, when they have no idea how that data will be used—which is also still the typical “experience” online. Please: just show them the shoes, say what they’re made of, what they’re good for, and (if it matters) what celeb jocks like them or have co-branded them.

8) The “value exchange” that fully matters is money for goods. “Relationship” beyond that is largely a matter of reputation and appreciation, which is earned by the products and services themselves, and by human engagement. Not by marketing BS.

8) Bixy’s pitch about “90% of conversation” occurring “outside the app as digital widgets via publisher and marketer SDKs” and “omnichannel personalization” through “buy rewards, affiliate marketing, marketer insights, CRM & CDP, email, ads, loyalty, eCommerce personalization, brand & retailer apps and direct mail” is just more of the half-roboticized marketing world we have, only worse. (It also appears to require the kind of tracking the video says up front that customers don’t want.)

9) The thought of “licensing my personal information to brands for additional royalties and personalization” also creeps me out.

10) I don’t think this is “building relationships from the consumer point of view.” I think it’s a projection of marketing fantasy on a kind of customer that mostly doesn’t exist. I also don’t think “reducing the sales cycle” is any customer’s fantasy.

To sum up, I don’t mean to be harsh. In fact I’m glad to talk with Bixy if they’re interested in helping with what we’re trying to do here at ProjectVRM—or at Customer Commons, the Me2B Alliance and MyData.

I also don’t think Cluetrain‘s first thesis (“Markets are conversations“) can be proven by tools offered only by sellers and made mostly to work for sellers. If we want real market conversations, we need to look at solving market problems from the customers’ side. Look here and here for ways to do that.

The true blue ocean

“Blue ocean strategy challenges companies to break out of the red ocean of bloody competition by creating uncontested market space that makes the competition irrelevant.”

That’s what  W. Chan Kim and Renee Mauborgne say in the original preface to  Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant, published by Harvard Business Review Press in 2005.  Since then the red/blue ocean metaphor has become business canon.

The problem with that canon is that it looks at customers the way a trawler looks at fish.

To understand the problem here, it helps to hear marketing talk to itself. Customers, it says, are targets to herd on a journey into a funnel through which they are acquired, managed, controlled and locked in.

This is the language of ranching and slavery. Not a way to talk about human beings.

Worse, every business is a separate trawler, and handles customers in its hold differently, even if they’re using the same CRM, CX and other systems to do all the stuff listed two paragraphs up. (Along with other mudanities: keeping records, following leads, forecasting sales, crunching numbers, producing analytics, and other stuff customers don’t care about until they’re forced to deal with it, usually when a problem shows up.)

In fact, these systems can’t help holding customers captive. Because the way these systems are sold and deployed means there are as many different ways for customers to “relate” to those companies as there are companies.

And, as long as companies are the only parties able to (as the GDPR puts it) operate as a “data controller” or “data processor,” the (literally) damned customer remains nothing more than a “data subject” in countless separate databases and name spaces, each with separate logins and passwords.

This is why, from the customer’s perspective, the whole ocean of CRM and CX are opaque with rutilance.

Worse, all CRM and CX systems operate on the assumption that it is up to them to know everything about a customer, a prospect, or a user. And most of that knowledge these days is obtained early in the (literally) damned “journey” through exactly the kind of tracking that has caused—

1. Ad blocking, which (though it had been around since 2004) hockey-sticked in 2013, when the adtech fecosystem gave the middle finger to Do Not Track, and which by 2015 was the biggest boycott in world history
2. Regulation, most notably the GDPR and the CCPA, which never would have happened had marketing not wanted to track everyone like marked animals
3. Tracking protection, now getting built into browsers (e.g. Safari, Firefox, Brave, Edge) because the market (that big blue ocean) demands it

Stop and think for a minute how much the market actually knows—meaning how much customers actually know about what they own, use, want, wish for, regret, and the rest of it.

The simple fact is that companies’ customers and users know far more about the products and services they own and use than the companies do. Those people are also in a far better position to share that knowledge than any CRM, CX or other system for “relating” to customers can begin to guess at, much less comprehend. Especially when every company has its own separate and isolated ways of doing both.

But customers today still mostly lack ways of their own to share that knowledge, and do it selectively and safely. Those ways are in the category we call VRM (when it shakes hands with CRM), or Me2B  (when it’s dealing broadly across everything a company does with customers and users).

VRM and Me2B are what make as free as can be, outside any company’s nets, funnels and teeming holds in trawler’s hulls.

It’s also much bigger than the red ocean of CRM/CX by themselves, because it’s where customers share far more—and better—information than they can inside existing CRM/CX systems. Or will, once VRM and Me2B tools and services stand up.

For example, there’s—

• What customers actually want to buy (rather than what companies can at best only guess at)
• What customers already own, and how they’re actually using it (meaning what’s their Internet of their things)
• What companies, products and service customers are actually loyal to, and why
• How customers would  like to share their experiences
• What relevant credentials they carry, for identity and other purposes. And who their preferred agents or intermediaries might be
• What their terms, conditions and privacy policies are, and how compliance with those can be assured and audited
• What their tools are, for making all those things work, across the board, with all the companies and other organizations they engage

The list is endless, because there is no limit to what customers can say to companies (or how they relate to companies) if companies are willing to deal with customers who have as much scale across corporate systems as those systems wish to have across all of their customers.

Being “customer centric” won’t cut it. That’s just a gloss on the same old thing. If companies wish to be truly customer-driven, they need to be dealing with free-range human beings. Not captives.

So: how?

There is already code for doing much of what’s listed in the seven bullets above.  Services too. (Examples.) There could be a lot more.

There are also nonprofits working to foster development in that big blue ocean. Customer Commons is ProjectVRM’s own spin-off. The Me2B Alliance is a companion effort. So are MyData and the Sovrin Foundation. All of them could use some funding.

What matters for business is that all of them empower free-range customers and give them scale: real leverage across companies and markets, for the good of all.

That’s the real blue ocean.

Without VRM and Me2B working there, the most a company can do with its CRM or CX system is look at it.

Bonus link. Pull quote: “People must own root authority, before a system transmutes your personal life into a consumer. Before you need the system to exist, you are whole.”

 

Where VRM fits

VRM is the hand CRM shakes.

That’s the simplest way of putting it. That’s what we wanted it to be when we started ProjectVRM in 2006, and that’s how we described it in 2011, when I gave this talk at SugarCRM‘s SugarCon conference:

Those “ways” are tools that belong to each customer and give them global scale: meaning they should work the same way for every company’s CRM system. Just like the customer’s phone, email and browser shake hands with every company already.

This is, as the marketers say, positioning. And it’s important, now that a number of significant .orgs have stepped up to take care of other work we helped start with ProjectVRM. Most notable are Customer Commons (a ProjectVRM spin-off), the Me2B Alliance, and MyData Global. There are others, but those are foremost on the ProjectVRM list.

The space we’re building out here is immense, so there is not only room for everybody, but more work than even everybody can do. Meanwhile it is essential that we clarify what all the roles are. Hence this post.

Markets as conversations with robots

From the Google AI blog: Towards a Conversational Agent that Can Chat About…Anything:

In “Towards a Human-like Open-Domain Chatbot”, we present Meena, a 2.6 billion parameter end-to-end trained neural conversational model. We show that Meena can conduct conversations that are more sensible and specific than existing state-of-the-art chatbots. Such improvements are reflected through a new human evaluation metric that we propose for open-domain chatbots, called Sensibleness and Specificity Average (SSA), which captures basic, but important attributes for human conversation. Remarkably, we demonstrate that perplexity, an automatic metric that is readily available to any neural conversational models, highly correlates with SSA.

A chat between Meena (left) and a person (right).

Meena

Meena is an end-to-end, neural conversational model that learns to respond sensibly to a given conversational context. The training objective is to minimize perplexity, the uncertainty of predicting the next token (in this case, the next word in a conversation). At its heart lies the Evolved Transformer seq2seq architecture, a Transformer architecture discovered by evolutionary neural architecture search to improve perplexity.

 

Concretely, Meena has a single Evolved Transformer encoder block and 13 Evolved Transformer decoder blocks as illustrated below. The encoder is responsible for processing the conversation context to help Meena understand what has already been said in the conversation. The decoder then uses that information to formulate an actual response. Through tuning the hyper-parameters, we discovered that a more powerful decoder was the key to higher conversational quality.

So how about turning this around?

What if Google sold or gave a Meena model to people—a model Google wouldn’t be able to spy on—so people could use it to chat sensibly with robots or people at companies?

Possible?

If, in the future (which is now—it’s freaking 2020 already), people will have robots of their own, why not one for dealing with companies, which themselves are turning their sales and customer service systems over to robots anyway?

People are the real edge

You Need to Move from Cloud Computing to Edge Computing Now!, writes Sabina Pokhrel in Towards Data Science. The reason, says her subhead, is that “Edge Computing market size is expected to reach USD 29 billion by 2025.” (Source: Grand View Research.) The second person “You” in the headline is business. Not the people at the edge. At least not yet.

We need to fix that.

By we, I mean each of us—as independent individuals and as collected groups—and with full agency in both roles. The Edge Computing is both.

The article  illustrates the move to Edge Computing this way:

The four items at the bottom (taxi, surveillance camera, traffic light, and smartphone) are at the edges of corporate systems. That’s what the Edge Computing talk is about. But one of those—the phone—is also yours. In fact it is primarily yours. And you are the true edge, because you are an independent actor.

More than any device in the world, that phone is the people’s edge, because connected device is more personal. Our phones are, almost literally, extensions of ourselves—to a degree that being without one in the connected world is a real disability.

Given phones importance to us, we need to be in charge of whatever edge computing happens there. Simple as that. We cannot be puppets at the ends of corporate strings.

I am sure that this is not a consideration for most of those working on cloud computing, edge computing, or moving computation from one to the other.

So we need to make clear that our agency over the computation in our personal devices is a primary design consideration. We need to do that with tech, with policy, and with advocacy.

This is not a matter of asking companies and governments to please give us some agency. We need to create that agency for ourselves, much as we’ve learned to walk, talk and act on our own. We don’t have “Walking as a Service” or “Talking as a Service.” Because those are only things an individual human being can do. Likewise there should be things only an individual human with a phone can do. On their own. At scale. Across all companies and governments.

Pretty much everything written here and tagged VRM describes that work and ways to approach that challenge.

Recently some of us (me included) have been working to establish Me2B as a better name for VRM than VRM.  It occurs to me, in reading this piece, that the e in Me2B could stand for edge. Just a thought.

If we succeed, there is no way edge computing gets talked about, or worked on, without respecting the Me’s of the world, and their essential roles in operating, controlling, managing and otherwise making the most of those edges—for the good of the businesses they deal with as well as themselves.