Data Love Story in the USA With a Few Spats, Too

You might call this time of year, Jan. 15 to March 15, marketing data’s “high season,” based on all of the goings-on. There’s a lot of data love out there — and, like all relationships that are precious, they demand a huge amount of attention, respect, and honor — and celebration.

I’ve been enjoying Alliant’s “Data and the Marketer: A Timeless Love Story” postings this month, leading up to Valentine’s Day.

You might call this time of year, Jan. 15 to March 15, marketing data’s “high season,” based on all of the goings-on:

The Alliant infographic download got me thinking of some other “key” dates that might also be recognized on the Data Love calendar, reflecting other aspects of the love story. Not all love affairs are perfect — are there any? Sometimes there’s a quarrel and spats happen, without any abandonment of a full-on love affair.

  • 1960 — The Direct Marketing Association (then, DMAA) develops its first self-regulatory ethics code for data and lists, in an early industry initiative to separate the good from bad players. It becomes the basis for practically every data protection (and consumer rights) framework since.
  • 1971 — The Mail Preference Service is launched (today DMAChoice) the first marketing industry opt-out control program for consumers — the essential framework for every consumer choice tool in marketing (in-house and industry-wide) since.
  • 1973 — The U.S. Department of Health, Education, and Welfare introduces and adopts eight Fair Information Principles. In 1980, the Organization of Economic Co-operation and Development adopts these principles for trans-border data flows. In 1995, The European Union, among other governments, enact variation and interpretation of these formally into law, eventually adopting the EU General Data Protection Regulation in 2018.
  • 1991 — Jennifer Barret is named Acxiom’s privacy leader — among the first enterprises to name what essentially would become a “chief privacy officer.” In 2000, Trevor Hughes launches the International Association of Privacy Professionals. A nascent cottage industry evolves into a huge professional education and development organization that today includes tens of thousands of members.
  • 1992 — A nonprofit and privacy advocacy organization, the Privacy Rights Clearinghouse, is formed, and soon thereafter begins tracking data security breaches, both public and private sector. Its breach list since 2005 is posted here. Data privacy and data security, as evidenced in Fair Information Practice Principles, go hand-in-hand.
  • 1994 — The first online display ad appears on the Internet, by AT&T. (And the first commercial email perhaps the same year.) So marked the humble beginnings of Internet marketing — “direct marketing on steroids.” I thought Jeff Bezos used this term in Amazon (formed 1994) early days during a DMA conference – but alas, I’m having a hard time sourcing that one. Perhaps this quote was related to Google (formed 1998) and the real-time relevance of search!
  • 1995-96 — Subscriber Ram Avrahami asserts a property right to his name in a lawsuit against S. News and World Report. Because he thwarted the spelling of his name on the magazine’s list – in a bid to discover who else the magazine rents its subscriber list to – the court ultimately rejects his challenge. The case, however, introduces a novel concept and set of questions:Is the value of any list or database tied to the presence of any one individual name on that list, a penny a name in this case?  Or, is its value because of the sweat of the brow of the list/database creator (a business, nonprofit group, or other entity) that built a common attribute to which a list may derive commercial value?The “walled gardens” of today’s Digital Giants largely were built on such data collection. These two questions recognize that a “data-for-value” exchange must be perceived as mutually beneficial, or else consumer trust is eroded. “Who owns the data?” (a 20th Century assertion) might be better substituted today as “Who has a shared interest in the value and protection of data?” (a 21st Century proposition).
  • 2006 — Facebook is formed, among the first companies that created a “social network.” (I’m sure the adult content sector preceded it, as it often points us the way.) In one industry after another, digital disruption reorders supply chains, consumer-brand relationships, shopping practices, and name-your-own-business here. The Great Recession, and venture capital, serves to speed the quest for data-defined efficiency and transformation.
  • 2017 — Equifax, one of the United States three leading credit and information bureaus on Americans, experiences a breach of epic proportions. While the nation was fascinated with subsequent public hearings about Facebook, its data deals, and its (ahem, beneficial) targeted advertising practices, a potentially much more egregious purveyor of harm – sponsored government hacking of the highest order – largely gets a ho-hum from the general public, at least until this past week.
  • 2020 — California fragments online privacy protection in the United States – only underscoring the need for the federal government to act sooner than later. Support Privacy for America.

So, yes, there’s a lot of Data Love out there — and, like all relationships that are precious, they demand a huge amount of attention, respect, and honor — and celebration. See you soon in Orlando!

 

 

Don’t Be a Data Hoarder — Why Data Governance Matters in Marketing

They say data is an asset. I say it, too. If collected data are wielded properly, they can definitely lead to financial gains, either through a revenue increase or cost reduction. But that doesn’t mean that possessing large amounts of data guarantees large dollar figures for the collector. Data governance matters.

They say data is an asset. I say it, too. If collected data are wielded properly, they can definitely lead to financial gains, either through a revenue increase or cost reduction. But that doesn’t mean that possessing large amounts of data guarantees large dollar figures for the collector. Data governance matters, because the operative words in my statement are “wielded properly,” as I have been emphasizing for years through this column.

Plus, collecting data also comes with risks. When sensitive data go into the wrong hands, it often leads to a direct financial burden for the data collector. In some countries, an assumed guardian of sensitive data may face legal charges for mishandling sensitive data. Even in the United States, which is known as the “freest” country for businesses when it comes to data usage, data breach or clear abuse of data can lead to a publicity nightmare for the organization; or worse, large legal settlements after long and costly litigations. Even in the most innocuous cases, mistreatment of sensitive data may lead to serious damage to the brand image.

The phrase is not even cool in the business community anymore, but “Big Data” worked like a magic word only a few years ago. In my opinion, that word “big” in Big Data misled many organizations and decision-makers. It basically gave a wrong notion that “big” is indeed “good” in the data business.

What is “good,” in a pure business sense? Simply, more money. What was the popular definition of Big Data back then? Three Vs, as in volume, velocity and variety. So, if varieties of data in large volumes move around really fast, it will automatically be good for businesses? We know the answer by now, that a large amount of unstructured, unorganized and unrefined data could just be a burden to the holder, not to mention the security concerns listed earlier.

Unfortunately, with the popularity of Big Data and emergence of cloud computing, many organizations started to hoard data with a hope that collected data would turn into gold one day. Here, I am saying “hoarding” with all of the negative connotations that come with the word.

Hoarders are the people who are not able to throw away anything, even garbage. Data hoarders are the same way. Most datasets are huge because the collector does not know what to throw out. If you ask any hoarder why he keeps so many items in the house, the most common answer would be “because you never know when you need them.” Data hoarders keep every piece of data indefinitely for the same reason.

Only Keep Useful Data

But if you are playing with data for business purposes, you should know what pieces of data are useful for decision-making. The sponsor of any data activity must have clear objectives to begin with. Analysts would then find out what kind of data are necessary to meet those goals, through various statistical analyses and cumulative knowledge.

Actually, good analysts do know that not all data are created equal, and some are more useful than others. Why do you think that the notion of a Data Lake became popular following the Big Data hype? Further, I have been emphasizing the importance of an even more concise data environment. (I call it an “Analytics Sandbox.”) Because the lake water in the Data Lake is still not drinkable. Data must get smaller through data refinement and analytics to be beneficial for decision-makers (refer to “Big Data Must Get Smaller”).

Nonetheless, organizations continue to hoard data, because no one wants to be responsible for purging data that may be useful someday. Government agencies may have some good reasons to maintain large amounts of data, because the cost of losing or misplacing data about some terrorist activities is too high. Even in that case, however, we should collectively be concerned if the most sensitive data about us — such as our biometrics data — reside in some government agency’s server somewhere, without clear and immediate purposes. In cities like London or Paris, cameras are on every street corner, linked to facial recognition algorithms. But we tolerate that because the benefit outweighs the risk (so we think). But that doesn’t mean that we don’t need to be concerned with data breach or abuse.

Hoarding Data Gives Brands the Temptation to Be Creepy

If the data are collected by businesses for their financial gains, then the subjects of such data collection (i.e., consumers) should question who gave them the right to collect data about every breath we take, every move we make and every claim we stake. It is one thing to retain data about mutual transactions, but it is quite another to collect data on our movement or whereabouts, unilaterally. In other words, it is one thing to be remembered (for better service and recommendation in the future), but it is another to be stalked (remember “Every Breath You Take” is a song about a stalker).

Have you heard a story about a stalker who successfully courted the subject as result of stalking? Why do marketers think that they will sell more of their products by stalking their customers and prospects? Since when did being totally creepy – as in “I know where you are and what you’re doing right now” – become an acceptable marketing tactic? (Refer to “Don’t Do It Just Because You Can.”)

In fact, even if you do possess such data, in the interest of “not” being creepy, you must make your message more innocuous. For example, don’t act like you are offering an item because you “know” that the target looked around similar items recently. That kind of creepy approach may work once in a while, but let’s not call that a good sales tactic.

Instead, sellers should make gentle nudges. Don’t say “I know you are looking for this particular skin care item.” The response to that would be “Who the hell are you, and how do you know that?” Instead, do say “Would you be interested in our new product for people with sensitive skin?” The desirable response would be “Hey, I was just looking for something like that!”

The difference between a creepy stalking and a gentle nudging is huge, from the receiving end.

Through many articles about personalization, I have been emphasizing the use of model-based personas, as they pack so much information in the form of answer to questions and cover the gap of missing data (as we’d never know everything about everyone). If I may add one more benefit of modeling, it coverts data into probabilities. Raw data is about “I know she is looking for a particular high-end skin care item,” where coverage of such data is seriously limited, anyway. Conversely, model scores are about “Her score for high-end beauty products is 8 out of 10 scale score,” even if we may not even have concrete data about that specific interest.

Now, users who only have access to the model score — which is “dull” information, in comparison to “sharp” data about some verified behavior — would be less temped to say “Oh, I know you did this.” Even for non-geeky types, the difference between “Is” and “Likely to be” is vast.

If converting sharp data into innocuous probability scores through modeling is too much for you to start with, then at least categorize the data, and expose data points to users that way. Yes, we are living in the world of SKU-level product suggestion (like Amazon does), but as a consumer, have you ever “liked” such blunt suggestions, anyway? Marketers do it because such personalization does better than not doing anything at all, but such a practice is hardly ideal for many reasons (Being creepy being one. Refer to “Personalization Is About the Person”).

The saddest part in all this is that most marketers don’t even know how to fully utilize what they collected. I’ve seen too many organizations that are still stuck with using a few popular data variables repeatedly, while hoarding data indiscriminately. Why risk all of those privacy and security concerns, not to mention the data maintenance cost, if that is the case?

Have a Goal for All of That Data

If analytics is part of the process, then the analysts will tell you with conviction, that you don’t need all those data points for certain types of prediction. For instance, why risk losing a bunch of credit card numbers, when the credit card type or payment method is all you need to predict responses and propensities on a customer level?

Of course, the organization must first decide what types of models and predictions are necessary to meet their goals. But that is the beginning part of the whole analytics game, anyway. Analytics is not about answering to some wishful thinking of data hoarders; it should be a goal-oriented activity, with carefully selected and refined data for clear purposes.

A goal-oriented mindset is even more important in the age of machine learning and automation. Because we should never automate bad behaviors. Imagine a powerful marketing automation engine in the hands of data hoarders. Forget about organizational inefficiency. As a consumer, don’t you get a chill down your spine just imagining how creepy the outcome would be? Well, maybe we don’t really have to imagine it, as we all get bombarded with ineffective and not-so-personal offers every day.

Conclusion

So, marketers, have clear purposes in data activities, and do not become mindless data hoarders. If you do possess data, wield them properly with analytics. And while at it, purge pieces of data that do not fit your goals. That “you never know” attitude really doesn’t help anyone. And you are supposed to know your own goals and what data and methodologies will get you there.

Marketers Doing the Data Privacy Balancing Act Ask What ‘I Want My Privacy’ Means

It’s not just policymakers who are trying to figure out how to act on consumer sentiments toward data privacy. We all, overwhelmingly, want it — business and consumer.

data privacy
Credit: Pexels.com

It’s not just policymakers who are trying to figure out how to act on consumer sentiments toward data privacy. We all, overwhelmingly, want it — business and consumer.

We are all seeking a U.S. federal privacy law to “repair” what may be broken in Europe (hey, the toaster needs fixing), and to correct any perceived privacy shortcomings in California’s new law (scheduled to take effect in January). Will such a federal law pass this year?

One of the ongoing challenges for policy in this area is what’s been called the privacy paradox. The paradox? Privacy in the form of consumer attitudes, and privacy in the form of consumer demands and behaviors, rarely are in sync. Sometimes, they are polar opposites, simultaneously!

  • Should law be enacted on how we feel, or respectful of what we actually do?
  • How do we define privacy harms and focus regulation only what is harmful and to go light, very light, or even foster wholly beneficial uses?
  • Should private sector controls and public sector controls be differentiated?
  • Do existing laws and ethical codes of conduct apply, and how might they be modified for the digital age?

On top of this, consumer expectations with data and technology are not fixed. Their comfort levels with how information is used at least in the advertising sector change over time. In fact, some marketers can’t keep pace with consumer demands to be identified, recognized and rewarded across channels. Generations, too, have differences in attitudes and behaviors.

What’s creepy today may in fact be tomorrow’s consumer-demanded convenience.

Case in point: It used to be people complained about remarketing the ad following them around on the Net as they browsed. (All the same, remarketing works that’s why it was so pervasive.) Today, in role reversal, consumers sound off when the product they purchased is the same product they still see in the display ad. The consumer has little patience when brand data is locked in data silos: the transaction database doesn’t inform the programmatic media buy, in this scenario.

The marketing and advertising business have been trying to solve for the privacy paradox since the Direct Marketing Association assembled its first code of ethics in the 1960s and introduced the Mail Preference Service in 1971. (Today, the Mail Preference Service is now known as dmaChoice, and DMA is now part of the Data Marketing & Analytics division of the Association of National Advertisers.) During the 1970s, consumers could use MPS to both add their names to marketing lists, and to remove their names from marketing lists for direct mail. At that time, far more consumers sought to add their names. Later, MPS strictly devoted itself to offering consumers an industry-wide opt-out for national direct mail, with add-ons for sweepstakes and halting mail to the deceased.

During the ’70s, DMA also required its member mailers (and later telemarketers and emailers) to maintain their own in-house suppression lists. These ethics behaviors were codified, to some extent, when the U.S. government enabled the Do-Not-Call registry and enacted the CAN-SPAM Act to complement these efforts.

Fair Information Practice Principles A Framework That Still Works Wonders

So here we are in the digital age, where digital display and mobile advertising are among addressable media’s growing family. Again, the marketing community rose to the challenge enacting the Digital Advertising Alliance YourAdChoices program (disclaimer, a client) and offering consumers an opt-out program for data collection used for interest-based advertising for Web browsing (desktop and mobile) and mobile applications.

Over and over again, the pattern is the same: Give consumers notice, give consumers control, prevent unauthorized uses of marketing data, protect sensitive areas recognize advertising’s undeniable social and economic power, enable brands to connect to consumers through relevance and trust and act to prevent real harms, rather than micromanage minor annoyances. Allow marketing innovations that create diversity in content, competition and democratization of information. Let the private sector invest in data where no harms exist.

‘I own my data!’

Data ownership is a dicey concept. Isn’t there sweat equity when a business builds a physical or virtual storefront and you choose to interact with it? Is there not some expectation of data being contributed in fair exchange for the digital content we freely consume and the apps we download and enjoy? And once we elect to become a customer, isn’t it better for the brand to know you better, to serve you better? Shouldn’t loyalty over time be rewarded? That’s an intelligent data exchange, and the economy grows with it.

The demand for access to everything free, without ads, and without data exchange, without payment to creators is a demand for intellectual property theft. Sooner than later, the availability and diversity of that content would be gone. And so would democracy. If you put everything behind an ad-free paywall, then only the elites would have access.

‘But I pay for my Internet service. I pay for my phone service!’

Sure you do and that pays for the cell towers, and tech and Web infrastructure, union labor with some profit for the provider. But unless you’re also paying for subscriptions and content it’s advertising that is footing the bill for the music you listen to, the news you read, the apps you use, and so on. All the better when ads are relevant.

At the end of the day, the consumer is always right and privacy is personally defined.

I’m all for limits on what governments can do with data when it comes to surveillance, and how it goes about maintaining our safety and security (a paradox of its own).

On the private sector side, policymakers might best act to give a privacy floor (do no harm) and where economic benefits accrue (to serve consumers without harms) allow consumers freely accessible tools to set their own privacy walls, using browser settings, industry opt-outs, brand preference centers and other widely available no-cost filters. It’s a wise society that can encourage responsible data flows, while blocking altogether irresponsible data flows. Get it right, and we all participate in a thriving 21st Century Information Economy. Get it wrong, and Europe and China will set the global rules. With some luck and deliberation, we’ll get this right.

Data Privacy Policymaking Words of Warning of Europe

Two weeks back, two hearings in Congress were held about a possible forthcoming new federal data privacy law for the United States. Some of the testimony included fascinating insight.

Two weeks back, two hearings in Congress were held about a possible forthcoming new federal data privacy law for the United States. Some of the testimony included fascinating insight.

It’s been nearly nine months since the European Union’s (EU) General Data Protection Regulation (GDPR) took effect with its tentacle effects worldwide – and it is helpful to look at what has transcribed, and to avoid making GDPR’s mistakes. That’s what one of the witnesses, Roslyn Layton, visiting scholar, American Enterprise Institute, had to say to the House Committee on Energy and Commerce, Subcommittee on Consumer Protection and Commerce, in her statement titled “How the US Can Leapfrog the EU.”

GDPR’s Early Impacts Are Foreboding

From Dr. Layton’s testimony, I found these excerpts (footnotes removed) to be particularly insightful – and somewhat frightful, though some of it predictable. She examined GDPR’s early deleterious effects which we, in the United States and elsewhere, would be wise to reject:

GDPR Is Not about Privacy  It’s About Data Flows

“A popular misconception about the GDPR is that it protects privacy; it does not. In fact, the word ‘privacy’ does not even appear in the final text of the GDPR, except in a footnote. Rather, the GDPR is about data protection or, more correctly, data governance. Data privacy is about the use of data by people who are allowed to have it. Data protection, on the other hand, refers to technical systems that keep data out of the hands of people who should not have it. By its very name, the GDPR regulates the processing of personal data, not privacy.”

GDPR Has Only Concentrated Big Digital Since Taking Effect

“To analyze a policy like the GDPR, we must set aside the political pronouncements and evaluate its real-world effects. Since the implementation of the GDPR, Google, Facebook and Amazon have increased their market share in the EU.”

GDPR Has Decimated Small- and Mid-Sized Ad Tech

“One study suggests that small- and medium-sized ad tech competitors have lost up to one-third of their market position since the GDPR took effect. The GDPR does not bode well for cutting-edge firms, as scientists describe it as fundamentally incompatible with artificial intelligence and big data. This is indeed a perverse outcome for a regulation that promised to level the playing field.”

GDPR Raises Costs, Prohibitively Acting as a Trade Barrier

“To do business in the EU today, the average firm of 500 employees must spend about $3 million to comply with the GDPR. Thousands of US firms have decided it is not worthwhile and have exited. No longer visible in the EU are the Chicago Tribune and the hundreds of outlets from Tribune Publishing. This is concerning because the EU is the destination of about two-thirds of America’s exports of digital media, goods and services. Indeed, the GDPR can be examined as a trade barrier to keep small American firms out so that small European firms can get a foothold.”

GDPR Denies Valuable Content to European Citizens

“Of course, $3 million, or even $300 million, is nothing for Google, Facebook and Amazon (The Fortune 500 firms have reportedly earmarked $8 billion for GDPR upgrades.), but it would bankrupt many online enterprises in the US. Indeed, less than half of eligible firms are fully compliant with the GDPR; one-fifth say that full compliance is impossible. The direct welfare loss is estimated be about €260 per European citizen.”

What if the US Enacted GDPR Here … Oh, the Costs

“If a similar regulation were enacted in the US, total GDPR compliance costs for US firms alone would reach $150 billion; twice what the US spend on broadband network investment and one-third of annual e-commerce revenue in the US.”

Dr. Layton, in her testimony, also questioned the California Consumer Privacy Act, which may create even more enterprise requirements then GDPR. She suggested more pragmatic paths need to be forged.

A Better Way Privacy by Design

“Ideally, we need a technologically neutral national framework with a consistent application across enterprises. It should support consumers’ expectations to have same protections on all online entities. The law should make distinctions between personally identifiable information which deserves protection, but not require same high standard for public data, de-identified, and anonymized data which do not carry the same risks. Unlike the GDPR, the US policy should not make it more expensive to do business, reduce consumer freedom or inhibit innovation.”

Data ‘Seat Belts and Air Bags’ for Privacy

In a second hearing, before the Senate Committee on Commerce, Science and Transportation, Interactive Advertising Bureau (IAB) CEO Randall Rothenberg provided a spirited statement of data’s role in the U.S. economy and the benefits that continue to accrue. He, too, drew from an another industry’s history which he believes offers a helpful analogy and cooperative blueprint:

IAB CEO Randall Rothenberg | Credit: Photo: Chet Dalzell

Internet’s Profound Communication Power

“The Internet is perhaps the most powerful and empowering mode of communication and commerce ever invented. It is built on the exchange of data between individuals’ browsers and devices, and myriad server computers operated by hundreds of millions of businesses, educational institutions, governments, NGOs, and other individuals around the world.”

Advertising’s Essential Role Online Much of It Data-Driven

Advertising has served an essential role in the growth and sustainability of the digital ecosystem, almost from the moment the first Internet browsers were released to the public in the 1990s. In the decades since, data-driven advertising has powered the growth of e-commerce, the digital news industry, digital entertainment, and a burgeoning consumer-brand revolution by funding innovative tools and services for consumers and businesses to connect, communicate and trade.

The Indispensable Ingredient: Trust

“Central to companies’ data-fueled growth is trust. As in any relationship, from love to commerce, trust underlies the willingness of parties to exchange information with each other; and thus, their ability to create greater value for each other. The equation is simple: The economy depends on the Internet; the Internet runs on data; data requires trust. IAB strongly believes that legislative and regulatory mechanisms can be deployed in ways that will reinforce and enhance trust in the Internet ecosystem.”

Universal Truth: Consumer Data Is Good

“We recommend Congress start with a premise that for most of American history was self-evident, but today seems almost revolutionary: consumer data is a good thing. It is the raw material of such essential activities as epidemiology, journalism, marketing, business development, and every social science you can name.

The Auto Industry Offers Us a Proactive Model

“We believe our goals align with the Congress’ decision to take a proactive position on data privacy, rather than the reactive approach that has been adopted by Europe and some states. We believe we can work together as partners in this effort with you to advance consumer privacy. Our model is the partnership between government and industry that created the modern concept of automotive safety in the 1960s. Yes, the partnership began as a shotgun wedding. Yes, the auto industry resisted at first. But an undeniable consumer right to be safe on the highways met well-researched solutions, which the Congress embedded in well-crafted laws that were supported by the states.

Auto Safety and Digital Wellness

“The result has been millions of lives and billions of dollars saved. We believe the analogy holds well here. Americans have a right to be secure on the information superhighway. Well-researched solutions and well-crafted laws can assure their ‘digital wellness.’ We should be thorough, practical and collaborative. Our goal should be to find the three or five or 10 practices and mechanisms the seat belts and air bags of the Internet era  that companies can implement and consumers can easily adopt that will reinforce privacy, security and trust.”

Notice and Choice Bombardment Or Predictable Rules of the Road

“Together, based on our members’ experience, we can achieve this new paradigm by developing a federal privacy law that, instead of bombarding consumers with notices and choices, comprehensively provides clear, even-handed, consistent and predictable rules of the road that consumers, businesses and law enforcers can rely upon.

One Federal Standard in Harmony

“Without a consistent, preemptive federal privacy standard, the patchwork of state privacy laws will create consumer confusion, present significant challenges for businesses trying to comply with these laws, and ultimately fall short of consumers’ expectations about their digital privacy. We ask the Congress to harmonize privacy protections across the country through preemptive legislation that provides meaningful protections for consumers while allowing digital innovation to continue apace.”

It is worth reading the testimonies of the privacy advocates present at these two hearings, as well. These GDPR fans have many sympathetic voices in the media and Congress, and truly need to be part of any conversation where consensus ought to be built. It is my hope the right federal legislation will result. The early evidence from Europe where advocates won over reason portends the punitive risks of getting it wrong.

It’s Decision Time for Data Privacy (or Will Be Soon)

Chet Dalzell’s recent thoughtful piece on “Our Digital Selves” came along at the same time I (and probably a gazillion others) were pondering the increasingly pressing question of data privacy in the digital age.

Chet Dalzell’s recent thoughtful piece on “Our Digital Selves” came along at the same time I (and probably a gazillion others) were pondering the increasingly pressing question of data privacy in the digital age.

It’s a much bigger question than what data can be used to target potential customers for the latest widget or widget club or to stop you in your tracks at the supermarket in front of the pet food shelves to tell you that Fido, your beloved Fido, seen in the picture on your cell phone, absolutely must have the new, nutritious and tasty Dogbit,s or he may bite your fingers off if you try to give him anything else.

The data question goes to the heart of how we see ourselves in the digital world. And how we see ourselves is in no way clear — even to ourselves.

“Bottom line: If Facebook’s users in the United States are similar to most Americans (and studies suggest they are), large majorities don’t want personalized ads — and when they learn how companies find out information about them, even greater percentages don’t want them.”

That’s what Joseph Turow, a professor of communications and Chris Jay Hoofnagle, an adjunct professor of law, say in The New York Times using various research to support their thesis. The problem is what people tell researchers is not always what they do. Facebook’s quarterly earnings statement showed these enlightening KPIs.

  • Monthly active users (MAUs) — MAUs were 2.32 billion as of Dec. 31, 2018, an increase of 9%, year-over-year.
  • We estimate that around 2.7 billion people now use Facebook, Instagram, WhatsApp or Messenger (our “Family” of services) each month, and more than 2 billion people use at least one of our Family of services every day, on average.

It has been said over and over again that everything has its price. Assuming that this is largely true, how much value or benefit should the consumer expect in return for how much and which data? As I wrote in a comment to Chet’s article, this is sure to be the data-use question we’ll all be turning in our minds as the algorithms get smarter and the temptations greater.

Imagine that you could put a value on each element of your personal, demographic, psychographic and behavioral data, and anyone wanting to use that data would have to pay your price, whether or not you ended up making a purchase or taking a desired action? Imagine further that a data user wanted to use $20 worth of your data to try to sell you a product you wanted, priced at $100? It would be an easy transaction, if the seller were willing to offer you a 20% or even a greater discount for the specific permission to use the data. You would have the product, the seller would have the sale and everyone would be happy.

However fanciful that scenario, it is not nearly as crazy as it sounds. In fact, in one form or another, that is exactly what is happening in the real marketplace; although without your specific permission. As a marketer, I have to spend money to acquire your data and, by making an attractive offer (say a 20% discount), I am offering to compensate you for your data, which allows me to talk to you.

Of course, I have over-simplified the argument. As stated earlier: How much value or benefit should the consumer expect in return for how much and which data?

I think we would all agree that this determination is much too complicated, so we let the “invisible hand of the market” do its magic. Which reduces the decision to a very simple one: Do we perceive that we get enough value from having our data out there in the marketplace to be manipulated however the marketers wish to and simply lie back and enjoy all the offers and benefits? Or should we bite the bullet, give our cell phones to a needy child, do without Waze and get lost again and again, be prepared to stand in the endless line at the bank, throw the “delete everything” switch and effectively remove ourselves from the digital economy? It is getting near decision time for all of us.

I remember many years ago in London, as “one of those Americans,” being lectured over lunch by a very traditional British publisher about the horrors of books being sold by mail order and direct mail and assuring me that the British wouldn’t have anything to do with book clubs or the like. Just when the bill had been paid and we were preparing to depart, she reached into her handbag and pulled out an all singing and all dancing mailing piece from the Readers Digest, offering a very handsome discount on their superb motorist bible, the “Book of the Road.”

She was going to order it right away.

 

Marketers Must Take Stock of Their Data-Driven Power Now

With the 2020 elections already underway, social media marketing is in the spotlight. Although I am not sure if the spotlight was ever really off of its data-driven science since the 2016 election. Although all of the major social networking platforms have been dragged in front of congress to discuss how they use data, it was the relationship between Facebook and Cambridge Analytica that drew the most media attention and become the poster child.

With the 2020 elections already underway, social media marketing is in the spotlight. Although I am not sure if the spotlight was ever really off of its data-driven science since the 2016 election.

Although all of the major social networking platforms have been dragged in front of congress to discuss how they use data, it was the relationship between Facebook and Cambridge Analytica that drew the most media attention and become the poster child.

What data-driven marketers need to recognize is that what happened with Facebook and Cambridge Analytica was not some off-the-books, sneaky misuse of social data. Rather, it was executed very much in line with the broader vision of social media marketing. That has implications for how we use social media as part of our digital marketing mix.

Why Data-Driven Marketers Must Take Stock Now

What makes social media a powerful platform for marketers is that it not only targets individuals based on demographics, but it could also targets based on their location, personality and current context.

Considering all of the conscious and unconscious information users can share on social platforms, there is a powerful amount of information algorithms can mine to generate marketing content and messages most likely to resonate with users. Not only can social media know where you are and what you like, but also your closest friends and your emotional state on any given day. It is even likely that social media algorithms have a better understanding of your underlying emotions and motivations than you do. To anyone who has spent time micro-targeting, this is not a surprise. Given enough data, a shockingly perceptive algorithm can be developed. This is why social media had mile-high stock valuations even when platforms were still hemorrhaging cash.

Let’s face it; marketing has always included an element of manipulation. The function of consumer insights and research is designed to provide marketers levers for manipulation. With some exceptions, we have been able to sleep at night knowing that the consumer stood a chance or that we were also offering a real benefit, so some manipulation was just part of it. When we started using rich data with algorithms to develop more targeted models, many of us saw this as the ultimate example of customer empathy. This was going to empower marketers to become highly relevant to their consumers.

Those who were not on board were behind the times. (To confess, I used to view most cautionary voices as laggards or technophobes. Some were, some weren’t, but they were also right to worry.)

Today, we need to take stock of how that empathy is used. With great empathy comes the power of even greater manipulation. Despite all of the data policies out there, we are not addressing the real question: How much manipulation is too much?

Is it fair to push an antacid ad at someone who posts about a visit to the county fair and winning the pie-eating contest? Seems “big brother-ish,” but benign?

How about pushing anti-anxiety medication ads to a college student going through a breakup during finals week?

While this sounds horrible, we technically can.

Don’t Do It Just Because You Can

How companies manage and leverage consumer data is becoming part of the company’s ethical standards, but we need to extend beyond data privacy to data use.

Just like use of child labor, environmental footprints and other ethical standards, standards on the use of consumer data will be a critical way that companies define their brands and the role they wish to play.

4 Reasons Data Privacy Is Just Too Boring to Matter

Facebook was simply the poster boy for an uncomfortable data revolution well under way, but the hearings were very revealing. I am not sure how we will finally manage the complex issue of data privacy. However, it is clear what is not likely to happen in the near-term.

When I think about the current controversy around Facebook, personal data and the recently departed Cambridge Analytica, I am reminded of MAD Magazine. (Stay with me for a bit.) MAD was a rite of passage for Gen Xers such as myself. Irreverent and satirical of all things pop culture, the magazine was edgy (for that time) and a shock to polite sensibilities of the day. At a time when most people’s exposure to comedy was laugh-tracked sitcoms and Carson’s “Tonight Show,” MAD exposed the artificially flavored vanilla entertainment we were consuming for what it was, formulaic and fake.

It may seem that MAD magazine is tenuously relevant to today’s topic of data privacy, and I would agree except for one critical element. While parents and teachers could feel the sedition and revolution brewing in those pages they were comically inept at doing anything about it. Despite their frowns, despite all of their threats to censure, confiscate or ban the magazine, the magazine made its mark on my generation and contributed to a progression in brutally honest and sardonic comedy (“The Simpsons,” “Family Guy,” “Chappelle’s Show,” etc., etc.)

Fast forward to the congressional hearings where Mark Zuckerberg was grilled for hours on Facebook’s use of user data. Facebook was simply the poster boy for an uncomfortable data revolution well under way, but the hearings were very revealing. We saw Senators struggle, sometimes comically, to understand what really bothered them about this fiasco. Occasionally, they threw out threats to salvage their visibly worn-out veneer of authority. It was that familiar hapless authority figure trying to manage something ambiguously unnerving, while submitting to the inevitable change.

I am not sure how we will finally manage the complex issue of data privacy. However, it is clear what is not likely to happen in the near-term.

  1. There Will Not Be Any Effective Data Privacy Legislation. First, legislators don’t fully understand the intricacies, so they are rightfully hesitant to take strong action. Even more important, consumers are no longer naive about how their personal data could be accessed and used. There are even widely accepted conspiracies about murky information-gathering techniques, such as digital eavesdropping (“I swear XYZ is listening to my conversations because …”). Yet, every day and in very clear ways, consumers are giving permission by default when they post or view content and engage with apps. The lesson is that consumers care, but not enough to meaningfully change behavior. While a case can be made that data-driven services are designed for addiction and compel users to act in personally detrimental ways, like cigarettes, they are still a long way from becoming vilified products. For now, market demand will continue to drive lax data policies.
  2. Business Models Will Not Change Dramatically. When asked in the congressional hearing if there was a mass exodus of Facebook users since the Cambridge Analytica fiasco, Mark Zuckerberg said there was not. Furthermore, after the hearings concluded, Facebook stock rose 4.5% and has been on a major recovery trend since. If you believe in the wisdom of market forces, then this is a very strong vote for business as usual.
  3. Permission-Based Data Policies Will Provide Temporary Relief. These policies mean consumers decide where and how their data can be used. They will be ineffective, but will provide temporary cover until the next blow-up. These policies assume the consumer has time, ability and inclination to review the data policy of every platform they use. There will be companies who will enter into the personal data market, helping consumers monetize and manage their data, but their interest generally will not align with data privacy. The only one really interested in privacy is the consumer and most will not pay for it.
  4. No One Cares. Of all of my posts, the most informative was an article that discussed the wide landscape of consumer data. It is also the one that has had the fewest views, by a long shot. It is so dull, I rarely reference it and that should tell you all you need to know about the battle between sound data policy and data-driven consumerism.

Are You Ready for GDPR, Europe’s Upcoming Data Privacy Requirements?

Privacy is probably one of the least appealing topics in marketing. But this one’s a doozy. On May 25, 2018, any company that is not compliance with the European Union’s new opt-in regulations is at risk of a fine of up to 20 million euros, or 4 percent of their global topline revenue.

European UnionPrivacy is probably one of the least appealing topics in marketing. But this one’s a doozy. On May 25, 2018, any company that is not compliance with the European Union’s new opt-in regulations is at risk of a fine of up to 20 million euros, or 4 percent of their global topline revenue. Yipes! Most B2B marketers have customers worldwide. The General Data Protection Regulation is something we cannot ignore.

The interesting thing about this new regulation is, it’s not about marketing per se. They are not just focused on prospecting, like the CAN-SPAM and Do Not Call regulations in the U.S. It’s about consumer control of their data, and their comfort that it’s being protected.

Linnette J. Attai, whose consultancy PlayWell, LLC, specializes in compliance, explains that the consumer is the data “subject,” and the firm with whom he does business is the data “controller.” The controller decides how the data will be used and protected, and may be supported by a “processor,” like an agency or data services provider. The controller must be able to demonstrate that the subject has agreed to the controller’s data usage and storage plans.

The data elements likely to be at issue include a name, a photo, an email address, bank details, posts on social media, medical information, or a computer IP address.

As business sellers, we may be in somewhat better shape than our consumer marketing counterparts. First of all, an existing business relationship implies consent on the part of the customer. Furthermore, the reg requires businesses to buy only from firms who are compliant. So your existing customers are probably already hounding you to amend their contracts to include GDPR language, says Attai. And if a new contact at the existing account gets involved in the relationship, they may be covered under your existing contracts. Or you could provide the required notices, ask that person to check a box on an online form, and be done with it.

But for a “net new” account, it’s murkier. In the course of business with a new customer — for example, in your contract — you need to gather their agreement as to how you will use their information. But apparently it does not always mean that you must get GDPR compliance in advance to make cold contact with prospects. Most EU prospecting data—email and direct mail lists—already include opt-in permissions. Look for prospecting data that was opted in under GDPR specifications.

GDPR also specifies various technical elements, like security levels, auditability, cross-border data transfer, and procedures for reporting data breaches. B2B firms are going to need help determining how to comply.

One helpful resource is Pauline Murphy, managing director of 1 Stop Data Limited, in the UK. She specializes in B2B prospecting, and operates a multi-language call center in Ireland that calls into the EU and the Middle East. Alongside lead generation and data hygiene calling, she offers GDPR compliance services. Seems like a nifty solution to me, since you get both a demonstrable compliance along with an extra marketing touch, plus a chance to update your customer records and add new contact names.

So, what should we all be doing? That’s the funny thing. Since the regs are new, no one is entirely sure what exactly needs to be done. But most experts advise that you take steps, and don’t dawdle. If the regulators want to make an example of a company next May, let’s not let it be yours. Get started with http://www.eugdpr.org/ and https://ico.org.uk/for-organisations/data-protection-reform/overview-of-the-gdpr/.

A version of this article appeared in Biznology, the digital marketing blog.