For Our Security, Does the FBI Need a Predictive Model?

If you’ve ever worked with a predictive model, you know it is not static, but an iterative effort that requires constant testing, tweaking and feeding of additional data points. It’s a living, breathing tool that is extremely useful in helping to determine where you should best spend your marketing investment for the highest return. This same premise could be used to predict the likelihood of terrorist activity — and therefore be a useful tool in our global war on terror.

Data ScientistIf you’ve ever tried to improve your direct marketing response rates, you’ve probably considered the use of a predictive model.

Predictive modeling is a process that uses data mining and probability to forecast outcomes. The model is made up of a number of variables about your customers: demographic variables (gender, age, household income, etc.), lifestyle variables (smoker, frequent flyer, etc.) and behavioral variables (last date of purchase, purchase amount, SKU, etc.). Each variable is weighted as to its likelihood to predict a specific outcome (like a future purchase) and a statistical model is then formulated. The model is then overlaid on your customer file and every customer is ranked based on their likelihood to respond to an offer, take your desired action, and even predict the average purchase amount.

If you’ve ever worked with a predictive model, you know it is not static, but an iterative effort that requires constant testing, tweaking and feeding of additional data points. It’s a living, breathing tool that is extremely useful in helping to determine where you should best spend your marketing investment for the highest return.

This same premise could be used to predict the likelihood of terrorist activity — and therefore be a useful tool in our global war on terror.

Think about it for just a minute.

The recent bombing in Manchester, U.K. might have been prevented if only the suspect had been higher on the terrorism watch list.

While authorities noted that the suspect (and his family) were on the list, it was added that there are “thousands” on the watch list and there isn’t enough manpower to track them all. Fair enough. But let’s consider those variables that may have predicted that something was about to happen and that, perhaps, he should have moved higher up on that list.

  • The suspects father was linked to a well-known militant Islamist group in Libya
  • His two brothers have been separately arrested on suspicion of terrorism offences
  • He was reported to authorities two years ago “because he [was] thought to be involved in extremism and terrorism”
  • Two friends separately called the police counter-terrorism hotline five years ago and again last year
  • Neighbors had called authorities within the last year, noting that the family had flown a flag for a short time that was black and had writing on it similar to jihadists

The final variable is that the suspect had traveled to both Syria and Libya — the latter only a few weeks before returning to the U.K. and launching his attack. Libya is well known as a terrorist hotbed, so add all the previous variables and the “traveled in May 2017 to Libya” variable would probably catapult this guy to the top of the model.

But why doesn’t such a database exist?

Well, privacy concerns, for one. While consumers — and in particular, Americans — argue about their privacy rights, they are already part of every large consumer database whether they realize it or not. If you’ve ever purchased a home, opened a credit card, paid a tax bill, enrolled in a public school, joined a Frequent Flyer program, registered a purchase for warranty coverage, made a political contribution or subscribed to a magazine, you’re in the Experian or Equifax master file.

In many countries around the world, these same kinds of consumer databases exist, so imagine if these files were combined, and then appended with data variables from law enforcement databases and ticket sales from airline databases. Add in databases about weapon and ammunition purchases, and surely there are enough predictive variables that would allow an analyst to build a model that would determine a way to help prioritize security watch lists, and aid in keeping our world just a little bit safer?

Privacy advocates get itchy just thinking about it.

And, of course, there are those concerned about how this wealth of information could be abused, or how hackers could infiltrate and release confidential information.

But as I head through another security check at my airline gate, and I hear more news about losing the ability to work on my laptop or read my Kindle while in the air, I have to think there’s got to be a better way than the seemingly randomization of these security measures. And it seems that a predictive model might be the answer — but since it depends on consumer data at its core, the future is uncertain without it.

Don’t Do It Just Because You Can

Don’t do it just because you can. No kidding. … Any geek with moderate coding skills or any overzealous marketer with access to some data can do real damage to real human beings without any superpowers to speak of. Largely, we wouldn’t go so far as calling them permanent damages, but I must say that some marketing messages and practices are really annoying and invasive. Enough to classify them as “junk mail” or “spam.” Yeah, I said that, knowing full-well that those words are forbidden in the industry in which I built my career.

Don’t do it just because you can. No kidding. By the way, I could have gone with Ben Parker’s “With great power comes great responsibility” line, but I didn’t, as it has become an over-quoted cliché. Plus, I’m not much of a fan of “Spiderman.” Actually, I’m kidding this time. (Not the “Spiderman” part, as I’m more of a fan of “Thor.”) But the real reason is any geek with moderate coding skills or any overzealous marketer with access to some data can do real damage to real human beings without any superpowers to speak of. Largely, we wouldn’t go so far as calling them permanent damages, but I must say that some marketing messages and practices are really annoying and invasive. Enough to classify them as “junk mail” or “spam.” Yeah, I said that, knowing full-well that those words are forbidden in the industry in which I built my career.

All jokes aside, I received a call from my mother a few years ago asking me if this “urgent” letter that says her car warranty will expire if she does not act “right now” (along with a few exclamation marks) is something to which she must respond immediately. Many of us by now are impervious to such fake urgencies or outrageous claims (like “You’ve just won $10,000,000!!!”). But I then realized that there still are plenty of folks who would spend their hard-earned dollars based on such misleading messages. What really made me mad, other than the fact that my own mother was involved in that case, was that someone must have actually targeted her based on her age, ethnicity, housing value and, of course, the make and model of her automobile. I’ve been doing this job for too long to be unaware of potential data variables and techniques that must have played a part so that my mother to receive a series of such letters. Basically, some jerk must have created a segment that could be named as “old and gullible.” Without a doubt, this is a classic example of what should not be done just because one can.

One might dismiss it as an isolated case of a questionable practice done by questionable individuals with questionable moral integrity, but can we honestly say that? I, who knows the ins and outs of direct marketing practices quite well, fell into traps more than a few times, where supposedly a one-time order mysteriously turns into a continuity program without my consent, followed by an extremely cumbersome canceling process. Further, when I receive calls or emails from shady merchants with dubious offers, I can very well assume my information changed hands in very suspicious ways, if not through outright illegal routes.

Even without the criminal elements, as data become more ubiquitous and targeting techniques become more precise, an accumulation of seemingly inoffensive actions by innocuous data geeks can cause a big ripple in the offline (i.e., “real”) world. I am sure many of my fellow marketers remember the news about this reputable retail chain a few years ago; that they accurately predicted pregnancy in households based on their product purchase patterns and sent customized marketing messages featuring pregnancy-related products accordingly. Subsequently it became a big controversy, as such a targeted message was the way one particular head of household found out his teenage daughter was indeed pregnant. An unintended consequence? You bet.

I actually saw the presentation of the instigating statisticians in a predictive analytics conference before the whole incident hit the wire. At the time, the presenters were unaware of the consequences of their actions, so they proudly shared employed methodologies with the audience. But when I heard about what they were actually trying to predict, I immediately turned my head to look at the lead statistician in my then-analytical team sitting next to me, and saw that she had a concerned look that I must have had on my face, as well. And our concern was definitely not about the techniques, as we knew how to do the same when provided with similar sets of data. It was about the human consequences that such a prediction could bring, not just to the eventual targets, but also to the predictors and their fellow analysts in the industry who would all be lumped together as evil scientists by the outsiders. In predictive analytics, there is a price for being wrong; and at times, there is a price to pay for being right, too. Like I said, we shouldn’t do things just because we can.

Analysts do not have superpowers individually, but when technology and ample amounts of data are conjoined, the results can be quite influential and powerful, much like the way bombs can be built with common materials available at any hardware store. Ironically, I have been evangelizing that the data and technology should be wielded together to make big and dumb data smaller and smarter all this time. But providing answers to decision-makers in ready-to-be used formats, hence “humanizing” the data, may have its downside, too. Simply, “easy to use” can easily be “easy to abuse.” After all, humans are fallible creatures with ample amounts of greed and ambition. Even without any obvious bad intentions, it is sometimes very difficult to contemplate all angles, especially about those sensitive and squeamish humans.

I talked about the social consequences of the data business last month (refer to “How to Be a Good Data Scientist“), and that is why I emphasized that anyone who is about to get into this data field must possess deep understandings of both technology and human nature. That little sensor in your stomach that tells you “Oh, I have a bad feeling about this” may not come to everyone naturally, but we all need to be equipped with those safeguards like angels on our shoulders.

Hindsight is always 20/20, but apparently, those smart analysts who did that pregnancy prediction only thought about the techniques and the bottom line, but did not consider all the human factors. And they should have. Or, if not them, their manager should have. Or their partners in the marketing department should have. Or their public relations people should have. Heck, “someone” in their organization should have, alright? Just like we do not casually approach a woman on the street who “seems” pregnant and say “You must be pregnant.” Only socially inept people would do that.

People consider certain matters extremely private, in case some data geeks didn’t realize that. If I might add, the same goes for ailments such as erectile dysfunction or constipation, or any other personal business related to body parts that are considered private. Unless you are a doctor in an examining room, don’t say things like “You look old, so you must have hard time having sex, right?” It is already bad enough that we can’t even watch golf tournaments on TV without those commercials that assume that golf fans need help in that department. (By the way, having “two” bathtubs “outside” the house at dusk don’t make any sense either, when the effect of the drug can last for hours for heaven’s sake. Maybe the man lost interest because the tubs were too damn heavy?)

While it may vary from culture to culture, we all have some understanding of social boundaries in casual settings. When you are talking to a complete stranger on a plane ride, for example, you know exactly how much information that you would feel comfortable sharing with that person. And when someone crosses the line, we call that person inappropriate, or “creepy.” Unfortunately, that creepy line is set differently for each person who we encounter (I am sure people like George Clooney or Scarlett Johansson have a really high threshold for what might be considered creepy), but I think we can all agree that such a shady area can be loosely defined at the least. Therefore, when we deal with large amounts of data affecting a great many people, imagine a rather large common area of such creepiness/shadiness, and do not ever cross it. In other words, when in doubt, don’t go for it.

Now, as a lifelong database marketer, I am not advocating some over-the-top privacy zealots either, as most of them do not understand the nature of data work and can’t tell the difference between informed (and mutually beneficial) messages and Big Brother-like nosiness. This targeting business is never about looking up an individual’s record one at a time, but more about finding correlations between users and products and doing some good match-making in mass numbers. In other words, we don’t care what questionable sites anyone visits, and honest data players would not steal or abuse information with bad intent. I heard about waiters who steal credit card numbers from their customers with some swiping devices, but would you condemn the entire restaurant industry for that? Yes, there are thieves in any part of the society, but not all data players are hackers, just like not all waiters are thieves. Statistically speaking, much like flying being the safest from of travel, I can even argue that handing over your physical credit card to a stranger is even more dangerous than entering the credit card number on a website. It looks much worse when things go wrong, as incidents like that affect a great many all at once, just like when a plane crashes.

Years back, I used to frequent a Japanese Restaurant near my office. The owner, who doubled as the head sushi chef, was not a nosy type. So he waited for more than a year to ask me what I did for living. He had never heard anything about database marketing, direct marketing or CRM (no “Big Data” on the horizon at that time). So I had to find a simple way to explain what I do. As a sushi chef with some local reputation, I presumed that he would know personal preferences of many frequently visiting customers (or “high-value customers,” as marketers call them). He may know exactly who likes what kind of fish and types of cuts, who doesn’t like raw shellfish, who is allergic to what, who has less of a tolerance for wasabi or who would indulge in exotic fish roes. When I asked this question, his answer was a simple “yes.” Any diligent sushi chef would care for his or her customers that much. And I said, “Now imagine that you can provide such customized services to millions of people, with the help of computers and collected data.” He immediately understood the benefits of using data and analytics, and murmured “Ah so …”

Now let’s turn the table for a second here. From the customer’s point of view, yes, it is very convenient for me that my favorite sushi chef knows exactly how I like my sushi. Same goes for the local coffee barista who knows how you take your coffee every morning. Such knowledge is clearly mutually beneficial. But what if those business owners or service providers start asking about my personal finances or about my grown daughter in a “creepy” way? I wouldn’t care if they carried the best yellowtail in town or served the best cup of coffee in the world. I would cease all my interaction with them immediately. Sorry, they’ve just crossed that creepy line.

Years ago, I had more than a few chances to sit closely with Lester Wunderman, widely known as “The Father of Direct Marketing,” as the venture called I-Behavior in which I participated as one of the founders actually originated from an idea on a napkin from Lester and his friends. Having previously worked in an agency that still bears his name, and having only seen him behind a podium until I was introduced to him on one cool autumn afternoon in 1999, meeting him at a small round table and exchanging ideas with the master was like an unknown guitar enthusiast having a jam session with Eric Clapton. What was most amazing was that, at the beginning of the dot.com boom, he was completely unfazed about all those new ideas that were flying around at that time, and he was precisely pointing out why most of them would not succeed at all. I do not need to quote the early 21st century history to point out that his prediction was indeed accurate. When everyone was chasing the latest bit of technology for quick bucks, he was at least a decade ahead of all of those young bucks, already thinking about the human side of the equation. Now, I would not reveal his age out of respect, but let’s just say that almost all of the people in his age group would describe occupations of their offspring as “Oh, she just works on a computer all the time …” I can only wish that I will remain that sharp when I am his age.

One day, Wunderman very casually shared a draft of the “Consumer Bill of Rights for Online Engagement” with a small group of people who happened to be in his office. I was one of the lucky souls who heard about his idea firsthand, and I remember feeling that he was spot-on with every point, as usual. I read it again recently just as this Big Data hype is reaching its peak, just like the dot.com boom was moving with a force that could change the world back then. In many ways, such tidal waves do end up changing the world. But lest we forget, such shifts inevitably affect living, breathing human beings along the way. And for any movement guided by technology to sustain its velocity, people who are at the helm of the enabling technology must stay sensitive toward the needs of the rest of the human collective. In short, there is not much to gain by annoying and frustrating the masses.

Allow me to share Lester Wunderman’s “Consumer Bill of Rights for Online Engagement” verbatim, as it appeared in the second edition of his book “Being Direct”:

  1. Tell me clearly who you are and why you are contacting me.
  2. Tell me clearly what you are—or are not—going to do with the information I give.
  3. Don’t pretend that you know me personally. You don’t know me; you know some things about me.
  4. Don’t assume that we have a relationship.
  5. Don’t assume that I want to have a relationship with you.
  6. Make it easy for me to say “yes” and “no.”
  7. When I say “no,” accept that I mean not this, not now.
  8. Help me budget not only my money, but also my TIME.
  9. My time is valuable, don’t waste it.
  10. Make my shopping experience easier.
  11. Don’t communicate with me just because you can.
  12. If you do all of that, maybe we will then have the basis for a relationship!

So, after more than 15 years of the so-called digital revolution, how many of these are we violating almost routinely? Based on the look of my inboxes and sites that I visit, quite a lot and all the time. As I mentioned in my earlier article “The Future of Online is Offline,” I really get offended when even seasoned marketers use terms like “online person.” I do not become an online person simply because I happen to stumble onto some stupid website and forget to uncheck some pre-checked boxes. I am not some casual object at which some email division of a company can shoot to meet their top-down sales projections.

Oh, and good luck with that kind of mindless mass emailing; your base will soon be saturated and you will learn that irrelevant messages are bad for the senders, too. Proof? How is it that the conversion rate of a typical campaign did not increase dramatically during the past 40 years or so? Forget about open or click-through rate, but pay attention to the good-old conversion rate. You know, the one that measures actual sales. Don’t we have superior databases and technologies now? Why is anyone still bragging about mailing “more” in this century? Have you heard about “targeted” or “personalized” messages? Aren’t there lots and lots of toolsets for that?

As the technology advances, it becomes that much easier and faster to offend people. If the majority of data handlers continue to abuse their power, stemming from the data in their custody, the communication channels will soon run dry. Or worse, if abusive practices continue, the whole channel could be shut down by some legislation, as we have witnessed in the downfall of the outbound telemarketing channel. Unfortunately, a few bad apples will make things a lot worse a lot faster, but I see that even reputable companies do things just because they can. All the time, repeatedly.

Furthermore, in this day and age of abundant data, not offending someone or not violating rules aren’t good enough. In fact, to paraphrase comedian Chris Rock, only losers brag about doing things that they are supposed to do in the first place. The direct marketing industry has long been bragging about the self-governing nature of its tightly knit (and often incestuous) network, but as tools get cheaper and sharper by the day, we all need to be even more careful wielding this data weaponry. Because someday soon, we as consumers will be seeing messages everywhere around us, maybe through our retina directly, not just in our inboxes. Personal touch? Yes, in the creepiest way, if done wrong.

Visionaries like Lester Wunderman were concerned about the abusive nature of online communication from the very beginning. We should all read his words again, and think twice about social and human consequences of our actions. Google from its inception encapsulated a similar idea by simply stating its organizational objective as “Don’t be evil.” That does not mean that it will stop pursuing profit or cease to collect data. I think it means that Google will always try to be mindful about the influences of its actions on real people, who may not be in positions to control the data, but instead are on the side of being the subject of data collection.

I am not saying all of this out of some romantic altruism; rather, I am emphasizing the human side of the data business to preserve the forward-momentum of the Big Data movement, while I do not even care for its name. Because I still believe, even from a consumer’s point of view, that a great amount of efficiency could be achieved by using data and technology properly. No one can deny that modern life in general is much more convenient thanks to them. We do not get lost on streets often, we can translate foreign languages on the fly, we can talk to people on the other side of the globe while looking at their faces. We are much better informed about products and services that we care about, we can look up and order anything we want while walking on the street. And heck, we get suggestions before we even think about what we need.

But we can think of many negative effects of data, as well. It goes without saying that the data handlers must protect the data from falling into the wrong hands, which may have criminal intentions. Absolutely. That is like banks having to protect their vaults. Going a few steps further, if marketers want to retain the privilege of having ample amounts of consumer information and use such knowledge for their benefit, do not ever cross that creepy line. If the Consumer’s Bill of Rights is too much for you to retain, just remember this one line: “Don’t be creepy.”

5 Things ’60 Minutes’ (Intentionally) Didn’t Tell Americans About Data Brokers

Kids, “60 Minutes” is no longer U.S. broadcast journalism at its former best—it’s pseudo-infotainment. Frankly, correspondent Steve Kroft and company had their own point of view that they wanted to report to whip up hysteria, and it wasn’t part of any of the data-driven advertising ecosystem that anyone of us practitioners recognize. Here’s what I know—that I want every consumer to know—and what CBS and “60 Minutes” should have told its viewers:

Kids, “60 Minutes” is no longer U.S. broadcast journalism at its former best—it’s pseudo-infotainment.

The Direct Marketing Association, my editor at Target Marketing, our friends at Direct Marketing News and The Magill Report were spot on with their responses.

Frankly, correspondent Steve Kroft and company had their own point of view that they wanted to report to whip up hysteria, and it wasn’t part of any of the data-driven advertising ecosystem that anyone of us practitioners recognize. Bryan Kennedy of Epsilon did yeoman’s work: Self-regulation exists because all marketers know that data is the currency of our livelihood, and consumer trust underpins us all.

Here’s what I know—that I want every consumer to know—and what CBS and “60 Minutes” should have told its viewers:

1. You Can Opt Out
For decades, Americans have had numerous free ways to “opt-out” of the data-sharing-for-marketing-use marketplace—and millions upon millions of Americans have taken advantage of these free industry-offered programs:

  • DMAChoice, offered by DMA, allows industry-wide opt-out of prospect direct mail, email, do-not-call (for selected states) and unaddressed mail delivery.
  • Nearly all consumer brands also offer their own preference centers and in-house suppression lists on their Web sites and Privacy Policies—both for do-not-send and for do-not-share, bridging multiple channels. Many business brands also do the same.
  • More recently, the Digital Advertising Alliance and its Consumer Choice Page provides an industry-wide opt-out mechanism for targeted display ads online that are served (in a de-identified basis, by the way) based on browsing behavior. Consumers can harden their choices against cookie removal once each opt-out choice is made.
  • A similar opt-out mechanism for mobile interest-based advertising from DAA is now in the works.

2. Marketing Data Is Used for Marketing Only
Every code of conduct and every ethics guideline in our business states this clearly. Furthermore, firewalls exist between marketing data (our business’s data sources) and individual referential data (information used for private investigation, employment, credit, insurance eligibility). If “60 Minutes”—or a consumer, or anyone else for that matter—has evidence that a marketer or service provider is sharing, renting or selling marketing data for non-marketing uses, the DMA’s Committee on Ethical Business Practice would want to be first to know—so as to investigate and bring any organization into compliance. Hypotheticals and inferences are not reality, despite the innuendoes used by Kroft.

3. Sensitive Data Are Already Regulated
Areas of sensitivity that most consumers care about—personally identifiable data related to their children, financial data, health information, credit data and a few other categories—are already regulated under federal law. Marketers must adhere to these laws and regulations.

4. Fraud Is Not Marketing
Another sensitive area—where and when marketing data is breached with a likelihood for fraud—you’ll find that most marketing organizations indeed want one national standard (not 50 plus one) for how consumers are notified and what protections they are afforded. Fraud prevention—as well as data governance and data stewardship—is a heightened priority for all businesses and organizations that rely on consumer information.

5. Data Benefits Customers
Data used for marketing purposes should be a government concern: not on how to stop it—but how to promote it, both domestically and globally, to benefit consumers and the economy. On the whole, consumers demand relevance. They demand recognition. They crave personalization. And every day—millions of times a day—they vote with their wallets: They shop, they donate, they subscribe, they raise their hands, all based on their participation in commerce. Marketing data also enables competition and the innovation and variety of choices consumers enjoy. As DMA has ably documented, marketing data exchange generates sales, jobs and tax revenue—and, might I add, satisfied consumers. Yes, we need consumer protection from fraud, bad players and unfair and deceptive practices—but “our data-driven economy” is a hugely wonderful default.

Which begs the question: Where is the harm, “60 Minutes”?