1 Year Later: Gen Z College Students Weigh in Again on Personal Data Collection

Last February, I reported on some of the things my Gen Z students wrote in response to an assignment about who gains the most from the value exchange of convenience-for-personal-data. A year later, I gave the same assignment with the same supplemental readings to students, and the results were notably different.

Last February, I reported on some of the things my Gen Z students wrote in response to an assignment about who gains the most from the value exchange of convenience-for-personal-data between consumers and marketers.

A year later, I gave the same assignment with the same supplemental readings to a similar group of 40 students from Rutgers School of Business Camden, and the results were notably different.

Last year, I wrote, in “Gen Z College Students Weigh-in on Personal Data Collection — Privacy Advocates Should Worry”:

“Some Gen Zers don’t mind giving up their personal data in exchange for the convenience of targeted ads and discounts; others are uneasy, but all are resigned to the inevitability of it. However, the language they use to describe their acquiescence to data collection should be troubling to privacy advocates.”

This year’s students are far more concerned about the collection and sale of their personal data, but they are just as resigned to the inevitability of it. At the same time, some bask in the advantages it brings them and they’re sympathetic to the needs of marketers to provide a personalized data-driven experience to consumers.

The privacy concerns of the current group are more pronounced than the previous group.

“I used to believe that the consumer benefitted from the perks of technology. But more and more, I believe that marketers benefit more. Social media, search engines, TVs, refrigerators, Alexa or Google Home, Kinsa Thermostat are all ways that marketers can reach the consumer with things we use in our everyday lives. Some people don’t even realize they’re feeding right into it just by providing some information about yourself.”

Another wrote:

“Privacy has almost become a thing of the past. Places like our kitchens, bathrooms, and bedrooms have transformed from places behind closed doors to areas that are willingly shared with thousands of others on the receiving end of the data being collected for business purposes.”

Yet, like last year’s group, they are resigned to giving up personal data for access to information and services.

“Consumers are beginning to realize how often what they do, speak, and read are all being recorded. Personally, I’ve been more aware than ever of what is being tracked. I’m more aware of every ad I look at and every website I clicked on. This lifestyle is something that can’t be avoided.”

A common complaint involves the lengthy user agreements that consumers must accept to use web-based services and Internet-connected devices:

“This type of ultimatum often means that consumers regularly grant permission on their personal devices, rather than lose their access to a particular product.”

The proliferation of the Internet of Things may be behind much of the change in attitude since last year. (Caveat: I confess that I’ve warned about small sample sizes in the past [“Beware the Small Sample”]. I’m not drawing quantitative conclusions here, but rather reporting on a trend from qualitative research done with 40 students each year).

“Some people who purchase these tech-savvy devices often don’t understand the policies of the product. Understanding the policy and happily opting-in for your information to be used is one thing, but complying because you’re unsure is another. Did you know that brands can start tracking your information at the age of 13? How can a child understand the policy and process of how this works if a grown adult cannot?”

Another stated:

“The terms of agreement can exceed 10,000 words and not be accessible unless the consumer searches the web for it. Consumers don’t get the full story of how much the companies invade their personal lives. Even aspects like your political preference are being monitored and can aid in influencing your votes.”

One student is mounting a fierce resistance:

“I am one of those people that have a Post-it over the camera on my laptop. I shut off the location on my phone, even though I feel like it is being monitored without my consent a lot of the time. My smart TV is not connected to the Internet, and I rarely use streaming devices, such as Netflix or Hulu — if I do, it is usually on my computer. Devices like Google Home and Alexa completely freak me out and I do not believe I would ever purchase one for my home. Even some of the newer home security systems — like Xfinity Home or the video doorbell, Ring — introduce new ways for people to hack in and monitor your personal activity.”

Data leaks and potential misuse are another concern. One student worried about home assistant devices mishearing innocuous phrases as legitimate commands to record and send private conversations:

“Families could be going through a family matter and these devices are listening and recording what is being said. Next thing you know, it is being sent to your boss or colleagues who did not need to hear or know what is going in in the comfort of your home. Also, the refrigerators that know exactly what is inside can share this information with marketers who then share it with insurers who can possibly charge consumers more for unhealthy diets.”

But it’s not all gloom and worry. One student who recently booked a trip to Disney World was delighted by the collection and use of her personal data:

“Being able to get discounted magic bands and Disney exclusive accessories catered for my needs has been a huge bonus. This also benefits Disney, as they are getting my credentials and can alter their research based on my specific data. A part of the reason they are so successful is because of how personal they make the process feel. Even from the first search, they are there to help guide you and aid in your conversion to purchase. (They) get you to come back, because they have that initial information and the personal details of your preference.”

(BTW, how great is Disney? Offering discounts on those magic bands that they use to track your movement and purchases throughout the park. They not only get you to agree to it, they get you to pay for it and be grateful for the discount).

So the time may be right for privacy advocates to gain a foothold among the generation whose members have gone so willingly into the world of sharing personal data.

Automation — With a Little Help From Good Machines

Some claim that human behaviors are just algorithmic responses developed over past 70,000 years or so. Now, armed with data that we are casually scattering around, machine-based algorithms outperform human brains in most areas already, and such evolution will continue.

We should be mindful when dropping buzzwords (refer to “Why Buzzwords Suck”). As more and more people jump on the bandwagon of a buzzword, it tends to gain magical power. Eventually, some may even believe that buying into a “word” will solve all their problems.

But does it ever work out that way? Did anyone make a fortune buying into the Big Data hype yet? I know some companies did; but, ironically, the winners do not even utter such words. I’ve never seen any news release from Google or Amazon that they are investing in “Big Data.” For them, playing with large amounts of data have been just part of their businesses all along.

Now the new buzz is about AI, machine learning and automation, in general; and it will be a little different from buzzwords from the past. Whether we like it or not, that is the direction that we are already headed in the world where each decision will be increasingly more dependent on deterministic algorithms.

Some even claim that human behaviors are just algorithmic responses developed over past 70,000 years or so. Now, armed with data that we are casually scattering around, machine-based algorithms outperform human brains in most areas already, and such evolution will continue until most humans will become largely irreverent in terms of economic value, they say. Not that it would happen overnight, but the next generation may look at our archaic way of things the way we look at our ancestors who were without computers.

First, the Marketing Case for AI

If such is our fate, why are contemporary humans so willingly jumping onto this automation bandwagon where machines will make decisions for us? Because they are smarter than average humans? What does “smart” even mean when we are talking about machines? I think people generally mean to say that machines remember details better than us, and calculate a complex series of algorithms faster and more accurately than us.

Some may say that humans with experiences are wiser with visions to see through things that are not seemingly related. But I dare to say that I’ve seen machines from decades ago finding patterns that humans would never find on their own. When machines start learning without our coaching or supervision — the very definition of AI — at a continuously increasing rate, no, we won’t be able to claim that we are wiser than machines, either. In the near future, if not already.

So, before we casually say that AI-based automation is the future of marketing, let’s ask ourselves why we are so eager to give more power to machines. For what purpose?

The answer to that philosophical question in the business world is rather simple; decision-makers are jumping onto the automation bandwagon to save money. Period.

Specifically, by reducing the number of people who perform tasks that machines can do. As a bonus, AI saves time by performing the tasks faster than ever. In some cases — mostly, for small operations — machines will perform duties that have been neglected due to high labor costs, but even in such situations, automation will not be considered a job-creating force.

Making the Marketing Case for Humans Using Data

Some may ask why I am stating the obvious here. My intention here is to emphasize that automation, all by itself, doesn’t have the magic power to reveal new secrets, as the technology is primarily a replacement option for human labor. If the result of machine-based analytics look new to you, it’s because humans in your organization never looked at the data the same way before, not because it was an impossible task to begin with. And that is a good thing as, in that case, we may be talking about using machine power to do the things that you never had human resources for. But in most cases, automation is about automating things that people know how to do already in the name of time and cost savings.

Like any other data or analytics endeavors, we must embark on marketing automation projects with clear purposes. What would be the expected outcome? What are you trying to achieve? For what types of tasks? What parts of the process are we automating? In what sequence?

Just remember that anyone who would say “just automate everything” is the type of person who would be replaced by machines first.

At the end of that automation rainbow, there lie far less people employed for given tasks, and only the logical ones who see through the machines would remain relevant in the new world.

Nonetheless, providing purposes for machines is still a uniquely human function, for now. And project goals would look like those of any other tasks, if we come back to the world of marketing here. Examples are:

  • Consolidate unorganized free-form data into intelligent information — for further analyses, or for “more” automation of related tasks. For instance, there are thousands of reasons why consumers call customer service lines. Machines can categorically sort those inquiries out, so that finding proper answers to them — the very next logical step — can also be automated. Or, at least make the job easier for the operator on the call (for now). Deciphering image files would be another example, as there has been no serious effort to classify them with sheer manpower in a large scale. But then again, is it really impossible for humans to classify large numbers of images? How about crowdsourcing? Or let an authoritarian government force a stadium-full of North Koreans to do it manually? We’d use machines, because it would be just cheaper and faster to do it with machine learning. But who do you think corrected wrong categorization done by machines to make them better?
  • Find the next, best product for the buyer. This one is quite a popular task for machines, but even a simple “If you bought this, you would like that, too” type of product recommendation would work far better if input data (i.e., product descriptions and product categories) were well-organized — by machines. Machines work better in steps, too.
  • Predict responsiveness to channel promotions and future value of a customer. These are age-old tasks for analytics teams, but with sets of usable data, machines can update algorithms and apply scores, real-time, as new information enters the system. Call that AI, if algorithms are updated automatically, all on its own. Actually, this would be easier for a machine to pick up than fixing messy data. Not that they will know the difference between easy and difficult, but I’m talking about in terms of ease of delegation, from our point of view.
  • Then ultimately, personalize every interaction with every customer through every touch channel. I guess that would be the new frontier for marketers, as approaching personalization on such massive scale can’t be done without some help from good machines. But I still stand by my argument that each component of personalization efforts is something that we know how to do (refer to “Key Elements of Complete Personalization”). By performing each step much faster with machines, though, we can soon reach that ultimate level of personalization through consolidation of services and tasks. And the grand design of such a process will be set up by humans — at least initially.

This Human’s Final Thoughts on AI

These are just some examples in marketing.

If we dive into the operational side, there will be an even richer list of candidates for automation.

In any case, how do marketers stay a step ahead of machines, and remain commanders of them?

Ironically, we must be as logical as a Vulcan to control them effectively. Machines do not understand illogical commands, and will ignore them without any prejudice (but it would “feel” like disrespect to us).

Teaching Humans to Automate

I heard that some overzealous parents started teaching computer programming to 4- or 5-year old children, in addition to a foreign language and piano lessons. That sounds all Cool and the Gang to me, but I wondered how they would teach such young kids how to code.

Obviously, they wouldn’t teach them JavaScript or Python from Day 1. Instead, they first teach the kids how to break down simple tasks into smaller steps. For example, if I ask you to make a grilled cheese sandwich, you — as a human being — will go at it with minimal instruction. Try to order an imaginary machine to do the same. For the machine’s sake, it won’t even know what a grilled cheese sandwich is, or understand why carbon-based lifeforms (especially gluttonous humans) must consume such large quantities of organic materials on a regular basis.

Teaching Machines to Human

If you try it, you will find that the task of writing a spec for a machine is surprisingly tedious.

Just for a little grilled cheese sandwich, you have to:

human automation, the grilled cheese story
Photo by: Christoher Del Rosario (www.christopherdelrosario.com) | Credit: Getty Images by Christopher Del Rosario / EyeEm
  • instruct it on how to get to the breadbox,
  • how to open it,
  • how many slices of bread should be taken out,
  • how to take them out without flattening them (applying the right amount of pressure),
  • how to open the refrigerator,
  • how to locate butter and cheese in the mix of many food items,
  • how to peel off two slices of cheese without tearing them,
  • how to ignite a stove burner,
  • how to find a suitable pan (try to explain “suitable,” in terms measurements and shape),
  • how to preheat the pan to a designated temperature (who’d design and develop the heat censor?),
  • how to melt butter on the pan without burning it,
  • how to constantly measure and monitor the temperature,
  • how to judge the right degree of “brown” color of grilled cheese,
  • etc. etc..

If you feel sick reading all of this, well, I didn’t even get to the part about serving the damn sandwich on a nice plate yet.

Anyway, Human Marketers, Here’s the Conclusion

I am not at all saying that all decision-makers must be coders. What I am trying to emphasize is the importance of breaking down a large task into smaller “logical” steps. Smart machines will not need all of these details to perform “known” tasks (i.e., someone else taught it already). And that is how they get smarter. But they would still work better in clear logical steps.

For humans to command machines effectively, we must think like machines — at least a little bit. Yes, automation is mostly about automating things we already know how to do. We use machines to perform those tasks much faster than humans. To achieve overall organizational effectiveness, break down the processes into smaller bits, where each step becomes the stepping stones for the next. Then prioritize which part would be the best candidate for automation, and which part would still be best served by human brains and hands.

For now, that would be the fastest route to full automation. As a result of it, many humans may be demoted to jobs like reading machine-made scripts to other humans on the phone, or delivering items that machines picked for human consumers in the name of personalization. If that is the direction where human collectives are headed, let’s try to be the ones who provide purposes for machines. Until they don’t even need such instructions from us anymore.

Data, Data Everywhere: Nary a Bargain to Find?

Stephen Yu’s recent and extremely thought-provoking piece on AI started me wondering once again about the dangers of data overload and whether we’ll ever really, really understand the purchasing decisions people make, how they make them and be able to track them accurately.

Data mining
“Big_Data_Prob,” Creative Commons license. | Credit: Flickr by KamiPhuc

Stephen Yu’s recent and extremely thought-provoking piece on AI started me wondering once again about the dangers of data overload and whether we’ll ever really, really understand the purchasing decisions people make, how they make them and be able to track them accurately.

Because today’s machines gobble data and — like my dog eats anything he can get jaws around — we marketers seem to search for more and more bytes in the hope that sifting through this mega data will hold the keys to the holy grail of maximum profitability. Perhaps it will. But as a disciple of Lester Wunderman, I can’t let go of his oft-expressed prescient warning that “Data is an expense. Knowledge is a bargain.”

Admittedly, when this was first expressed, data was one hell of a lot more expensive to keep and handle than it is today and shaking knowledge out of it was very difficult. But that’s hardly the point. Our trade press is now overflowing with titles like “Planning and Measuring Social Media Campaigns” (Sysomos), the “Email Marketing Metric You May Not Know” and unnumbered guides to the customer journey. But I’m still waiting for the definitive article that leaves all of the peripheral data by the side of the road and presents a usable and believable knowledge-based metric model to measure the cost of each step in the journey from awareness through to final purchase. In today’s multi-media environment, that’s the metric model we are all waiting for. Will we ever get it? Will AI provide it? I’m not so sure.

There is historically a different focus between top management whose attention is quite sensibly on macro numbers and operational marketers who know that it is the micro numbers that spotlight big opportunities. The ROMI, the return on the total marketing investment, is the bottom line for both: How much did we earn for how much marketing money invested? Simple.

But at what milestones in the customer journey did the momentum toward purchase increase and at what others did the potential customer take a turn away from purchase and why? That’s the type of data we need if we are to optimize our practice and it will surely impact the ROMI. Sadly in many cases, we will never know.

Recently, some of my Brazilian colleagues created a very strong email campaign as the first stage in persuading well-segmented prospects to clickthrough to a website to register interest and gain a price advantage in making a major purchase. The client reported that while the website was receiving a lot of activity, only a tiny fraction came as the expected clickthrough from the emails. The client was understandably angry and it didn’t make any sense.

Every adult Brazilian has a unique CPF number, which is regularly requested and used to identify the individual in financial transactions. It’s rather like an American Social Security number. Because my colleagues were fortunate enough to have the CPFs of the prospects to whom the emails had been sent and as registration on the website also required a CPF, it was a relatively easy task to compare the two groups to determine how many of the registrants had been sent the emails, even if they hadn’t availed themselves of the clickthrough option. It turned out to be a happily large percentage.

While research has been undertaken to determine why, any measurement of the relation of emails to registrations and their cost would have been both misguided and meaningless. If the marketers had decided to stop using the emails because, as they said, ”emails didn’t generate any response,” they would have been making a critical error.

Perhaps that’s a long way around the issue of just why, with all of the enormous data and sophisticated tools at our disposal, we just can’t develop a meaningful metric model that reliably tracks the prospect along the path to becoming a customer. And it argues that while AI will certainly add valuable knowledge, getting inside the head of a prospect and truly understanding his/her actions is a long way off.

Top Holiday Season Digital Trends

The holiday season is nearly in full swing. How will it be different than past seasons? The most striking difference is not in what consumers are buying, it’s how they are shopping. Consumers have been gravitating toward digital over the past decade, but this year, shoppers have indicated that they will pass a new threshold.

The holiday season is nearly in full swing. How will it be different than past seasons? The most striking difference is not in what consumers are buying, it’s how they are shopping.

Consumers have been gravitating toward digital over the past decade, but this year, shoppers have indicated that they will pass a new threshold. For the first time, they anticipate making the majority (51 percent) of their holiday purchases online, according to a study by Synchrony Financial*. This has been steadily increasing over the past three years, up from 47 percent in 2015 and 49 percent last year.

Synchrony Holiday Season Shopping StatsWhich devices will they be using to make these purchases? Consumers indicate that one in five holiday purchases will be made on their mobile device. So, not only is shopping trending toward online purchases, many shoppers are planning to do it on-the-go.

Shoppers like mobile because, quite frankly, it’s easy and always around. The mobile device is with the shopper continuously. Whether riding on a bus, waiting in line for coffee or binge watching your favorite Netflix show. If you think of the perfect gift for Aunt Helen, you can order it immediately. And, not to worry about keeping track of your purchases — half of mobile shoppers say they use mobile because they can easily view the confirmation in their email.

And, discount hunting via mobile is ubiquitous. More than one-third (36 percent) of shoppers say they will shop via mobile during the holiday season because they can more easily link their email offers and coupons to their purchases. So, bargain hunters don’t have to worry about missing out on a good deal. The ability to scan available coupons and download offers gives shoppers confidence that they are getting the best price.

With the ease of shopping online and the widespread availability of next-day shipping, consumers may be less rushed to get their shopping done early this holiday season. Only 44 percent of consumers say they will be shopping earlier this year. Last year, 53 percent said they would be shopping earlier than in the past.

And, shoppers are less likely to be “hunting for a deal” on specific days like Thanksgiving, Black Friday or Cyber Monday. This is perhaps due to the prevalence of deal hunting throughout the season. Consumers have been less hooked on shopping on specific days, if they are certain they can find the best price on any given day.

How are retailers responding to these trends? One way is having websites that are optimized no matter which device consumers use — laptop, tablet or mobile. Retailers are spending time and resources building websites that are easy to navigate and intuitive. The experience is important — the top reason shoppers delete a retailer app is due to poor functionality, according to the Synchrony Financial 2017 Digital Study.

Also, shipping will be a big element of the online shopping experience this year. Many retailers have graduated from two- to three-day shipping to one-day, or next-day shipping. And, since shoppers say they will be shopping later in the season, this will be a big deal this year.

Finally, and perhaps most important, bargain hunting remains a key ingredient in the shopping habits of consumers, whether they are early bargain hunters or last minute deal seekers. The ability to check product reviews, compare prices and use coupons is a key part of the holiday shopping experience. If the consumer can do it all on one website, great! If not, off they go to the next retailer.

* Note: The views expressed in this blog are those of the blogger and not necessarily of Synchrony Financial. All references to consumers and population refer to the survey respondents from the Synchrony Financial 2017 Pre-Holiday Study unless otherwise noted.

Will the Internet of Things Make Us Dumb?

As CES wrapped in early January, all things shiny, cool and tech were on the top of many people’s minds, from the consumers who want to buy them, to the journalists who write about them, and to the marketers who must, simply put, market them.

Brace yourself, more useless smart devices are comingAs CES wrapped in early January, all things shiny, cool and tech were on the top of many people’s minds, from the consumers who want to buy them, to the journalists who write about them, and to the marketers who must, simply put, market them.

Even my publisher stopped by my desk to get my opinion on the Picobrew, given my experience as a homebrewer. While I still need to do more reading, I’ve had a tough time finding an explanation for how the device actually works and if it brews well, but I did find an article likening it to the Keurig of beer, and well, gross.

Picobrew aside (I swear Drew, I’ll wrap up my research and get you a formal opinion by Spring at the latest), Smart Devices and the Internet of Things (IoT) have been on my mind ever since seeing the following tweet from Sally Ekus, a cookbook-focused literary agent who I follow:

I like tech. I love to cook. And I’m a millenial, so I clicked on Sally’s link and dove into Allrecipe’s “Measuring Cup Trend Report,” (opens as a PDF) featuring information from its 2016 Smart Kitchen Survey.

Some of the report was pretty interesting, but a fair bit of the new IoT product information felt borderline absurd. Like this gem of a product:

Sereneti Cooki Robotic Chef
In the early stage of development, inexperienced cooks and busy, working families will love the convenience of having a robot such as Cooki do the cooking for them so hot, perfectly prepared meals are ready to eat the minute they arrive home.

You know what that’s called? A slowcooker. Trust me, they’re amazing. If you can’t bear the idea of having a “dumb” one, don’t worry. There’s one with wifi that can be controlled with the WeMo app. Bon appétit.

I’ll Pass on the Vibrating Finger Bling, Thanks

Cruising through my Facebook feed the other day, I found a sponsored post for Ringly. Don’t get me wrong … I find new tech exciting and a lot of it blows my mind, like Tesla’s electric car technology and 3D-printed prosthetic limbs. But a ring that tells me, via lights and vibrations, that I have a text message?

Cruising through my Facebook feed the other day, I found this sponsored post nestled between my women’s cycling group post about vehicle safety and a college bestie’s status update:

Ringly Facebook Sponsored PostI actually uttered, “What the …” A ring that pairs with your smartphone to notify you of “what matters”?

Don’t get me wrong … I find new tech exciting and a lot of it blows my mind, like Tesla’s electric car technology and 3D-printed prosthetic limbs. But a ring that tells me, via lights and vibrations, that I have a text message?

No. No thank you.

Now, before I got too steeped in curmudgeoness, I decided to look up Ringly, check out the wearable’s website — which is rather pretty — and read a few articles to better understand the device.

https://youtu.be/C5c06ayfTYs

The video … well, first, a lady prancing rather carefree doesn’t help sell this to me. If she’s so carefree, then couldn’t she handle picking up her phone to read notifications (or just ignore them)? What about the rest of us, juggling work and personal emails, social media notifications, phone calls from our mothers, etc., while still functioning in the offline world?

Then the opening line kills it for me: “With Ringly, you can live freely while staying connected to the things that matter most.”

First World Problem MemeI have SO many problems with this. People need to stop subscribing to this #firstworldproblem that we HAVE to be tethered to our phones. Are many of us? Yes. The solution? Put it down. Turn it off. You don’t need MORE solutions beyond that.

In other words, I strongly feel I don’t need to spend $195 for a heavy “smart” ring that will only last three years (you can’t replace the battery) to live freely. Maybe this makes me a bad millennial, or bad techie, but I just can’t do it.

Reading a review of Ringly on Tech Insider, the ring the reviewer received was described as bulky, with one coworker telling her it looked like “a toy that you might find in a gumball machine for 50 cents.” Another article from TechCrunch explained how, unlike the AppleWatch or Pebble, Ringly only notifies you — it doesn’t let you take action.

I understand that the team from Ringly is trying to stake its claim on the wearable-as-classy-jewelry market. But it failed on the classy jewelry side, and to be honest, it has me wondering if they really asked themselves the most important question: “Why?” Why are we doing this?

A bulky, vibrating, lighting-up piece of jewelry that is possibly more distracting than having your phone out? Is this a piece of wearable technology that is really necessary?

You tell me. Leave me a comment below!