Category Archives: Targeting

The real reason consumers are creeped out by online ads

(Originally published in iMediaConnection, September 2010) by Eric Picard

Direct response marketers have been using various statistical models for decades to determine how to predict human behavior. They’ve built proven models that can help a marketer reach a highly targeted audience with a high degree of reliability and show that audience a message that has a higher probability of success than a random untargeted message. The easiest way to see this at work is to buy a house.

Two years ago, I bought a house (my timing was impeccable). Within weeks of my mortgage closing, I began to receive all sorts of interesting things in the mail. This was interesting because I explicitly opted out of having the data from my mortgage shared with anyone (or so I thought). As it turns out, this isn’t really possible — at least, I wasn’t able to pull it off, and I am aware of how the DR industry works. The average consumer hasn’t got a chance.

The kinds of mail I began receiving included lots of offers for things like mortgage refinance (despite that I had only bought my house weeks before), various types of insurance (most were flavors of home warranties), and then literally hundreds (possibly thousands) of offers from local businesses to try their services. This included some that were logical and tied to my physical relocation to a new neighborhood — various dentists, hair salons, landscapers, accountants, hardware stores, and roofing companies.

The DR industry has statistical models that clearly show the series of marketing opportunities that are associated with major life events. So when you have a baby, there are many things you’re likely to need to buy. When you buy a house, it’s very similar (in fact, these events are highly correlated). For instance, having a baby frequently is followed by purchasing a new (and safer or more spacious) car, SUV, crossover, or minivan. Life insurance is another highly correlated purchase.

These models are built, and the “sensing” mechanisms flow out into the various sources of publicly available data, as well as numerous private sources of data like financial services companies. For decades, your every credit card purchase has been carefully scrutinized and analyzed and applied against highly refined statistical models to figure out what opportunities exist to sell you other products and services.

Many people have begun to realize this — but it took decades to build the systems, and decades more to have the knowledge of its existence permeate the culture. So by the time you read this, many of you have simply accepted that this is standard practice. You’ve come to terms with your outrage at the fact that, without explicitly asking for your permission, data about your private life has been used to segment you into various buckets in order to more effectively market to you.

One of the major problems with this traditional direct response marketing is the massive expense behind it. Despite being a highly profitable, high-revenue business, it’s extremely expensive to operate. Building the statistical models, mining the data across numerous sources, and then building personalized (not private in any way, mind you) profiles against which to sell the personal contact information you’ve amassed — including phone numbers, physical home addresses, and names — isn’t cheap. And when it first started out, the costs were much higher because computing power was relatively much more expensive.

And that’s been the problem with DR since it began: Building these mailing lists of highly personalized targeting opportunities is so expensive, the pools of individuals who match them are so small, and the amount of time that the data are fresh and relevant is so short that the opportunity for any single marketer to reach target audiences is pretty small. Maintaining the freshness of the data is a big part of the expense. From a marketer’s perspective, the decision to use these mechanisms is quite simple — the response rates are well known and the ROI decision is easy. But the number of customers any one company can create using these tools is low enough that other forms of marketing are needed.

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If the benefits of DR are its targeted, effective nature and clear ROI, its handicap is the limited audience size for any one company. DR is like fly fishing; pick the fly that will work on that specific type of fish and get the fly into the right location at the right moment. Good old brand advertising has nothing to fear from DR for this reason. The benefit of brand advertising is that you reach a large-scale audience at a low cost and get your message to the masses. Brand advertising is like fishing with a big net; you catch a lot of fish, but you have to throw a lot of them back because they weren’t what you were looking to catch. The problem is, at these large scales, the ability to know how effectively you’re reaching the ideal audience is pretty limited.

Over time, a secondary market of service providers using panels of users that fit various criteria has developed. And at very large scale, marketers have been able to look at various media planning tools for decades that can show them the likelihood of reaching a desired audience based on association of the audience with various television shows, magazines, radio stations, newspapers, etc. But all these tools show is that there is a probability of reaching a certain relatively broad type of audience (e.g., women in a certain age group). But this is better than nothing and has worked fairly well.

And thus the market flourished. And along came online advertising.

When online advertising began, many saw this as the holy grail of marketing. Finally (they said) here is a place where computers are deeply integrated by nature, and we can combine the two methodologies: We can build systems that enable DR and brand advertising to coexist, and eventually we can find a way to do both things. We can reach highly targeted audiences at large scale and low cost and dynamically generate targeting profiles that radically improve ROI.

I cannot tell you how many meetings over the past 15 years that I’ve been in where the conversation flowed essentially like this. “What we’re really trying to do is build a database with one row for each person on the planet, and one column for each targeting attribute we believe we can sell to marketers.” This 6 billion row database with millions of columns has been theoretical of course; neither the technology to pull it off nor the reach to every person on the planet has been available.

And there is, of course, the major issue with privacy that keeps coming up and biting this industry on the backside. Whereas it took decades for the idea of big DR databases with personal data to permeate into the culture, online advertising showed up when the issues were a lot clearer to most people. And since the state of the art of behavioral targeting has begun to show some noticeable results, people are beginning to get “creeped out.” Recent Wall Street Journal and New York Times articles have highlighted how the industry has begun to change; they’ve talked about all the various targeting tags all over the commercial web that track interest and behavior. Users are noticing targeted ads, for better or worse. And the consumer response typically has been something along the lines of, “Who gave you the right?!”

Recently a friend of mine said that she had searched for a specific pair of shoes online, added them to the shopping cart of a website, and then decided to hold off on the purchase. For the next few days, she saw ads for that specific pair of shoes on numerous websites as she surfed across the web. She didn’t find this targeting of a relevant ad to be useful or “less annoying” than non-targeted ads. She found it creepy.

When I talk to people in our industry about the issues surrounding privacy and targeting, they frequently fall back on the defensive leg of providing consumers with more relevant advertising. They say that that once ads are more relevant, consumers will resent advertising less — that they might even like it. I’ve used these arguments myself in the past. The reality is that consumers would benefit from more relevant ads and might resent advertising less if the content of those ads matched better against their interests. But when we make them feel like someone is watching over their shoulders as they do things online, make no mistake — they resent it.

The example of comes up frequently in conversations around our industry. Amazon inherently shows products that match the kinds of things you’ve shopped for or purchased in the past. And often I’ve heard examples like, “When I go into a store and the shopkeeper recognizes me and makes a recommendation for me, I like it, and I begin to frequent this store more often because of the personalized service.”

But the reality is that this is a direct relationship that the consumer has with a specific merchant. It’s a one-on-one relationship that gives specific benefit and that has a clearly understood set of relationship rules. One colleague recently described behavioral targeting like this: “It’s like you are shopping in a store, and a guy in dark sunglasses and a trench coat is following you around and whispering into his watch. Then when you go into another store, he sidles up to the merchant and whispers in her ear that you were just shopping for negligee in another store down the street, and that you seem to prefer underwire cups.”

The reality of behavioral targeting is not far off from this example, and this seems to be missed by the marketing industry. Ultimately, consumers will decide what is and isn’t acceptable to them, and beware the marketing industry executives who believe they will make that decision on the consumer’s behalf. Now that people are relatively aware of the DR marketing practices in the traditional world, they are getting fed up with them in the online world, where they felt relatively anonymous and private. Consumers recognize that might know a lot about their purchase and shopping behavior while on that particular website; however, they would likely feel very uncomfortable if that data were then sold on the open market without their explicit permission to any advertiser willing to pay for it. Politicians have become aware of this growing consumer resentment, meaning that legislation is likely not far behind.

The online advertising industry isn’t wholly clueless, and many have been trying to come up with new approaches that they feel are less antagonistic to consumers, while still providing value to advertisers. In future articles, I’ll be exploring some of the ways that companies are thinking about the problem and beginning to address the issues.

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Fixing Online Advertising’s Privacy Woes

(Originally published in iMediaConnection, August 2010) by Eric Picard

Privacy is something I’ve been concerned about for some time when it comes to online advertising. John Hagel and Marc Singer’s excellent book “Net Worth” raised the issue in a significant way for me from a business perspective, way back in the ’90s, and Cory Doctorow’s recent novel “Little Brother” paints a bleak picture of what could happen to private citizens if privacy isn’t carefully guarded.

I raise this, of course, because of the recent Wall Street Journal and New York Times articles that have raised the specter of major privacy concerns because of the widespread tracking done by numerous parties in the online advertising space. I began worrying about the likelihood that targeting and privacy would begin to clash in a significant way back in 2004 when I started to understand what was going to happen with display advertising as we moved as an industry away from selling mainly context-based display ads and toward personalized, highly targeted audience-based display ads. And as we began moving toward automated buying systems and real-time bidding for ads based on audience attributes over the last five years, I knew we were in for it once again. From my point of view, it’s always been about when, not if, we were going to run into a consumer backlash against how much data we can (and do) collect in the online space.

Of course, the part that is a little ironic is that very detailed tracking of purchasing behavior and extrapolation of that behavior to other personal life stages and psychographic profiles (a process that is pretty accurate) of each person’s behavior has been common for decades via credit cards, financial services, and offline (traditional) targeting for direct marketing. And for the most part this hasn’t been widely reviled by the press, nor has it caused a consumer backlash against so-called massive mega-corporations with vast amounts of data about what we personally buy, do, and who we are.

Yes, it’s ironic that traditional marketing media have been tracking far more data than we can today online, and yes, it really could be interpreted that we are “less bad” than our traditional media cousins. However, this is not really a strong defensive statement, though it is still frequently stated by my colleagues in this industry. Perhaps only slightly less frequently than that other old nugget about consumers getting the benefit of “more relevant” or “personalized advertising” if they submit to being tracked for the purposes of selling targeted advertising against their anonymous profiles. This is, of course, only a statement I’ve ever heard espoused by folks in the online advertising industry — and not something consumers are consciously happy or excited about, nor something almost any consumer would react positively to.

It’s a bad meme — something we as an industry know to be true (after all, many magazines, as an example, are bought just as much to see the ads as read the articles. Think fashion, home improvement, and technology magazines if you disagree.) But that just isn’t a powerful message for consumers, and it is generally used by the press with some sarcasm to show how out of touch we are with consumers. And don’t get me wrong — I’ve made these statements myself. In fact, I was videotaped last year for a privacy-related video where I talk about targeting and online advertising — and I ultimately don’t get much beyond any of the arguments above in my short clip.

So, what is the issue here? Let’s look at some of the main questions being posed:

  • Should we be able to target ads based on tracking of anonymous user behavior? I believe so.
  • Is there significant chance of consumers being personally identified and something nefarious happening to them? Not today — although down the road, that could change as computing power gets much more advanced.
  • Do consumers get any value from targeting that we can use as a value proposition in educating them about these issues? Absolutely yes, but which messages we should use are not always clear.
  • Is the massive amount of data being tracked about consumer behavior a good thing or a bad thing? Well, that depends.

The advertising economy
When my parents were children in large working-class families in Massachusetts, it was a very big deal to have chicken for dinner. Chicken dinner was something their families typically had on Sunday — with a large family carefully dividing up a relatively small bird (by today’s standards.) Oranges might be available at certain times of year, but year-round access to all sorts of fresh vegetables and fruits was simply unheard of. And products in general were scarcer, relatively costlier, and were generally less affordable to large swaths of the population.

But with advances in supply chain management, modern manufacturing and farming techniques, and reduced transportation costs, the way the average modern family lives would be considered vastly wealthier and more privileged by the standards of my parents’ or grandparents’ generations.

As technology across all industries improves, we continue to see cost reductions in products and a wider variety of products due to general efficiencies and capabilities growing over time. And as media has fragmented, we’ve seen the costs and inefficiencies of marketing and advertising grow significantly as well. Targeting and personalization of marketing are mechanisms that help us rein in the growing costs and gain efficiency as well as effectiveness.

I have a core belief that I’d like to share with you. I believe that advertising is a fundamental driver of our economy. Advertising, as it so happens, actually works. Companies that advertise (especially those that do it well) sell more products and services. Those companies prosper, and hire more employees to work for them, thereby creating more jobs. And this virtuous cycle is very clear.

It is fairly well understood that watching the marketing spend of major corporations is a major predictor of the economy. When marketing spend drops, the economy soon drops as well. And it’s a leading indicator of a return to economic health — when marketing spend increases, the economy is on its way back to health. The question is: Which is driving which effect? Ultimately, I believe that advertising is both a predictor and a driver of the economy. It’s been shown repeatedly that those companies that increase marketing spend during an economic downturn generally do better during that downturn than competitors, and they tend to have incredible long-term advantage over competitors that decreased spend during the downturn. In some cases, this long-term advantage can create a market-leading company.

So when we talk about techniques for improving the effectiveness of advertising, like targeting, I get very excited. I believe there is incredible value to increasing the effectiveness, reducing inefficiency and increasing the amount of spending we do on advertising as a society. The overall increase in economic value from advertising is something I believe in. And one major way to increase the amount of spending done on advertising is to increase efficiency and decrease waste.

That’s where targeting and personalization of advertising are incredibly important. By showing ads to consumers that are relevant to them — and personalized to whatever possible degree — we can help advertisers hone their messages, spend money on reaching the audience interested in their products or services, and do it at scale. The positive impact of this isn’t well understood by most people — even many of those in our industry. Many parrot these words about “more relevant” advertising as if they are a shield to keep away the hounds of regulation. But there is a truth in this message that goes far beyond what is generally understood.

So — is this economic boom on its way? When will we feel its effects? Read on.

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In reality, even the most sophisticated systems we have for targeting and personalizing messages to consumers are pretty bad at it. Even if we knew literally every piece of information about a consumer that could possibly be used to deliver a targeted advertising experience, we couldn’t really do much with it today. Maybe publishers are able to charge a bit more for those ads that can be sold on a targeted basis. And maybe advertisers and agencies can bid higher in real-time for ads they know are going to be delivered to their target audience. But this is really just the beginning of a much more sophisticated advertising industry, and not a world where we can effectively reach an audience with the mythical “right ad at the right time in the right place.”

In a sense, the whole way we go about it is wrong. The surreptitious surveillance of the population in order to data-mine their online activity and build statistically driven models for how to deliver appropriate and relevant ads is possible to some extent today. As computing power grows over the next few years, it will become even more accurate and effective. And eventually the ad creative itself will become intelligent and customize itself to fine-tune the images, sounds, videos, and even the pitches to the individual consumer’s preferences. But doing this quietly in the background — hiding that it is being done — is perhaps destructive to the relationships businesses should be building with their customers.

Hagel and Singer raised this issue very effectively in “Net Worth.” Their prediction was that some entity would become an “infomediary,” building a set of tools and technologies that would allow the user to control what information is tracked about their behavior. This infomediary would enable the user to control which other entities would get access to this data, and perhaps even ensure that the consumer is paid for access to the data that enable better targeting of marketing. In other words, the infomediary would represent the consumer’s data to marketers on their behalf and share the proceeds with them. In 1999, this sounded like so much science fiction. And in a sense, it was. But we’re much closer to a world where this is possible — and desirable to both consumers and businesses.

So is the infomediary the only way to protect consumers?

No. There really isn’t anything shady going on here. While every industry will always have a few “bad actors” who try to game the system, the motivation for targeting marketing communications to potential and existing customers is self-evident value. Any company trying to sell its products must educate potential customers of the fact that its product exists (make them aware), educate them on the value proposition of that product (create purchase intent if it’s possible), and ultimately create demand for that product.

Some products are well suited to some consumers and ill suited to others. Enabling the kind of filtering that shows ads for adventure vacations to those who like to take them and quiet romantic beach vacations to those who are more likely to take them is an easy-to-understand motivation to most people. The concern is that something nefarious will be done with this data. People are concerned that, at best, some big faceless corporation will profit off of data collected on their customers. At worst, people fret that information that is sensitive or embarrassing would be used in a way that somehow affects the consumer.

And why shouldn’t people be worried that something bad will happen, or that they are being “used” by companies and taken advantage of?

Ultimately, we’re in a nice quiet moment where the technology is not yet advanced enough to have much happen — good or bad. While there is definitely a statistical advantage to having the data applied to marketing campaigns, the advantage is really just tightening up efficiencies for marketers at this point. But there’s little question in my mind that things will progress pretty quickly; within three to five years, much more sophisticated and effective technologies will exist.

I do think that the ad industry has a golden opportunity to self-regulate, and it’s also likely that some form of regulation will be applied to this space as well in the next few years. I’m personally not happy about this, as the nuance in how these technologies work is quite important. Heavy-handed regulations will stymie the development of this space at a time we can ill afford it.

An argument could be made that if a viable infomediary model were to arise, consumers could share in the revenue generated by it. But the reality is that we’re talking about a very small amount of money. On the individual consumer’s behalf, it’s probably not enough money to be meaningful. On the other hand, the impact that the data could have on advertising spending is significant, and the positive impact of this would be incredibly valuable to all consumers.

Before legislators begin jumping in and trying to “protect consumers” from this kind of technology, they should really understand what both the downside and upside of these technologies are likely to be. The downside is relatively painless, while the upside is potentially massive. There are great opportunities for this nascent industry to get momentum and really create a positive impact. But that will only happen if we as an industry are careful to avoid any perception of bad behavior in the way we track consumer behavior and target the delivery of ads.

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Facebook’s frighteningly impressive ad potential

(Originally published in iMediaConnection, September 11, 2009) by Eric Picard

I’m pretty active on Facebook. I check my account at least once per day, and I frequently will fill downtime by reading through my friends’ status updates on my phone. I find Facebook to be a brilliant and incredibly useful tool. It has reconnected me with old friends, given me a closer relationship with relatives who live far away, and helped create a closer, more personal relationship with many of my professional colleagues. And the amount of data that Facebook stewards for me is both impressive and scary.

In 10 years, Facebook will know what an entire generation’s boyfriends, girlfriends, spouses, and children look like. It will not only have a map of the social graph and deeply understand the relationships between people across the world, but it will also know what things they like, what companies they’ve worked for, and, in many cases, minutiae of value to advertisers — such as what products they’ve owned.

And despite the relative quiet around what Facebook is doing in advertising, the network has created one of the most powerful and elegant advertising tools I’ve seen so far. For the past six months, I’ve been telling people in almost every advertising discussion I’ve had that they should go and create an ad on Facebook. The process is a revelation.

The buying process inherently involves targeting. Keyword targeting is only one method used — and not required. Ads can be targeted not only to geography and demographics, but also according to workplaces, relationship status, and even ads shown on people’s birthdays. The tool implicitly gives you an estimate of the audience size you could potentially reach. And as an advertiser, I can’t imagine a buying scenario where I’d trust the estimate more. In a city like Seattle, which has numerous technology companies, an advertiser could even build offers specifically to employees of specific technology companies.

Recently I saw an ad from a guy who was trying to find a job in marketing at Microsoft (I work at Microsoft). His ad had a picture of him, a brief background, and a goal for what kind of job he was looking for. And it linked to his profile. Now, I must admit that I had mixed feelings about this ad, but I was also impressed at his chutzpah and also by the simple fact that it was possible to do this.

Scott Tomlin is a colleague of mine who owns a comic book store here in Seattle called Comics Dungeon, and we’ve chatted repeatedly about the difficulty he has as a local small business owner with advertising online. This is despite the fact that he has worked as a software engineer on advertising platforms for the past six years, and knows quite a lot about advertising.

Unfortunately the lessons of national advertising don’t apply very well to his local small business. He’s tried all the “usual suspects” in traditional media, but has really pushed hard on the idea of advertising online, especially given his main career. And he has had a hard slog of it — with the exception of his efforts on Facebook.

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Scott’s main push with online advertising has been selling subscriptions to comic books, and while he’s a local business, customers of his subscription service are spread across the U.S. The main reason he focused here is that he can justify the relatively high acquisition costs for a subscription customer, rather than just driving in foot traffic. And his acquisition costs with online advertising have been high — especially via paid search.

As I mentioned, the one shining ray of hope he’s had is Facebook. With Facebook, he can target so incredibly well that he can get his ad in front of folks he could never reach using other methods. He walked me through some of the campaigns he’s running on Facebook right now, and the results were pretty impressive. With Facebook he’s been able to branch out beyond his subscription sales and effectively target local customers to bring traffic into his store. And with Facebook’s features for hosting events, he’s found a very powerful tool to bring potentially high value customers from around the region into his store.

Unlike a national advertiser, as a small business, it’s in Scott’s best interest to spend some time honing his campaign to address incredibly small micro-targeted audiences — audiences that would be too much work and too tiny for a big advertiser to bother with. He showed me one campaign he’s been running to promote an event at his store. With the five targeting parameters he’d assigned to the campaign, his estimated audience was only 620 people. But he had more than 40 clicks on this campaign and, at last check, had 24 people who had signed up to participate — using Facebook’s event promotion tools. It is this integration of incredibly rich targeting with tools specifically available for individuals, organizations, and companies that make Facebook so incredibly valuable from a small local businesses standpoint.

I first recognized this power when I happened to notice an ad for a local Vietnamese restaurant called Monsoon East on my Facebook homepage. I still don’t know if Facebook was somehow able to glean that I love Vietnamese food, or if the ad just targeted me as a local. But what really grabbed my attention was not the ad itself, but what happened when I clicked on it. The ad didn’t link me through to the restaurant’s website. It brought me to a group page for the restaurant. My first thought was, “Oh — smart — it’s providing a landing page for local advertisers so they don’t need a website.” But then I saw that Monsoon East did, in fact, have a website — and after a bit of clicking, I realized that the restaurant actually has one hell of a website. It’s elegant, beautifully designed, and a fantastic site for a local restaurant. At first I was baffled as to why Monsoon East didn’t link to its website, but I quickly realized that its group fan page is brilliant.

This was a fan page with concise, relevant information that told me about why I might like the place, and then the magical “bit at the end” — the members’ list and discussion board. Monsoon East currently has 109 members on its group page, mostly filled with young, good looking, active-lifestyle (judging by their profile pictures) people. Despite my cynical ad-pundit view of advertising, I thought, “This looks like the kind of place I might like.” Just that they had 109 members on their fan page made this restaurant much more legitimate to me (as a consumer). And that’s powerful.

So kudos to a savvy set of local entrepreneurs who are unleashing the power of social networking to promote their businesses. I think we all have something to learn from them.

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You! Appearing Soon in an Ad Near You

(Published originally in ClickZ, September 2008) by Eric Picard

It occurs to me that in 10 years, Facebook will know what every ex-girlfriend and ex-boyfriend of an entire generation looks like. They already know what millions of people’s children look like and obviously have numerous images of almost every person that uses its service.

I was talking with a friend the other day about the fact that people haven’t considered the ramifications of Moore’s law (define) on real-time image processing. With more powerful computers and the increases in processing power growing more significant in 10 years, many things we think of today as technically impossible or, at the very least, technically difficult will no longer be. Certainly this will impact technologies like targeting and analytics; it will also impact computer graphics. Looking across both of these worlds and their intersection, it’s easy to start predicting how this could come together.

It won’t be long before the kind of photo and video compositing done painstakingly by hand with lots of CPU horsepower today will be handled in real time on a consumer PC or even on servers in the cloud. This means advertising could be assembled in real time, too. Some companies have been doing this for a while. Visible World, for instance, has enabled creative shops to build template-driven ads that enable elements of the video to be swapped out based on targeting parameters. Near Mother’s Day, residents of an affluent neighborhood might see the expensive flower arrangement while residents of a working-class neighborhood see the inexpensive flower one.

But the kinds of things we’ll see in the next 10 years will make this seem amateurish and quaint. Imagine the following commercials:

  • A man stepping out of the new Lexus sedan catches your eye, as he seems somewhat familiar. As he crosses over to the trunk, winking at the attractive (and also somewhat-familiar looking) woman passing through the parking lot, you notice something. He looks an awful lot like you! He opens the trunk and hefts a set of golf clubs. The scene cuts to him beautifully teeing off into the sunrise. You really pay attention — because it’s almost as if someone had peered into your dreams and put them on the television. And you appear in the commercial as an idealized, slightly more chiseled, rugged, and handsome version of yourself.
  • A woman who looks oddly like your wife is getting three kids roughly the age, size, and look of your own kids into a minivan that matches the criteria of cars you’ve been shopping for just this week. The eight-year-old boy is carrying a soccer ball — just as your son would be. The toddler even carries a stuffed animal that resembles the one your daughter carries with her everywhere! You see the kids calmly watching a movie on the installed screens, and they seem quite comfortable. The mom seems calm, relieved to have such a nice ride that all the kids enjoy getting into — without squabbling.
  • An oddly appealing woman is fly-fishing. She seems so familiar, like you know her from somewhere. The ad focuses in on the graphite rod she’s using, just like the one you were shopping for online last week but didn’t buy. You keep watching because the woman in the ad has such a nostalgic appeal to you. It’s almost as if she were a combination of three women you dated in college. And in truth, she is.

All these commercial seem like science fiction but aren’t far-fetched at all. We think about profile-based targeting as dealing with our habits and anonymously delivering products we’re interested in. But there’s no reason that down the road technology won’t enable the situations I just described. And while the privacy implications are vast — and the ads may seem a bit creepy — over time they may become acceptable. As we’ve seen in numerous studies, the current younger generation has very different feelings about privacy than older generations. And opting in to scenarios like I described may be quite commonplace in 10 years.