Technology has a a fascinating way of turning yesterday’s paranoid nightmare into today’s commercial opportunity. This is true partly because the adoption of any technology takes place over time, giving society the opportunity to adjust its values and norms accordingly. And these things never quite affect our culture in ways we expect.

Look back at the 1967 film comedy The President’s Analyst, where the telephone company – there was only one back then – wants to have wireless receivers implanted in everyone’s brain so we can all engage in instantaneous, wireless communication. The scene where a phone company executive explains the “cerebrum communicator” to the President’s psychiatrist is worth a look on YouTube. His reaction – “The phone company is psychotic!” – sums up the horror with which such commercial intrusion into personal space was viewed during the era of peace, love and harmony. Not so much today, in our smart-phone, Bluetooth-obsessed mobile environment.

“Big Brother is watching you” has been part of our culture since 1949, when George Orwell’s 1984 was published. In those days, with television still in its infancy, being on camera constantly represented as heinous an invasion of privacy and personal freedom as one could imagine. Today, the idea seems benign, if not largely beneficial. We see news reports every night with criminals being apprehended after surveillance cameras caught them in the act. On the other hand, there are those infernal cameras catch our red-light transgressions, but they only result in a fine and not a trip to Orwell’s notorious Room 101.

Next in line – Big Data

Big Data is another story. The term speaks to the rapidly increasing capacity of information technology systems to compile and manipulate immense amounts of data and extract useful information. The potential benefits range from controlling crime, preventing disease, and spotting social and business trends. Drilling down to the personal level, however, Big Data may leave many of us feeling somewhat uncomfortable.

The ability to capture, compile and analyze the vast amount of data that exists in an individual’s digital footprint and digital shadow is much more revealing than anything physical surveillance could hope to capture. It provides insights into our interests, behaviors and relationships beyond anything Orwell could have imagined. For marketers, it’s a dream come true.

Phil Davis, CEO of Rapleaf, an email data cruncher and list provider, has described Big Data as possibly a key to “the holy grail of one-to-one marketing, getting the right message to the right person at the right time in the right way… at a cost that doesn’t cost more than the actual conversion.”

But there’s a crisp line between the warmth that comes from feeling loved and the icy chill that says you’re being stalked. About a month ago I researched routers (woodworking, not networking) online. Since then I can barely go anywhere on the web without ads popping up for routers, router tables, router bits, accessories and such – from manufacturers and retailers alike.

Here come the “Quants”

It’s safe to say that the Statistical and Applied Mathematical Sciences Institute (SAMSI) and the advertising industry would have been considered odd bedfellows not long ago. Last summer SAMSI, in association with the Society for Industrial and Applied Mathematics (SIAM) hosted a two-week workshop on Computational Advertising. Stanford University offers a course in the subject, and describes it as “an emerging new scientific sub-discipline, at the intersection of large scale search and text analysis, information retrieval, statistical modeling, machine learning, classification, optimization, and microeconomics.”

In the ad world, we call them algorithm-based marketing campaigns. They are supported not by creatives, but by so-called ad quants – the mathematicians, data analysts, engineers and statisticians behind them. They’ve worked successfully for the likes of Zappos, Bridgestone and BMW. The Zappos campaign, for example, linked local weather forecasts with merchandise appropriate to the climate and conditions and other demographic data, such as age and gender, to target an online display ad.

A year ago, IBM teamed with a major movie studio and used data analytics to evaluate the buzz that resulted from the broadcast of a movie trailer during Super Bowl XLVI. The data sources they used included Twitter, and “hundreds of thousands” of message boards and blogs. They compared the interest and reaction to those from trailers from other movies to project the trailer’s effectiveness and its potential for attracting an audience.

This isn’t your father’s advertising… nor is it David Ogilvy’s or Bill Bernbach’s. But I doubt either of those iconic ad men would have had a problem with it. Our business hasn’t changed; it’s still about finding the most efficient way to get your client’s message into heads of its potential customers. What’s changed is that the tools for finding those heads have gone from the macroscopic view of mass media planning to the microscopic perspective of personal data mining.

Engaging creative is still needed to plant that message, although its nature may be changing too. Broadly addressing a market’s common denominators will no longer cut it when we know exactly to whom each message is going.

The world beyond marketing – yes, there still is one

I’m relieved that I no longer have teenage sons living at home, surfing on my computer and dropping their “cookies” in the kind of places teenage boys like to explore. My digital shadow might have turned into a dark and threatening digital cloud. But as a member of the advertising profession, I see a wealth of opportunities in the world of Big Data.

Could Big Data ultimately predict national trends accurately based on digital “buzz” or identify public opinion more accurately than poll sampling? Is it possible that it could eventually predict election results more accurately than exit polling, even in advance of the actual vote?

On a personal note, I find the idea of Big Data more disturbing than Orwell’s Big Brother. It’s one thing to be responsible for what you actually have done. But it’s quite another to be judged on the basis of a phantom, statistically derived construct for thoughts and behaviors inferred by an algorithm, however sophisticated it might be. As a marketer, however, I find the promise of where we might go from here to be both interesting and exciting.