With big data comes big responsibility

Dare's Steve Graves checks out the risks and rewards of predictive analytics.

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By Steve Graves

For anyone with skin in the digital marketing game, Apple’s “exciting announcements” at the 2014 Worldwide Developers Conference probably came with little surprise. The updates to its incredibly successful mobile operating system, the iOS8, made it clear Apple is staking large parts of its future success in the Internet of Things. Features such as HomeKit, its smart-home interface app, HealthKit, a wearable tech data interface, plus furthered core-functionality built around its iBeacon technology, showed Apple is set to prosper in the coming wave of digital innovation — one that continually blurs the line between digital and the real world.

Considering that the Internet of Things is forecasted to represent a $7-trillion industry by 2020, it makes sense that Apple would be looking to slice itself the biggest piece of it that it can. Not that it’s alone. The promise of the Internet of Things is huge, meaning tech companies and startups that realize this are set to be rewarded handsomely.

Take Intel’s recently released Edison computer. As far as technical specs go, it’s pretty standard fare — dual-core PC with Wi-Fi and Bluetooth capabilities. What makes it special is the fact it’s the size of an SD card.

Alongside Intel’s Edison announcement came the sponsored Make it Wearable contest, offering up $1.3 million to developers willing to help establish Edison as the “brains” in the coming onslaught of wearable tech products. Not that you have to wear Edison. Intel also showcased its Nursery 2.0 that featured a whole shopping cart’s worth of Edison embedded products, including a smart toy frog that wirelessly reports an infant’s vitals to a parent via an LED coffee cup, while remotely starting a milk warmer at the sound of a crying baby. The fact it’s cute makes it especially interesting considering it represents one of the greatest changes in human history. This is the dawn of the truly quantified self — whether we like it or not.

This much is true: the smaller and more powerful computers get, the more we integrate them into all facets of our lives. And with computers comes data — vast amounts of it generated by our every action. Up to now, the data we’ve been most focused on has been happening online. It’s where every one of your clicks, page views, bounces, etc. is systematically recorded, measured and analyzed. All that data analysis has given digital marketers an incredible leg up as it effectively removes the guesswork. But how much “guesswork” can be removed before it’s no longer marketing, and more just a fish-in-a-barrel-type exercise?

If you’re looking for proof, consider Amazon’s recent patent that outlined a way to ship your order before you actually make it. What it is calling “anticipatory package shipping” looks at your prior behaviour (searches, purchases, wish lists, etc.), and identifies patterns. From there it predicts the likelihood of you ordering a particular product you’ve shown interest in, and if that’s high enough, starts packaging and shipping it before you click the “add to cart” button. For the user, the benefit (assuming it’s accurate — and it will be) is less wait time for your item, and for Amazon, happier, more satisfied customers. And where there are happy customers, there’s profit. Predicting behaviour, which is fuelled by big data, is proving itself to big business.

Now what would happen if the behaviours we could measure and analyze extended well beyond online? For example, let’s say your LED coffee cup connected to a toy frog that monitored your infant’s vital signs, which in turn synced wirelessly with the milk warmer. It doesn’t take much imagination to consider the kinds of data that could be theoretically generated as a result. Just the “smart” coffee cup alone could track when and how frequently you drink coffee, how long it takes you to drink a cup, if you use cream and sugar, the type of roast you prefer, how often you wash your cup, what brand of detergent you use when you wash it, etc. The list goes on — and that’s just a coffee cup. Marry that up with all the other data generated from the coming onslaught of “smart” devices (plus your existing online habits) and you’ve got yourself some serious data scientist porn.

No question that big data represents one of the biggest game-changers in our industry — and arguably for society too. It’s already proven itself to be an incredibly effective tool in the advertiser’s arsenal allowing us to predict behaviour and intercept consumers at their most receptive. But the quality and quantity of data that is going to be generated as a result of the rapid spread of smart tech — and with that, our ability to analyze vast sets of it — means we might very well know more about a person than they do about themselves. It’s a tremendous power to have over the consumer, and one that brings with it the same level of responsibility.

The potential for abuse is significant and there is good reason to believe it will steadily increase alongside innovations in integrated tech. With no compelling historical precedent, it raises complex practical and moral questions that we as digital marketers need to start asking. Ultimately, it’s up to society to decide what rules and guidelines it imposes on this emerging industry. But until that happens, just remember what the biggest collector of data (and arguably the world’s most powerful company) made its informal corporate motto: “Don’t be evil.” That should be enough…let’s hope.

Steve GravesSteve Graves is a senior planner at Dare Vancouver. He’s obsessed with all things digital and boasts an eclectic CV, including stints as web designers and running his own SEO marketing shop before joining the global agency. 

Image via Shutterstock.