If you didn’t pay for it, you’re not the customer, you’re the product

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Ultimately we all know that when we sign up for Twitface, LinkedIn, Tumblr or Foursquare and we give away our email, address and so on to use a service that’s “free”, we’re going to be “monetized” somehow. We’ll be advertised at and our data will be sold to someone else who’ll no doubt send us the latest compelling offer for – in my case it was a $2500 loan I’ve been pre-approved for and the offer to have sex with a lonely housewife.

At least that’s the part we do see – and most of us understand.

The other side of it is much more exciting, much more compelling and for marketers, probably represents the future of how marketing is going to work. It’s called Big Data, and it’s the proverbial ten-ton truck heading right for your advertising budget. It’s a quiet revolution being played out by Google, Amazon, IBM, Accenture and pretty much every one of your clients (if they have any sense).

It’s you and your behaviour that’s being captured, sorted, structured, sold and integrated across datamarts in India to serve you up as a segment of one. It’s perfectly and precisely YOU – everything you say, like and think; everything you buy and what you might buy next; everywhere you go and why you go there. It’s you as algorithm – understandable, predictable, accessible and addressable.

I saw firsthand the power of this at a SXSW panel last month. A fascinating panel made up of the head of analytics for Obama’s campaign, the head of analytics for Mitt Romney’s campaign and the head of a non-for-profit Washington analytics group.

The headline takeout was this. The US election ultimately came down to about 36,000 swing voters for Obama. That’s a pretty narrow focus at the end of all that campaigning. What’s more impressive was that “The Cave” as it’s become known, was able to identify these swing voters down to the voting precinct and even in some instances the household. Even more impressively, they were able to also identify what the top issues were for the swing voters and serve them messages that were relevant and compelling to encourage them to swing in favor of the Democrats.

OK, so big data can help identify, target and solve for the US election. We might call this one the Big Data Election. Mitt’s team, by comparison, looked like they were playing in the schoolyard.

So all this might help explain why IBM is targeting CMOs for their budget; why the CIO and CMO are increasingly two-in-a-box in most large data rich organizations; and why as GE Global CMO Beth Comstock noted on her recent trip to Sydney, “that we are all so breathless with the potential for Big Data”.

If you’re not into Big Data in your organization it might also explain why you’re beginning to feel a little uncomfortable in your seat. I am. You should.

So let’s jump over the fence together. What’s it going to take for marketing to get data-fit?

The experts talk about three basic principles:

Build a culture of data

It’s all very well spending a gazillion dollars on building your own data mart, hiring a bunch of modelers and quant scientists, cross referencing multiple structured and unstructured data sets to build to a segment of one. But are your people going to act on that data? Or will they just shrug, and carry on with their jobs when you tell them you’ve identified the individuals who will buy the next product you’re bringing to launch?

If the highest paid opinion to the lowest paid opinion in your organization is ready and willing to act on data analysis then you have a culture of data. If they are not, then you’ve likely just wasted lots of money.

What problem are you solving?

Seems obvious this one but there are countless big data projects underway right now that are entirely aimless. Let’s pay a consulting firm millions of dollars to build us a state of the art data warehouse – hell, everyone else is building one and we’ve got petabytes of data so it must be valuable, right? Maybe. It really depends what you want to do with it.

Do you want to target individuals with individual offers and products built specifically for them? Do you want to understand what your individual customers will buy next and offer it to them? Do you want to get rid of unprofitable customers? Do you want to understand who the swing voters are and what matters to them? As with any strategy, you MUST understand what problem you are trying to solve BEFORE you spend lots of time and money being busy.

Again, it might sound obvious, but one of the best funded big data programs on Earth have been at it for six years now and confess they are still a long way off being perfect in determining how an election campaign in the USA will run.

Be capable of personalisation

OK, so you know what problem you’re solving, you’ve built your data culture and you have your data layers and analytics to be able to market to a segment of one. But can you personalize? Are you ready to serve messages on an individual basis; can you create 20,000 offers? To do that requires a marketing machine of incredible scale and most simply cannot afford the investment, however much efficiency it might create. The capability simply isn’t there.

So start by working out what level of personalization you are capable of and build from there. Maybe you can manage CRM programs to individuals, but you still need to target outbound marketing by geography. Wherever you sit on the journey to realize your big data dreams, it all starts with execution capability.

The power of big data is undoubtable. And if you’re not on the train, there’s every chance it’s going to hit you in the face. We all need to get data-fit and it’s likely that none of us are doing enough to be ready to compete.