Finding the next big data giant

By 15 August, 2016Blog
Finding the next big data giant

How linking behavioral, profiling, reported and predictive data will determine the rise of the next top advertising and data player.

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Innovation waits for no one and the technologies that surround us carry the most tangible evidence of this progress.

We are in an age where technology has surpassed us, forcing us to push our brains to the max to keep pace, learn quickly and stay in tune with how the ecosystem is evolving. But thanks to automation this technology is also working FOR us, helping us, assisting us, relieving us, making us move even faster through the day.

We are becoming embedded in this technology as our physical life is fused into the digital one and, at the core of this fusion, lies data. This is no news, data and privacy have been on the world’s front pages for a while now, with technology racing forward as legislations and governments struggle to keep up.

But let’s leave the privacy debate for another time and stay on target. Where do you think data will be in 5 to 10 years? How will our surrounding technology evolve? And what challenges is the industry facing?

The rise of the Smartfridge

In a world worthy of the best Isaac Asimov novel it’s not hard to imagine that soon, this machine assisted ecosystem, will be “sucking” the data out of us. Smartphones, Smartwatches and TVs are already doing this to some extent but there will be more. Cars will know if we’ve put on weight through sensors in the seats and record if we’ve been grocery shopping this week. Our fridge will know how much milk we’ve been drinking and probably poke our smartphone to remind us to buy more the next time we park at Tesco’s. Who knows what our washing machines will do? grow legs and eat-up our dirty socks because it’s laundry time?

Behavioral data

Jokes aside, we will be surrounded by devices that know us, know our habits, favorite food, favorite places, movies genres we like, people we like to date and more. A vacuum for behavioral data (or call it ‘life data’) constantly adding to a digital version of ourselves stored in hundreds of cloud servers across the globe with no single entity being allowed to access them all.

Self-reported data

But behavioral data is only a slice of our “data pie”. Indeed, behavioral data today only reflects habits or preferences, but what about what we think? Our opinions and ideas are a different deck of cards, so to speak. Even 10 years from now we will be forced to ask people what they are thinking and why they are thinking that. The answers that people give to these questions are the exact opposite of the previous kind. This is self-reported data and it’s been around for a while, evolving in different forms, from the answers our parents used to give a few years back during those dinner-time telephone surveys, to the latest brand page you liked on Facebook. This type of data can also confirm if a predictive model is on target and even confirm if a user was touched by an online advert showing the effect of it and if the brand or message is top of mind.

Profiling data

Asking questions and getting answers looks simple but if you want to make sure that you are reaching the right people with your questions then pre-profiled demographic data is what makes your world go round. This data is still self-reported but it focuses more on aspects like age, sex, education, employment, income and so on. And making sure that your database is updated with relevant and contemporary data points is an odyssey by itself with some prominent data & insight platform players having developed advanced software for capturing this information on a daily basis.

How to bring value to this chaos

Or better, how will our cloud-scattered-digital-self bring value to businesses and advertisers in the future? Projected behavior is one of the answers; feeding all of this stored data into models that plot our future choices to predict what we will do or buy even before the thought crosses our minds.

But before any algorithm can do that there is a bigger challenge to overcome, a cloud-scattered one.

Right now this data ecosystem is a jungle. The number of marketing technology solutions has been growing exponentially in the past years and now counts around 3 500 companies worldwide, while the Economist recently reported that there are 2 500 players currently fighting to display ads online as they rely on thousands of databases containing billions of data points scattered around the world.

Accessibility, interconnectivity, compatibility and relevance

So you see where the challenge lies. Of course, marketing technology companies rely on partnerships to bring this data together, but nobody to date has all of the partnerships nor a cross-platform solution that can read through thousands of databases, and the tech player that will manage to pull this off while still providing relevant organized data to its customers will become the next giant, unless of course Google beats us to it while the others die trying ;)

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