From Big Ideas to Big Data

The term “big data” might just give “content” a run for its money as the buzzword of the year. In this year’s IAB Engage conference, Bryan Melmed said this… “When people start talking about big data, it’s like they are on cocaine.”

He then explains the signs:

Big data makes you feel smart

Big data makes you feel sexy

Big data makes you talk a lot

Big data means many different things to many people…and some sectors have been better at capturing big data than others. But when it comes to Advertising & Marketing big data is in fact, measuring people. However, big data seems almost like a front, a hype. Everyone seems to want it, and anyone who has it seems to want more.  The reality is – nobody seems to know what they have or what they are getting. This collective rush to big data makes a number of errors – both statistical and practical.

There’s no point in collecting data for data’s sake, we want data we can actually use.

What clients really want is the actionable insights that data can provide.

More is not necessarily better

Most often, more data means more noise, and fewer signals. In many cases, large amounts of data that is available makes for predictions at the level of mass, and not by individual behaviour. Like a telescope surveying billions of galaxies, it works as long as the predictions are kept to the same big scale. Big scale, often means that the predictions can be mundane.

The limitation here is “observational data” – seems like a trivial notion, but our brains are very powerful computers designed through millions of years of evolution to make sense of another’s behaviour.

SPOILER: Big data can miss the basics –  it does not provide the full picture (even though these days organisations think this is the Holy Grail).

This is possibly why the next generation of big data will enable search engines to outsource the most complicated tasks (for example, facial and voice recognition), back to humans.

Big data is not magic

In the past, people generally relied on observations alone to make their decisions. Only now, we have sufficiently advanced technology to create sophisticated and complex algorithms, behavioural and correlation models. Big data is great, but it means nothing without the ability to do something useful with it…and often, that is the case.

90% of the world’s data today, was created in the last 2 years.

Big data works best when it magnifies our common sense with more accurate “ears”. In marketing, we typically think in stereotypes – ‘soccer moms’, ‘connected urban professionals’, that sort of thing. When we say we’re going to market to soccer mums, that’s not a person, that’s a stereotype. Our brains are designed to create patterns and shortcuts, but that does a huge disservice to every single person we deal with, who is not easily summarised by 30 or so demographic characteristics. The fact of the matter is, marketers are not necessarily looking for data. They are looking for insights that convince people to spend money in their products or services. If only we had more of the right kind of data, we would be more certain about what individuals are going to do next, and how advertising will be better placed to serve relevant communication messages. What big data does is force us to abandon stereotypes in targeting and dig deeper into the concept of personalisation.

But there is a big shortage of people that can understand the breadth and depth of big data.

The big question is, where will we find these people?

Without a doubt the demand for new talent will give rise to data scientists. These people will be as much in demand as the software developers of the dot-com boom, and the Wall Street maths wizards of the 80’s. As big data becomes better defined, there will be a need for specific skills such as data scientists, analysts, marketing and risk analytics.

In the early days of LinkedIn for example, it was a data scientist who spotted the need for better information analysis to predict and help people’s networks for them. That way, LinkedIn did not just become a place to store existing address book contacts, instead, a key feature  “people you may know” was born.

We will see a rise in a new breed of profession, people who understand big data and can take all this data, process it into meaningful insights to make true business decisions. In some aspects, this is not new – actuaries are professionals who are already skilled at using their analytical, statistical and mathematical skills to calculate probability, risk and financial impact of future events. The reality is, big data feeds predictive models, which have always been the domain of the actuarial profession. The only difference today is, predictive models are suddenly being put to use in non-financial and IT fields.

Can the Marketing & Advertising industry attract talent in big data?

A research by McKinsey showed that only actuaries, operations research analysts and statisticians have 100% of the deep analytical skills and talent needed for big data processing. Frankly these jobs are highly skilled and in short supply, and they are also applicable to almost any industry. Given the Marketing & Advertising industry has developed a reputation as analytics laggards, it will be an interesting challenge to find ways to battle these perceptions to woo the talent they need. The industry is in the hands of people with big data skills, and it is in their every favour to follow larger industries with fatter pay-checks.

Without a doubt we love big data, but until we fill the industry with this talent pool… we can only continue to talk about it.

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