Monthly Archives: January, 2017

Hey, Media: Do You Know Who Is Consuming Your Content?

January 30th, 2017 Posted by Analytics 0 thoughts on “Hey, Media: Do You Know Who Is Consuming Your Content?”

Fake news always seems to be in the news these days.

Media companies are working themselves into a frenzy wondering why so many disaffected readers have turned towards click-baity headlines and conspiracy- monging websites, instead of opting for their own tried and true content.

So, how can a website hold onto an increasingly divided audience when there are so many other – more ideologically tailored — options to choose from?

I think the answer is simple. Mainstream news outlets have done enough solid reporting throughout the presidential campaign to earn the trust of the broader American electorate. But the content needs to be placed in front of the right pair of eyes.

If The Washington Post wants more Trump supporters to visit its website, it should place its vigorous reporting on the failings of Hillary Clinton as a candidate front and center when they visit the website.

If it wants liberals to remain loyal readers, it should send them constant updates on its investigations into Trump’s nonprofit organization and controversial past.

By clustering their audience in a clever way, media companies can hold onto their readership – and even grow it. Even in these contentious times.

And media consumers are rarely uni-dimensional. Once they’re in, they will move beyond the content that drew them in. They will check out other verticals. (Cat videos, perhaps). And eventually, they will warm up to the stories that contradict their world view.

It’s more important than ever for media companies to place an emphasis on targeting readers with the right content.

This should begin with the use of sophisticated tools like behavioral analytics, which allows websites to cluster visitors based on how they act, what they read, how much time they spend on each story, do they read the entire story or skip to the end, do they watch the embedded video, do they watch the entire advertisement or skip etc.  rather than the demographic category they belong to. Knowing these behaviors and more will help companies in the business of content to personalize and monetize their content by serving them advertisements that are relevant to their behavior.

Netflix did this brilliantly, and guess what happened? They are no longer remembered for their “Be Kind, Rewind” days. They rose overnight to become one of the preeminent media companies of our day. Youtube gives you video recommendations without you even knowing that they are recommendation.

It’s time for newspapers and other traditional media companies to shed their old ways. Once we get people on both sides of the political divide to trust real news, then we will start having constructive debates over the future of our country.

IoT and Behavioral Analytics: A Perfect Marriage of Big Data

January 18th, 2017 Posted by Analytics 0 thoughts on “IoT and Behavioral Analytics: A Perfect Marriage of Big Data”

Big data is about to get even bigger.

As the Internet of Things (IoT) grows – connecting everything from our cars to our FitBits and inventory pallets to coordinated networks – so does the need for sophisticated data analytics processes like behavioral analytics.

First, it is important to note that the Internet of Things places the onus on dynamic analysis. What do we like about self-driving car? They process information instantaneously to produce the most efficient, and safe, outcome possible for the rider.

The days of gathering data to inform business decisions to be made in the next quarter are over. Companies now need a direct input-analysis-output vector to satisfy customers or make strategic decisions. And on the other hand, customers also expect quick results. The days of waiting for customer’s next visit to the site are over – companies need to capture their attention and sell a product during their first digital touch.

Additionally, machines are better at predicting not only large-scale outcomes – like the state of the traffic on your local interstate – but also individual human behavior.

That’s what a team of MIT professors proved last year in an experiment that compared how a computer system fared in creating predictive algorithms for unfamiliar dataset.

The computer finished ahead of 615 human teams out of 906 – and worked exponentially faster. It even produced better results in predicting human behavioral outcomes, like dropout rates, by selecting more relevant data than its human competitors.

This is all good news, because not only will IoT make behavioral analytics processes stronger by increasing the data pool by several orders of magnitude. It will also make it more valuable.

Take your FitBit. Imagine, after the company has gathered ten years of data on millions of users, what a sophisticated algorithm will be able to infer from your heart rate, monitored hour after hour, day after day.

FitBit will have enough information to create advanced counterpart identification models to not only diagnose users’ health problems – but also estimate what they are at risk for.

Tesla Motors has over 1 billion miles of customer driving behavior data so they can design a better car and feed the data into a smarter autonomous car.

That’s the beauty of behavioral analytics, synced to IoT. It should make your heart race with excitement.

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