Monthly Archives: January, 2017

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

January 30th, 2017 Posted by Behavioral Data 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-bait 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 its liberal readers to remain loyal subscribers, it should send them frequent updates on investigations and new allegations. If The Washington Post wants more Trump supporters to visit its website, it should place its vigorous reporting on the shortcomings of candidate Hillary Clinton front and center, but only when these particular readers visit the website.

By clustering their audience in a clever way, media companies can hold onto their readership – even grow it. And media consumers are rarely one dimensional. Once they’re in, they will move beyond the content that drew them in and they will check out other verticals (perhaps a cat video?).

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 such as behavioral analytics, which allows a company to cluster its web visitors based on, for example, how they navigate content, how much time they spend on each story, if they read the entire store or scroll to the end, if they click to watch an embedded video, or if they skip or decide to sit and watch an entire ad before a video starts. Understanding these kinds of behaviors helps media companies to serve each web visitor the most relevant and personalized content.

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. And Youtube gives video recommendations without you even knowing that they are recommendations.

It’s time for newspapers and other traditional media companies to shed their old ways. When we get people on both sides of the political divide to trust real news, and warm up to the stories that may question their world view, we can 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 Behavioral Data 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 as we connect everything from our cars to our FitBits, inventory pallets to coordinated networks, so does the need for sophisticated data analytics processes like behavioral analytics.

First, it’s worth noting that IoT places the onus on dynamic analysis. Think about what it is that we like so much about self-driving cars. They process information instantaneously to produce the most efficient, and safest, outcome possible for the rider.

The days of gathering data to inform next quarter’s business decisions are over. Today companies need a direct input analysis and output vector in order to achieve business outcomes with the least amount of digital touches required from the customer. After all, customers are expecting instant satisfaction, or else they’ll move on to anther site as quickly as they came.

Additionally, machines today 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 an 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 (such as 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 FitBit, for example. After the company has gathered ten years of data on millions of users, imagine what a sophisticated algorithm will be able to infer from your heart rate, monitored hour by hour, day after day. FitBit will have enough information to create advanced counterpart identification models to not only diagnose a user’s health problems, but also estimate what they are at risk for. Another example, is at Tesla Motors, where acquiring 1 billion miles of customer driving behavioral data will allow engineers to design and feed data into smarter, autonomous vehicles.

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

Copyright 2018 SYNTASA®. All Rights Reserved.