Here’s why behavioral analytics is the next generation of business intelligence

Behavioral analytics is unlocking a new frontier of data that can be presented to decision-makers within a more actionable context.

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Businesses collect intelligence – immense quantities of it. This statistical information has the potential to help companies gain a market edge, streamline operations and improve profitability. The challenge exists in finding ways to collect a diverse set of data, and then compile it into a format that is actionable.

Design theory is one way that companies can better design their reporting dashboards so that everyone, not just those with a PhD, can benefit.

But it’s also important to attack the other side of the equation. Customer data is acquired through various channels: in-store traffic, mobile apps, website cookies, and social platforms, just to name a few.

Previous generations of business intelligence tools assisted with tracking clicks and page loads on the web and mobile, but they required a significant architecture, including a brick-and-mortar data warehouse and separate visualization tools. This created a complicated workflow and even murkier analysis. Gaining even the simplest of takeaways was virtually impossible.

CIOs focus on the low hanging fruit

Many CIOs, to get around this, chose to focus on activity levels and conversion rates. They would deploy analytics products that are very narrow, and only focus on single channels, such as website visitors and their page clicks or mobile activity.

This is helpful, but only presents a small part of the data, and it is not in real time. Thankfully, cloud systems, like Google Analytics, have stepped into the space to provide the horsepower required for real-time analysis. But, it’s still only a small slice of the statistical pie.

In-house server deployments hamper analysis

For CIOs that are willing to stay in the fight, it’s an expensive proposition.

Enterprises struggle with data that sits in different silos. It is challenging to get an accurate understanding of what it means because the current data warehouses have a complex integration process, and require knowledge of SQL and a development team.

In addition, products to build out the warehouse are a huge expense: Mixpanel for funnel analysis, Amazon Redshift data system, and Tableau for dashboarding and BI. It can cost companies hundreds of thousands of dollars annually, and there are too many opportunities for data to go awry.

“This is very expensive and time consuming,” explains Dan Schoenbaum, CEO of Cooladata, a behavioral analytics platform. “However, running a business without this information is like trying to see with a hand covering one eye – you have information, but lack the complete picture.”

Behavioral analytics platforms offer CIOs new hope

Enter cloud-based behavioral analytics platforms – responsible for intelligently aggregating and unifying all channels across the full spectrum of digital activity, including Facebook ads, email campaigns, web traffic, mobile applications, third-party applications like Hubspot or Optimizely, and many more.

When platforms are integrated into a single, complete picture, business leaders can more easily analyze the entire customer journey.

Of course, behavioral analytics is happening in some industries faster than others. And it goes way beyond measuring customer interactions.

Online merchants have been fast adopters of behavioral analytics, in part because the space they work in is highly competitive and the market leaders are constantly innovating their technologies to stay ahead. But there are a broad range of industries ripe for this business intelligence, including cyber security, gaming, publishing, and fintech.

In cyber security, user behavior analytics (UBA) is an example of data that allows user behavior activity to be studied, much in the same way a fraud detection system would monitor a customer’s credit cards for theft. UBA systems are successful at detecting significant security events, such as charges in a distant country, to demonstrate a rogue user.

Behavior is really at the center of how companies need to organize their data. Similar to a Word document for analytics, the future of BI tools will provide a larger variety and higher quality of visuals and statistical analysis. The documents can then embed in other applications or platforms and receive third-party data directly via API or internal data. Furthermore, they will have the means to sort data not just by value, but by sets of similar users or patterns of behavior over time, for example.

Schoenbaum explains that the increasing amount of analysis is temporal in nature and businesses are increasingly looking for how a certain event unfolds over time. For instance, what were all the online actions of a user leading up to a purchase online? Or a gaming company may want to know if its users are progressing through all the levels of its game.

Startups in years past have leveraged cloud servers from providers like Amazon Web Services, but they are now seeing the advantage of providers that offer analysis of various data points to provide the "why" insights to consumer behavior.

Behavioral analytics is the next generation of business intelligence (BI)

The challenges are many, but the solutions are much simpler thanks to behavior analysis. What once took huge, interconnected systems to crunch can now be done with ease thanks to the cloud. And CIOs can avoid the overhead of managing in-house analytics hardware.

It’s my sincere hope that we continue to see the positive ripple effect across industries that impact every aspect of our daily lives. And it will be up to the boldest of CIOs to make that a reality – by transitioning from outdated systems into a more cost-effective world of data collection and analysis.

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