Businesses look at new data analytics methods for 2016

With a focus on edging out their competition in 2016, businesses are looking at a variety of new approaches to advanced data analytics.

As 2016 gets under way, businesses are exploring a range of emerging data analytics methods to gain an edge on their competition.

For Stephen Barone, COO at digital marketing firm FullFunnel, 2016 will be all about moving from siloed, client-specific analytics projects to a more generalized big data approach to data collection and analysis.

"We are small data, and the reason is that each client is somewhat unique in their specific niche or industry," he said. "We can't really leverage the power of big data in what we do on a day-to-day basis."

Barone's position is similar to that of many businesses as 2016 gets underway. Although many businesses spent the past few years launching and perfecting basic data analytics methods, some are expecting to focus more on advanced techniques in the new year.

In spite of current limitations, Barone is sure FullFunnel can do more by implementing data analytics methods. He recently hired a sales analyst who has a background in math and economics that he hopes will be able to pull together insights from across clients. Currently FullFunnel focuses on inbound marketing and paid search activities. It uses a tool from DataHero to track the success of these initiatives for its clients, essentially amounting to retrospective reporting. But going forward Barone hopes this retrospective information can be analyzed more systematically to identify and recommend effective strategies for clients. This will be one of his chief focuses in the first quarter of 2016.

"We know we can analyze that data and draw more broad conclusions, but we haven't really been able to put enough time into it yet," Barone said.

The year of real-time insights

Jeff Bodzewski, chief analytics officer at digital marketing and public relations firm M Booth and Associates, also expects to focus on more advanced data analytics in 2016. Right now he wants to develop more real-time insights.

M Booth has been a big user of data analytics methods in the past to identify audience attributes and tailor messages to them based on their specific characteristics. But in the past the focus was about making sure the right message was delivered to the right audience. In 2016 Bodzewski and his team want to make sure these messages are also delivered at the right time.

"Now, with the influx of data sources, particularly a person's location via mobile data, we add 'at the right time' to our marketing approach," Bodzewski said.

To accomplish this, Bodzewski plans to leverage mobile data to a greater extent. This data includes the location of mobile users, making it possible to deliver messages that acknowledge the context around the audience.

Cognitive computing gains ground

Although there's no doubt it's still early days for cognitive computing, one of the most talked about data analysis methods going into 2016, some businesses are becoming interested. At Nationwide Insurance, chief data officer Wes Hunt said he's looking into how the technology could improve business processes and customer experience.

For him, the potential for cognitive computing is all about streamlining operations. Indeed, much of the promise of cognitive computing at this early stage centers on using machines to replace or augment humans in tasks that involve digesting large amounts of data, making it a potentially useful tool in day-to-day operations.

Ed Burns is site editor of SearchBusinessAnalytics. Email him at [email protected] and follow him on Twitter: @EdBurnsTT.

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