Many companies are embracing Big Data as the solution to their marketing challenges, but the bigger discussion should be centered on ensuring the quality of that information and interpreting it for business use, particularly marketing. Streaming large amounts of data from a variety of sources is only the first step in achieving insight - organizations also need to be able to cleanse it and sort through it to understand the details.
As BtoB magazine reports, Big Data can even be useful for direct marketing programs, but not without the help of data quality
tools and data analysts. The source cited data from an IBM survey of chief marketing officers, pointing out that 71 percent perceive Big Data to be their greatest marketing challenge. While many admitted that they were unprepared to cope with the increasing complexity of Big Data, 79 percent said the complexity would rise in the next five years.
"In the past, it's been prohibitively expensive to actually make sense of [so much data], to infer opportunities," David Cummings, CEO of marketing automation company Pardot, told the magazine. "Now, tools exist to see, for example, website traffic patterns hour by hour, minute by minute or Tuesday at 2 p.m."Preparing for the challenges
The Financial Times reports that as companies start to rely more on data to get insight on their processes, they will need to treat the information as an asset and realize the consequences of not focusing on quality. As Noel Yuhanna, a Forrester Research analyst, explains to the newspaper, harnessing the power of Big Data will require sifting through and interpreting unstructured, semi-structured and structured information at a higher speed.
There will be a greater demand by businesses to get help with protecting data quality, the source notes, and vendors will be busy working with clients to develop systems for collecting, parsing through and analyzing the information that flows into and through their networks.
"I think one of the biggest challenges companies face is having staff that can look at entirely new data sources, often unstructured, and understand what needs to happen to the information these contain before it's analyzed," Soumendra Mohanty, global technology delivery lead for Accenture analytics, told the FT.
This means that as companies work to make use of their data, they will have to first determine what they hope to learn from the information. Pursuing data for data's sake will prove fruitless.