The Big Data revolution has meant that there are nuggets of insight within customer data everywhere: customer relationship management data, reviews, complaints, enquiries, surveys, social media etc. This applies to employees too, e.g. engineer logs, staff comments and forums etc. The ability to harvest and analyse such data in an automated way to provide predictive, actionable insight is a holy grail for marketers and customer experience professionals. It can also help to provide automation in the customer journey, for example, by improving the artificial intelligence of chatbots and customising the customer journey depending on what the customers say and how they act.
However, across all organisations, ever-expanding amounts of data remain unanalysed, primarily due to their growing size and complexity. Furthermore, most of these data are unstructured or raw. Unstructured data such as text, image, audio, video, machine and sensor information all present major issues for organisations and the data scientists they employ. It is estimated that over 90 per cent of the data in existence today are unstructured.1
But how fast are these complex data growing? To put this in perspective, it is estimated that 90 per cent of all data in existence today were generated during the last five years. The digital universe is doubling in size every 12 months. Indeed, it is expected to reach 44 zettabytes (44 trillion gigabytes) in size by 2020 and will contain nearly as many digital bits as there are stars in the universe.
Buried deep within this mass of complex raw data are insights critical to innovation, decision making, customer service and revenue — that is, if they can be extracted with the right analytical tools.
At the moment, however, organisations are simply unable to access this insight. Some commentators estimate that less than 0.5 per cent of data are currently analysed.4 Meanwhile, IDC estimates that by 2020, as much as 37 per cent of the digital universe will contain information that might be valuable if analysed.
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