How to convert big data into big returns
Does this scenario ring any bells?
A senior level, multi-channel marketer is asked by the board to tell them about ‘Big Data’. The typical response would be “It’s a good concept, one which has huge potential benefits – but it is extremely costly and would require a complete overhaul of marketing processes and IT infrastructure – put simply it is not realistic.”
A few years ago that particular statement would have been true, but nowadays many of the technical obstacles of gathering detailed multi-channel customer data have been removed and the opportunity to understand customers in minute detail is readily available.
The arrival of technologies that can gather individual-level online data, the ability to access and mine unstructured data - such as social media - and advanced call centre and voice analysis software, mean that an organisation can now amass huge amounts of customer insight which allows them to market to individual customer requirements.
The ability to gather this data is, however, taking more focus around Big Data than it should. At the end of the day, turning all that data into actionable insight is where the true value of Big Data lies. No matter how well data can be gathered and analysed, unless the effort actually results in enhanced customer engagement, an improved customer experience and ultimately increased revenue and/or reduced costs, it would appear to be a pointless task.
Big Data has transitioned from an IT-focussed term into something that now needs to be understood by the wider business. It’s critical that marketers understand the importance of Big Data has on driving value for the business - Big Data should lead to big returns, not huge headaches.
Getting value from data in a Big Data world involves a much more complex multi-functional team than previously. Senior marketers, analysts, IT professionals and database experts need to work together as a true team with a clearly defined set of objectives.
With so many different ways of thinking and business objectives amongst that group, finding productive harmony can be hard, but it is as essential if the value from Big Data is truly to be realised.
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