The world is moving towards a data driven economy, with companies buying and selling information in order to learn more about their consumers to improve targetted sales campaigns. But with so many platforms now enticing consumers to hand over their own personal information, David Parcell, managing director EMEA and corporate officer for data security software firm Verint Systems, discusses the growing trend and its management.
Big data is fast becoming one of today’s most talked-about technology trends. Marketers are one of the professional groups who stand to gain most from these new-found capabilities to analyse data that a few years ago would have been too complex to capture and store, never mind make sense of. Behind the hype lies a golden opportunity for marketers to add a new arrow to their quiver – and help their organisation get ahead of the competition. Cutting through all the hoopla can be a challenge, so it’s important to understand just what big data can achieve, what data is most useful, and how to go about using it.
For example, we recently worked with O2 Ireland, which was striving to encourage its customers to adopt a particular top-up plan. Opt-ins had been disappointing, but analysis of unstructured customer service data, focussing on references to the plan, showed that the offering itself was popular – but customers were simply forgetting to top up by the required deadline. As a result of this new insight, the company began sending out SMS reminders, and the opt-in rate quickly started to improve.
Another recent example involved marketers at a leading UK insurer, who were struggling to address a high rate of churn. The team had assumed that the issue was price, and that the company was losing out to better deals available on price comparison websites. However, analysis of the available data showed that the company’s customers were actually not at all price-sensitive. In fact, they were quite happy to pay a premium for good service. The reason customers were leaving was that they found the company’s policies confusing, and ill-suited to their needs. This insight allowed the company to change both its service offering and its marketing message, and significantly reduce its turnover of customers.
Managing and understanding such large volumes of data needn’t be as daunting as it first appears. In both these examples, the information was freely given by customers, but the organisations lacked the means to capture and interpret it. For marketers, customer service data is often the easiest place to apply big data analysis, as it includes unsolicited feedback that is often so illuminating. There is much to be gained from the asides and chance remarks that your customers make about your brand - but they have historically been very hard to capture and use on any meaningful scale.
Traditional tools for data management and analysis are often inadequate for making sense of the information in thousands of transcribed phone calls, call centre agents’ notes, customer emails, Facebook posts, scanned letters, webchats, and tweets. Customer analytics is changing this and can be a rich source of insight, allowing you to listen directly to the true voice of your customers. It searches customer comments and feedback for key words or phrases as well as their context to uncover sentiment and emotion.
Technology can support the creativity and ingenuity required to gain insight into customer attitudes, and using them to build brand awareness and encourage loyalty. It helps remove some of the guesswork and if you start with the right kind of data, choose the right kind of analytic tools, and set them up in the right way, then you have a powerful tool with which to test your assumptions, and demonstrate the value of marketing tactics to the rest of the business.
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