How exactly do you turn Big Data into Smart Data?

28 Jan 2016

Managing the customer experience is becoming the focal point for everything digital.

In the payments arena, new banks and new apps are being launched with alarming frequency, where the focus is partly on price saving but more so on the experience the customer has. In retail, too, innovation in the buying process and delivery (a big part of that experience) is getting massive attention. In a few short years, retailers have gone from trying to block shoppers comparing prices while in-store to actively promoting their online deals while in-store.

For everyone, the challenge is to make the customer experience as good as the masters (i.e. Amazon, Google and Apple) do. The retail store and online worlds are blurring, and the best companies will be judged not on price but on the experience their customers are having.

How, then, do telcos (and indeed ‘legacy’ banks) hope to catch up and regain their place in customers’ affections?

The good news – for telcos at least – is that customers basically trust them. And trust is an asset that needs to be carefully leveraged.

The way to do that, according to a discussion paper from real-time specialist Openet, is by converting big data into ‘smart’ data. While this may sound like turning lead into gold, or a bit of a stretch by the marketing team, the paper presents some very practical examples of how to do it.

Telcos must, as the paper points out, get beyond using historical data to ascertain what a customer wants. This approach worked well when telcos or CSPs were selling static services like traditional voice and basic data connectivity, but a customer’s telecoms spend is now part of an ever-increasing digital spend. This includes everything from movies, music and telecoms connectivity to home security and automation, health and wellness, and even digital voice services.

Understanding what customers are experiencing at all touch points (from network to self-service) and using this information in a timely (increasingly real-time) manner is the new way to drive relevant offers, communications and deliver a better customer experience.

There are, of course, many different sources of data which CSPs can draw on. Location data, network usage data, usage patterns, device type and ownership and actual financial value of a customer can all be tapped into. Getting a holistic customer view is not just about having a central repository of all customer subscription and usage data. It also includes understanding customer context.

This data alone is not ‘smart’, and almost 90% of it is unused or thrown away. It takes common sense, some clever data scientists and the integration of data sources to make it ‘smarter.’ In order to provide context aware CEM, CSPs need to monitor the experience of each subscriber and react to issues in seconds.

Combining usage patterns with current network conditions and location will forewarn and therefore forearm customer service teams. Understanding quickly that a high value customer is having difficulties in accessing a service can be acted on. This one example can be easily extended to self-service, where constant improvement will pay dividends and monitoring social media will alert managers of problems in a timely manner.

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