By adaptive - June 25th, 2013

Raw data is about as useful as a chocolate teapot so here’s how to manage it effectively for powerful business results.

To be successful you need to look after your customers.  In part one we established that the market today is far too busy, noisy and demanding to allow lackadaisical support or shoddy customer service and that now, more than ever, organisations have to find various solutions for capturing the data they need in order to stand out from the crowd. However, now we have this data in spades, where are we to put it? How is that data to be managed in order to be of any value?

“Some people have likened data, and especially big data, to the new oil, but exactly like oil, it must be processed to become worthwhile,” says Adam Beales, Distribution and Industrial Leader, Big Data, IBM Europe.

Lawrence Jones, CEO of UK Fast, agrees, “Without capturing and analysing data it’s difficult to see the full picture. When you have a good overview of your customers, then you can really hone your approach to customer service.”

Lawrence Jones, CEO of UK Fast

Fortunately, unlike oil, the refining processes need not be as expensive, or environmentally unfriendly. There are several solutions that have been devised to meet the needs of organisations – regardless of size – as they gather and attempt to interpret their data. It isn’t so much a question of whether you can interpret your raw data, but rather which option you will choose that best suits your business model and how you plan to use the information you have accumulated.

“Once you get the right technology in place, everything else should follow,” says Marjie Gould, VP Marketing EMEA at Verint Systems, “To really get to the heart of data you have to be able to interpret vast volumes quickly and easily. This can only be done with comprehensive analytics tools that gather data from a variety of sources, analyse it, and display the results in a clear and visual way.”

A solution ahoy

There are several different methodologies available to your business for handling and managing raw data: These can be tailored to your business and adapted to suit the different demands of the different markets. Beales believes that there are three levels of sophistication where IBM is seeing the adoption of technologies to streamline the development of insights from social media:

1.    Sentiment analytics

2.    Integration with corporate data

3.    Real-time application of insights

“Combining insight and sentiment with corporate data really allows organisations to understand the business impacts of the buzz,” adds Beale, “With the ‘so what?’ question, for example, 88% of tweeters in London like my new ad campaign. So what? The statement should read – 88% of Londoners like my new ad campaign and sales are up by 12% in the south, while only 3% in the north.”

To achieve this goal, your business needs to examine the value of investing in a platform that can handle the volume of data produced in relation to your business, and deliver vital corporate facts that can be used to drive sales, manage stock and even isolate specific product issues.

“Ideally, data should be managed centrally on one platform to give a complete overview of the business at the touch of a button,” says Gould, “This approach will enable information from different departments to be collected and analysed from one system.”

Processing the data and translating it into manageable chunks of information needs more than just a platform. The business also has to have clearly defined goals before they head into the fray. A bundle of data is of little use if it hasn’t been structured appropriately or targeted towards the right area of the organisation.

Many corporations are unaware of how to use the information gleaned from their data. According to Gartner, they outlined three social analytic techniques which can help your business better understand social audiences:

  • Dashboard key performance indicators
  • Social metrics
  • Visualisation

Example of Basic Dashboard for Monitoring Twitter

Management is key

Using these analytics will provide you with a robust strategy for handling the way your data is interpreted. That said, however, where does the data go? Does it need to be shared across all business silos? Should every element be available to all? The jury is out on this. Beale believes that this is questionable and asks why the HR department would want to know about customer service data.

On the other hand, Jones reveals a successful business model where the managing director of UK Fast presents data insights to the teams to ensure that everyone in the organisation understands how they can improve and how well they are faring. The dissemination of data needs to fit the business and, in addition, to determining where the information needs to be fed. There is still question of how to ensure the customer services team gets value from it.

“The team that uses this data needs to be adequately trained before the systems are implemented so the business can reap the benefits of such technology, while remaining productive,” says Gould, “This will also ensure buy-in from the staff that use it which will be critical to the success.”

It’s all very well implementing a shiny new data management platform that can analyse customer thoughts at the flick of a switch, but how is that information being processed? Is it easy to get to? The data needs to be accessible to the teams and it needs to be structured in a way that allows them to easily connect the dots and see how the information can be used effectively.

“There are reasonable filters which can be applied, of course, focusing on current and future target markets, customer segments, product and service categories relevant to strategic plans,” says Beale, “It is incredibly difficult to put a value on data without having an understanding of how it will be used. Once that is known, it becomes a much more achievable task.”

The value of data cannot yet be fully estimated. There are still factors that are not realised yet and ways of interpretation that may yet come to light; and so it is increasingly important that businesses invest in the technology that can store and handle this data so information isn’t lost. A decent platform, clear-cut goals and a well-trained team that can interpret the information properly – these are the ingredients of a successful implementation of a customer feedback system.

In the final part of the series we will be examining the value of sentiment and how this can work within the context of the business and the customer services team.          

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