'Read My Mind' - Using Analytics to Improve Customer Experience

Posted by Matthew Vallance

There has been a lot of hype around Big Data and its implication for customer engagement. At the same time, more and more organisations are realising the need to go beyond mere storage of data, and focus on analysis which transforms it into actionable insights. Big corporations like Amazon and Google are already on the forefront of combining Big Data with business analytics to understand customer behaviour more effectively and tailor product offerings accordingly.

According to a recent Research and Markets study, the global advanced analytics market is expected to increase 30 percent year-over-year between 2014 and 2018 helping businesses across industries decrease churn, reduce fraud, identify top customer prospects, and predict customer behaviour to offer solutions for improved service. The latter, offers exciting possibilities by leveraging historical data to anticipate customer needs and take appropriate action.

However, it remains to be seen how many businesses are actively pursuing big data initiatives to squeeze out valuable insights about customer behaviour and use it improve their service delivery models. There has been some traction with consumer goods companies embracing analytics, but I believe much more can be done.

One of our clients Unilever is a thought leader in converting Big Data into actionable insights. One of the ways it achieves this is through effectively using contact centres to understand what customers have to say  about its brands.

Yet another client, TalkTalk is focused on fostering a culture of continuous improvement through intelligence gathering. Through deploying speech analytics in its contact centres, the telecom operator is increasingly able to identify churn drivers and modify training programs for loyalty agents, to serve customer needs in the best possible manner. HGS which runs TalkTalk’s customer retention program has been able to implement a step change in its coaching regime for loyalty agents through leveraging such data. This is a great example of integrating continuous improvement into the DNA of your operation based on business analytics.

The other point I wish to emphasize is there has been an increasing maturity in the nature of analytics deployed – moving from simply descriptive to predictive and now prescriptive analytics (which suggest solutions based on predictions of customer behaviour). However, businesses also need to remember that analytics is only as good as the implementation of the action plan that follows. For analytics to drive change and continuous improvement, they should point to actionable tasks which can be implemented. If not, your operation runs the risk of ‘analysis paralysis’ with no quantifiable outcome to all your analytic efforts.

Consumers today are no longer passive recipients – they actively take to social media and digital platforms to advocate, criticise, review and rate brands and quality of service delivery. Businesses which have built capabilities to capture these customer interactions to transform them into actionable insight, will not only have the ultimate competitive edge, but will be better placed to deal with the customer if and when he falls foul of their service.


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