Enterprise IT News, Malaysia: Cognizant’s Vice President of Technology Practice Makes a Case for Digitally Transformed Product Support

“Many organizations are still in the era of customer contact centers, where support is provided in a reactive mode when customers reach out to the organizations with their problems, and receive fixes,” says Yoosuf Mohamed. “The Support Halo paradigm addresses and overcomes these shortcomings by leveraging information not just from in-house CRM and support systems, but also from social forums and device analytics.” Excerpts:

“Leading support organizations are using meaning mined from Support Halo to recode support processes and deliver more profound, positive and increasingly delightful customer experiences.

In fact, post-sales support is fast emerging as the key competitive advantage for staying relevant and winning market share.

The shortcomings that Support Halo wants to address stem mainly from traditional support, which focuses only on customer contact and fixing the issue.

The support is more transactional and the important KPIs tracked include customer satisfaction (CSAT), average handle time, average turnaround time, and average time-to-resolution.

Traditional support involves analysis of customers and support issues based on the data from in-house CRM and support systems.

Support Halo improves the customer experience in every support interaction. For instance, when the customer calls, the support team is ready with analytical data around the history of the reported problem, potential reason(s) for the current call, their business priorities, product features, and usage patterns.

This helps in call personalization and ensures better call resolution.

Creating the role of a Chief Support Officer to bring executive management focus to the support function is important. Support needs to be viewed as a revenue-enabling function rather than a cost center.

Through this model, we can go a step further and enable call router intelligence, based on interactions resulting in customer delight. Integrating data analytics, feature usage patterns and historical problem patterns thus provides predictive analytics to support agents and helps them to provide better customer service.”

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