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Data Analytics for Tech Support Enterprises


Imagine that a customer has an issue with the product and is calling up a tech support agent. The agent understands the issues, troubleshoots it and gets the feedback. The question is: The large amount of data’s which are collected through e-mails, text messages, audios, survey responses have been analyzed properly or not? The tech support companies don’t realize that these data’s are just sitting and not utilized as a source of information to increase customer satisfaction.

Now a days, the Enterprise tech support faces a lot of challenges on how to handle huge quantities of data and derive customer intelligence from it due to constant inflow of data through Omni channels like Phone, Email, Chat, & Social Media.

That is why Analytics led support plays a major role in the tech support organization which can manage not only the volume and velocity of data but also the variety in the form of dashboards.

It helps to analyze the customer data and derive customer insights to utilize the information that can add value to the support process.

These Insights are very useful to improve the customer metrics such as the Average Handling time, First call resolution, Net Promoter score which results in enhancing superlative customer experience.

Benefits of using Analytics

  • Gather appropriate information.
  • Competitive Advantage.
  • Provide better business decisions.
  • Effective Marketing.
  • Faster Issue Resolution.
  • Increase Customer Satisfaction.
  • Accelerate revenue & ROI.

Different Types of Analytical Techniques

  • Speech analytics: This helps the Tech support agents to identify, understand and analyze the customer’s requirements through phone conversation regarding an issue.
  • Text analytics: This is similar to speech analytics but it involves understanding the customer’s requirements through text or written documents.
  • Desktop analytics: It helps you to track and monitor your employees’ desktop activity and performance of systems which is useful for staff interactions. This allows you to gauge the performance of your agents and their systems and guide them if necessary.
  • Cross channel analytics: It allows you to identify and assess different channels used by the customers to interact with your organization which becomes easier to optimize customer interactions.
  • Self-service analytics: This allows you to assess customer experiences in self-service channels through internet such as the Knowledge base.
  • Predictive analytics: This allows you to assess and recognize ways to effectively communicate with your customers. This helps to optimize your sales, services, and interactions.
  • Performance Analytics: In the past, Tech support managers used to rely on daily reports to get a picture of how well things were going. But this type of reporting didn’t always provide an accurate picture of what was working and what wasn’t with respect to agents, teams and strategies. Today many outsourced tech support analytical services offers solution for online reporting and dashboard views of critical performance data, both real-time and historical. This helps the organizations to ensure the best possible experience for their customers.

AndrewRajdev Manohar

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