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The need for hyper-personalized self-service and omnichannel customer experience

The customer engagement ecosystem has a high potential to produce business intelligence and analytics to improve experience as well as business growth, and requires a new data-acquisition approach with intent-driven analytics. However, businesses face the challenge of dealing with the unstructured nature of conversational data and deriving multidimensional inferences from conversational analytics. Insight engine analyzes interactions and derives meaningful insights to drive critical transformational and operational businesses elements. A structured approach to transform the engagement hub into an insight engine entails:

  • Data ecosystem preparation: Capturing conversation data from each channel of the engagement ecosystem and analyzing the intent and emotions of conversations
  • Data transformation: Identifying business cases to perform targeted analytics on raw data
  • Presentation layer: Generating storytelling dashboards with transformed data and establishing real-time connectivity of data ecosystem for business users
  • Inference stage: Making fact-based inferences and decisions on continuous improvement of customer engagement ecosystem
Arvind Sangvikar

Head, Experience & Intelligence, Business & Technology Services, TCS

Jinal Shah

Data Science Consultant, Experience & Intelligence, Business & Technology Services, TCS


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