How to overcome the many challenges associated with analysing VoC

It stands to reason that if we claim that ‘things’ are changing constantly that the Customer Experience Executive must understand these changes, constantly. They need to understand and stay informed about new or existing products and services as well as changes in customer expectations and competition.

This executive need for information is not new!  Current Voice of Customer (VoC) analytics can provide some insight capability such as satisfaction scores and topic trends, but quantifying the detailed topics including predictive factors was not possible - until now.

What we need now is:

  • A live early warning system of VoC insight, classified in a consistent and accurate way.
  • Quantifying what is happening in the business and the sentiment of those topics,
  • Generate further predictive models to identify the drivers of those insights and their financial impact.
  • Assistance for operational users to quickly prioritise and solve issues,
  • Guidance for CX and marketing executives identify revenue and cost-saving opportunities as well as take strategic decisions regarding investment and customer journey enhancements.

At the Customer Experience World 2017 (CEW2017), Rob Martin, Head of Sales at Warwick Analytics will reveal how their latest software, PrediCX, overcomes the many challenges associated with analysing VoC data. The delegates of the CEW2017 will come to understand how PrediCX will generate actionable insight from both structured data and the unstructured Voice of Customer (“VoC”) data automatically. Typically data such as:

  • Complaints
  • Reviews
  • Surveys
  • Enquiries
  • Social media.

PrediCX features two key technologies to automatically classify Voice of Customer data to a high degree of accuracy with minimal user input.

  1. AIR (Automated Information Retrieval) extracts all of the possible topics and associated sentiment from the raw data.
  2. OL (Optimized Learning) takes this rich output from AIR and uses it to generate predictive models. Crucially, OL ‘asks’ users for specific input for validation where it needs it to optimise performance.

Warwick Analytics software is based on sophisticated computer algorithms, developed at WMG at the University of Warwick, over a decade of academic research.

Rob Martin will highlight a few uses of this unique technology, PrediCX, born from over a decade of university research, that incorporates machine learning with the ease of text analytics – giving much greater accuracy, insight and early detection of issues, without the manual work, time and expense that text analytics requires.

At Customer Experience World we cover all aspects of how to implement successful customer experience transformation, using various tools and techniques, to better understand your customers in order to build loyalty.