Advanced Analytics for Voice of the Customer (VoC) Programmes
Many companies today are increasingly challenged to maintain customer satisfaction and loyalty and to improve the customer experience. While organisations have programmes to measure and manage customer experiences, major challenges are the multiple information sources and the huge amount of structured and unstructured data available.
Although most organisations conduct continuous customer satisfaction surveys, the ability to deliver real insight and to implement actions for customer experience improvements from basic survey data is limited.
The other big challenges in retaining and delighting customers, improving the customer experience and understanding how to best manage customer relationships are to move beyond the raw survey and customer transactional data and to understand the voice of the customer in context.
However, the efforts to integrate all streams of structured and unstructured data are simply not efficient and cost-effective without advanced analytics. Advanced analytical approaches, either on their own or in conjunction, can help companies put customer insights in context, identify areas for customer experience improvements and new products and services, and build sophisticated models to understand, predict and proactively manage customer relations and interactions, and therefore customer loyalty and profitability. The application of these advanced analytical techniques enables users to extract knowledge from data and to create predictive models for better decision making.
The various procedures of advanced analytics that companies can utilize to integrate into Voice of the Customer programmes to better understand customers are described in a recent white paper published by SPA Future Thinking.
They include: key driver analysis, modelling anlaysis, insight mining, segmentation, social media integration and more.