In the Hastings Direct VoC Feedback Analyses example, we analysed public review feedback for a period of 12 months to understand what improvements could be made and identify the impact such improvements could have on customer experience, as well as how these impacts would transfer to revenue savings and operational improvements.
Analysing VoC feedback over a prolonged period allows you to detect changes in customer experience. Using AI to do this enables a user to analyse unstructured text data in volumes that are much higher than traditional methods such as manually reading comments, and removes the risk of sampling bias.
Categorising this feedback using NLP & Sentiment analysis gives users the ability to group common themes together and helps detect key areas of interest and commonality (in engagement, processes, products and more) that are undetectable through manual tagging processes. It also highlighs key areas of concern within the businesses operations as well as defining subtopics from these high-level groups giving specific stakeholders granular insights in to areas that impact their aspect of the business. Most importantly, reporting consistent, detail-relevent and actionable information, with proven impact measurements, to key stakeholders in a timely manner is the critical link between identifying and acting on customer pain points.
Explore in-depth how these findings were achieved using Touchpoint Group's AI Customer Analytics Tool by visiting the case study here. If you have data to analyse, get in touch with our team of experts to get started analysing your customer feedback data today.
Contact our team of experts to learn more about the VoC Feedback Analysis.