Adds new reports for net promoter score issues, customer churn and competition
Attensity Group has released Analyse for VOC Version 5.2, a text analytics application that enables business managers, customer analysts, customer service teams and marketing departments to analyse Voice of the Customer (VoC) feedback across a variety of customer conversation channels including emails, CRM notes, survey responses and social media.
According to Attensity, the new offering introduces new reports for sentiment, Net Promoter Score (NPS) issues, customer churn and competition. It also includes social media intelligence capabilities that make the application’s Natural Language Processing (NLP) engines better at understanding social media speak.
The company claims that the real-time integration architecture available in version 5.2 provides an environment for driving action into CRM systems, email management systems such as Attensity Respond, social media and more based on the millions of potential customer communications that happen each month for most large enterprises.
The company said that combining Analyse for VOC with the add-on module Attensity Cloud expands analysis capabilities to the vast sources of information found online. Users can expand their customer analytics to the insights hidden online by analysing conversations in social media outlets such as web forums, blogs, wikis, micro-blogs including Twitter and Facebook, LinkedIn, Xing, customer portals such as Epinions.com, news feeds, and many others.
In addition, new capabilities of version 5.2 includes business intelligence and CRM integration through an architecture which enables deep analysis of large amounts of customer data to drive actions into CRM, business intelligence and legacy systems, and the ability to share key VOC insights with other users via a portable flash enhancement. It also includes analysis enhancements, which includes normalised time-series charts and calculated values that enable users to track customer issues and sentiment over time; and deep sentiment scoring and issues analysis.