Understand Feedback

Understanding customer feedback, at both individual and group levels, is an essential prerequisite to action.

CentraCX VOC is the platform to assist your business in collecting customer feedback and gaining deep insights in to your customers, products, processes an employees.

Key to effective understanding, is not just effective surveying, but incorporating context. Without the context of the survey it’s not possible to understand the factors that have led to the customer opinion.

CentraCX VOC Tribal Analytics builds on context by bringing together the wisdom of frontline employees, business stakeholders and machine learning to drive understanding that is not otherwise possible.


CentraCX VOC incorporates contextual information in regard to each survey. The context is passed with the survey trigger and can include as much information about the specific customer, interaction, products, processes and services that is available.

All context information is retained with the survey through the analysis and action stages allowing deep analytics and insights to occur both within CentraCX and within the business’s CRM or Data Warehouse systems.

Machine Learning

CentraCX Machine Learning analyses all customer and employee feedback. Verbal feedback is automatically transcribed and together with digital feedback is analysed for sentiment, names and reason for opinion.

As well as powering Tribal Analytics all Machine Learning analysis is incorporated in to the context associated with each survey creating the opportunity to analyse customer opinion from every dimension.

Tribal Analytics

Tribal Analytics delivers the ability to deeply understand customer opinion at scale, by engaging Machine Learning and the wisdom of employees through out the business.

Delivering real-time customer opinions to the frontline team members that supported the customer, brings critical context, through the translation of ‘customer language’ to ‘internal language’.

Bringing contextualised customer opinion to stakeholders that are otherwise disconnected from customers, creates the opportunity for truly deep understanding of customer perspectives.

Single Source of Truth

As surveys are completed and analysed, data is sent to your CRM or Data Warehouse. With the full set of feedback data, including metrics, qualitative feedback, contextual information and machine learning data, inserted in to your customer record systems, there is a single source of truth.

Leveraging the power of CentraCX VOC Tribal Analytics, together with a single customer data repository, creates the opportunity for deep data analysis, to really understand customer and employee opinion in the context of your enterprise data.


CentraCX VOC dashboards are specific to each user, displaying the metrics that are most relevant to them.

With over 50 different preconfigured CX metrics, and the ability to easily create entirely new ones, dashboards showing at a glance what customers think of your business, are seconds away.

Every frontline team member, manager and stakeholder can have their own personalised dashboard displaying the most relevant information for them.


Creating easy to understand, but informative charts, is essential to communicate performance trends and directions effectively.

CentraCX VOC supports data visualisations that allow businesses to view performance over time. Enriched with customer and interaction context, charts are filtered to show the performance of the product, service, process or any contextual information included with the survey.​

Drill down through the hierarchy to compare performance between individuals, teams, business units and divisions.

Deep Dive

Deep Dive into data, by searching and filtering customer feedback. Utilise criteria such as:

  • Scores & Metrics
  • Context information such as customer ID, Segment, Products
  • Employee information such as the team, agent, location or business unit that serviced the customer
  • Words and phrases of the qualitative feedback
  • Comments and feedback that employees have made on the customer’s feedback.
  • Machine Learning results such as sentiment, entity and reason for sentiment.