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Automated Predictive Analytics for Customer Experience

PrediCX provides automated predictive insight from VoC data embedded straight into the company’s processes. It does this firstly by classifying VoC data and then generating the predictive factors of those classifications. The output is an Early Warning System of topics and factors e.g. the hotspots of an emerging service issue, quantifying its impact, as well as factors hinting as to the potential root cause. It can also be used to automate the handling of queries and complaints as well as warranty processes where relevant, and employee voice data can be analysed too. This is invaluable for executives and operating managers alike.

How it works

PrediCX features two key technologies developed over a decade of academic research. Firstly AIR (Automated Information Retrieval) extracts all of the possible topics and associated sentiment from the raw data. Secondly 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 optimize performance.

As a result, PrediCX can automatically classify VoC data to a high degree of accuracy with minimal user input. And because it’s accessed via an API (cloud or onpremise) it can be easily deployed and operationalized.

Watch an overview of PrediCX

Typical use cases for PrediCX

Use CaseImpact and Impact Type
Early Warning SystemHuge and tactical. Early warning and quantification of ‘hotspots’ on customer journey. Feeds existing processes

Predictive Factor Identification

Huge and strategic. Prescriptive analytics based on business impact

Automated Query Handling (Complaints, Claims and Warranty)

Large and tactical. Improve accuracy, turnaround time and satisfaction

PrediCX Technical Comparison to other 'best in class' products

FeaturePrediCXText AnalyticsPredictive Analytics
Handles complex sentiment analysis

Classifying unstructured data

Extracting features from unstructured data

Predictive analytics with heterogeneous data

Process improves proactively with use

Automation: Real-time early warning system

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