Unlock Customer Insights
AI-Powered Sentiment Analytics for Call Centres
DoxaMeter – our Sentiment Analytics tool for outbound call centres – a powerful software that helps businesses understand customer intent from voice call conversations.
Measure Your Customer Mood using DoxaMeter.
Doxameter, the sophisticated sentiment analytics engine, enables customer-facing organizations to efficiently manage customer perceptions, enhance customer experiences, and thereby drive positive customer responses. This is accomplished by extracting actionable insights from call centre agent conversations. The result? An augmented customer conversion rate.
Sentiment
Analytics
Unlocking emotional insights intelligently, with more than 90% accuracy rate.
Emotional State Discovery
A data-based approach to finding sentiment and intent from customer interactions.
Advanced LLM Solution
Analytics Engine leverages LLM, NLP and BERT for sentiment extraction and analytics.
From the CPaaS Suite
A conversational analytics tool belonging to the Communication Platfom-as-a-Service suite.
Unlocking emotional insights, intelligently.
The tool uses customer conversations as input and opinion of the customer on different dimensions as output.
- Boost agent performance with upto 15% uplift
- Categorizes customer intent in more than 90% cases
- Return on investment within 12 months
How We Help Your call centre Business
Performance uplift upto 15% in agent performance
Customer-centric Conversations
Better understanding of customer intent allows for enhanced conversations, leading to increased customer satisfaction and potential sales growth.
Boost Outbound Sales Effectiveness
Identify areas for improvement in call centre operations and ensure that agents highlight crucial product advantages, adhere to the scripted flow, consistently.
Improve CC Agent Performance
Aids the agent with a workable call-flow and critical customer info to be solicited, identifies agent misconduct and areas for improvement.
Actionable Customer Insights
The hidden trends and patterns in customer conversations generates quantifiable insights about how positively or negatively you are viewed by target customers.
core features
Custom-built to monitor sentiments from call-centre conversations
The software uses Aspect Matching and Opinion Mining methods for sentiment extraction. Customer Intent is classified using Bi-directional Encoder Representations from Transformers. The tool identifies and categorizes customer intent with more than 90% accuracy rate. It can benchmark call-centre agent performance, ensuring outbound call quality and compliance. Better understanding of customer intent allows for enhanced customer conversations, leading to potential sales growth.
- High Accuracy Rate
- High Processing Rate
- ML-based Analytics Engine
- Advanced Text Analytics
- Intent Mining Algorithm
- Compliance & Security
- Multiple Language Support
how it works
The Process Flow
Speech Recognition & Pre-processing
The audio WAV files is ingested into the analytics system, then voice-to-text conversion using Azure, including language identification, transcription and formatting for sentiment classification.
Identification of Dimensions
Based on the planned process flow and identified KPIs, information is extracted using lexicon based parsing rules and classifiers are used to classify words into aspects.
Aspect Matching & Extraction
Roberta Model is used for extraction which classifies aspect into each configured dimension, while intent miniing algorithm categorizes customer interactions.
Data Aggregation & Data Visualization
The values calculated at transcript level are aggregated to generate overall metrics for each dimension, and integrated using Elasticsearch for efficient indexing and retrieval.
