Overview
Once call recordings are uploaded and processed, detailed insights become available in the Call Analysis view. This page provides a comprehensive breakdown of the interaction, including the conversation transcript, sentiment analysis, speech metrics, and AI-generated summaries. The analysis helps reviewers quickly understand the context of the conversation, identify key events during the call, and evaluate agent performance more efficiently.AI Analytics
The AI Analytics tab provides automatically generated insights about the call based on the conversation between the agent and the customer. These insights help users understand the purpose of the call, how it progressed, and how effectively the interaction was handled.1. Call Summary
The Call Summary section highlights the most important aspects of the conversation. It includes the following insights:1.1 Reason of the Call
This describes the primary purpose of the interaction based on the conversation between the agent and the customer. Example: The primary reason for the interaction is to initiate a conversation regarding financial services with the customer.1.2 Resolution
This indicates whether the agent addressed the customer’s request and how the conversation concluded.It summarises the outcome of the interaction.
1.3 Summary
This provides a short narrative describing how the conversation progressed from start to end. It typically includes:- Greeting and introduction
- Discussion between the participants
- Key conversation points
- Outcome of the interaction
1.4 Feedback
The feedback section highlights possible improvements in the interaction. These insights may include suggestions such as:- Improving communication clarity
- Providing additional context
- Enhancing customer engagement
1.5 Call Forwarding
This indicates whether the call was transferred or forwarded during the interaction. If the call was not transferred, the value is displayed as No.2. Recording & Transcript
The Recording & Transcript section allows users to review the conversation in detail.3. Call Recording
The audio player allows users to listen to the call recording directly within the interface. Features include:- Play and pause controls
- Playback timeline
- Adjustable playback speed
4. Transcript
The transcript displays the conversation between the agent and the customer in a chat-style format. Each message is tagged with:- Speaker identification (Agent or Customer)
- Sentiment detected for that message
- Emotion associated with the response
5. Sentiment Indicators
The transcript also highlights sentiment detected in each message. Examples include:- Positive
- Neutral
- Negative
6. Rate of Speech
The Rate of Speech metric measures how fast the agent is speaking during the conversation. This is typically measured in words per minute (WPM). Monitoring speech rate helps identify communication issues such as:- Speaking too quickly for customers to understand
- Long pauses during conversation
7. Key Indicators
Key Indicators allow organizations to track specific conversation signals that are important for quality monitoring. These indicators may represent:- Compliance phrases
- Required statements
- Product mentions
- Process confirmations
8. Key Metrics
The Key Metrics section highlights important operational metrics related to the interaction. These metrics help understand how effectively the conversation progressed. Examples of metrics may include:- Conversation duration
- Key interaction signals
- Process adherence indicators
9. Advanced Metrics
The Advanced Metrics section provides deeper analytics about the interaction. These metrics help analyze conversation flow and communication patterns. Metrics include:9.1 Initial Language
The language detected at the beginning of the conversation.9.2 Number of Turns
The number of conversational exchanges between the agent and the customer. Each turn represents a switch between speakers.9.3 Number of Nudges
This metric indicates the number of times the system detected potential prompts or cues that could guide the conversation.9.4 Dead Air
Dead air represents periods of silence during the conversation where no one is speaking. Long periods of silence may indicate issues such as:- Delays in response
- System interruptions
- Agent hesitation
9.5 Interest Conversion Turns
This metric measures the number of conversation turns where customer interest or engagement increased during the call.9.6 Average Customer Response Time
The average time taken by the customer to respond during the conversation.9.7 Average Agent Response Time
The average time taken by the agent to respond to the customer. This helps evaluate responsiveness during the interaction.10. Key Topics
The Key Topics section highlights frequently used words or topics that appeared in the conversation. These topics are presented as a visual word cluster to help reviewers quickly identify the dominant themes of the interaction. This provides a quick overview of the discussion topics without reviewing the full transcript.QA Analytics
Overview
The QA Analytics section provides a structured evaluation of the call using a scorecard form. This evaluation measures the quality of the interaction based on predefined criteria such as greeting, communication clarity, professionalism, and process adherence. When a call is processed, the system automatically applies the default scorecard form and generates an evaluation score based on the responses detected from the conversation. This allows reviewers to quickly assess how well the agent adhered to the expected call-handling guidelines.Scorecard Evaluation
At the top of the page, the scorecard used for evaluation is displayed. The scorecard contains multiple sections, each representing a category of evaluation. Examples of sections include:- Call Opening
- Soft Skills & Professionalism
- Communication Skills
AI Score
The AI Score represents the overall quality score generated from the scorecard evaluation. This score is calculated based on the marks assigned to each question in the scorecard. Example: AI Score: 35 / 100 This score provides a quick indicator of how well the agent performed during the interaction.Scorecard Questions
Each section contains multiple questions that evaluate specific behaviors during the call. Examples include:- Did the agent greet the customer and introduce themselves appropriately?
- Did the agent clearly state the purpose of the call?
- Was the agent’s tone friendly and professional?
- Did the agent inform the customer that the call is being recorded?
- Yes
- No
- N/A (Not Applicable)
Question Scoring
Every question in the scorecard has predefined marks. Example scoring:- Yes → Full marks
- No → Zero marks
- N/A → Question excluded from scoring
Section Scores
Each scorecard section has a maximum mark value. Example: Call Opening – Total Marks: 10 The marks obtained from questions within that section are aggregated to generate the section score. Example: 5 / 10 marks This helps reviewers understand which parts of the interaction were handled well and which areas need improvement.Collapsible Sections
Scorecard sections are collapsible, allowing users to expand or collapse sections as needed. This helps reviewers focus on specific parts of the evaluation without scrolling through the entire scorecard.Using QA Analytics
The QA Analytics view helps organizations:- Monitor adherence to call handling guidelines
- Evaluate agent performance consistently
- Identify training opportunities
- Improve overall customer interaction quality