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Overview

eigi.ai’s Call Analysis feature automatically processes every conversation to extract valuable insights, generate summaries, and trigger automated workflows. Turn unstructured conversations into structured, actionable data.

Enabling Call Analysis

Configuration

1

Navigate to Analysis Tab

Open your agent and select the “Analysis” tab
2

Enable Analysis

Toggle “Call Analysis Enabled” to activate the feature
3

Configure Schema

Define what data you want to extract from calls
4

Set Up Notifications

Optionally configure alerts based on analysis results

Analysis Schema

Define What to Extract

Create a custom schema that tells the AI exactly what information to pull from conversations:

Text Fields

Extract text data like names, reasons, feedback

Number Fields

Capture numeric values like ratings, quantities, scores

Boolean Fields

Yes/No determinations like “interested”, “resolved”

Choice Fields

Categorical values from predefined options

Example Schema

FieldTypeDescription
customer_sentimentChoicepositive, neutral, negative
issue_categoryTextType of issue discussed
resolution_statusBooleanWas the issue resolved?
satisfaction_scoreNumber1-10 rating if provided
follow_up_neededBooleanDoes customer need follow-up?
key_topicsTextMain topics discussed
action_itemsTextNext steps identified

Analysis Prompt

Customizing Analysis

Write specific instructions for how calls should be analyzed:
Analyze this customer service conversation and extract:

1. Customer Sentiment: Determine if the customer's overall sentiment
   was positive, neutral, or negative based on their tone and words.

2. Issue Category: Identify the main reason for the call
   (billing, technical, general inquiry, complaint, etc.)

3. Resolution: Did the agent successfully resolve the customer's issue?
   Answer true or false.

4. Satisfaction Score: If the customer expressed satisfaction or
   gave a rating, capture it on a 1-10 scale. Otherwise, estimate
   based on the conversation tone.

5. Follow-up Needed: Based on the conversation, does this customer
   need any follow-up action? Answer true or false.

6. Summary: Provide a 2-3 sentence summary of the call.

Call Recording

Capture Every Interaction

Enable recording for compliance, training, or quality assurance:
  • Enable/Disable: Toggle recording per agent - Automatic Start: Recording begins when call connects - Secure Storage: Encrypted storage with access controls
  • Review recordings directly in the dashboard - Synchronized with conversation transcript - Adjustable playback speed
  • Configurable retention periods - Automatic cleanup of old recordings - Export before deletion if needed

Video Analysis

For Video-Enabled Agents

When using video avatars, additional analysis capabilities are available:
  • Engagement Detection: Measure user attention and engagement
  • Visual Context: Capture context from screen shares
  • Interaction Quality: Assess video call quality and experience
Video analysis is available for agents using HeyGen or Tavus video avatars.

Structured Data Extraction

Automatic Data Capture

The AI extracts structured data from natural conversations: Example Conversation:
Agent: "May I have your email address for the confirmation?"
Customer: "Sure, it's john.smith@email.com"
Agent: "And what date works best for you?"
Customer: "How about next Tuesday at 2pm?"
Extracted Data:
{
  "email": "john.smith@email.com",
  "preferred_date": "Tuesday",
  "preferred_time": "2:00 PM"
}

Analysis Results

Viewing Results

Access analysis data for each conversation:
1

Open Call History

Navigate to Call History in the dashboard
2

Select Conversation

Click on any completed conversation
3

View Analysis

See the Analysis tab with all extracted data
4

Export

Download data in JSON or CSV format

Data Fields

Each analyzed call includes:
FieldContent
TranscriptFull conversation text
SummaryAI-generated call summary
DurationCall length
OutcomeSuccess/failure/transfer
Custom FieldsAll schema-defined extractions
TimestampsStart, end, key moments

Notifications

Alert Configuration

Trigger notifications based on analysis results:

Email Alerts

Send email when specific conditions are met

Trigger Fields

Alert based on any extracted data field

Threshold Rules

Notify when values exceed or fall below thresholds

Instant Delivery

Receive alerts immediately after call analysis completes

Example Triggers

TriggerConditionAction
Hot Leadlead_score > 80Email sales team
Negative Sentimentsentiment = negativeAlert support manager
Escalation Neededescalation_requested = trueNotify supervisor
High Valuedeal_value > 10000Alert account executive

Use Cases

Quality Assurance

  • Monitor agent performance across all calls
  • Identify training opportunities
  • Track resolution rates and customer satisfaction

Sales Intelligence

  • Score and prioritize leads automatically
  • Extract buying signals and objections
  • Track conversion metrics

Compliance

  • Ensure required disclosures are made
  • Verify identity confirmation steps
  • Audit conversation quality

Customer Insights

  • Identify common pain points
  • Track feature requests
  • Measure sentiment trends

Best Practices

Start Simple: Begin with a few key fields and expand as you learn what’s valuable.
Be Specific: Clear, specific schema fields yield more accurate extractions.
Test Your Schema: Run analysis on test calls to verify fields extract correctly.
Ensure your analysis practices comply with privacy regulations and disclose recording where required.

Troubleshooting

  • Verify “Call Analysis Enabled” is toggled on - Check that you have an analysis prompt configured - Ensure the call completed successfully
  • Review your analysis prompt for clarity - Make field definitions more specific - Test with sample conversations
  • Some fields may be empty if data wasn’t discussed - Add “N/A” or default value instructions to your prompt