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‎Specialized Areas/Virtual Agent Conversation Analyzer/README.md‎

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# VA Conversation Analyzer
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A background script that generates comprehensive analytics reports on Virtual Agent conversations, providing insights into usage patterns, topic performance, and user engagement.
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## ⚠️ Important Note
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This script analyzes data from the ServiceNow Virtual Agent (VA) `sys_cs_conversation` table.
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## What It Does
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The script:
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1. Analyzes all Virtual Agent conversations within a specified time period (default: 30 days)
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2. Generates statistics on topic usage, completion rates, and abandonment patterns
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3. Breaks down conversation data by department, time of day, and user engagement
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4. Identifies topics with high abandonment rates that may need improvement
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5. Provides actionable recommendations based on the data
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6. Calculates user engagement metrics including power users vs. casual users
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## Use Cases
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- **Topic Performance Review**: Identify which topics are most/least effective
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- **Service Improvement**: Find topics with high abandonment for optimization
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- **Resource Planning**: Understand when and how users interact with VA
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- **Executive Reporting**: Generate comprehensive VA usage reports
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- **User Behavior Analysis**: Understand your user base's engagement patterns
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- **ROI Measurement**: Track VA adoption and success metrics
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## Sample Output
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```
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=== VA Conversation Analysis Report ===
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Analyzing conversations from last 30 days
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Total Conversations: 1,247
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=== Topic Statistics ===
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Top Topics by Conversation Count:
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-----------------------------------
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Password Reset
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Total: 324 | Completed: 298 | Abandoned: 26 | Abandon Rate: 8.0% | Unique Users: 215
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Software Request
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Total: 187 | Completed: 165 | Abandoned: 22 | Abandon Rate: 11.8% | Unique Users: 134
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Topics with High Abandonment (>30%):
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-------------------------------------
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⚠️ VPN Setup - 42.3% abandonment (11/26)
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⚠️ Printer Configuration - 35.7% abandonment (5/14)
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=== Department Statistics ===
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IT: 456 conversations (36.6%)
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HR: 298 conversations (23.9%)
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Finance: 189 conversations (15.2%)
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=== Time of Day Statistics ===
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Morning (6am-12pm): 423 (33.9%)
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Afternoon (12pm-5pm): 587 (47.1%)
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Evening (5pm-10pm): 201 (16.1%)
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Night (10pm-6am): 36 (2.9%)
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=== User Engagement Statistics ===
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Total Unique Users: 542
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Power Users (5+ conversations): 89
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Casual Users (<5 conversations): 453
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Average Conversations per User: 2.3
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=== Overall Statistics ===
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Total Conversations: 1,247
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Completed: 1,089 (87.3%)
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Abandoned: 158 (12.7%)
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Average Daily Conversations: 41.6
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=== Recommendations ===
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🔍 Review 2 topic(s) with high abandonment rates
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📢 Low engagement - consider promoting VA to increase awareness
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```
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## Configuration Options
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### Adjust Analysis Time Period
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```javascript
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// At the top of the script, modify:
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var config = {
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daysToAnalyze: 30, // Change to 7, 14, 60, 90, etc.
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includeAbandoned: true,
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includeCompleted: true,
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minConversations: 5
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};
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```
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### Focus on Specific Topics
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```javascript
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// Add after line 15 (conversations.query()):
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conversations.addQuery('topic', 'specific_topic_sys_id');
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```
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### Filter by Department
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```javascript
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// Add department filter:
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conversations.addQuery('user.department', 'IT');
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```
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## Prerequisites
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- **ServiceNow Virtual Agent** plugin enabled (com.glide.cs)
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- Access to `sys_cs_conversation` table
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- Background script execution rights
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‎Specialized Areas/Virtual Agent Conversation Analyzer/conversation_analyzer.js‎

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// ========================================
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// VA Conversation Analyzer - Background Script
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// ========================================
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// Purpose: On-demand analysis of Virtual Agent conversations
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// Usage: Run from Scripts - Background when you need immediate insights
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// Output: Detailed analytics report in system logs
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// ========================================
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(function analyzeConversations() {
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// Configuration
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var config = {
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daysToAnalyze: 30, // Analyze last 30 days
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includeAbandoned: true,
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includeCompleted: true,
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minConversations: 5 // Minimum conversations to show in report
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};
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gs.info('=== VA Conversation Analysis Report ===');
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gs.info('Analyzing conversations from last ' + config.daysToAnalyze + ' days');
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gs.info('');
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// Get all conversations in time range
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var conversations = new GlideRecord('sys_cs_conversation');
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conversations.addEncodedQuery('sys_created_on>=javascript:gs.daysAgoStart(' + config.daysToAnalyze + ')');
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conversations.query();
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var totalConversations = conversations.getRowCount();
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gs.info('Total Conversations: ' + totalConversations);
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if (totalConversations == 0) {
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gs.info('No conversations found in the specified time period');
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return;
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}
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// Analytics collections
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var topicStats = {};
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var userStats = {};
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var departmentStats = {};
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var timeStats = { morning: 0, afternoon: 0, evening: 0, night: 0 };
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var abandonmentReasons = {};
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var totalAbandoned = 0;
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var totalCompleted = 0;
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// Process each conversation
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conversations.query();
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while (conversations.next()) {
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var topicId = conversations.getValue('topic');
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var topicName = conversations.topic.getDisplayValue() || 'Unknown Topic';
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var userId = conversations.getValue('user');
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var state = conversations.getValue('state');
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var timestamp = conversations.getValue('sys_created_on');
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// Topic statistics
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if (!topicStats[topicName]) {
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topicStats[topicName] = {
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total: 0,
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abandoned: 0,
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completed: 0,
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users: {}
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};
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}
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topicStats[topicName].total++;
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topicStats[topicName].users[userId] = true;
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if (state == 'abandoned') {
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topicStats[topicName].abandoned++;
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totalAbandoned++;
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} else if (state == 'complete') {
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topicStats[topicName].completed++;
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totalCompleted++;
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}
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// User statistics
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if (!userStats[userId]) {
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userStats[userId] = 0;
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}
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userStats[userId]++;
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// Department statistics
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var department = getUserDepartment(userId);
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if (!departmentStats[department]) {
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departmentStats[department] = 0;
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}
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departmentStats[department]++;
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// Time of day statistics
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var timeSegment = getTimeSegment(timestamp);
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timeStats[timeSegment]++;
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}
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// Print Topic Statistics
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gs.info('');
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gs.info('=== Topic Statistics ===');
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gs.info('');
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var topicArray = [];
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for (var topic in topicStats) {
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var stats = topicStats[topic];
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topicArray.push({
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name: topic,
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total: stats.total,
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abandoned: stats.abandoned,
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completed: stats.completed,
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uniqueUsers: Object.keys(stats.users).length,
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abandonRate: ((stats.abandoned / stats.total) * 100).toFixed(1)
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});
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}
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// Sort by total conversations
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topicArray.sort(function(a, b) {
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return b.total - a.total;
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});
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// Print top topics
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gs.info('Top Topics by Conversation Count:');
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gs.info('-----------------------------------');
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topicArray.forEach(function(topic) {
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if (topic.total >= config.minConversations) {
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gs.info(topic.name);
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gs.info(' Total: ' + topic.total +
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' | Completed: ' + topic.completed +
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' | Abandoned: ' + topic.abandoned +
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' | Abandon Rate: ' + topic.abandonRate + '%' +
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' | Unique Users: ' + topic.uniqueUsers);
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}
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});
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// Print topics with high abandonment
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gs.info('');
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gs.info('Topics with High Abandonment (>30%):');
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gs.info('-------------------------------------');
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var highAbandonmentFound = false;
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topicArray.forEach(function(topic) {
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if (parseFloat(topic.abandonRate) > 30 && topic.total >= config.minConversations) {
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gs.info('⚠️ ' + topic.name + ' - ' + topic.abandonRate + '% abandonment (' + topic.abandoned + '/' + topic.total + ')');
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highAbandonmentFound = true;
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}
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});
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if (!highAbandonmentFound) {
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gs.info('None - all topics performing well!');
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}
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// Print Department Statistics
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gs.info('');
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gs.info('=== Department Statistics ===');
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gs.info('');
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var deptArray = [];
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for (var dept in departmentStats) {
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deptArray.push({
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name: dept,
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count: departmentStats[dept]
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});
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}
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deptArray.sort(function(a, b) {
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return b.count - a.count;
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});
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deptArray.forEach(function(dept) {
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var percentage = ((dept.count / totalConversations) * 100).toFixed(1);
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gs.info(dept.name + ': ' + dept.count + ' conversations (' + percentage + '%)');
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});
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// Print Time of Day Statistics
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gs.info('');
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gs.info('=== Time of Day Statistics ===');
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gs.info('');
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gs.info('Morning (6am-12pm): ' + timeStats.morning + ' (' + ((timeStats.morning / totalConversations) * 100).toFixed(1) + '%)');
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gs.info('Afternoon (12pm-5pm): ' + timeStats.afternoon + ' (' + ((timeStats.afternoon / totalConversations) * 100).toFixed(1) + '%)');
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gs.info('Evening (5pm-10pm): ' + timeStats.evening + ' (' + ((timeStats.evening / totalConversations) * 100).toFixed(1) + '%)');
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gs.info('Night (10pm-6am): ' + timeStats.night + ' (' + ((timeStats.night / totalConversations) * 100).toFixed(1) + '%)');
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// Print User Engagement Statistics
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gs.info('');
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gs.info('=== User Engagement Statistics ===');
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gs.info('');
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var totalUsers = Object.keys(userStats).length;
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var powerUsers = 0;
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var casualUsers = 0;
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for (var user in userStats) {
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if (userStats[user] >= 5) {
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powerUsers++;
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} else {
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casualUsers++;
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}
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}
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gs.info('Total Unique Users: ' + totalUsers);
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gs.info('Power Users (5+ conversations): ' + powerUsers);
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gs.info('Casual Users (<5 conversations): ' + casualUsers);
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gs.info('Average Conversations per User: ' + (totalConversations / totalUsers).toFixed(1));
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// Print Overall Statistics
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gs.info('');
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gs.info('=== Overall Statistics ===');
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gs.info('');
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gs.info('Total Conversations: ' + totalConversations);
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gs.info('Completed: ' + totalCompleted + ' (' + ((totalCompleted / totalConversations) * 100).toFixed(1) + '%)');
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gs.info('Abandoned: ' + totalAbandoned + ' (' + ((totalAbandoned / totalConversations) * 100).toFixed(1) + '%)');
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gs.info('Average Daily Conversations: ' + (totalConversations / config.daysToAnalyze).toFixed(1));
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// Recommendations
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gs.info('');
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gs.info('=== Recommendations ===');
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gs.info('');
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var highAbandonTopics = topicArray.filter(function(t) {
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return parseFloat(t.abandonRate) > 30 && t.total >= config.minConversations;
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});
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if (highAbandonTopics.length > 0) {
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gs.info('🔍 Review ' + highAbandonTopics.length + ' topic(s) with high abandonment rates');
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}
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if (timeStats.night > (totalConversations * 0.1)) {
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gs.info('🌙 Significant night-time usage detected (' + timeStats.night + ' conversations) - consider 24/7 support topics');
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}
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if (totalUsers > 0 && (totalConversations / totalUsers) < 2) {
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gs.info('📢 Low engagement (avg ' + (totalConversations / totalUsers).toFixed(1) + ' conversations/user) - consider promoting VA to increase awareness');
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}
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if ((totalCompleted / totalConversations) > 0.85) {
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gs.info('✅ High completion rate (' + ((totalCompleted / totalConversations) * 100).toFixed(1) + '%) - VA is performing well!');
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}
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gs.info('');
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gs.info('=== Analysis Complete ===');
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// Helper functions
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function getUserDepartment(userId) {
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var user = new GlideRecord('sys_user');
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if (user.get(userId)) {
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return user.getDisplayValue('department') || 'Unknown';
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}
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return 'Unknown';
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}
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function getTimeSegment(timestamp) {
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var dt = new GlideDateTime(timestamp);
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var timeStr = dt.getDisplayValue();
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var hour = parseInt(timeStr.split(' ')[1].split(':')[0]);
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if (hour >= 6 && hour < 12) return 'morning';
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if (hour >= 12 && hour < 17) return 'afternoon';
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if (hour >= 17 && hour < 22) return 'evening';
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return 'night';
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}
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})();

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