Similar Tickets
Find related past tickets instantly. AI identifies tickets with similar issues, helping you learn from previous solutions.
What Are Similar Tickets?
Similar tickets uses AI to find past tickets that match the current ticket's issue, context, or customer situation—helping you:
- Learn from past solutions
- Identify duplicate requests
- Find related customer issues
- Spot patterns and trends
Example
Current ticket: "My battery drains really fast after the update"
Similar tickets found:
- #2341 - "Battery life decreased since firmware update" (Resolved)
- #2298 - "Scooter only lasts 2 miles now" (Resolved)
- #2189 - "Is there a fix for the battery drain issue?" (Resolved)
How It Works
Semantic Matching
AI looks for meaning, not just keywords:
| Current Ticket | Finds Tickets About |
|---|---|
| "Won't turn on" | Power issues, startup problems |
| "Charged but died" | Battery, charging issues |
| "Going slow now" | Performance, speed issues |
What's Compared
- Ticket subject
- Description content
- Issue type
- Customer messages
- Resolution notes
Where to Find Similar Tickets
AI Sidebar
View "Similar Tickets" in the AI Insights panel:
🔗 Similar Tickets
• #2341 - Battery life decreased (92%)
Status: Resolved | 3 days ago
• #2298 - Scooter only lasts 2 miles (85%)
Status: Resolved | 1 week ago
Ticket Actions Menu
Click ... → "Find Similar Tickets" to search on demand.
Using Similar Tickets
Learn from Solutions
- Click a similar ticket to view it
- Read how it was resolved
- Apply similar solution to current ticket
- Adapt as needed for specifics
Check for Duplicates
If tickets are truly duplicates:
- Verify same customer, same issue
- Use "Merge" to combine tickets
- Or close as duplicate with reference
Spot Patterns
Multiple similar tickets might indicate:
- Product bug or defect
- Documentation gap
- Common confusion point
- Trending issue
Similarity Scores
Understanding Scores
| Score | Meaning |
|---|---|
| 90%+ | Nearly identical issue |
| 70-89% | Very similar, likely relevant |
| 50-69% | Somewhat related |
| Below 50% | Different but potentially related |
Factors in Scoring
- Content similarity
- Issue type match
- Resolution relevance
- Time proximity (recent = higher)
- Same customer (higher relevance)
Filtering Similar Tickets
By Status
Focus on resolved tickets for solutions:
- Show only: Resolved, Closed
- Exclude: Open (still being worked on)
By Time
- Last 30 days (recent issues)
- Last 90 days
- All time (comprehensive search)
By Agent
Find tickets you or specific team members handled.
Duplicate Detection
Identifying Duplicates
Signs of duplicate tickets:
- Same customer
- Very high similarity score (95%+)
- Same timeframe
- Identical issue description
Handling Duplicates
Option 1: Merge
- Open the duplicate
- Click "Merge into" → select original
- Conversations combined
- Duplicate closed
Option 2: Link and Close
- Add note: "Duplicate of #1234"
- Close as duplicate
- Original ticket continues
Improving Similar Ticket Results
Good Ticket Data
Better results when tickets have:
- Clear, descriptive subjects
- Detailed descriptions
- Proper categorization
- Resolution summaries
Resolution Notes
When closing tickets, add resolution notes:
"Resolved by performing firmware rollback. Customer confirmed battery life restored."
This helps future similar tickets find the solution.
Use Cases
Training New Agents
- New agent gets a ticket
- Views similar tickets
- Sees how experienced agents resolved
- Learns best practices
Complex Issues
- Unfamiliar issue arrives
- Find similar past tickets
- Discover if it's been seen before
- Apply known solutions
Customer History
- Customer has new ticket
- Similar tickets may show their past issues
- Understand if this is a recurring problem
- Provide informed support
Privacy & Scope
What's Searched
- Tickets within your organization only
- Respects user permissions
- Includes resolved and closed tickets
Not Searched
- Other organizations' tickets
- Deleted tickets
- Tickets you don't have access to
Troubleshooting
"No similar tickets found"
- Issue may be truly unique
- Ticket content may be too short
- Try after adding more details
"Similar tickets aren't relevant"
- Similarity is based on content
- Different root causes can look similar
- Use your judgment
"Same tickets keep appearing"
- These may genuinely be most similar
- Try narrowing by time period
- Check if duplicates should be merged
Tips for Maximum Value
- Check before responding: Similar tickets may have the answer
- Link related tickets: Build connections for future reference
- Add resolution notes: Help future agents (and AI)
- Merge true duplicates: Keep data clean
- Note patterns: Multiple similar = potential issue