- Benchmarks
- Ticket Volume
Ticket Volume Benchmarks (2026)
The global average ticket volume is 400 per agent/month. Good teams target Under 350 per agent/month, and excellent teams achieve Under 250 per agent/month. These benchmarks are compiled from Industry composite aggregated from MetricNet, HDI, and LiveChatAI benchmarks (2025) and other publicly available industry reports.
What Is Ticket Volume?
The total number of support conversations or tickets received per month. Understanding volume patterns helps with staffing and automation decisions.
Ticket Volume by Industry
Ticket Volume varies significantly by industry. Industries with simpler, higher-volume queries (e-commerce, restaurants) tend to have better numbers than those with complex, compliance-heavy interactions (healthcare, fintech).
| Industry | Average | Good | Excellent |
|---|---|---|---|
| SaaS | 320 | 256 | 192 |
| E-commerce | 550 | 440 | 330 |
| Fintech | 280 | 224 | 168 |
| Healthcare | 200 | 160 | 120 |
| Agencies | 180 | 144 | 108 |
| Fashion | 480 | 384 | 288 |
| Beauty & Cosmetics | 420 | 336 | 252 |
| Gaming | 600 | 480 | 360 |
| Crypto & Web3 | 350 | 280 | 210 |
| Travel & Tourism | 500 | 400 | 300 |
| Hospitality | 380 | 304 | 228 |
| Restaurants | 450 | 360 | 270 |
| Hotels | 360 | 288 | 216 |
| Real Estate | 150 | 120 | 90 |
| Education | 250 | 200 | 150 |
Ticket Volume by Channel
Channel choice has a major impact on ticket volume. Messaging channels (chat, WhatsApp) consistently outperform email and social media.
| Channel | Average |
|---|---|
| Live Chat | 45% |
| 20% | |
| 25% | |
| Social Media | 8% |
| Phone | 2% |
Ticket Volume by Company Size
Larger teams don't always mean better metrics. Company size affects ticket volume through staffing, tooling, and process maturity.
| Company Size | Average |
|---|---|
| Small (1-10 agents) | 500/month total |
| Medium (11-50 agents) | 5,000/month total |
| Enterprise (50+ agents) | 50,000+/month total |
Year-over-Year Trends
Ticket Volume has been improving steadily as teams adopt AI, automation, and messaging-first strategies.
| Year | Average | Notes |
|---|---|---|
| 2024 | 380/agent | Steady growth in messaging volume |
| 2025 | 400/agent | WhatsApp and social channels adding volume |
| 2026 | 420/agent | Self-service deflecting some, but new channels adding more |
How to Improve Your Ticket Volume
Implement self-service for your top 10 most common questions to deflect 20-30% of volume
Use auto-replies with FAQ links to resolve simple questions without agent involvement
Track volume by channel and day-of-week to optimize staffing schedules
Set up proactive messaging to address common issues before customers contact you
Monitor volume trends monthly -- sudden spikes often indicate product issues
Sources: Industry composite aggregated from MetricNet, HDI, and LiveChatAI benchmarks (2025). Benchmarks are compiled from publicly available industry reports and may vary significantly by company size, geography, support methodology, and channel mix. These figures represent approximate cross-industry averages and should be used as directional guidance, not precise targets.
Frequently Asked Questions
The global average ticket volume is 400 per agent/month. A good target is Under 350 per agent/month, and excellent teams achieve Under 250 per agent/month. These vary significantly by industry and channel.
Ticket Volume varies widely. SaaS averages 320, E-commerce averages 550, Fintech averages 280. See the full industry breakdown table above.
Live Chat typically has the best ticket volume at 45%. Phone tends to be slower at 2%.
Key strategies: Implement self-service for your top 10 most common questions to deflect 20-30% of volume. Use auto-replies with FAQ links to resolve simple questions without agent involvement. See our detailed improvement tips section above for all 5 strategies.
In 2024: 380/agent (Steady growth in messaging volume). In 2025: 400/agent (WhatsApp and social channels adding volume). In 2026: 420/agent (Self-service deflecting some, but new channels adding more). The trend is driven by automation, AI adoption, and messaging-first strategies.
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