Question 1

When should I implement support automation?

Accepted Answer

When you're answering the same questions repeatedly and volume exceeds team capacity. Even simple automation (canned responses, macros) helps. AI chatbots when you have content to train them.

Question 2

What's the difference between chatbots and AI?

Accepted Answer

Traditional chatbots: rule-based, follow scripts. AI chatbots: understand intent, generate responses, learn. Modern tools blend both. AI is more flexible but needs good knowledge base.

Question 3

Which chatbot platform should I use?

Accepted Answer

Intercom Fin: best for existing Intercom users. Zendesk Answer Bot: integrates with Zendesk. Ada: enterprise-grade. Chatbase: simple, train on your docs. Match to existing stack.

Question 4

Will customers hate talking to bots?

Accepted Answer

Not if bots are helpful. Customers hate bad bots. Good bots that solve problems are appreciated. Be transparent. Easy escalation to humans. Test extensively.

Question 5

How do I train a chatbot?

Accepted Answer

Start with knowledge base content. Add FAQ responses. Review bot mistakes and correct. Ongoing training improves accuracy. AI bots need less training than rule-based.

Question 6

What percentage of tickets can bots handle?

Accepted Answer

20-40% for simple implementations. 50-70% for mature deployments. Varies by complexity of product. Start with easy wins (FAQs, status checks, password resets).

Question 7

How do I measure chatbot effectiveness?

Accepted Answer

Resolution rate, escalation rate, CSAT for bot interactions, containment rate. A/B test with and without bot. Track both efficiency and satisfaction.

Question 8

When should bots escalate to humans?

Accepted Answer

Complex issues, frustrated customers, billing/sensitive topics, explicitly requested. Better to escalate too much than frustrate users. Train on edge cases.

Question 9

What about using ChatGPT for support?

Accepted Answer

Can work with proper guardrails. Train on your content to prevent hallucinations. Tools like Chatbase, CustomGPT make this easier. Requires supervision and testing.

Question 10

How do I handle multiple languages?

Accepted Answer

AI tools often handle translation built-in. Or integrate translation APIs. Prioritize languages by customer distribution. Test quality in each language.

Question 11

What are macros/canned responses?

Accepted Answer

Pre-written responses for common questions. Agents personalize and send. Faster than typing. Consistent quality. Start here before full automation. Every help desk has this.

Question 12

How do I implement auto-tagging?

Accepted Answer

AI classifies incoming tickets by topic. Routes to right team. Enables reporting. Most modern help desks offer this. Training improves accuracy over time.

Question 13

Should bots collect information before handoff?

Accepted Answer

Yes—context saves human agents time. But keep it brief. Name, email, brief issue description. Pre-qualified tickets = faster resolution.

Question 14

How do I get buy-in from support team?

Accepted Answer

Position as help, not replacement. Bots handle boring stuff, humans handle interesting problems. Involve team in training and feedback. Show how it makes their job better.

Question 15

What's the cost of support automation?

Accepted Answer

AI chatbots: $50-500/month for SMB, more at scale. Savings: cost per bot resolution is a fraction of human ticket. ROI usually quick for high-volume support.

I need chatbots and automation for customer support

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Intercom

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