Chatbot Launch Checklist: 30 Things to Test Before Going Live

The fastest way to embarrass a chatbot is to launch it the way you demoed it — answering the three questions you remembered to test. Real users arrive with typos, half-finished thoughts, edge cases, and questions you never imagined. A pre-launch checklist forces you to probe the bot the way the world will, before the world does. Below are 30 things to test before going live, grouped by area. Work through them deliberately, and convert your real test conversations into a suite you can re-run every time you change something — the single best habit for catching regressions early.

Content and understanding

• Top intents covered: confirm the bot recognizes your most common real questions, phrased the way customers actually phrase them, not the way you wrote them.
• Phrasing variety: test slang, typos, abbreviations, and short fragments ("where order"), not just full sentences.
• Tone and brand voice: read every default response aloud; it should sound like your brand, consistently.
• Factual accuracy: verify the bot's answers against your real knowledge base and confirm it does not invent details.
• Knowledge gaps: list questions the bot cannot answer yet and decide whether to add content or route them.
• Multi-language: if you serve more than one language, test each path end to end, not just the default.

Fallbacks and error handling

• Unrecognized input: send gibberish and off-topic messages; the fallback should be graceful and offer a next step, never a dead end.
• Repeated misunderstanding: test what happens after two or three failed turns — the bot should escalate, not loop.
• Empty and oversized input: send blank messages and very long pastes to confirm the bot does not break.
• Interruptions: change the subject mid-flow and check the bot recovers instead of getting stuck.
• Sensitive topics: test how the bot responds to complaints, anger, or distress, and confirm it routes appropriately.

Forms and data capture

• Required fields: confirm the bot collects every field it needs before completing a task.
• Validation: enter bad emails, malformed phone numbers, and wrong date formats; the bot should reject and re-ask politely.
• Correction: mid-form, change an earlier answer and verify the bot updates it rather than ignoring you.
• Abandonment: drop out of a form halfway and check whether partial data is saved or cleanly discarded.

Integrations and actions

• Real connections: test against your actual CRM, help desk, store, or calendar — not mock data.
• Action side effects: confirm bookings, tickets, and orders are actually created in the connected system.
• Failure handling: simulate a downed API and verify the bot tells the user honestly instead of pretending it succeeded.
• Latency: check the bot behaves acceptably when an integration is slow to respond.
• Authentication: test any login or verification step, including the wrong-password path.

Escalation and handoff

• Trigger conditions: confirm the bot hands off when it should — on request, on repeated failure, on sensitive issues.
• Context transfer: verify the human agent receives the full transcript so the customer never repeats themselves.
• Off-hours behavior: test what happens when no agent is available; offer a callback, ticket, or clear expectation.
• Channel handoff: if you run omnichannel, confirm the conversation continues cleanly across channels.

Privacy and security

• Data handling: confirm sensitive data is collected, stored, and transmitted according to your policy and obligations.
• Consent and disclosure: verify users are told they are talking to a bot and given any required privacy notice.
• Access controls: check who can read conversation logs and confirm permissions are appropriate.
• Data retention: confirm transcripts are retained and deleted per your stated policy.

Analytics and final checks

• Tracking live: confirm your key metrics — containment, fallback, escalation, resolution — are actually recording before launch.
• Mobile and devices: test the widget on phones and different browsers, not just your desktop.
• Regression suite: convert your real test conversations into an automated suite and run it on every change to catch breakage early.

Bottom line

A launch checklist is not bureaucracy; it is the difference between a bot that earns trust in week one and one that gets disabled by Friday. Run these 30 checks with real data and real edge cases, capture the conversations as repeatable tests, and you will catch the embarrassing failures in private. Then go live knowing the bot has already met the messiness of real users — because you brought it to them first.

Sources and further reading