Find out where my customer service chatbot fails and fix it

Analyze my customer service chatbot's performance and tell me how to improve it. What the bot handles: [products/services, industry, channels] Metrics I have: [e.g. containment rate, handoff rate, CSAT, conversion, fallback/"didn't understand" rate, drop-off points] Conversation samples: [paste 20-50 transcripts, ideally including failures and handoffs] User groups: [e.g. new vs. returning customers, mobile vs. desktop, regions] What the bot can access: [FAQ, help center, order system, account data, none] Goal: [e.g. resolve more without a human, increase sales, cut wrong answers] Analyze: 1. Failure patterns: group failed conversations by cause: missing knowledge, misunderstood intent, no access to needed data, policy limits, bad flow design, or wrong answer. Count each and quote one example. 2. Accuracy risk: answers that were wrong, outdated, or made up, and where they came from. 3. User groups: how different groups use the bot and where each struggles. 4. Handoffs: whether people reach a human at the right moment, with context passed along. 5. Metrics: what the numbers suggest, and which metric I'm missing. Return: - A table of issues: issue, frequency, impact, fix (content, flow, data integration, or handoff rule), effort (low/med/high). - The top 5 fixes in priority order. - Rewritten responses for the 3 worst examples. - A test set of 10 questions to rerun after the changes. Only use numbers from my data; label anything estimated.