Chatbot Escalation Design Review (QA)

Chatbot Escalation Design Review (QA)

1. 01

   Map every conversation path to a clear resolution or human handoff

   For each intent the bot handles, confirm there is a defined end state: a completed transaction, a booked meeting, or a warm transfer to a live agent. If a path dead-ends without escalation, flag it for redesign.

2. 02

   Verify escalation triggers are set to the client's tolerance for automation

   Check that the bot hands off to a human after a set number of failed attempts, on explicit user request, or when sentiment turns negative. Align these thresholds with the client's service-level expectations.

3. 03

   Test the bot with real-world edge cases and out-of-scope queries

   Run a script of unusual phrasings, typos, and off-topic questions to see if the bot responds gracefully or loops. Document any instance where the bot gives a confident but wrong answer.

4. 04

   Confirm the client's knowledge base is current and complete

   Review the sources the bot is trained on, such as website content or uploaded PDFs, and check for outdated policies or missing product details. Stale data is a common cause of poor CX.

5. 05

   Review analytics for drop-off points and unresolved sessions

   Look at the last 30 days of chat logs to identify where users abandon the conversation or where the bot fails to resolve the query. Use this data to prioritize fixes before launch.

6. 06

   Document the escalation workflow and share it with the client's support team

   Create a one-page guide that shows how the bot hands off to a human, including what context is passed along. Ensure the client's team knows how to pick up a conversation mid-thread.