When the “Participant is Teammate” option is selected for a conversation Topic, the text and content of Fin’s answers should be included when looking for keywords and assigning topics.
We use Fin on a majority of our cases, and typically include teammate responses as part of topic identification. This means that at the moment, not including Fin as a teammate means topic identification does not work properly for a majority of cases.
Users will often make spelling mistakes or use a very large variety of non-standard words and phrases, which do not get picked up by the Topic assignment ML algorithms. However, Fin can use context to understand the customer’s message, then identify and restate the topic in a way that is standard with our help center content, which would then be caught by topic tagging. This is currently a large gap that is pushing us to look for topic identification/AI categorization tools outside of Intercom, instead of being able to use the readily available tools we’re already paying for.