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Topic enrichment analysis

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Analyzing unrecognized intents

Copilot Studio has built-in conversational boosting and fallback system topics. These topics are set to trigger when the Natural Language Understanding (NLU) model isn't able to find a matching topic or action for a given user query. In terms of priority, conversational boosting triggers before the fallback topic.

If most unrecognized utterances are escalated to a human representative–that is, not deflected–there's an opportunity to improve the deflection by addressing the usage patterns of the user that triggers fallback consistently.

Tip

Topic enrichment is an offline data analysis exercise, focused on repurposing user queries that triggered the Fallback topic into triggering relevant topics in Copilot Studio.

The analyzed user queries from the Fallback topic typically fall into these buckets:

  1. User queries that are expected to trigger existing topics, but somehow are missed by the agent's NLU.

  2. User queries that can be converted to newly suggested topics.

  3. Unmapped user queries that aren't relevant to any existing or new topics.

  4. Other categories, including user queries that triggered a Multiple Topics Matched (also known as "did you mean") topic followed by conversational boosting or fallback. Unclear user queries that hit conversational boosting or fallback. As well as user queries from incomplete conversations that led to conversational boosting or fallback.

Of the four categories, the first and the second are immediately actionable. Based on the findings from these categories, you can enrich the topics by adding more trigger phrases for existing topics or creating new topics.

Diagram that illustrates a process flow to improve fallback analysis.

Topic enrichment through out-of-the-box analytics

Copilot Studio provides advanced AI capabilities out of the box. To identify a list of suggested new topics, turn on the AI features for topic suggestion from chat transcripts, when the author doesn't want to enable the Conversational boosting or Fallback topic.

Important

Only classic chatbots or Teams copilots have access to these legacy AI capabilities.

This information can also be used to create new topics to improve deflection rate.

Screenshot of the topic suggestions from chat transcripts window.

Topic confusion analysis