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Use the Topics Explorer to see what’s driving volume

Know exactly what’s driving support volume with Al-generated topics and subtopics - no tagging or manual effort required.

Updated over a week ago

The Topics Explorer uses AI to automatically group your support tickets/cases into topics and subtopics. It shows what customers are asking, how those conversations are performing, and where to focus.

  • See what’s driving volume—no tagging required: AI topics and subtopics are generated automatically, giving you a live view of what customers are asking without any manual effort.

  • Track performance by topic, not just team: Each topic includes key metrics like CX Score, resolution rate, and handling time—so you can see which issues are handled well and which need attention.

  • Catch problems early, before they escalate: Monitor changes in volume and sentiment over time to spot emerging issues and act before they grow.

  • Focus where it matters most: Identify high-volume, poor customer experience topics and make targeted improvements that move the needle.

Note:

  • Topics Explorer is currently in open beta and available to all Fin customers who meet the following criteria:

    • Have imported conversations from your source platform (e.g. Zendesk or Salesforce) which you can toggle on and off.

    • Have deployed Fin.

  • The Topics Explorer currently only works for English conversations. Support for conversations in other languages is coming soon.

Understanding AI-powered topics and subtopics

AI topics use machine learning to group tickets/cases into topics (broad themes) and subtopics (highly specific, recurring issues).

How AI topics and subtopics are discovered

The system analyzes a large amount of historical conversation data—specifically from the past 90 days. It looks for patterns in the questions customers ask, then groups similar conversations together.

  • Subtopics are discovered first by clustering similar questions from past conversations.

  • These subtopics are then grouped into broader topics.

  • Finally, the system automatically generates clear topic titles to help you quickly understand each topic and subtopic.

Note: Topics and subtopics are not based on predefined keywords. Any keywords shown in the product are only there to help explain what each topic is about.

How conversations are assigned to AI topics

Once topics and subtopics are discovered, the AI takes two steps:

  1. Backfilling: The system looks at tickets/cases from the past 90 days and retroactively assigns them to the appropriate topics and subtopics.

  2. Inference: Each day, the system reviews new tickets/cases and assigns them to relevant topics right after they’re closed.

Conversation criteria for generating AI topics

To build accurate topics and subtopics, the system uses conversations that meet certain criteria:

  • Tickets/cases must be in English.

  • Tickets/cases must not be marked as spam.

  • Tickets/cases must have at least two participants (for example, a customer and Fin or a teammate).

  • Each ticket/case is summarized into up to three key questions, which are used to identify patterns and assign to a subtopic.

  • At least 15 questions or tickets/cases are needed to form a meaningful subtopic.

Note: If your tickets/cases are too varied, or if there isn’t enough volume around a single theme, no topics may appear—even if there are many conversations.

Ongoing updates to AI topics and subtopics

Topics/subtopics are built to adapt:

  • Daily updates ensure new tickets/cases are categorized promptly.

  • New topics and subtopics are added as they emerge, without removing or changing the ones already discovered.

  • Some conversations may not get assigned to any topic if they are too different, low quality (like spam), or don’t meet the criteria.

Note: It’s currently not possible to modify or edit the AI topics/subtopics that are shown for your conversations, but we’re exploring ways of providing you with more control.

Why you may have many smaller topics

It’s common to see a few large topics with lots of subtopics and conversations within them, and many smaller topics with only a few subtopics and conversations. That’s because:

  • Some topics come up frequently across customers, while others are highly specific or niche and don’t fit well with existing clusters.

  • The system avoids combining unrelated subtopics just to form larger topics—it focuses on natural groupings.

Note: AI topics and subtopics do not:

  • Detect spam

  • Analyze sentiment

  • Determine if a query is informational or requires action

How to use AI-powered topics and subtopics

Support leaders and teams can use AI topics to understand what’s driving volume and how to prioritize efforts to optimize their support.

Spotting topic trends

To view the Topics Explorer, go to Analyze > Topics Explorer. Here, you’ll see two main sections:

  • The left side has a tree map of topics:

    • The size of the box signals the volume of conversations in that topic.

    • The color of the box is related to the metric selected.

    • In light mode, the darker colors signal areas needing attention. In dark mode, lighter colors signal areas needing attention.

  • The right side has a series of ridge line charts: These take the same topics from the tree map and show their performance over time.

Select how many topics you want to display and choose which metric to use:

  • CX Score

  • Fin involvement rate

  • Fin resolution rate

  • Median handling time

  • Median first response time

Focus where it matters most by identifying high-volume, poor customer experience topics and click on them to see the tree map and line charts broken down by subtopics. This enables you to make targeted improvements to the most impactful subtopics by addressing the root cause of the volume and poor CX.

Catch problems early, before they escalate by monitoring changes in volume and key metrics over time to spot emerging issues and act before they grow. For example, the chart below shows a sudden spike in volume with negative CX Scores for the “Account locked” topic. This could highlight a bug or unexpected issue that’s preventing customers from accessing their account.

Hover over a topic/subtopic to see a description of what’s included in that topic and view conversations.

From the conversations view, you can quickly click through conversations to identify issues and use the CX Score to understand how they were resolved. You can also open a conversation in the inbox to reply to the customer directly.

Identifying areas to optimize

These topics also appear in the Fin Optimize dashboard to help you prioritize efforts in improving Fin across involvement rate, resolution rate, and customer experience.

Tip: Start with a topic that’s driving a high volume of conversations with low CX Scores and review the suggestions to improve Fin’s performance.

Filtering other reports

You can use the AI topics/subtopics to filter your Custom Report too. Simply add a filter for AI Topic or AI Subtopic to select specific topics you want to filter by.

FAQs

How do new AI topics get generated, and will it recategorize existing tickets when this happens?

New topics are generated through machine learning analysis of historical ticket data from the past 90 days. Subtopics are identified first by clustering similar questions, then grouped into broader topics. Importantly, new topics and subtopics are added without removing or changing existing ones.

Why do some tickets not have topics?

Some tickets might not appear under any topic if they:

  • Are too varied or don’t have enough volume around a single theme.

  • Are too different from existing topics.

  • Are low quality (e.g., spam).

  • Don’t meet the criteria (e.g., must be in English and have at least two participants).

When will I start seeing AI topics/subtopics?

You’ll begin to see topics/subtopics after deploying Fin. Your workspace needs to have more than one eligible conversation. However, even if your workspace meets these criteria, AI topics may not appear right away. Here’s why:

  • Topic generation is part of a pipeline that updates periodically. If your conversations qualify, they will be included in that pipeline.

  • Some customers start seeing topics after just 30–50 conversations, while others may need more to generate a related topic.

  • Once your workspace accumulates enough qualifying conversations, topics will begin to appear automatically as the pipeline processes new data.

Why do my AI topics/subtopics change over time?

Topics and subtopics are updated daily to include new tickets. As patterns evolve or new issues emerge, new topics are added, though existing ones remain unchanged. This ensures a live and accurate reflection of current support trends.

What does the color size/scheme mean on the Topics Explorer tree map?

  • Size of each box = volume of conversations.

  • Color of each box = value of the selected performance metric (e.g., CX Score, resolution rate, etc).

    • In light mode: Darker colors indicate areas needing attention.

    • In dark mode: Lighter colors indicate areas needing attention

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