Fin Attributes automatically classifies every conversation - using attributes can help you define, issue type, sentiment, or urgency. Conversations are instantly tagged, so you can route them to the right team, trigger the right actions, and get accurate reporting without manual effort.
Quick Start: Set up Fin Attributes in 3 steps
Decide what to detect
Choose the structured attributes you want Fin to classify - like issue type, sentiment, urgency, or spam.
Create or convert a attribute
Go to Fin → Train → Attributes. Define your attribute values with clear descriptions, or convert an existing list-formatted attribute.
Preview and enable
Use the preview tool to test Fin’s accuracy. Tweak your value descriptions, then enable the attribute for real conversations.
Once enabled, use the detected attribute values in Escalation Rules, Workflows, and Reporting.
Key benefits
Custom attributes that reflect your business: Train Fin to detect attributes like issue type, urgency, sentiment, or spam status.
Intelligent, adaptive detection: Fin evaluates context at key moments and updates values as the conversation evolves.
Smart routing and escalation: Combine Fin Attributes with workflows and Escalation Rules to route conversations to the right team at the right time.
Reporting-ready structure: All detected attribute data flows into Intercom reports for deep insight—no manual tagging required.
Full transparency and control: View, validate, and override Fin’s attribute logic at any time.
Note: If you're already using AI Category Detection, learn how Fin Attributes compares and how to transition.
How and when Fin applies attributes to conversations
1. Default: Applying an attribute when Fin’s job is done
By default, Fin assigns or updates attributes when it decides its role in a conversation is complete — for example:
When handing off to a teammate
When a customer expresses resolution (positive feedback)
When a customer becomes inactive
💡 Why this matters: These moments naturally mark when a conversation’s intent or outcome becomes clear. Applying an attribute here ensures your routing and reporting reflect the final context of the customer’s need — not an early guess.
You can use this data to:
Define post-Fin routing or handover logic in Workflows (e.g., “If issue type is Billing → route to Finance team”)
Generate accurate reports on what types of queries Fin handled or handed off.
2. Dynamic re-detection (when used in Escalation Rules)
When a Fin Attribute is used in escalation rules, Fin automatically re-evaluates that attribute based on the latest customer interaction.
💡 Why this matters: This behaviour ensures Fin reacts immediately to changes in customer intent or sentiment that might require escalation. For example, if the issue type changes from General question to Refund request, Fin can instantly hand off the conversation per your rules - helping teammates step in at exactly the right moment.
3. Optional: Detect on close
When you enable “Detect on close” for a attribute, Fin will check and update the value again when the conversation is closed - whether by a teammate or automation. This can be enabled when creating or editing an attribute.
💡 Why this matters: If new information or context emerged late in the thread, Fin gets a final chance to correct or refine the classification. This ensures your reporting stays accurate and up to date, even if things shift late in the conversation.
How to set up Fin Attributes
Step 1: Decide what to classify
Think about the types of structured information you want Fin to detect. Common examples include:
Issue type (e.g., Billing, Projects, Account Management)
Sentiment (Positive, Neutral, Negative)
Urgency (Urgent, High, Normal, Low)
Spam detection (Spam, Legitimate)
Step 2: Create a new attribute (or convert an existing attribute)
To create a new Fin Attribute:
Go to Fin > Train > Attributes to get started.
Click New.
Fill in the Name and Description for your attribute.
Add Attribute Values (with clear descriptions for each)
Tip: Learn how to create effective attribute names and descriptions to help Fin classify your support conversations with high accuracy
To convert an existing attribute:
Go to Settings > Data > Conversations, click edit on a list-formatted attribute, and then click Let Fin detect.
Once converted, the attribute will appear under Fin AI Agent > Train > Attributes.
Note: Once converted, an attribute can't be reverted - but you can leave it disabled if needed.
Step 3: Preview before enabling
Before enabling an attribute, use the built-in preview in Fin AI Agent > Train > Attributes to:
Test the attribute values against example customer messages
Check how accurately Fin applies the right value
Iterate on names and descriptions before enabling
[Optional] Step 4: Add Conditional Rules
Use Conditions to create rules that control precisely when Fin should detect a specific attribute. This allows for more accurate classification, which leads to cleaner routing and reporting.
Conditions work by linking attributes together, creating a parent/dependent relationship. Fin will only attempt to detect the dependent attribute after it has first identified the parent attribute and its value.
How it works
The logic for Conditions is a simple If/Then statement:
If Fin detects a specific value for a parent attribute, then it will attempt to detect the dependent attribute.
You can configure these rules in the attribute settings side drawer under the Conditions tab. For each rule, you’ll define:
Define the parent attribute value.
Choose the condition that should be triggered when that parent value is detected.
Specify which condition values are allowed.
Examples:
If Issue type = Refund request → then detect Refund request reason.
If Sentiment = Negative sentiment → then detect Urgency.
When this logic is in place, Fin will first detect the parent attribute. If the defined value matches, Fin will then attempt to detect the linked conditions.
Note: Conditions logic is respected in Rule-based Escalation Guidance. If a condition is referenced in a Rule-based Escalation Guidance, Fin will re-evaluate the conversation after each customer message to see if the parent and condition values match.
Monitoring and reviewing Fin Attributes
Once your Fin Attributes are enabled, Fin provides real-time stats to help you understand how attributes are being applied.
You’ll see:
Conversations → the number of conversations Fin has detected for each attribute and specific attribute value.
Resolved → the percentage of those conversations that Fin was able to fully resolve.
Routed → the percentage of conversations successfully routed using that attribute.
You can also drill down into individual conversations to review how Fin applied a attribute and validate accuracy. This enables you to monitor classification accuracy, review misclassified conversations and update attribute descriptions based on patterns.
Example use cases
Below are some examples of ways that customers are using Fin Attributes to classify conversations.
Issue Type attribute example:
Projects - Projects are a collection of related tasks and activities aimed at achieving a specific objective or deliverable which can involve teammate collaboration, time tracking, milestones or goals, and status.
Billing - Billing encompasses managing subscription plans, invoices, payment methods, discounts, plan features, trials, account restrictions, refunds, and more for a seamless billing experience.
Account Management - Account Management covers discussions related to user accounts, including account creation, deletion, updating personal and payment information, and more.
Sentiment attribute example:
Positive - A positive sentiment means the user who wrote the message seems generally happy or satisfied and is probably feeling a positive emotion.
Negative - A negative sentiment means the user who wrote the message seems generally unhappy or dissatisfied and is probably feeling a negative emotion.
Neutral - A neutral sentiment means the user who wrote the message seems to be neither happy nor unhappy and it is difficult to guess their emotion.
Spam Detection attribute example:
Spam - Automated spam that is sent to the customer support agents. This includes auto-responders, newsletters, guest posts, and other general spam messages that could be ignored by the CS analyst.
Legit - Legitimate conversations in which the user has an actual issue that should be handled by a customer support analyst.
FAQs
What does Fin use to detect Fin Attributes?
What does Fin use to detect Fin Attributes?
Fin uses the attribute name, its description, and the value names and descriptions when evaluating which attribute value to apply. Ensure that all of these fields are written in a human-readable way that is easy for Fin to interpret.
What if the attribute applied to the conversation isn’t accurate?
What if the attribute applied to the conversation isn’t accurate?
We recommend checking that the naming and descriptions. Use our best practices and test with real customer messages in the preview tool.
Pro tip: To help review your attribute value labels and descriptions, you might like to try using an AI writing tool such as Chat GPT or Claude.
Example prompt:
You are an expert in customer-support AI. You are evaluating a taxonomy used by a LLM to classify customer support conversations. For each attribute (e.g., Topic, Sentiment), the LLM chooses the most appropriate attribute based on a combination of the attribute name and its description. This taxonomy will directly impact the LLM's ability to classify real customer support conversations. Your task is to assess the quality of this setup using the following best practices: Create clear, concise names - Choose short, descriptive names that immediately convey the attributes purpose. Write comprehensive descriptions - Take the time to write detailed descriptions and include all relevant information about what belongs in the attribute. Think about every type of conversation that should fall under this attribute and describe them in the description. Providing a detailed description will help Fin classify conversations correctly. You can include keywords and examples of customer questions. Make attributes distinct - Avoid creating attributes that overlap too much. Your attributes should be clearly different from each other, making it easy to determine which one best fits a given situation. This should be checked within each attribute only. It's fine for different attributes to apply to the same conversation. It shouldn't affect the score. Overlap with values in other attributes is allowed and does not affect this score. Ignore Archived Attributes - If a attribute is marked as archived, do not evaluate or score it. Add 5 Columns to the CSV Clarity/Conciseness (1–5), Description Comprehensiveness (1–5), Attribute Distinction (1–5), Final Score, Comment Assess each parameter for each attribute, and write a comment of why you applied this rating. Then calculate the overall score for this setup. After you've done this add one more column: Overlapping Attributes. If you think any given attribute overlaps with other attributes - list these attributes there.
What if Fin doesn’t detect a value?
What if Fin doesn’t detect a value?
Fin will return a null value if no attributes applies, which will leave the attribute empty. You can include an "Other" option to catch unclassified conversations if preferred.
I’m using AI Category Detection - should I switch to Fin Attributes?
I’m using AI Category Detection - should I switch to Fin Attributes?
Fin Attributes are the next generation of AI Category Detection. Fin Attributes run automatically, require less workflow maintenance, and work seamlessly with Escalation Rules, giving you full control over the conversations Fin hands to your team.
Your current setup won’t change, but we recommend learning more and switching to Fin Attributes for an improved product and experience.
What happens when I convert an existing AI Category Detection attribute to a Fin Attribute?
What happens when I convert an existing AI Category Detection attribute to a Fin Attribute?
When you convert an existing AI Category Detection conversation attribute into a Fin Attribute, Fin simply uses the same underlying conversation attribute. That means:
The converted attribute will continue to work in your existing workflows and reports without interruption.
When enabled, Fin will start classifying attribute values at key moments, so you may see these attributes being updated twice at first (once by AI Category Detection, once by Fin).
To simplify, you can eventually remove your AI Category Detection workflow blocks once you’re happy with how Fin is applying attributes.
Conversion is a one-way action - attributes cannot be reverted back to AI Category Detection, but they can be disabled if needed.
What can Fin Attributes not be used for?
What can Fin Attributes not be used for?
Fin Attributes cannot be used in conjunction with Custom Answers. Custom Answers are unavailable for customers who joined Intercom on or after March 19, 2025.
Do I have to involve Fin in every conversation to use Fin Attributes?
Do I have to involve Fin in every conversation to use Fin Attributes?
Yes. Fin Attributes are applied by Fin when it is present in a conversation. This means Fin must be included in your workflows in order to classify conversations.
If you’d prefer Fin not to answer in certain cases, you can use Escalation Rules. This allows Fin to classify the conversation and then exit immediately, based on conversation or user attributes of your choice.
For example, you could:
Escalate all conversations where Channel = Email
Escalate all conversations where Attribute = Billing
This way, you get the benefits of consistent classification across all conversations, while maintaining full control over when Fin does or doesn’t respond.
What if the Fin Attribute applied to the conversation isn’t accurate?
What if the Fin Attribute applied to the conversation isn’t accurate?
Check that the naming and descriptions follow the Best practices advice for Fin Attributes.
Can I use Fin Attributes on my existing Intercom plan?
Can I use Fin Attributes on my existing Intercom plan?
Yes, Fin Attributes are currently available on all plans with no additional cost. Any pricing changes will always be communicated to you in advance.
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