As a Support Agent, Fin’s goal is to resolve customer queries quickly and accurately while providing guidance and reassurance throughout their journey.
Fin achieves this through two essential Support Agent skills:
Handling common queries with deep knowledge
Troubleshooting and triaging complex issues
This guide walks you through how to train Fin as a Customer Agent on these skills so it can automate support at scale, while staying true to your brand voice and policies.
Skill: Handling common queries with deep knowledge
Fin can resolve common queries and immediately help customers find answers without waiting on a human agent.
With this skill, Fin acts as a Support Agent by using your FAQ content, how-to guides, best practices, and basic troubleshooting resources to deliver clear answers. Fin follows your policies, knows when to escalate, and can classify and assign conversations effectively.
What Fin needs
Content to cover FAQs, how-to guides, best practices, and basic troubleshooting.
Fin Attributes for topic detection, triaging, and reporting.
Guidance so Fin can follow your policies and knows when to escalate.
Workflow for Fin to respond and assign conversations effectively.
Training Fin
First, go to Knowledge and make sure you’ve enabled Fin with content covering FAQs, how-to guides, best practices, and basic troubleshooting.
Next, use Fin Attributes to automatically classify every conversation, like issue type, sentiment, or urgency.
For example, to classify conversation topic:
Create an attribute called “Topic” and give Fin more context about this attribute, what it's for, and how Fin should use it in the description.
Then control who this attribute applies to by selecting an Audience. If you want it to be applied to all conversations, select Everyone.
You can also control how your teammates see and interact with this attribute in the Inbox (these settings won't affect how Fin uses it).
Add values for this attribute which align with your product or support structure, for example:
Tasks
Projects
Pricing
Other
Give each of these values a very clear description of the conversation topics it applies to, common customer keywords or questions, and when it should be chosen instead of other values.
Enable this attribute for Fin to start using it.
Create an attribute for each conversation topic or type that’s important for Fin to classify during a conversation.
Fin Attributes give you precise control over which conversations Fin handles and which ones are passed to your team. By classifying every conversation, Fin knows which ones to escalate and you can configure these settings under Fin AI Agent > Train > Escalation.
For example, if you always want “Pricing” queries to be handled by your team, add an Escalation Rule to escalate if the Fin Attribute selected for “Topic” is “Pricing”.
Then go to Fin AI Agent > Train > Guidance and create guidance to train Fin on your brand tone and policies.
For example, create “Communication style” guidance which tells Fin how to handle sensitive conversations: “If a customer sounds upset, confused, or mentions a bad experience, respond gently and with empathy. Acknowledge the emotion before offering help.”
Or create “Content and sources” guidance which tells Fin which source it should use for troubleshooting a particular issue: “If a customer says they're experiencing an issue with saving a project, always use [📄 Public article: Troubleshooting projects] to walk them through the exact steps to resolve this issue.”
Now it’s time to get Fin involved in conversations by deploying it in your workflows. You can decide when Fin responds and how it routes conversations which are unresolved or require escalation.
Skill: Troubleshooting and triaging complex issues
Fin can handle complex customer issues by guiding them through technical troubleshooting or gathering the right context before escalation.
With this skill, Fin acts as a Support Agent by using connected customer data to personalize support and walk users through troubleshooting steps. When escalation is needed, Fin ensures all relevant details are collected and routed to the right team, making handoffs faster and smoother.
What Fin needs
Data connectors to give Fin access to external systems and customer data.
Fin Attributes for topic detection, triaging, and reporting.
Tasks for navigating technical troubleshooting (note: this feature has managed availability).
Training Fin
First, go to Settings > Integrations > Data connectors to set up connectors that access data in external systems such as your Statuspage, Stripe, or Shopify Storefront. These data connectors can then be used in your Fin Task.
For example, you could connect Fin to your Statuspage to check for unresolved incidents when a customer reports an issue.
Next, use Fin Attributes to automatically classify every conversation, like issue type, sentiment, or urgency.
For example, to classify conversation urgency:
Create an attribute called “Urgency” and give Fin more context about this category, what it's for, and how Fin should use it in the description.
Then control who this attribute applies to by selecting an Audience. If you want it to be applied to all conversations, select Everyone.
You can also control how your teammates see and interact with this attribute in the Inbox (these settings won't affect how Fin uses it).
Add values for this attribute which align with your support structure, for example:
High
Medium
Low
Give each of these values a very clear description of the conversation topics it applies to, common customer keywords or questions, and when it should be chosen instead of other values.
Enable this attribute for Fin to start using it.
Create an attribute for each conversation topic or type that’s important for Fin to classify and triage during a conversation.
Now go to Fin AI Agent > Train > Tasks and click New task.
Note: Fin Tasks are under managed availability and you may need to reach out to your Account Manager to get access. If you don’t have Fin Tasks yet, you can still set up Fin for handling common queries.
Give the task a title such as “Troubleshoot issue”.
Describe exactly when Fin should trigger this task. For example: “Use this when a customer reports a bug, error message, or technical issue with the product. Do not use it if the customer is confused by an existing feature, is asking about a new feature, or is seeking product guidance unrelated to a malfunction.”
Then train Fin on example questions for when to trigger and when not to trigger. If you don’t define examples, Fin might misclassify user intent. Example questions you could use:
“The app crashes on this page”
“I'm stuck on a loading screen”
“When I click on the button nothing happens”
“I'm getting an unknown error message”
Since this task is designed specifically for customer support, set the audience to Users only. You can also define channel availability and more specific audience rules using data attributes.
Now click into the Instructions block to define the steps Fin should take to effectively troubleshoot issues, including the relevant external data Fin should access.
For example:
Understand customer issue
If not already provided, gather details on the issue the customer is experiencing.
If it sounds like a missing feature, exit task.
If it sounds like they're looking for guidance for how to use an existing feature, exit task.
If it sounds like a bug or a technical issue with the product, continue to next steps.
Confirm with customer they've attempted basic troubleshooting steps. Only suggest troubleshooting steps that are relevant to their issue, for example:
Ask the customer to refresh the page or restart the app.
Ask them to try in an incognito/private window or a different browser/device.
Check if their internet connection appears stable.
Suggest clearing cookies/cache.
If issue persists, check active incidents
[Use:Get Unresolved Incidents] to check if there's any active incidents related to the issue they're experiencing.
If there's relevant issues, tell the customer the incident status and any relevant updates. Exit task once complete.
If there's no relevant incidents, do not mention any active incidents and continue to the next step.
If there's no relevant incidents, submit issue
Capture relevant details and [Update:Temporary attribute for issue description] with a description of the issue for the engineering team.
Confirm with the customer that the issue has been logged and then escalate it to the team.
If the customer’s issue is unclear or doesn’t fit the pattern of a technical problem, ask for clarification or escalate to the team.
Tip: When you’ve finished giving Fin instructions, run a simulation to check how Fin handles different scenarios.
Click Done to save your instructions and return to the task builder. Here, you can use your Fin Attributes to classify and route issues that need escalation. For example:
If “Urgency is High” and “Fin AI Agent resolution state is Routed to team” assign to “Engineering support”.
If “Urgency is Medium or Low” and “Fin AI Agent resolution state is Routed to team” assign to “Tier 2 Support”.
Else close.
Once you're happy with how Fin performs the task, go ahead and select Set live to let Fin get to work! 💪
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