Fin Tips and Best Practices

Hi Intercom team 👋,I’m currently setting up our Help Center and testing different layouts for the collections.At the moment, in the Grid layout, the collection icon is always displayed above the collection title. I’d like to achieve a layout where the icon is positioned to the left of the title, similar to a horizontal “card” or list-style layout, while still keeping a clean, visual overview of collections.I know it’s possible because I saw it on a help center made with Intercom. I’ve tested:Grid, List, and Minimal layouts Different icon formats and sizes (PNG, SVG, high resolution) Various Help Center customization settingsHowever, I couldn’t find any option to:change the icon position (top vs left) control the structure of collection cards beyond the default layoutsMy questions are:Is the icon position for Help Center collections fixed by design? Is there a

Hi everyone!Hope this isn’t too off-topic. 🙂I recently discovered that it’s possible to connect Intercom directly to ChatGPT (at least with a Business license), and I’m really curious to hear how others, especially smaller support teams like ours, are using it to save time and work more efficiently.I haven’t had much time to dive deep yet, but I’ve started experimenting. So far, I’ve used the connector to scan recent conversations and surface common feedback patterns or recurring issues. I’ve also used it to gather feedback on specific topics. Another helpful use case has been content updates: when we launch a new feature, I can ask ChatGPT to review our help articles and point out where information needs to be updated.I’d love to hear how others are using the Intercom → ChatGPT connection. Any workflows, prompts, or clever tricks you’d recommend?

 Most teams switch on Fin and hope for the best. The best teams build a ritual.In this episode of Support Stack, Conor Pendergrast (CustomerSuccess.cx) and Jen Weaver (Supportman) show you how just 15 minutes a day reviewing Fin’s conversations can transform your AI performance and customer outcomes.What you’ll learn in this episode:🔍 Where to find the conversations Fin couldn’t resolve🛠 How to turn those conversations into better answers with snippets and articles⚖️ Why snippet sprawl is a hidden risk — and how to avoid it📈 The habits that help Fin (and your team) get smarter every dayIf you’re using Intercom and want to get serious about AI-powered support, this conversation will give you practical steps you can use immediately.Subscribe for more behind-the-scenes looks at how real teams are making Intercom wor

 Guessing where to improve Fin wastes time. Topics Explorer shows you the exact conversations where Fin struggles so you can fix what matters first. In this Support Stack episode, Jen Weaver (Tettra) and Conor Pendergrast (CustomerSuccess.cx) walk through:Selecting the right scope and metric to surface real opportunities Generating a Testing Group from past conversations by topic Rating answers with keyboard shortcuts and product-expert notes Deciding whether the fix is content (articles/snippets), data (attributes/connectors), or actions (Fin Tasks) Preventing wrong-product answers by pushing the right user attributes into Intercom and guiding Fin accordinglyYou’ll see a real example where a new product area had a low resolution rate due to thin documentation and missing signals. We show how to diagnose i

Tired of getting customer messages that just say “It’s broken”? In this episode of Support Stack, Jen Weaver from Supportman shows Conor Pendergrast (CustomerSuccess.cx) exactly how they trained Fin to clarify error details before the ticket ever hits an agent.We go behind the scenes in Intercom’s Fin guidance settings so you can see the wording, the workflow, and the real impact this setup has on reducing back-and-forth.Practical, real-world Intercom examples — no theory, no fluff. 

 What changed when Pupil Progress pushed Intercom’s Fin to the front of their support flow and rewrote their help centre for humans and AI? In this episode of Support Stack,  Conor Pendergrast (CustomerSuccess.cx) interviews Tobi Davis (Head of Customer Experience, Pupil Progress) about how Tobi’s team lifted Fin’s resolution rate from ~55% to ~75% in about two months, and why it now holds steady at 75–80% weekly. You’ll learn: Why going AI-first with a clear “talk to a human” option lets users self-select the path they want How to rewrite your help centre for two audiences: people and Fin The role of audiences and attributes so answers change by role, subject or context When to use custom answers, snippets and narrow articles for precise guidance Why they focused on content and

Discover  how to Use Fin Attributes for Escalations in Workflows & Tasks from Intercom Community Top Expert ​@Nathan Sudds 💡  

📊  When Your Data Doesn’t Tell the TruthHow Fin’s AI Categorization Turned Messy Data into Clarity Every CX or ops leader knows the feeling. You pull up a report, and at first glance the numbers look fine. But something feels off. The story in the charts doesn’t line up with the reality on the floor. The problem isn’t the report—it’s the tags feeding it. When tagging is inconsistent, the data turns unreliable. And unreliable data makes reports lie. That was the bind this team found itself in. They needed to spot product issues early—like which models were most likely to crack, which parts kept showing up damaged or missing, or which shippers were the least reliable. With that kind of clarity, they could protect revenue, get ahead of problems, and spare customers unnecessary pain. But with inconsistent tags, they weren’t seeing the full picture. The pivot: Stop Wrestling with Tags. Start Tracking Reality 🔁 Here’s th

Hey everyone — curious to learn from other teams here!We’re building out a Case Closure Data Model as part of our Intercom + Fin AI rollout, with the goal of turning every resolved ticket into AI-ready data for automation, prevention, and knowledge training.Our current thinking includes adding structured closure fields like: Technology / Sub-Technology Problem Code / Resolution Action / Root Cause Repeatability / Escalation / Customer Effort KB Linked The intent is to improve data quality, reduce “Other” categories, and help Fin identify repeatable automation candidates over time.I’d love to hear how others are approaching case hygiene at closure: Which closure fields have been most valuable for your AI or reporting goals? How do you

This Fin Task was designed to help customers quickly understand whether an issue they’re experiencing is related to a known incident, without needing to contact support directly. The goal was to make it feel fast, human, and reassuring while surfacing relevant technical information from our infrastructure. 🌍 Step 1: Detect the Customer’s Hosting RegionWe start by detecting the customer’s data hosting region, which is stored as a company-level attribute in Intercom. This attribute is critical — it allows the task to tailor its response and status checks to where the customer's workspace is hosted.Regions we support include:

Recently we made a small change with a big impact in our Intercom workspace. We’ve now enabled Fin to re-engage customers if their conversation hasn’t been picked up yet. After a set wait time, Fin checks back in: “While you're waiting, would you like to chat with me (Fin AI Agent)?” If the customer says yes, Fin will attempt to resolve the customers issue. If not, the conversation stays right where it is in the team queue. Why this matters?Because it’s a game-changer for speed and efficiency. We’re seeing more conversations resolved automatically, fewer customers waiting around, and less work piling up for the team. How to enable it in your workspace: Go to your Workflows page Create a new workflow using the If teammate has been unresponsive trigger In your audience rules select the team inbox(es) you want this to fire in,

When using collapsible sections in your articles, consider repeating the core question of your FAQ (Frequently Asked Question) within the answer itself.  This significantly helps AI agents like Fin more accurately find and utilize the relevant content for their answers. It's a handy trick to optimize your FAQ sections for better AI performance!

You can use AI tools like Claude or ChatGPT to: Repurpose internal content: Quickly convert internal documents and product updates into customer-friendly Help Center articles. Review and rewrite: Rephrase content to match customer language. Ensure proper formatting (headers, bullet points, etc.). Clarify ambiguous terms.  Using AI tools works really well if you create a style guide with the structure, formatting, tone of voice, and template you'd

One of the easiest ways to improve how Fin handles conversations is to use if–then logic in your Guidance. It helps Fin understand exactly when to apply a response, and what that response should look like.Here’s a simple example:"If a customer asks how to change their password, tell them to click 'Forgot password?' on the login screen and follow the steps."That’s much clearer than:"Explain the password reset process."By adding a condition (“if a customer asks…”) and a specific action, you give Fin a clear playbook to follow. It also helps prevent Fin from jumping in with the wrong response in unrelated situations.To take it further, you can include a direct link to your help center or a relevant support article. This makes it even easier for Fin to guide customers to the right place, without needing to explain every detail.

On the surface, it can seem that Copilot is a simple yet powerful tool that helps your team answer customers questions. But, it’s so much more than that!We've been using Intercom’s Copilot across our team and it's been a game-changer for us. If you're not using it to its full potential yet, here’s a quick breakdown of some ways to use Copilot you may not have thought of that help streamline work and boost efficiency:Faster Onboarding for New AgentsNew joiners no longer need to ping senior teammates every five minutes. Copilot acts like a super-smart buddy, guiding them with internal resources and examples from previous chats. It’s drastically shortened our onboarding ramp time.Internal Process GuidanceWhenever someone has a “how do we do this again?” moment, Copilot jumps in with answers sourced from our internal articles and documentation. It’s perfect for navigating complex or frequently changing internal workflows.Ma

Since it was in early beta we have been using the AI Summaries feature in our Intercom workspace and it’s proven to be a massive time-saver for our support team. Before this, whenever a teammate picked up a conversation after Fin handled it, they had to scroll through everything to understand what had already been covered. Now, Intercom generates a quick, clean summary at the point of handoff from Fin in an internal note.It’s a small change with big impact—no more duplicated steps, no more “Let me check what’s already been said,” and a much smoother handoff between Fin and our human teammates.🛠 How to enable it in your workspace: Go to your Workflows page Go to one of your existing triage workflows or create a new workflow In the path (or before) you are assigning to an inbox, add the “Add summary note” action Done! The summaries will automatically app

Here’s something that’s easy to overlook: Fin isn’t reading between the lines. It’s taking your guidance literally, so the simpler and more specific your language, the better the results.We’ve all written something like:"Be friendly and professional."It sounds good, but it’s open to interpretation.A clearer version might be:"Use a professional yet warm tone. Keep responses short and avoid jargon. When a customer is frustrated, acknowledge the issue and say something like, ‘I understand how that can be frustrating. Here's what we can do.’"This type of Guidance gives Fin a clear tone to follow and reduces guesswork. It also helps keep responses consistent across your support experience.Think of it like coaching a new team member. If you wouldn’t rely on vague tone tips when onboarding a new agent, don’t use them with Fin either.

We noticed a recurring issue in some of our Fin-involved conversations. Fin was surfacing Help Center content that included phrases such as "please contact support" or "reach out to us through the Messenger."While this wording makes sense when someone is reading an article independently, it can cause confusion during a live support interaction. When Fin presents this type of content mid-conversation, it can give the impression that the customer is not already receiving support. This creates friction and can lead to drop-off.To improve the experience, we provided more specific guidance for Fin to follow. We instructed it not to include phrasing that directs customers to contact support, since they are already in a support conversation. Instead, Fin should treat the interaction as part of the support experience by either providing the information the customer needs or asking for clarification to help resolve the issue.This change reduced unnecessary loops and made

A lot of us naturally default to vague guidance like,"Make sure Fin understands our product types."But Fin thrives on clarity. A stronger version might be:"If a customer asks about the 'search' feature, first ask which product they’re using. Then give product-specific instructions."See the difference? That second version gives Fin clear steps and a condition under which to act. It's specific, it's actionable, and it’s something Fin can consistently follow.When you're writing guidance, ask yourself: what should Fin say first? What should happen next? That simple shift in thinking can make your guidance 10x more effective.How do you typically plan out what Fin should do in different scenarios?