Fin

I will have data of my customers on my website (e.g. hours played). I want FinBot to answer certain questions differently depending on this data. Is there any way to do this? 

Currently our customer support operations is very manual and we are growing. We’d like to implement AI automation that would both A) help answer customer questions but also B) help take common actions (refunds, issue credit, cancel subscriptions etc) -- initially after human review. We use Stripe and have our own API for our backoffice tools.My questions are: 1) can intercom handle off of this? And 2) If I want to find a consultant or expert to help us implement this, any recommendations?

Hey everyone!I’m curious to hear from other Fin users – what key metric are you focusing on to demonstrate Fin’s success to your organization? Personally, I’ve found that resolution rate isn’t always the best indicator since so many variables can impact it. For example, a customer might receive a perfect answer but still choose to speak to an agent, or Fin could close a conversation automatically due to spam, both of which can skew the resolution rate.I’m leaning toward deflection rate as a more telling metric – measuring the percentage of support handled by Fin versus what’s escalated to humans. But I realize this might be oversimplifying things. Would love to hear what others are tracking and why! 

I added a bunch of data from my database, but fin can’t answer a single question related to that.

Hi everyone,I’d love to get a conversation-type thread going! Is anyone using Fin actions and tasks in practice already?If so, it would be cool to share some best practice examples and your experiences, especially with technical and security aspects of connecting Fin and customer data to APIs.  

Hi - We want our users to be able to interact with Fin but not give certain domains the option to “Talk to a person”. Is it possible to configure this? We are open to turning this off for all customers for now, if we can’t turn it off for specific customers 

My company has three products. Each of them have their own knowledge center. Each customer conversation is tagged based on which app the user originated from. Fin doesn’t seem to be able to connect the dots that when a conversation is tagged with Product A, it should use the associated knowledge center. I have provided this instruction via the guidance section of the training system.Do you have suggestions about how I can get FIN to focus it’s answers based on a tag?

Will Fin ever have the ability to reply to a customer’s question with a screenshot or potentially a video? It is good at reviewing what we have and describing it but it would be very helpful to share the actual image (especially in a navigation question scenario).

Currently when syncing with Confluence, the only visible sources are those contained within ‘Pages’. Anything that’s in a folder or subfolder is hidden and so cannot be located and used for FIN or CoPilot. Is there a workaround for this that doesn’t mean we have to remove everything from the folders and have 1000 individual pages for our knowledge base? Has anyone found a workaround that isn’t too time consuming?

I am working on new Fin Tasks where I want to create a branches with conditions that are dependent on the results of a custom action. Can anyone help me understand how to build this? For example if a Custom Action returns [X] then follow this path, and if Custom Action returns [Y] follow a different branch

Hi there,We’ve implemented Fin AI (Chat and Email) on our support desk, and it’s been fantastic so far—it’s doing a great job handling first-line queries! 😊However, we’ve noticed a challenge when a customer submits a vague message. Fin will respond with technically correct information, but it’s often not relevant to what the customer truly needs.I’m wondering if it’s possible to improve this by getting Fin to ask clarifying questions before responding. I’ve been advised to set up a new workflow where specific vague questions prompt Fin to ask follow-ups, but trying to predict and account for all the potential vague queries customers might come up with feels inefficient.Is there a better way to manage this? Any advice or insights you could share would be hugely appreciated!Thanks so much

Hi, The feature of "Fix grammar & spelling" is handy, however, when the selected sentence is incomplete (not ended correctly), it does add the missing word and/or punctuation marks to the end of that sentence (Expected); but, it also prefixes the missing word/punctuation to the top of the text!!!Example: It changes"I can assist you in this"to"matterI can assist you in this matter."

Would love to keep a thread going of what prompts are working for your teams, so we can generate some best practices across the community. 🙌🏻Share away!

Hi!I am a software developer working at Greenly.We are already using Intercom for custom support, for months.We recently saw that Fin will soon be available over an API (https://bfy.intercom.com/ “06 - Fin over API”Can you give more information of when will this be available please?Best regards,Maxime Broussart

We have a large database of typical customer questions and answers. These come from a service desk that is not currently supported by Intercom. What is the best strategy to add this content to Fin Knowledge?There are too many entries to manually input them as snippets.We’re considering adding them as a PDFs, but we’re not sure how Fin will chunk the data—whether it might split Q&As incorrectly or merge unrelated entries.Is there any guidance on how to format the PDF, or an alternative way to upload the data in a Q&A format?

Hello team! This maybe very normal question. Just would like to understand what are the differences between FIN AI and Chatbot please? In terms of how it can help to support customer service team We are looking to improve percentage of conversations which resolved by FIN AI. Also, percentage of improvement for conversations which closed by Chatbot as attached picture. To start with, I would like to get more understandings on how Chatbot can help the team to close conversation different from FIN AI please? Saw that percentage in report between FIN AI and Chatbot are separated. So I assumed that the way they work in the system on conversations are different? Moreover, if you have any suggestions/real practices about Intercom Chatbot improvement would you mind help to suggest. That would be really helpful on my end! Really appreciated :) Thank you in advance! Ploy

Our confirmed resolution rate is between 6-7% usually and our assumed resolution rate is near 60%. Looking at the conversations, I would estimate that 1/3rd at least of the assumed resolutions represent a correct answer and our clients are just not clicking the “Yes that helped” button that would mark it as a confirmed resolution. My experience with bots is similar, I rarely give bots feedback, because I know its not human. Any tips or methods that you have tried that increase clients use of the confirmed resolution? 

Hi,We have been using Intercom for our customer support for several months now and we are exploring AI automation solutions. Initially, we built workflows to handle basic support tickets, but we quickly found this approach to be unsustainable, as it became burdensome to maintain and scale.We also tried Intercom Fin, which we found to be an improvement over workflows. However, it is quite expensive, occasionally provides incorrect answers, and struggles with more complex tickets. With Fin charging $1 per resolution and our support agents resolving tickets at about $0.66 each, we decided to explore alternative solutions.I was tasked with identifying a viable option, so I’ve reviewed nearly all the apps listed under the Automation category in the Intercom App Store.There are approximately 140 apps in the Automation category, and we focused on identifying those that can automatically respond to customer messages. From this list, we found over 20 apps that either offer or claim to offer thi

Our deflection rate was 10-15 points below our average yesterday. It’s not the end of the world, but we’re typically very consistent.Was this a fluke or were there system bugs with Fin?

Hi all, I’m new here and trying to improve the FIN AI resolution rate. However, I would like to understand why the extracted data is always shows 0% or not higher than 2% if FIN AI Resolution rate is filtered with "Team currently assigned" but shows 27% for FIN AI Resolution rate of the company We do have our CS team across countries using Intercom chat. As the extracted data, there are two resolution rates that we’re looking at1.) FIN AI resolution rate of company as a whole2.) FIN AI resolution rate with filtered “Team currently assigned” each countries’ CS team However, the data extracted are always different. For an example, latest company FIN AI resolution rate is 27% but if I filtered the FIN AI resolution rate with “Team currently assigned” and see data of CS team in each countries. The data always show as 0% and never higher than 2% Would anyone have an explanation about this please that why it is different? I’ve read about the definition in Intercom but still unsure if my thou

Hi team,I’m looking into the possibility on FIN collecting information when a customer starts a live chat, and sets the Conversational Attribute to a certain value (‘I want to make a manual booking’).When this attribute has been selected, I’m envisioning that FIN will collect information from the customer and then pass over the compiled list of answers to an agent in the form of a ticket/a conversation, but with little need for the customer to reach out back and forth with the agent. For example:Customer starts chat Customer selects ‘I want to make a manual booking’. FIN answers, but because of Step 2, he has specific instructions to ask for the answers to a list of pre-determined questions (such as, ‘What is the name of the supplier, what dates, what room type, etc...’  FIN then thanks the customer and says that this will be booked for them ASAP, and we will reach out if we need anything else.For step 3, I am struggling to find where we would set up this list of questions that we know

FINs newest feature Guidance is now live in Beta? Are you using it?With such a new feature, that is possible the most powerful and complex, moved to Beta recently I’d love to hear how many of you are using it and how you are all finding it?Lets try share tops tips in the below, so we can all learn from each other.Examples of how you are using it What's working well What's not doing what you expect Anything else that is good to know

Is there a way to train FIN for more scenario based questions. Our customers have different use cases for our product and it would be very helpful if we can train fin to help answer scenario based questions. 

Hi! I'm currently in the process of setting up Fin for email. As we'd like to offer personalized (Human) Customer Support to our Users, I want to set up Fin for email for Leads. However, 56% of our emails sent by Leads are spam/marketing messages, and I don't want to be charged for all these emails.In related topics (How to avoid Fin trying to offer solutions to marketing emails and other spam?) I see that other users tag these emails and exclude them from Fin's audience. However, I'm not sure how to identify these emails as such so I can set up my workflows and give them a tag. Does anyone have some advice? 🙏 Thanks in advance!

Can Fin read data from my excel sheet or Google sheet and answer user question? I tried to add the google sheet as webpage for Fin content, but it shows error.