Analyze Fin

I’ve learned from Intercom’s documentation that CX scores are calculated using three signals: Customer sentiment, Resolution status, and Service quality.When I want to understand why a conversation has a certain CX score, the single blended number doesn’t always give enough detail. For example, was it customer sentiment that drove the score down, or did resolution status carry more weight?Is there a way to see the score for each of the three signals individually, rather than just the overall CX score? Having visibility into the individual components would really help in analyzing conversations more deeply and understanding what’s driving the overall CX score.

I’m working on setting performance targets for FIN—does anyone have experience or data they could share around Resolution Rate or CX benchmarks?!--endfragment>!--startfragment>

Hi all,How is your team’s CX Score performing?Our Fin has scored 86% over the last 30 days while resolving 69% of conversations (90.9% and 74.3% respectively when limited to the Chat channel only).

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! 

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?

Hello! I’m working on integrating Fin AI to our queries handling.When conversations are handled by a teammate, we use a custom attribute “Subject Line” to ‘tag’ the query and report on volumes each week. Subject Lines would look like this:[Account] Login issue, [Account] Change Email Address[Billing] Refund Request[General] Query / Premium, [Feedback] Contentetc etc If I want Fin to handle tickets, how can I get it to tag the conversation based on its content? either via our Subject Line attribute or via tagsAt the moment, we have a workflow where users select what they want to talk about with buttons (“Question about my account”, “Help with my subscription”, “Share feedback”, “Something else”). Subscription queries go through Fin, the rests goes to a teammate. I’d like to open “Something else” to Fin AI too but I’d need to be able to tag the conversations properly to create usable data. What’s the best practices here? What have you found the most helpful?

Hi everyone!If you are using FIN as the chatbot, I’m curious about what is the current CSAT score of your FIN profile. Ours is currently ~50%, and we are not really sure if it’s a good one. Thanks!

I noticed when I manage snippets I no longer see a count of how many times the snippet was used in a FIN answer. Is that stat appearing somewhere else now or was it removed for some specific reason? The use count for snippets was super helpful to show effectiveness and also to help justify cost for FIN. Thanks!

Hello Intercommunity! I have a question about Fin. I want to measure CSAT for CSAT handled by AI vs. handled by a human.  Question: Is it possible to see CSAT for conversations fully handled by AI?  Caveat: I know I can see overall CSAT, but I’d like to be able to measure CSAT for conversations fully handled by AI. This is the tab I am using to measure CSAT, and I can’t find a way to filter down to only conversations handled by AI.