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Friends, are there any Paid Consultations around Fin optimization? I’m wanting someone to hop on a call with me so that I can check my logic. 

I pulled ticket information via the MCP into claude and did some ticket analysis. We’ve learned what our top support gaps are and we created documentation with SME’s to fill those gaps especially on the troubleshooting side. 

The rub is that I don’t know how to effectively attribute the benefit of the document(s) that we created - to the potential improvement of Fin Resolution rate (nor by how much).  

Also, separate thought - is there a way to review edits that were updated through the suggestions in Train? 

Sorry for the vomit, I just want the effort we put it to count! :)

Hi ​@Malachi Hopoate , great questions and not a vomit at all 🙂

On the first part: Intercom doesn’t currently offer paid consulting calls specifically for Fin optimization. What most teams do is lean on their Customer Success Manager (if you have one) or open a ticket with Intercom Support to get routed to the right specialist.

If you want outside help, you can try the Experts tab and get in touch with one of the community-listed experts. https://community.intercom.com/p/experts
 

For measuring the impact of your new docs: afaik, there isn’t a direct “X document = Y% Fin resolution” metric. What you can do is track Fin resolution rate over time before and after those docs were published, and cross-reference with the “Articles viewed in Fin” report or the Fin AI Agent reporting dashboard. If you see that resolution rate goes up while Fin is referencing those new docs, that’s your strongest correlation. It won’t be exact attribution, but it’s the accepted way of showing value.

On your last point: yes, in Train, you can review edits suggested by teammates and AI. Head to Fin - Train - Suggestions in your workspace, and you’ll see the edits and feedback history there. That way you can approve/reject and keep track of how the content has evolved.

Cheers!

 

Hi ​@Malachi Hopoate 

Really helpful breakdown already shared above. Just wanted to add that I have built attribution models with MCP + Fin data before.

Happy to review your logic or explore ways to tighten the correlation.

You can reach out to me on my email here

Colin

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