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I would like to be able to reply to an email and schedule send it for the morning. I am sometimes working late at night or I know the person I am emailing is on vacation and I don’t want to bother them. I would like to be able to schedule the email for another date/time and have it send then. I should be able to edit that email after I click “schedule” and make updates if I need to. There should also be an area where I can see all my scheduled emails. This is a feature that exists already in gmail and most other emailing platforms.
It would be good to have the ability to schedule emails sent from the inbox to allow forward planning of adhoc outreach.
Currently, reports can show ticket metrics like “New tickets,” but there isn’t a way to report on how many tickets a specific teammate has created by ticket type (for example, Tracker tickets). You can only see the ones they are assigned to. It would be useful to add a report metric or breakdown that shows tickets created by each teammate, with the ability to filter by ticket type such as Tracker tickets. This would make it easier to measure individual contribution and track volume for internal ticket categories.
I want to be able to pull reports using criteria found in the “event history” of a ticket. For example, I have an agent who gets a ticket assigned via Balanced Assignment. He then goes in and manually changes Assignee: unassigned, and Team Inbox: unassigned. The activity appears in the event history of a ticket. I am not able to pull any data around actions that only appear in the event history. I can only pull data around tickets being reassigned, which is not helpful in this case. I also can’t use the filters around ‘current assignee’ because that has changed between the time of the action taking place and pulling the report, and is also not relevant to what I need to track. Use case: Agent is unassigning themselves from tickets they don’t know how to do. Create a report to track Tickets that have the action “X agent changed status from Assignee: X to Assignee: Unassigned”. That way I can then filter by ticket category or case type to understand product knowledge gaps and use for training purposes.
I was surprised to find out that if a participant of a ticket is changed, the CSAT still sends to the original person. For example, someone from our sales team might forward an email to us, and even though we've removed them and added the customer as the participant, the CSAT score will go to the original sender (in this case, the sales person). I was definitely surprised that it doesn't take into account the person who is actively the participant on the ticket, but I assumed the system was smart enough to pick up who the active participant is at the time of sending a CSAT survey.
The search is very basic and doesn't allow to even use operators likecontainsbeginsWithmatchesgreaterThanor even wildcards *, ?
The ProblemWhen customers reply to email conversations, their email client includes the entire previous thread below their new message — as virtually every email client does by default. Intercom's Inbox renders this quoted trail fully expanded, inline, for every single message in the conversation. The result is that a 6-reply email thread becomes an endlessly scrolling wall of duplicated text, where the same content is repeated over and over, growing exponentially with each reply.This makes it genuinely painful to work through email-based tickets. Instead of quickly scanning the latest reply at the top and moving on, agents have to scroll past pages of repeated content just to orient themselves. Multiply that across dozens or hundreds of tickets a day and you're looking at a real productivity hit — not to mention the mental fatigue of parsing the same text blocks repeatedly.Why This Is FrustratingEvery major email client and nearly every competing helpdesk platform handles this gracefully. Gmail, Outlook, Zendesk, Freshdesk, Help Scout — they all detect the quoted text delimiter and collapse it behind a simple "show quoted text" toggle or ellipsis. It's a solved problem. It has been a solved problem for over a decade.The fact that Intercom still displays raw, fully expanded email trails in 2026 is baffling. This isn't a complex engineering challenge. Email clients universally use standard markers for quoted text (> prefixes, --- Original Message --- delimiters, etc.). Detecting and collapsing these behind an expandable toggle is straightforward — it's the kind of thing a single engineer could prototype and ship in a day.What We'd ExpectQuoted email trail text should be collapsed by default in the Inbox conversation view. A simple "Show quoted text" or expand toggle (like Gmail's ellipsis ...) should let agents reveal the full trail when they actually need context. This should apply to all inbound email messages where quoted/forwarded content is detected.The ImpactThis affects every single team that handles email-based conversations or tickets in Intercom. It's not an edge case — it's the core workflow. For teams processing high volumes of email tickets, the lack of this basic functionality adds up to hours of wasted scrolling and lost focus every week.This feels like the definition of a quick win: low complexity, high impact, long overdue. We'd love to see it prioritized.
Currently SLA’s support First Response Time and Next Response Time, but FRT counts down as soon as the conversation starts rather than counting as soon as it’s assigned to an agent. I’d like the ability to create an additional (not replacement) SLA, First Response Since Assignment. It will only start counting down when the ticket has been assigned to a human agent. This works well with the Balanced Assignment system, which supports SLA within prioritization rulesets.
When you pulling all articles, you are loosing the order they have within a certain (parent) section.https://developers.intercom.com/docs/references/rest-api/api.intercom.io/Articles/listArticles/ When you pull sections or collections, it is exporting the order (by exporting the order-value).See API for collections: https://developers.intercom.com/docs/references/rest-api/api.intercom.io/Help-Center/collection/(there is a misspelling in this one, it says “… The order of the section in relation to others sections within a collection. ...” )API for sections: https://developers.intercom.com/docs/references/2.7/rest-api/api.intercom.io/Help-Center/listAllSections/ Can you please implement the order-key for articles (in the webinterface it is possible to order them, but its not reflected in the exported data via API)
It would be very handy if when you went to re-snooze a conversation that the ‘Last Custom Snooze’ setting was remembered and available form the list of preset selections. ie a conversation is snoozed at a future check in/deadline date which won’t change but the customer replies with some thing like ‘Thanks, see you then’ a hour later so it reopens - you have to custom select that snooze date all over again
I wish I could set the order of Help Center articles via the API. Right now, one can only do it via the Intercom UI.
Problem: Hard to find mentions that I haven’t yet “done” or “handled”. I get like 5-8 mentions every day from team members with technical questions. When I’ve answered my team members in the conversation, the mention still stays in my list. Some mentions are quick to answer but some might take several days or even weeks to handle, so old unhandled mentions are relevant for me, but are very hard to find since I mostly see the latest mentions which might be handled already. Current workaround is to use “Mark as unread” after I’ve read it and not handled it yet. Then I can use the filter to show only “unread” mentions. This has obvious problems: as soon as I click on a mention, the system marks it as read. Requested feature:A separate "Mark as Done" or "Resolve Mention" button that removes the mention from my personal Mentions list without affecting the conversation status or other teammates' views.This is not the same as closing the conversation - the conversation might be about more things, and our team members still should answer the customer etc…
The warning message occupies almost half of the reply screen. Please allow to minimize or close the warning message as there is not enough space to work with especially when creating long responses.
The ability to clear out the Mentions view in Intercom, both in bulk and to individually check off items, would make using that view much easier. Currently, the view is difficult to manage as all Mentions remain in the view.
Currently managing large volumes of mentions (3,000+) requires opening each conversation individually to clear the unread count. There's no bulk functionality for mention management.Requested features:Bulk 'mark as read' option for mentions Bulk 'clear all mentions' functionality Mass selection tools for mention management (similar to conversation bulk editing)Current limitation: Only way to clear unread mentions is going to Inbox → Mentions → Unread mentions, then opening conversations one by one.This would significantly improve efficiency for users with high mention volumes who need streamlined inbox management.
Problem:Fin AI Agent tags individual conversations with a "Fin referenced memory" event when Fin draws on stored memory to respond. That event is visible at the conversation level, but it's not exposed anywhere in reporting. The Fin AI Agent Analyze dashboard shows resolution rate, CX score, and involvement rate, but there's no way to filter or segment any of those metrics by whether memory was used.What we'd like to see:Turn the existing "Fin referenced memory" event into a reportable attribute, similar to how other conversation-level tags already feed into Analyze. Since the tagging already happens at the conversation level, this would mainly be a matter of surfacing that field for filtering and segmentation rather than building new tracking from scratch.Why it matters:Without this, teams have no way to measure whether Fin Memory is actually helping resolution rates, hurting them, or making no difference. Right now the only way to check is opening conversations one at a time and looking at the event log, which doesn't scale for anyone trying to evaluate memory as a feature. Being able to compare memory vs. non-memory conversations on resolution rate and CX score would let teams make an informed call on whether to keep leaning into it.
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