Macha

Front Tags vs Statuses vs Assignment (2026): Organizing Conversations

Abbas, Customer Support & AI, Macha

Written by

Ankeet Guha, Co-founder & CTO, Macha

Reviewed by

Published July 16, 2026

Updated July 16, 2026

Open a busy Front shared inbox and you are looking at three different organizing systems at once, even if it does not feel like it. A conversation has one or more tags describing what it is about, a status describing where it sits in your workflow, and an assignment describing who owns it. Teams that treat these as one big pile of "labels" end up with cluttered inboxes and reports that do not add up. Teams that understand the three axes separately can find any conversation, reach inbox zero honestly, and trust their analytics. This guide walks through what tags, statuses, and assignment each actually do, how they combine in the shared-inbox tabs your team lives in every day, what each one means for your numbers, and where the native system runs out of road.

Front Tags vs Statuses vs Assignment (2026): Organizing Conversations

Three axes, not one pile

The cleanest way to think about a Front conversation is that it lives at the intersection of three independent questions.

Tags answer "what is this about?" A tag is a label — billing, bug, refund, VIP — that you attach to a conversation to categorize or file it. Tags are orthogonal to everything else: a conversation can be tagged "refund" whether it is open or archived, assigned or unassigned.

Status answers "where is this in my workflow?" Open, snoozed, archived, trash, spam. Status is a single state — a conversation is in exactly one of them at a time. It is the difference between "I need to deal with this now," "later," and "done."

Assignment answers "who owns this?" A conversation can be assigned to a specific teammate or left unassigned for the team to pick up. Assignment is the accountability layer of a Front shared inbox — it is how a group mailbox stops being a free-for-all.

Keep those three questions distinct and the whole system clicks. Tags describe, status sequences, assignment owns.

Tags: private folders vs shared labels

Front has two flavours of tag, and the difference matters more than people expect. Per Front's guide to using tags to label and file conversations, private tags act as personal folders visible only to you — filing a conversation in a private tag does not affect what anyone else sees. Every conversation in your main inbox even carries a default private Inbox tag, which is automatically removed once you file the conversation under another private tag. That is why "moving" something to a folder in Front is really just a tag swap under the hood.

Shared tags, by contrast, are team-wide labels. When one teammate tags a shared conversation "escalation," everyone working that inbox sees it. Shared tags are the ones you build reporting and rules around, because they carry the same meaning for the whole team.

A Front conversation with the tag menu open (Add tag search, Recently used, All tags: billing, Billing, Bug, Inbox, Refund, plus Create new tag) alongside the conversation header status controls (Assign dropdown, open/status icons) - showing how tags and statuses together organize the inbox.
A Front conversation with the tag menu open (Add tag search, Recently used, All tags: billing, Billing, Bug, Inbox, Refund, plus Create new tag) alongside the conversation header status controls (Assign dropdown, open/status icons) - showing how tags and statuses together organize the inbox.

You can add a tag by hand from the conversation header (the tag menu shown above), drag a conversation onto a tag in the sidebar, or let a rule apply it automatically on inbound. Front's sidebar supports up to 500 tags, and a lock symbol marks the private ones so you never confuse a personal folder with a team label.

Statuses: open, snoozed, archived, trash, spam

Status is where most "why can't I find this conversation?" confusion comes from, so it is worth being precise about each state.

  1. Open — the conversation needs attention. It is your to-do list. In a shared inbox, open conversations are the ones the team is actively responsible for.
  2. Snoozed — hidden until a chosen wake time (or until new activity arrives). Front's inbox sections file snoozed items under a "Later" view: not resolved, but not something you are actively working right now.
  3. Archived — done. Per Front's guide to archiving, archiving moves a conversation out of your Open tab and into the Archived tab — "tasks you've checked off." Crucially, if new activity arrives on an archived conversation, it automatically reopens. You never lose a customer reply by archiving.
  4. Trash — removed. Trashed conversations are deleted from normal view.
  5. Spam — flagged by your email provider or by a teammate.

The archived-vs-trashed distinction is the one to internalize, because it has real analytics consequences (more on that below): archived conversations count toward team analytics and appear in search by default; trashed ones do not count and require an explicit filter to surface.

How the three combine in your inbox tabs

Here is where tags, status, and assignment stop being abstract and become the tabs your team clicks all day. Per Front's guide to inbox tabs, a shared inbox can be configured two ways, and the key insight is that its tabs filter by status and assignment at the same time.

  • Split view (default): separate Unassigned and Assigned tabs. The Assigned tab shows conversations that are assigned and still open; Unassigned shows conversations that are open and not yet claimed. Then Snoozed, Archived, Trash, and Spam filter by status.
  • Combined view: a single Open tab that merges assigned and unassigned into "all unarchived conversations," with the same Snoozed/Archived/Trash/Spam tabs alongside.

Each teammate picks the view they prefer under gear icon → Preferences → Shared inbox tabs — it only changes their own interface, not the underlying data. Tags then cut across all of these: a saved view or sidebar tag can show you every "refund" conversation regardless of which tab it currently lives in.

AxisAnswersPossible valuesCan a conversation have more than one?
TagWhat is it about?Any label (billing, bug, VIP…)Yes — many at once
StatusWhere is it in the workflow?Open, snoozed, archived, trash, spamNo — exactly one
AssignmentWho owns it?A teammate, or unassignedOne assignee (per copy)

What each axis means for analytics

Because the three axes are independent, they show up differently in reporting — and mixing them up quietly distorts your numbers.

Status drives your volume and resolution metrics. Archiving is the signal Front reads as "handled": archived conversations feed team analytics, so if your team trashes conversations they have actually resolved instead of archiving them, your resolved-volume numbers will read artificially low. Trash is for genuine noise, not for closing tickets. This is the single most common way a Front report ends up wrong.

Tags drive your categorical breakdowns. If you want to know how many billing questions came in this month, that is a tag-based report — which is exactly why shared (not private) tags are the ones to standardize on. Private tags are invisible to team analytics, so a teammate quietly filing things under a personal folder contributes nothing to the shared picture.

Assignment drives your per-teammate workload. Who is handling what, and who is overloaded, is an assignment question — separate from how many of those conversations happen to be tagged "refund."

The takeaway: report on status for throughput, on tags for topic, and on assignment for workload. Conflate them and the dashboard lies.

The honest limits — and where an AI layer picks up

This three-axis system is genuinely good. It is simple, it is consistent, and it scales from a two-person team to a large support org without breaking. Nothing here needs replacing.

But notice what it can and cannot do. Every one of these axes is descriptive, not resolving. A tag records that a conversation is about billing; it does not answer the billing question. A status of "open" records that something needs a human; it does not do the work. Assignment records whose job it is; it does not make the reply any faster. The organizing system is a filing cabinet, not an assistant — it puts the right folder in the right person's hands and then waits.

There is also honest plan and structure friction worth naming. Some organization power — granular permissions over who can create or edit shared tags, and the SSO/admin controls larger teams need — sits on higher Front tiers, and collision-avoidance features only matter once you actually have teammates sharing an inbox (they are inherently shared-inbox-only). None of that is a knock on Front; it is just where the native product draws its lines. Front's own team inboxes model covers those boundaries in detail.

This descriptive-versus-resolving gap is exactly the seam where an AI agent layer fits. The category of AI agents for customer service exists to do the reasoning work a label cannot. Macha is one such layer: it runs on top of the Front you already use through the live Macha–Front connector — it does not replace Front, your tags, your statuses, or your assignment logic. You keep those axes doing what they do best: describing, sequencing, and owning. Then Macha's agent reads an open, tagged, assigned conversation, understands the intent behind it rather than the label on it, and drafts or sends a grounded reply — pulling a real order or account status through a custom tool that turns your REST API into something the agent can call. A tag says "billing"; the agent actually resolves the billing question and lets the conversation archive itself. Macha's credits are consumed per AI action, never per resolution — because reading, retrieving, and replying are distinct pieces of work, and it is honest to price them that way.

The clean division of labour: let Front's tags, statuses, and assignment be the organizing system they are excellent at being, and layer an agent on top for the part a label can never do — reading the conversation and answering it. For how the pieces fit together, see Front tags explained and the wider Front shared inbox model.

FAQ

What is the difference between a tag and a status in Front? A tag describes what a conversation is about (billing, bug, VIP) and a conversation can have many at once. A status describes where the conversation is in your workflow — open, snoozed, archived, trash, or spam — and a conversation has exactly one status at a time. They are independent: a conversation can be tagged "refund" whether it is open or archived.

What is the difference between archiving and trashing a conversation? Archiving marks a conversation as done and moves it to the Archived tab; it still counts toward team analytics and appears in search by default, and it auto-reopens if new activity arrives. Trashing removes a conversation from normal view, excludes it from analytics, and requires an explicit filter to find in search. Archive resolved work; trash only genuine noise.

What is the difference between snoozed and archived? Snoozed means "not now, remind me later" — the conversation is hidden until a chosen wake time or until new activity arrives, then it resurfaces as open. Archived means "done" — it stays out of your Open tab unless a customer replies. Snooze is for deferral; archive is for completion.

How do assignment and status work together in shared-inbox tabs? Front's shared-inbox tabs filter by both at once. In the default split view, the Assigned tab shows conversations that are assigned and still open, while Unassigned shows open conversations no one has claimed. You can switch to a combined Open tab under gear icon → Preferences → Shared inbox tabs.

Can I add AI to Front without changing my tags and statuses? Yes. An AI agent layer like Macha connects to Front as a live connector and runs on top of your existing inboxes, tags, statuses, and assignment — it does not replace them. Your organizing system keeps describing, sequencing, and owning; the agent reads the routed, tagged conversation, understands intent, and drafts or sends a grounded reply.

Ready to turn "open and tagged billing" into "answered and archived"? Start a free trial of Macha and connect it to your Front in minutes.

Macha

About Macha

Macha is an AI agent platform that works on top of the help desk you already use — Zendesk, Freshdesk, Gorgias, or Front — and connects to the rest of your stack, even your own internal systems. Its AI agents resolve tickets and automate entire workflows end to end, all set up in plain English, no code. Learn more about Macha →

Zendesk
5.0 on Zendesk Marketplace

Loved by support teams worldwide

See what support teams are saying about Macha AI.

The application seems excellent to me! We are still testing, and we need support for some details and they were extremely efficient too!

Daniela Costa

Daniela Costa

Head of Support, Seabra

Macha has been a great addition to our support toolkit. It generates clear, well-organized responses that fit naturally into our workflow. One feature we particularly appreciate is its ability to automatically reply in the same language as the ticket.

Marius F

Marius F

Support Head, Zentana

We've been using Macha for a little while now and it's been really great addition so far! It's powerful, convenient, and makes getting work done a lot easier for our agents.

Alexander Wedén

Alexander Wedén

Head of Support

Support team is very helpful and responsive. Really enjoy how lightweight this is within Zendesk itself vs other more intrusive tools.

Cathleen Wright

Cathleen Wright

Zendesk Admin, Cortex IO

So far it's pretty good! Our queries are a little nuanced, so we can't always use it, but it's got enough utility for us. It can even incorporate our bilingual country with greetings in a second language.

Jae Oliver

Jae Oliver

Head of Support, Wise

Really enjoying using Macha, it has made a noticeable difference to our support team in a short amount of time. I really like the ticket summary feature, saves us a lot of time.

Harry Jackson

Harry Jackson

Head of Support, Crumb

Macha AI is a great addition to my workspace! It's powerful, convenient, and it really makes productivity so much easier for our agents!

Dave G

Dave G

Head of Support, Cyber Power Systems

Very impressed! AI integration for Zendesk has certainly come a long way and Macha seems to set the standard for now. This will for sure save lot of time in our support team.

Pauli Juel

Pauli Juel

Head of CS, Dokument24

Macha has been working great for us so far! The auto-responses are accurate and our resolution time has dropped significantly.

Lana T

Lana T

Zendesk Admin, Swotzy

Macha AI is a great addition. The knowledge base feature means our agents always have the right answers at their fingertips.

Mischa Wolf

Mischa Wolf

Head of Support, Topi

We're enjoying this integration so far. It's made our support team more efficient and our customers get faster responses.

Paula G

Paula G

Head of Customer Support, Xly Studio

The team enjoys using it. It saves considerable time on common questions and the integration options are excellent.

Kilian Leister

Kilian Leister

Support Head, Didriksons

Ready to supercharge your team with AI?

Get started in minutes. Connect your tools, configure your agents, and let AI handle the rest.

7-day free trial · no credit card required