#### Re-organize your tickets, build instant reports, and export it — all in a risk-free environment
We’ve learned from customer success teams that tagging is critical for turning heaps of conversations into prioritized action across the company. But it’s also _hard._ In a previous post
, we went over some of the ways things go wrong.
Today we’re announcing the first step of our solution: a tag management layer that takes the pressure off of designing a masterpiece tag taxonomy, tagging conversations perfectly as they happen, or anticipating future needs far in advance. What if you could…
- rename, merge, and split tags with a few clicks
- organize tags into groups that are understood by search and visualization
- bulk edit tagged conversations based on search or AI suggestions — or even enable full auto-tagging on a tag-by-tag basis
- … all in a safe sandbox where you can’t accidentally corrupt your source data
Our goal is for Frame AI's tag management layer to change the way you think about tagging, reporting, and acting on your conversations — turning an impossible chore into the place where you feel you can leverage all of your hard work communicating with customers to solve bigger problems.
A simple, powerful UI for renaming, merging, grouping, and hidingtags
Here’s how we help a few common scenarios:
### 1. Modify ExistingTags
You’re staring at years of “tag debt, and that new schema you dreamed up 14 months ago still hasn’t been implemented. If only you could freeze time, update all your data, and ask your reps to perfectly tag everything going forward!
Rename tags and merge similar tags together. Hide tags that are irrelevant for current reporting. Or hide all your tags, create a new schema, and bulk-edit your historical data to apply them.
### 2. Organize Tags IntoGroups
Within your existing tag hierarchy, you use a broad “catch-all” tag, like “Product,” followed by sub-tags that specify which product it’s about. This adds noise to your tag-specific reporting.
Create a group called “Product,” put all the sub-tags into it, and hide the catch-all “Product” tag from reports. As a bonus, you can search on groups of tags with the syntax
and use groups to interact with visualizations, making it easier to explore your data and create exact reporting views.
### 3. Bulk Edit / AutoTag
You’ve found a bunch of conversations that weren’t tagged properly but are now closed/resolved, so you export everything to a spreadsheet and re-tag it manually.
Quickly highlight one to 100,000 conversations and apply or remove the desired tag(s). You can find these conversations manually or with Frame’s neural tagging help, which will suggest conversations that look like they match a particular tag. (It only takes about 20 tagged conversations for a tag’s neural model to become helpful.)
For ultimate assistance, turn on auto-tagging for a given tag, and let Frame AI automatically find and update matching conversations as they arrive.
### 4. Create NewTags
You or your boss has come up with something new they want to have lots of information about. If only you had been tagging the conversations this way all along!
In Frame AI, create a new tag, then bulk edit any set of conversations you can find as described above. Once you’ve tagged a few, turn on a neural model and let Frame find more similar conversations to bulk edit. With a few minutes, you’ve conducted a research effort that can become a permanent part of your process or undone easily by deleting the tag.