Product Update: Introducing the Tags Dashboard
Slice and dice data from multiple chat and email systems to see how tags are being applied to all customer conversations.
Throughout the alpha preview of Frame’s intelligence hub, our Zendesk and Intercom users have consistently asked for help getting a grip on their own conversation data. We hear terms like “data black hole” a surprising amount.
What a data black hole feels like
In interviews with customers, we hear questions like:
- What other tags appear most often on conversations with this tag?
- How often are we failing to tag conversations properly?
- Which customers are asking about a particular topic?
- Which tags are becoming too much of a catch-all?
- How many hours are we actually spending on these types of requests?
- Which agents need help knowing which tags to apply?
- How often are customer questions the result of a bug?
You get the idea.
Slicing and dicing by tags
Like the other dashboards, the tags dashboard is responsive to your search query. Your search will return full transcripts and meta data about each conversation, but you can also visualize them. Here’s a search example:
On the tag dashboard, Frame dynamically subdivides the current time range into smaller units so you can see how various tags on these exchanges have been applied over time. In real terms, this can help understand how bugs, feature requests, etc. have changed over time — perhaps in line with product releases, marketing campaigns, or updates to your knowledge base.
In addition, here’s a sample of tag-specific views, including where tags co-occur with other tags, customers, and agents.
If you’re curious how your data looks in Frame, it’s easy to get started:
- Get started at frame.ai
- Sign in and create your team’s account
- Connect to your source data (e.g., Intercom, Zendesk)
- Sit back and relax while Frame backfills your historical data
