Zendesk untagged ticket rate report: fix gaps before they distort your metrics
Every Zendesk report that slices data by tag, topic, or category inherits the same weakness: tickets without tags disappear from the analysis. A high untagged ticket rate does not just mean messy data. It means your reports are answering questions with incomplete information, and the missing tickets are usually the ones that would change the story.
This guide shows how to build an untagged ticket rate report in Zendesk, how to interpret it, and how to reduce the rate without slowing agents down. Pair it with your Zendesk tags analysis guide and support metrics dashboard so tagging quality stays visible alongside the metrics it supports.
What untagged ticket rate measures
For the metric definition, see untagged ticket rate in the glossary. In short, untagged ticket rate is the percentage of solved or closed tickets that carry no tag (or no tag from a defined taxonomy). It answers a simple question: how much of your ticket data is invisible to tag-based reporting?
An untagged rate of 5% is usually tolerable. At 20%, your tag-based reports are describing only four out of five tickets. At 40%, you are making decisions on a minority of your actual work.
Why untagged tickets matter
Tags drive the most useful downstream reports in Zendesk. When tickets are untagged, the following analyses break:
- Topic distribution — You cannot see which issues are growing if those tickets are not categorized.
- Tag-to-resolution time — Your tag-to-resolution time report only covers tagged work. If the hardest tickets are the ones agents forget to tag, your slowest topics stay hidden.
- Root cause analysis — Untagged tickets cannot be grouped into root causes, so product and engineering teams get an incomplete picture.
- Automation accuracy — If you use tags for routing or priority assignment, untagged tickets skip those rules entirely.
The risk is not just inaccuracy. It is silent inaccuracy. The dashboard looks fine because the missing data never shows up as a gap — it simply is not there.
How to build the report in Zendesk
In Zendesk Explore, the report starts with the tickets dataset and a filter for resolved tickets (Solved or Closed).
- Count all resolved tickets for the period you care about (last 7 days, 30 days, or a custom range).
- Count tickets with no tag applied. In Explore, filter where the Tags attribute is empty or null.
- Calculate the rate: untagged tickets ÷ total resolved tickets × 100.
- Break down by group to see which teams have the highest untagged rates.
- Break down by channel to see whether certain intake paths (email, chat, API) are more likely to produce untagged work.
- Add a time trend so you can track whether the rate is improving or drifting.
If your team uses a defined taxonomy (a required set of topic tags rather than free-form tags), adjust the filter to count tickets missing a taxonomy tag rather than any tag. This is stricter but more useful for reporting accuracy.
How to read the report
- High untagged rate in one group often means that group’s workflow does not prompt or require tagging. It may also mean the available tags do not match their ticket types well.
- High untagged rate on one channel usually points to an intake path that skips tagging automations. API-created tickets and some chat integrations are common offenders.
- Rising untagged rate over time suggests a process change, a new agent cohort that has not been trained on tagging, or a tag taxonomy that no longer fits the work.
- Low untagged rate overall but high rate on complex tickets means the easiest tickets get tagged (often automatically) while the harder, more ambiguous ones do not. Those are exactly the tickets you most need to categorize.
Interpret the report alongside tag coverage rate and Zendesk tags analysis to see not just whether tickets are tagged, but whether the tags themselves are useful.
How to reduce untagged ticket rate
Reducing the rate is a process problem, not a willpower problem. Asking agents to “tag more” without changing the workflow rarely works.
Automation-first approaches:
- Required fields — Make tag (or a custom topic field) mandatory before an agent can set a ticket to Solved. This is the single most effective lever.
- Auto-tagging triggers — Use Zendesk triggers to apply tags based on subject line keywords, form fields, or channel. This catches the easy cases and leaves agents to handle only the ambiguous ones.
- AI classification — If available, use Zendesk’s intelligent triage or a third-party classifier to suggest or apply tags on ticket creation. Review accuracy regularly.
Process approaches:
- Simplify the taxonomy — If agents must choose from 80 tags, they will skip the step. Aim for 10-20 top-level categories that cover 90%+ of ticket types. Nest detail under those categories if needed.
- Weekly audit — Include untagged rate in your weekly support ops review. When the rate drifts, investigate quickly rather than letting it compound.
- Onboarding — New agents produce the most untagged tickets. Include tagging expectations and the “why” behind tags in onboarding. See Agent Onboarding: Metrics to Track Progress for related onboarding metrics.
Common mistakes
- Treating all tags as equal. Free-form tags and taxonomy tags serve different purposes. Measure coverage against your defined taxonomy, not just “has any tag.”
- Requiring too many tags per ticket. One well-chosen topic tag is more valuable than three vague ones. Overloading the requirement increases friction and decreases quality.
- Celebrating low untagged rate without checking accuracy. A 2% untagged rate means nothing if agents are picking “Other” or a catch-all tag to satisfy the requirement. Pair this report with tag distribution analysis to catch junk tagging.
- Only measuring at solve time. Tickets that are merged, deleted, or suspended may also carry tagging gaps. Decide whether those matter for your reporting and adjust the denominator accordingly.
FAQ
What is a good untagged ticket rate? Below 5% is strong for most teams. Below 10% is workable. Above 20% means your tag-based reports are unreliable enough to question decisions made from them.
Should I measure untagged rate on all tickets or just solved tickets? Solved tickets are the most common denominator because those are the ones that appear in historical reports. Measuring on all tickets (including open) can help catch tagging gaps earlier but adds noise from tickets still in progress.
How does untagged rate relate to tag coverage rate? Tag coverage rate is the inverse: the percentage of tickets that do carry a tag. They measure the same thing from opposite directions. Use whichever framing resonates with your team. Most ops teams find “untagged rate” more actionable because it highlights the gap.
Can TicketBoard help track this? Yes. TicketBoard surfaces tag coverage and untagged rates alongside your other Zendesk metrics, so you can spot gaps without building custom Explore reports.