In short: Auto-Moderation applies labels to new posts the moment they arrive, using rules you control, so your moderation queue starts pre-sorted.
Understanding Auto-Moderation
Auto-Moderation takes repetitive labelling off your team. Instead of a moderator labelling every post by hand, Zeal checks each new post against your rules and applies the right label straight away, so decisions stay consistent from the moment a post enters Zeal.
It's the automated half of the Moderation step in the Zeal workflow. Your rules are typically used to:
Protect trusted sellers: label your own and authorised accounts as Official Store or Legitimate, so they're never mistaken for infringers.
Label clear infringements: catch high-confidence counterfeits, impersonation and copycats.
Clear out noise: set aside posts with no brand signal, so moderators only see what matters.
Learn more: Understanding the Zeal Workflow
1. How Auto-Moderation works
Knowing how rules are applied helps you predict which label a post will get.
Rules: each rule combines one or more conditions, such as an AI image signal, a keyword or an account detail, with the label to apply.
All conditions must match: a post only gets the rule's label if it meets every condition in that rule.
Rule order: if a post matches more than one rule, the rule highest in your list wins. You can drag rules to change the order.
Default rules: every Organisation starts with default rules that identify legitimate sellers and flag counterfeit, trademark and design infringement risks. You can adjust them or add your own.
Note: Rules apply only to new, incoming posts that haven't been labelled yet. Posts already in Zeal before a rule was activated aren't moderated by it.
Learn more: Building Auto-Moderation Rules
2. Who can manage rules
Everyone can see which rules are running; only some roles can change them.
Action | Who can do it |
View rules | All users |
Create, edit, reorder or activate rules | Brand Partners and Admins |
You'll find the rules in Settings → Moderation → Auto-moderation.
3. Checking a rule's accuracy
The Rule Precision Score tells you how far you can trust a rule: of all the posts it labelled, how many did your team confirm during Review?
For example, if a rule labels 100 posts and the Quality Analyst keeps 90 of those labels, its score is 90%. To see it, open a rule with the pencil icon and select the Preview tab.
Score | Precision | What it means |
90–100% | High | Safe to rely on for automatic labelling |
70–89% | Moderate | Right 7 or 8 times out of 10; keep a human check on it |
Below 70% | Low | Needs tuning straight away; it's creating extra work |
Tip: Treat a score based on fewer than 500 reviewed posts as an early signal only. It becomes more reliable as your team reviews more of the rule's labels.
Quick reference
If you want to know… | Look at… |
Why a post got a particular label | 1. How Auto-Moderation works (rule order) |
Why older posts weren't labelled | 1. How Auto-Moderation works (new posts only) |
Whether you can change a rule | 2. Who can manage rules |
Whether a rule is accurate | 3. Checking a rule's accuracy |
How to create or reorder rules | |
Which rules to set up |