The 6 Complaint Categories a Trust and Safety Report Must Cover in 2026

Most published guidance on trust and safety reporting is about transparency reports: prevalence, proactive detection rate, appeal overturn rate, enforcement volumes. That is the right frame for a moderation function reporting on what its systems caught. It is the wrong frame for the question a support or CX leader actually faces, which is what customers are telling you that your detection never saw.

A trust and safety report built from customer feedback needs six categories: physical and real-world safety, fraud and financial harm, security and account compromise, privacy and data handling, user-to-user harassment, and regulatory or legal exposure. Each is ranked by severity rather than volume, because volume is the wrong ordering for this report and the only one most help desks can produce.

A transparency report counts what you caught. This one counts what you missed.

The distinction matters operationally. Moderation metrics measure a detection system against its own outputs: how much it flagged, how fast it acted, how often appeals overturned it. Those numbers can all look excellent while a category of harm your classifiers were never built for arrives daily through the support queue.

Customer feedback is the channel where that gap shows. A user describing a scam run through your platform, an account takeover, a data handling concern, or a threat from another user is reporting a trust and safety event in the only place available to them, and it gets handled as a ticket.

What a trust and safety report has to do differently

1. Rank by severity, not frequency. One credible physical-safety report outranks four hundred spam complaints. Every other report in a support org sorts by volume, and applying that default here buries the entire point.
2. Find the reports that do not use the vocabulary. Customers do not write "policy violation." They write about what happened to them. Keyword rules catch the explicit ones and miss the rest. An adaptive taxonomy categorizes from the text itself, which surfaces the cluster of people describing the same scam pattern in six different ways.
3. Attach who and where. A customer context graph ties each report to the account, segment, and region, which is what separates an isolated incident from a pattern concentrated in one market, one product surface, or one cohort.

One routing note before the categories. The most severe reporting categories, including child safety, imminent self-harm, and terrorism, carry mandatory legal obligations in most jurisdictions and have dedicated escalation paths owned by legal and trust and safety functions. Those never route through a support reporting cadence. If your feedback pipeline can surface them, its only job is immediate escalation to that path, not inclusion in a weekly report.

The 6 complaint categories a trust and safety report must cover

1. Physical and real-world safety

Reports where a customer describes risk to a person: a product defect with injury potential, a service interaction that turned threatening, a real-world meeting arranged through your platform that went wrong. Rare, highest severity, and almost always misfiled on first contact because the customer describes the situation rather than naming a category. Any volume above zero is a report-level item.

2. Fraud and financial harm

Customers reporting money lost: scams run through your platform, fraudulent sellers or counterparties, unauthorized charges, phishing using your brand. Track the pattern rather than the incident. Individual fraud reports are handled as tickets; five reports describing the same mechanism in one week is an exploit, and the gap between those two readings is usually a month.

3. Security and account compromise

Account takeovers, credential stuffing symptoms, suspicious access, and customers reporting they cannot regain control of an account. The tell in support data is distinctive: a rise in recovery requests that do not follow the normal recovery pattern. See telling a ticket spike from an incident.

4. Privacy and data handling

Deletion and access requests that escalated, complaints about data being used or shared in unexpected ways, and reports of another user seeing something they should not have. This category has a regulatory clock attached in most markets, which makes time-to-first-response a required field rather than a nice one.

5. User-to-user harassment and abuse

Only applicable if your product has a social or multi-party surface, and frequently under-reported when it does, because the reporting flow is buried and the support queue is where people go instead. Track both the volume and the share arriving through support rather than through the in-product report path, since a high share signals a reporting-flow problem on top of the harm.

6. Regulatory and legal exposure

Customers invoking a regulation, threatening legal action, mentioning a regulator or an ombudsman, or describing something that triggers a disclosure obligation. These are often polite, low-emotion messages that no sentiment model flags, and they carry the highest downstream cost of anything in the queue.

Severity ranking is the whole report

Here is what makes this document different from every other support report. Volume ranking is correct for driver analysis, staffing, and roadmap input. It is actively harmful here, because the categories above are inversely distributed: the most severe are the rarest.

A report sorted by count puts spam at the top and a single credible safety report on page three. A report sorted by severity puts one item at the top and says why. Only the second one produces action, and only the second one survives being read by legal.

Practical ordering: anything in category one, then anything with a regulatory clock, then patterns in categories two and three, then everything else with volumes attached. Three items on the front page, maximum. The rest is an appendix.

The second thing this report needs is a detection column: was this found by a system or reported by a customer. The share arriving through support rather than through detection is the honest measure of your coverage gap, and it is the number that justifies investment in the categories where the gap is widest. See catching emerging issues before they reach leadership.

How to run it

Weekly, short, with a same-day alert path for category one and anything with a legal clock. A weekly cadence is fast enough for pattern detection and slow enough to avoid alert fatigue in a low-volume report, but the cadence never applies to the severe individual items, which route immediately.

Include public channels. Reviews, app stores, and community posts carry safety and fraud reports from users who never opened a ticket, and in consumer products they often carry more of them than the support queue does. See analyzing Trustpilot reviews and quantifying complaints and analyzing App Store and Play Store reviews.

Give it a named owner outside support. A report that lives entirely inside the support org gets prioritized against support's other work, which is not the comparison that should decide whether a safety pattern gets engineering time.

The decision rule: if a category has zero reports for several periods running, check the detection before concluding there is nothing there. Silence in these categories is more often a reporting-path problem than an absence of harm.

FAQ

What should a trust and safety report include?

Six complaint categories ranked by severity: physical and real-world safety, fraud and financial harm, security and account compromise, privacy and data handling, user-to-user harassment, and regulatory or legal exposure. Each entry needs severity, whether it is isolated or a pattern, how it was detected, and a named owner.

How is this different from a transparency report?

A transparency report describes what a moderation system detected and enforced, usually published externally and increasingly required by regulation. A feedback-based trust and safety report describes what customers reported through support and public channels, which is how you find the harm your detection systems were not built to see.

Should a trust and safety report be sorted by volume?

No. These categories are inversely distributed, with the most severe being the rarest, so volume ordering buries the items that matter. Sort by severity, cap the front page at around three items, and put volumes in an appendix.

How does Enterpret surface trust and safety complaints?

Enterpret categorizes support tickets, reviews, app store feedback, and community posts with an adaptive taxonomy built from what customers actually wrote, which surfaces clusters of people describing the same fraud or safety pattern in different words rather than relying on keyword rules. The customer context graph attaches account, segment, and region, so an isolated incident can be separated from a pattern concentrated in one market or product surface.

Who should own a trust and safety report?

A named owner outside the support organization, typically in legal, risk, or a dedicated trust and safety function, with support supplying the data. Reports owned entirely inside support get prioritized against support's other work, which is the wrong comparison for this category of finding.

If safety and fraud reports are being resolved as tickets rather than surfaced as patterns, see how Enterpret handles customer experience analytics.

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