Quality Control

the quality control (qc) module is designed for platforms that rely on multiple moderators, enabling the continuous assessment and improvement of your team’s performance the module ensures constant feedback, tracks performance, and is critical for maintaining consistent, high quality moderation decisions at scale key features the qc process revolves around three core components sampling strategy a method to pull flags for review based on predefined criteria, ensuring the audit process is unbiased and representative audit by qc experts moderators' original decisions are anonymously reviewed by specialized qc experts to determine accuracy quality control score the outcome of each audit session produces a measurable score, used for performance tracking, moderator coaching, and identifying training needs sampling strategy the sampling strategy defines the criteria for which flags are pulled for review sampling rule configuration qc admins define rules for each queue, specifying parameters like the timeframe, content type distribution (e g , 40% approved, 60% rejected), and which moderators' decisions should be sampled default rules are provided for immediate functionality sampling rule preview a feature that allows qc admins to validate their configuration by viewing the expected outcome (number of flags, content type distribution, moderators involved) before applying the rule qc queue a dedicated subset of a moderation queue that contains sampled flags there is a 1 to 1 relationship between a moderation queue and its corresponding qc queue process flow setup qc admins define and finalize the sampling strategy for a specific queue session start a qc expert starts a qc session the system fetches flags based on the defined sampling rule and pulls them into the qc queue qc experts can pull flags into the queue at any time for flexibility quality control review qc experts review the cases in the qc queue crucially, the original moderator’s decision is hidden during this review to maintain anonymity and prevent bias the system also prevents multiple qc experts from reviewing the same flag simultaneously scoring and reporting a score is generated based on the matches and mismatches between the expert's decision and the original moderator's decision this score is updated dynamically and displayed in real time for performance tracking reports are generated for management to evaluate overall policy effectiveness and identify training needs user roles and permissions qc expert start qc sessions review sampled flags and provide feedback cannot configure or update sampling rules qc admin configure and update sampling rules start qc sessions access all qc queues