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Est. read: 2 minTikTok

TikTok Shop Adjusts Late Dispatch Rate Calculation Standards

TikTok Shop is adjusting the calculation logic for its late dispatch rate. A transition period will begin on June 15, with formal violation assessments and shop operations enforcement starting in July.

What are the key facts?

  1. 1Transition period begins June 15, 2026
  2. 2Formal enforcement begins in July 2026
  3. 3Late dispatch rate calculation standards updated

What happened?

TikTok Shop is updating the calculation formula and assessment standards for its late dispatch rate, or LDR, with the goal of improving buyers' expectations for delivery times. The new rules will enter a transition buffer period on June 15, 2026, and formal violation assessments and enforcement will begin in July. The revised calculation method will place greater focus on the timeliness of order processing by sellers and logistics handover, and will link the relevant fulfillment results to shop benefits management. The policy applies to cross-border and local sellers. The platform will use the updated LDR standards to assess whether orders have been dispatched as required. The changes cover the LDR calculation logic, transition arrangements, and subsequent assessment and enforcement. Sellers need to interpret order dispatch and logistics handover points according to the platform's new standards.

What does this mean for cross-border sellers?

The new LDR methodology means sellers must treat dispatch, carrier pickup, and logistics handover as one continuous fulfillment chain rather than focusing only on whether dispatch was marked in the backend. A common mistake is assuming the risk ends when the warehouse ships the order; delays at later checkpoints may still affect shop assessments. The highest-priority action is to check, order by order, the time of warehouse dispatch against the first logistics scan this week and identify the most common delay point.

Source: TikTok

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Compiled by the Niceggie editorial team from public reporting; translation and summary are AI-assisted.

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