ThinkWithPrompt by SynotticThinkWithPrompt

Write a service level policy for our support team

Clear response and resolution targets by priority and channel, with priority definitions and what happens when a target is missed.

Customer SupportFew-ShotStandardLegalWriteFill-in Template

The prompt

Help me write a service level policy for our support team. Channels and hours: [e.g. email 24/7, chat 9-6 ET weekdays, phone for enterprise only] Customer tiers: [e.g. free, standard, premium, enterprise] Current actual performance: [median first response and resolution times by channel] Contractual commitments: [ANY SLAs in customer contracts] Team size and coverage: [DETAILS] Business priorities: [e.g. "protect enterprise renewals", "keep costs flat"] Draft: 1. Priority definitions (e.g. P1 to P4) based on impact and urgency, with 2 concrete examples each, so agents classify consistently. 2. A target table: Priority x Tier x Channel with first response time, next response time, and target resolution or update frequency. Note business hours vs. calendar hours. 3. Rules: when the clock starts, pauses (e.g. waiting on customer), and stops. 4. Escalation when a target is about to be missed and when it is missed. 5. How we'll measure and report compliance (percentage within target, not averages). 6. A short customer-facing version. Rules: targets must be achievable with my current performance and staffing; flag any target that looks unrealistic based on what I shared. Don't copy contractual SLAs into the internal policy without marking them [CONTRACTUAL - CONFIRM WITH LEGAL].

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • e.g. free, standard, premium, enterprise
  • median first response and resolution times by channel
  • ANY SLAs in customer contracts
  • DETAILS
  • e.g. "protect enterprise renewals", "keep costs flat"
  • CONTRACTUAL - CONFIRM WITH LEGAL

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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