Magick.com Customer Service — Expert Operational Playbook

Executive overview and goals

This document presents an expert, operationally detailed playbook for Magick.com customer service as of 2025. It is written from the perspective of a customer experience consultant who has implemented/supported digital-native consumer platforms since 2016. The primary goal: deliver a measurable, repeatable support operation that targets 90% chat SLA, 24-hour email resolution for non-urgent inquiries, and a Net Promoter Score (NPS) of 50+ within 12 months.

Magick.com should treat customer service as a revenue-preserving function. Targets recommended below translate directly into retention and conversion: improving First Contact Resolution (FCR) from 60% to 75% typically reduces churn by 1–3 percentage points annually, and a 0.5 improvement in average CSAT (customer satisfaction) often raises lifetime value (LTV) by 7–12% in subscription businesses.

Channels, tools and core SLAs

Channels must be chosen for customer preference and cost efficiency. The core channel stack recommended for Magick.com includes phone, email, live chat, in-app messaging, and a self-service knowledge base. Aim for channel mix: 40% self-service, 30% live chat, 20% email, 8% phone, 2% social/direct messages. Live chat should be staffed to answer 90% of incoming chats within 30 seconds; phone calls should be answered within an average speed of answer (ASA) of 120 seconds for customers on paid plans and 300 seconds for free-tier customers.

Operational SLAs: email first response within 12–24 hours (priority email within 4 hours), chat response <30s, phone ASA <120s (priority), first-contact resolution target 70–80%, and average handle time (AHT) for live channels 6–9 minutes. Maintain a documented incident response runbook for outages with a maximum time-to-public-response of 15 minutes and customer update cadence every 30–60 minutes during major incidents.

• Recommended platform stack (2025): Zendesk or Freshdesk for ticketing, Intercom or LiveChat for messaging, Aircall or Twilio for telephony, and a knowledge base on Readme or Help Scout. Integrate with product analytics (Segment, Amplitude) and CRM (HubSpot) for context-rich tickets.
• Security and compliance: store transcripts for 12 months minimum, encrypt data in transit and at rest; follow GDPR/CCPA rules—collect only necessary PII and provide deletion pathways within 30 days of request.

Staffing model, training and costs

Headcount planning: start with a one-year staffing plan sized to expected ticket volume. Baseline assumption: 100,000 active users = ~1,200 monthly tickets (industry average 1.2% contact rate). That equates to roughly 6–8 full-time agents to maintain the SLAs above (assuming 1 agent handles ~200 tickets/month across channels plus chat coverage). For product launches or marketing spikes budget an additional 25–40% temporary capacity.

Cost considerations: average agent fully-loaded cost (US-based) is $45,000–$65,000/year including benefits and tools; offshore or nearshore options typically reduce fully-loaded cost to $18,000–$30,000/year but require more supervision. For planning, assume $55k/agent/year for onshore and $24k/agent/year for offshore. Add $15–20/user/month for SaaS tools and telephony at scale (or a $5k–$20k/year platform license depending on vendor).

Training, quality assurance and knowledge management

Initial training program should be 2–3 weeks: 40% product immersion, 20% policy and escalation, 20% tool and workflow practice, 20% shadowing and role-play. Create certification checklists and require 2 weeks of monitored live support before an agent handles tickets independently. Expect ramp time of 6–8 weeks to reach full productivity.

Quality goals: QA scorecards with at least 12 criteria, evaluated weekly; target QA pass rate 85% for active agents and improvement of +10% in underperformers within 30 days. Knowledge base should be maintained with versioned articles, a 90-day review cadence, and analytics to track containment rate—aim for 60–70% containment via self-service within 9–12 months of launching the KB.

Pricing tiers, support entitlements and contact information templates

Tie support entitlements to pricing tiers to protect agent time and incentivize upgrades. Example pricing architecture: Free tier (limited KB + community), Pro $9.99/month (email + chat with 24h SLA), Premium $49.99/month (priority chat + 120s phone + 4h incident response), Enterprise custom (SLA, dedicated CSM, 24/7 support). Clearly list SLA differences on pricing pages and in billing emails to reduce disputes.

Public-facing contact templates to publish on magick.com/support and in-app:
Support phone (priority line): +1 (800) 555-0123
General line: +1 (503) 555-0199
Support email: [email protected]
Status page: https://status.magick.com
Headquarters (example): 123 Arcane Way, Suite 400, Portland, OR 97205
These templates should be configurable and replicated into auto-responders that cite expected SLAs and ticket IDs to set customer expectations immediately.

Escalations, metrics and continuous improvement

Create a clear 3-tier escalation matrix: Tier 1 (agents) resolves 70–80% issues; Tier 2 (product specialists, available 09:00–18:00 local) handles complex cases and fines; Tier 3 (engineering/CTO on call) triggers for outages and PII incidents. Define escalation thresholds: any P1 outage escalated within 15 minutes and handled with a 30-minute on-call response time.

Key metrics to track weekly and monthly: CSAT (target 4.5/5), NPS (target 50), FCR (target 75%), AHT (6–9 minutes), SLA compliance (90%+ for chat), ticket backlog (0–2% of daily inflow). Run quarterly business reviews with product and marketing to resolve systemic issues; allocate 20% of QA findings to product backlog items each quarter.

Implementation roadmap (90–180 days)

Phase 1 (0–30 days): establish tooling, contact templates, and basic KB; hire 2–3 core agents; publish support pages and SLAs. Phase 2 (30–90 days): optimize channel routing, launch proactive messaging and self-service drives, implement QA scorecards and training cadence. Phase 3 (90–180 days): scale to full staffing levels, introduce enterprise SLAs, and begin regular R&D/feedback loops tied to product metrics.

By following these specifics—SLAs, staffing ratios, pricing entitlements, escalation procedures, and measurable KPIs—Magick.com can build reliable, scalable customer service that reduces churn, improves conversion, and supports sustainable growth. For a custom operational plan, running a 4–6 week audit of existing volume and backlog will refine the numbers above to your exact traffic and product mix.