What it means
Resolution rate tells you how much of your incoming support volume is actually getting closed — a low rate signals backlog buildup, unresolved customer issues, or agents marking tickets 'pending' instead of closing them.
Resolution rate = (tickets resolved in period ÷ tickets received in period) × 100. In practice, the calculation depends on how your team defines "resolved" — closed by the agent, confirmed by the customer, or automatically closed after a period of no response. In ecommerce support, resolution rate is closely tied to ticket complexity. Order-status and tracking questions have near-100% resolution rates because the answer is definitive. Escalated complaints, damaged-goods claims, or fraud disputes may sit open for days while awaiting merchant action, pulling the overall rate down. A healthy resolution rate for a Shopify store is typically 85–95% within the same business day for AI-handled tickets, and 90%+ within SLA for human-handled ones. A rate below 80% usually points to backlog, under-staffing, or unclear ownership of complex tickets.
Why it matters
Unresolved tickets represent customers still waiting for help. Low resolution rates erode CSAT and trust, and they create a growing backlog that compounds during peak periods like BFCM. Tracking resolution rate separately for AI-resolved and human-resolved tickets helps pinpoint where the bottleneck lives.
Related concepts, explained
These terms are part of the same idea, so they live here rather than on pages of their own.
Automated Resolution Rate
Automated resolution rate is the percentage of incoming support tickets that are fully resolved by an AI agent or automated workflow — with no human agent involvement at any point in the conversation.
Automated resolution rate = (tickets closed by AI or automation ÷ total tickets received) × 100. Unlike deflection rate, which captures issues resolved before a ticket is created, automated resolution rate counts only tickets that entered the system and were then closed by automation without human intervention. For Shopify stores, automated resolution concentrates in a predictable set of intents: order tracking, estimated delivery, return eligibility checks, refund status, product availability, and basic policy questions. These intents typically make up 50–70% of total volume, which is why top-performing AI deployments achieve automated resolution rates in the 40–65% range. The metric is distinct from deflection rate and containment rate, though the three are related. A ticket that was deflected (never submitted) doesn't count toward automated resolution rate — it was never in the queue. Automated resolution rate strictly measures what the AI closed once the ticket was open.
Automated resolution rate sets the ceiling on how efficiently a support team can operate. A store with 10,000 monthly tickets and a 60% automated resolution rate only needs human agents to handle 4,000. That's a structural cost reduction — not dependent on agent speed or scheduling — that compounds as the store grows.
How Bookbag helps
AI closes the loop automatically
When Bookbag's AI resolves a question, it closes the ticket immediately — no manual step required — keeping resolution rate high without agent effort.
Resolution analytics by topic
Bookbag breaks down resolution rates by ticket category so you can see exactly which question types are getting closed and which are stalling.
Auto-close on no reply
Tickets that customers don't respond to after resolution can be automatically closed on a schedule you set, preventing artificial backlog.
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Guides & benchmarks
Frequently Asked Questions
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