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How-To6 min read

How to Cut Your Support Ticket Volume by Up to 80%

Squid Support Team · Product · 20 February 2026

If you look at the support inbox of almost any e-commerce store, you'll find the same tickets appearing over and over again. "Where is my order?" "Can I change my delivery address?" "I'd like to return this." "Do you have this in a different size?" These questions are entirely predictable — and entirely automatable.

Start by auditing your current tickets

Before you can automate, you need to understand your ticket distribution. Pull the last 30 days of tickets and categorise them. Most stores find that 70–80% of volume falls into just four or five categories. Those are your automation targets.

  1. Order tracking & delivery status
  2. Returns, refunds, and exchanges
  3. Product questions and sizing
  4. Discount codes and promotions
  5. Payment and billing issues

Connect your e-commerce data

An AI agent that can only respond with pre-written text isn't much better than an FAQ page. The real power comes when your AI is connected to live order data, inventory, and customer records. When a customer asks where their parcel is, the AI should be able to look up the tracking number in real time and give a specific answer — not a generic one.

Squid Support integrates directly with Shopify, which means it can fetch order details, trigger refunds, apply discount codes, and update records without any manual work from your team.

Set clear escalation rules

Not every ticket should be handled by AI. Define upfront which scenarios always go to a human — complex complaints, high-value customers, situations involving potential legal issues. A good AI helpdesk makes escalation seamless rather than frustrating.

Measure, iterate, improve

Once you've automated your high-volume categories, track your resolution rate, CSAT, and average handle time weekly. You'll quickly identify where the AI needs better training data or where a human still adds more value. The best AI helpdesks get steadily more capable over time as they learn from your specific customer base.

"Teams that implement AI automation report saving an average of 12–15 hours of support work per week within the first month."

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