AI Customer Support Agent
Tier-1 support handled automatically with CRM context — so human agents focus on complex cases, not repeat questions.
- Industry
- E-commerce
- Location
- Australia
- Timeline
- 12 weeks
By the numbers
- <5 min
- First response on 60% of tickets
- 24h → minutes
- Tier-1 response time
- 3x
- Ticket volume absorbed without new headcount
- 60%
- Of tickets resolved at tier-1 by the agent
The problem
A fast-growing e-commerce brand saw support ticket volume triple after a product launch, but the support team stayed the same size. First-response times stretched past 24 hours. Agents spent most of their day answering the same order status, return policy, and shipping questions. Customer satisfaction scores dropped, refund requests increased, and the team had no bandwidth for escalations that actually needed a human. A basic chatbot had been tried but could not look up orders or update the CRM.
What we built
We built an AI customer support agent connected to order data, the helpdesk, and CRM. It handles tier-1 inquiries — order tracking, return eligibility, policy questions — with real account context, escalates edge cases to humans with full conversation history, and logs every interaction for quality review. Agents get a focused queue of cases that need judgment, not repetition.
Our approach
- Analyzed 3 months of ticket data to identify the top 20 repeatable question types
- Connected order lookup, returns policy rules, and CRM customer history
- Built agent with guardrails — no refunds or account changes without human approval
- Ran parallel mode alongside human agents before customer-facing rollout
- Set up analytics dashboard for resolution rate, escalation reasons, and CSAT impact
Results & outcomes
- First-response time under 5 minutes for 60% of incoming tickets
- Tier-1 resolution rate of 45% without human intervention
- Support team capacity freed for complex escalations and VIP customers
- CSAT recovered to pre-growth levels within 6 weeks of launch
- 24/7 coverage without overnight staffing costs
<5 min response time
Analysis
The constraint was a 3x rise in tickets against flat headcount, so the goal was never to replace agents — it was to absorb the repetitive 60% so humans could focus on the complex 40%. Grounding the agent in real order and CRM data, rather than a generic FAQ bot, is what made instant answers trustworthy enough to send unattended at tier-1. Response time dropping from 24 hours to minutes also reduces volume upstream: most "where is my order" anxiety disappears when the answer is immediate, which quietly prevents follow-up tickets.