How We Automated 81% of E-commerce Support Requests With AI
A fast-growing e-commerce company was handling thousands of repetitive customer questions every month across email, live chat, and order support. We designed an AI-powered support system that connected their help desk, Shopify store, internal knowledge base, and fulfillment data. Within eight weeks, 81% of routine requests were resolved automatically while the support team gained more time to focus on high-value customer conversations.
Industry
Company
Founded
Engagement
81%
Support requests automated
12K+
Tasks run monthly
42 sec
Average response time
120 hrs/mo
Team capacity recovered
Challenge
Repetitive requests were overwhelming the support team
As order volume grew, the team spent most of its time answering the same questions about deliveries, returns, refunds, product availability, and order changes. Response times slowed during peak periods, while hiring more agents offered only a temporary solution. The challenge was to reduce repetitive work without sacrificing a helpful, human customer experience.
Our Approach
Customer growth was outpacing the support team
As order volume increased, the support team found itself answering the same questions hundreds of times each week. Customers wanted updates on deliveries, returns, refunds, product availability, and order changes—often across multiple channels. The team was spending most of its day on repetitive requests instead of complex issues that genuinely needed human attention. Response times began to increase during peak periods, and hiring more agents would only solve the problem temporarily. The goal was clear: reduce repetitive support work without creating a frustrating, robotic customer experience.
1
Audit the support workload
We reviewed recent support conversations and categorized requests by frequency, complexity, and automation potential. Order status, return eligibility, delivery questions, and product information represented the largest opportunity.
2
Connect customer and order data
The automation layer was connected to the company’s storefront, help desk, fulfillment system, and internal support documentation. This allowed responses to use current customer and order information instead of generic answers.
3
Automate high-volume requests
We created workflows for common support scenarios including order tracking, return instructions, address-change requests, refund updates, and frequently asked product questions.
Solution
An AI support system that can answer, act, and escalate
The final system operates as an intelligent layer between incoming customer requests and the existing support team. When a message arrives, the system identifies the customer’s intent, retrieves the information required to resolve the request, and determines whether the issue can be handled automatically. For routine questions, customers receive an immediate personalized response using live order and account data. When an issue requires human judgment, the conversation is passed to an agent together with a summary, customer details, and suggested next action. This reduced repetitive work while keeping the support team in control of sensitive or complex conversations.
Results
Faster support without adding headcount
Within eight weeks of deployment, automation had become the first line of support for the company’s highest-volume request types. Customers received answers faster, routine tickets stopped filling agent queues, and the support team recovered more than 120 hours of capacity each month. Most importantly, the company was able to support continued order growth without expanding the team at the same rate.
of routine customer support requests resolved automatically
average response time for automated support conversations
customer support tasks processed by the system every month
of support team capacity recovered each month
We automated repetitive support without losing the human touch. Customers get faster answers, and our team has more time for complex conversations.
James Reynolds
Founder
North & Pine
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