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Case StudyE-CommerceTicket Routing

From Manual to AI: Ticket Routing in E-Commerce

Learn how a e-commerce company used Arahi AI to automate ticket routing, achieving 99.5% faster faster average routing time and 32% increase in customer satisfaction.

Company Profile

Company Type

Multi-channel ecommerce retailer

Team Size

15-60 employees

Industry

E-Commerce

Key Challenge

Struggling with inefficient manual ticket routing processes that were slowing growth and increasing operational costs. Their primary concern was customer lifetime value.

Tools Connected

ShopifyStripeShipStationMailchimpGoogle Analytics
Setup Time90 minutes
Agents Deployed4 AI agents

The Challenge

Manual ticket routing was the biggest bottleneck in this multi-channel ecommerce retailer's operations. Their team of 15-60 employees processed hundreds of ticket routing requests weekly, each requiring multiple steps, cross-referencing against e-commerce-specific requirements, and coordination between departments. The average ticket routing request took 45 minutes to complete manually, and the backlog was growing by 15% each quarter.

Beyond the time drain, the quality of their ticket routing output was inconsistent. Different team members followed different procedures, and there was no standardized way to handle edge cases that are common in e-commerce. A recent audit revealed that 12% of completed ticket routing records contained errors that required rework — costing the organization an additional $50K annually in correction and remediation efforts. The leadership team recognized that continuing to throw people at the problem wasn't viable and began searching for an AI-powered solution.

The Solution

Arahi AI provided the automation backbone this e-commerce team needed. They deployed a multi-agent workflow that breaks the ticket routing process into discrete, automated steps — each handled by a specialized AI agent. The first agent monitors triggers from Shopify and Mailchimp. The second agent analyzes and processes incoming requests using e-commerce-specific business logic. The third agent executes actions across connected tools and notifies team members via Zendesk.

The beauty of the no-code approach was speed of implementation. The team had their first agent live within 90 minutes, and the full ticket routing workflow was operational within a single afternoon. They used Arahi AI's template for e-commerce ticket routing as a starting point, customized the business rules to match their specific process, and connected their existing tool stack without writing a single line of code. Within the first week, the agents had processed over 200 ticket routing instances with 99%+ accuracy — more than the team typically handled in a month.

The Results

Measurable improvements across key e-commerce ticket routing metrics.

Average Routing Time

99.5% faster

Before

34 minutes

After

< 10 seconds

First-Contact Resolution

62% improvement

Before

42%

After

68%

Misrouted Tickets

87% reduction

Before

23%

After

3%

Customer Satisfaction

32% increase

Before

3.4/5

After

4.5/5

Support Cost per Ticket

59% savings

Before

$22

After

$9

What impressed me most was the setup speed. I expected a months-long implementation, but we had AI agents handling our e-commerce ticket routing workflow within a single afternoon. The no-code approach meant our team could configure everything themselves without waiting on IT.

Director of Business Operations

Multi-channel ecommerce retailer

Key Takeaways

The most important lessons from this e-commerce ticket routing automation project.

This e-commerce team proved that ticket routing automation doesn't require technical expertise — the no-code platform made it accessible to business users.

Scaling ticket routing capacity by 10x without adding headcount fundamentally changed the economics of their e-commerce operations.

Consistent AI-powered processing eliminated the quality variance that came with different team members handling ticket routing differently.

Real-time visibility into ticket routing metrics gave leadership the data they needed to make better strategic decisions.

Implementation Timeline

From zero to production in 90 minutes — here's how they did it.

Step 1: Mapped the existing ticket routing workflow

Documented every step of the current manual ticket routing process, including decision points, exceptions, and handoffs between team members. Identified which steps could be fully automated versus those needing human oversight.

Step 2: Built the automation in Arahi AI

Used Arahi AI's no-code builder to create the ticket routing workflow: connected Shopify and ShipStation as data sources, configured AI decision logic for e-commerce-specific requirements, and set up automated actions and notifications.

Step 3: Parallel run with manual process

Ran the AI agents alongside the manual process for one week to compare outputs. The AI matched or exceeded human accuracy on 98% of ticket routing instances, with the 2% of edge cases automatically flagged for human review.

Setup Time

90 minutes

AI Agents

4 AI agents

Tools Connected

5 integrations

Frequently Asked Questions

Common questions about automating ticket routing in e-commerce.

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This case study represents a typical customer scenario. Individual results may vary.