An IT support firm slashed response times in half and boosted customer satisfaction by automating ticket triage and client updates with Make and ChatGPT. Workflow automation now handles 80% of routine tickets, freeing agents for complex cases.

By integrating Make’s automation platform with ChatGPT for intelligent ticket handling and client communication, Flow Genius helped this IT company streamline support operations. The result: faster ticket assignment, instant client updates, and measurable gains in efficiency and customer experience.

The Challenge

Manual ticket triage and client communication were bottlenecks for this 30-person IT support company. Incoming support tickets arrived via email and web forms, but assigning them to the right technician was slow and inconsistent. Agents spent up to 4 minutes per ticket just categorizing and forwarding requests.

Clients were often left waiting for status updates, leading to frustration and lower satisfaction scores. With over 1,000 tickets per month, the team struggled to keep up—response times averaged 2 hours, and customer satisfaction hovered at 78%.

The Solution

Flow Genius designed an automated workflow using Make (formerly Integromat) and ChatGPT. Make handled ticket intake, categorization, and assignment, while ChatGPT generated real-time client updates and suggested solutions for common issues.

This workflow automation ensured each ticket was routed to the right technician within seconds. ChatGPT’s AI integration provided personalized, professional updates to clients, reducing uncertainty and improving communication.

Implementation Steps

1. Integrated ticketing system (Zendesk) with Make to monitor new tickets in real time. 2. Built rules in Make to analyze ticket subject and content, assigning priority and category. 3. Used ChatGPT to draft instant client acknowledgement emails and status updates. 4. Automatically assigned tickets to the right technician based on skill set and workload. 5. Scheduled follow-up messages via ChatGPT, keeping clients informed at each stage. 6. Tracked ticket progress and escalated unresolved cases automatically after set timeframes. 7. Gathered feedback from clients via automated post-resolution surveys.

Results

Response times dropped by 50%, from 2 hours to under 1 hour on average. Over 80% of routine tickets were triaged and assigned without human intervention. Customer satisfaction scores rose from 78% to 91% within three months.

The IT support team saved an estimated 65 hours per month previously spent on manual triage and communication. According to McKinsey (2024), companies adopting workflow automation see up to 30% productivity gains—this firm’s experience matched those findings. Additionally, a Zendesk benchmark report (2024) found that faster response times directly correlate with higher customer loyalty, which was reflected in the company’s improved retention rates.

Key Takeaways + CTA

Automating ticket triage and client communication with Make and ChatGPT delivers measurable efficiency and happier clients. AI integration reduces manual work, speeds up response times, and ensures consistent updates. Workflow automation is accessible for IT support firms of any size. Ready to cut response times and delight your clients? Contact Flow Genius to see how workflow automation and AI integration can transform your support operations: https://flowgenius.ai

FAQ

How does Make automate ticket triage? Make connects to your ticketing system, analyzes incoming tickets, and routes them to the right technician based on predefined rules—no manual sorting needed.

Can ChatGPT handle client communication securely? Yes, ChatGPT can generate secure, professional updates without accessing sensitive client data, ensuring compliance and privacy.

What if a ticket is too complex for automation? The system flags complex or unusual tickets for human review, so your team always handles critical cases directly.

How quickly can my IT support team implement this solution? Most teams can deploy a tailored workflow automation with Flow Genius in 2–4 weeks, depending on existing systems and requirements.