Case Study: How Substack resolves 90%+ of support inquiries with Decagon
Key results
The challenge
Substack's support team handled a high volume of repetitive Tier 1 requests, such as cancellations and email imports, managing each conversation manually. An in-house chatbot addressed response management but lacked segmentation, user analytics, and Voice-of-Customer insight.
The solution
Substack deployed Decagon's AI chat agent, adding tags and custom filters for tailored support, Voice-of-Customer insights from tagged conversations, and integrations that automatically identify, track, and report feature requests and bugs.
“With Decagon's AI agents, we've shortened our time-to-resolution rate, raised and maintained a high CSAT and deflection rate, and are proactively engaging our most valuable readers and publishers.”
JAJordan A.Product Operations, Substack
The results, in context
According to the case study, Decagon's AI agent resolves more than 90% of user inquiries without human intervention. Substack reports consistently high CSAT and deflection rates and a shorter time-to-resolution while scaling support capacity without increasing team size.