Reshaping Chat Support for Our Users

This post details the product and design approach to building an in-house chat tool for support, focusing on preventing disconnections, improving agent productivity, integrating with internal systems, and routing users to specialists. It covers the MVP experiment, scaling efforts including reducing waiting time and time to reply with ML-driven suggestions and dynamic queue limits, and overall chat time reduction through visibility prompts. Key learnings emphasize starting with the end in mind, leveraging data, remote user testing, addressing root causes, and shadowing users.