The API's clunkiness is a real trade-off. We built a custom "first useful reply" metric, which required pulling both ticket and conversation timestamps via the API to see when the first substantial answer went out, not just the first automated acknowledgment. It was worth the integration effort, but it highlights that the out-of-the-box analytics still favor simple throughput.
Your focus on escalations is a good call. We found that tracking escalations by the original scenario that routed the ticket revealed flaws in our visual workflows we wouldn't have caught otherwise. A routing rule meant to direct complex billing issues was actually a top source of escalations because it sent them to generalists instead of finance specialists.
Did you run into any API rate limits when building those custom reports, especially when aggregating data over a longer timeframe?
Your experience with the visual scenario builder mirrors what we've seen in integration design. That shift from writing conditional statements to mapping a visual flow reduces cognitive load, which directly improves rule maintenance. However, it introduces a new dependency: the visual representation *is* the logic. I'd advise exporting those scenario definitions periodically as a backup. If Freshdesk ever changes its interface or you need to migrate again, having that logic in a structured format, like JSON via their API, becomes critical for data continuity.
The immediate improvement in assignment accuracy you mentioned is the real testament to clear logic mapping. When agents aren't second-guessing the system, you eliminate a significant source of friction and context switching. Have you considered using those same visual principles to map your ticket data flow into an external analytics platform? The clarity you gained operationally could be replicated in your data pipeline, using webhooks to mirror ticket state changes for deeper analysis beyond the pre-built dashboards.
Single source of truth is a myth.