It would be very valuable if Vambe could incorporate more comprehensive reporting capabilities for managing and monitoring care teams into its roadmap for improvements.
Currently, a significant portion of these metrics requires manual collection and analysis. Having this information directly within Vambe would make it possible to measure productivity, identify operational gaps, manage workloads, and improve the quality of care.
The key metrics that would be worth incorporating are:
1. Volume and distribution of tickets
Total number of tickets handled per day.
Number of tickets handled per day and per funnel.
Volume of tickets per funnel, to identify and optimize the operational workload.
Number of inquiries/tickets received outside of business hours.
2. Tracking and Resolution
Tickets that are submitted and remain unchanged in status, particularly those that remain in “Unresolved” and do not change to “Resolved.”
Number of tickets that end the day unresolved and with no comment or action logged.
Ratio of resolved tickets to pending tickets at the end of the workday.
3. Response Times
Human response time: from the time the ticket is submitted until the first effective response from an agent.
Ideally, include averages, medians, and distribution by funnel/agent to identify deviations and opportunities for improvement.
4. Qualitative indicator of responses
It would be particularly useful to incorporate a quality indicator for human responses—potentially supported by AI—using a simple classification:
This would allow us to move beyond measuring only quantity and response times to also measuring the quality and effectiveness of customer service.
5. Recommendations for Improvement Using AI
It would be very helpful if Panda AI could analyze this data and generate recommendations for improvement, for example:
Funnel stages with high workload or higher ticket volume.
Peak demand times.
Main reasons for contact.
Tickets with longer response times.
Conversation patterns requiring multiple interactions.
Opportunities to improve responses, resolution rates, and the customer experience.
Ultimately, the opportunity would be for Vambe to evolve from a primarily operational reporting tool into a customer service management dashboard that allows users to view volume, workload, response times, service levels, resolution rates, and response quality all in one place, while also incorporating actionable recommendations powered by AI.
We believe these metrics would be highly valuable not only for monitoring operations but also for making decisions, anticipating problems, and continuously improving the customer experience.
