As a fast growing group of businesses, we really need better call analytics in order to continue using RingCentral. We need to be able to understand how many inbound calls our business receives, and an accurate percentage of calls our agents are answering live during regular business hours. As of right now, with 3 different call queues in place (1 for sales, 1 for customer service, and 1 for 'overflow' (i.e. any calls not answered on sales or customer service queues), we've been unable to get the end-to-end call information needed as a key performance indicator for our office team. From an operations standpoint, that is one inbound call journey. But with queue-based reporting, it is easy for the data to be split across multiple queues instead of being measured as one end-to-end event. Our KPI - Live Answer Rate during business hours
= unique inbound calls received during regular business hours that were answered by a live agent
÷ unique inbound calls received during regular business hours. Again, we do not need only queue activity metrics. We need a business-hours, end-to-end inbound call KPI that measures unique inbound call journeys across Sales, Customer Service, and Overflow. A single caller interaction should be counted once from first entry to final disposition, so we can accurately measure total inbound demand and live answer rate for our office team.
Shannon
supported this idea
·
As a fast growing group of businesses, we really need better call analytics in order to continue using RingCentral. We need to be able to understand how many inbound calls our business receives, and an accurate percentage of calls our agents are answering live during regular business hours. As of right now, with 3 different call queues in place (1 for sales, 1 for customer service, and 1 for 'overflow' (i.e. any calls not answered on sales or customer service queues), we've been unable to get the end-to-end call information needed as a key performance indicator for our office team. From an operations standpoint, that is one inbound call journey. But with queue-based reporting, it is easy for the data to be split across multiple queues instead of being measured as one end-to-end event. Our KPI - Live Answer Rate during business hours
= unique inbound calls received during regular business hours that were answered by a live agent
÷ unique inbound calls received during regular business hours. Again, we do not need only queue activity metrics. We need a business-hours, end-to-end inbound call KPI that measures unique inbound call journeys across Sales, Customer Service, and Overflow. A single caller interaction should be counted once from first entry to final disposition, so we can accurately measure total inbound demand and live answer rate for our office team.