Using Regal Events in Reporting
A blueprint for building your reporting data model off of Regal events
In order to build reports and analytics off of Regal's real-time reporting events, you can use the data model we've built to power our In-App Reporting Dashboards as a blue print.
This table describes which raw events roll up into which reporting tables and what types of metrics or reports you can power off of them.
| Regal Events | Tables | Table Descriptions | Example Metrics / Analysis |
|---|---|---|---|
| agent.activity.updated | Agent Activity | - Unique record for each Agent activity period with dimensional columns like agent_email, activity_name, and start and end timestamps. - Composite primary key of agent_name and start_timestamp | - Total and avg. time spent in each activity by agent - Can join to Aggregated Tasks table for tasks completed per available agent hour |
| task.created task.canceled call.completed call.recording.available sms.conversation.completed task.reservation.accepted | Aggregated Tasks | - Unique record for each task with dimensional columns like task id, disposition, recording link, handling_agent, etc. as well as lifecycle timestamps - created_at, canceled_at, completed_at, etc. - Unique identifier = Task Id | - Completed tasks per day - Inbound answer rates - Outbound answer rate and connect rate (based on agent disposition and/or call duration) - Completed Tasks by disposition - Avg talk and handle time |
| task.reservation.created task.reservation.accepted | Reservations | - Unique record for each reservation - Unique identifier = reservation_id | - Reservation acceptance rate by Agent - Speed to accept reservations - Avg. number of reservations per task to get it accepted |
| contact.created contact.subscribed contact.unsubscribed | - Aggregated Contacts - User Rollup | - Aggregated Contacts - single record for each contact that includes dimensional data (“what we know about who the user is”) - User Rollup - single record for each contact that includes activity metrics and flags (“we know what the user has done”) - Unique identifier = contact_phone | - Count of contacts created by day - Count of contacts by source - % of contacts subscribed - Cohort analyses - Can join to Aggregated Tasks to get “speed to lead” metrics |
| scheduled.callback.requested | Scheduled Callback Requests | - Unique record for each scheduled callback requests joined to the scheduled callback task created from that request - Composite primary key of agent_email and created_at | - Count of scheduled callback requests by agent by hour of day - % of scheduled callback requests completed by the scheduling agent |
| sms.received sms.sent sms.undelivered | Messages | - Unique record for each SMS sent or received - Dimensional data such as the direction (inbound/outbound), automated vs. manual, the number the sms is sent from and to, the content of the message, and the associated campaign (if applicable) - Primary key = message_id | - Count of sms sent by campaign by day - SMS delivery rate - SMS response rate by campaign |
| contact.experiment.assigned | Experiment Assigned Events | Record for each assignment | Conversion rate by experiment variant |
| Track events sent to Regal | Important Events | - Subset of track events that represent lifecycle/funnel milestones e.g., Lead Created, Lead Converted, Lead Canceled Subscription (the events are tagged and unique to each brand) - Composite primary key of event_name and created_at | - Can join to aggregated contacts and aggregated tasks to get % of conversations that lead to a conversion, % of leads who convert |
Updated 7 months ago