Automated detection triggers fire on every inbound event, routing each contact into a structured pipeline with timestamped records.
The mechanics of Opportunity Capture begin with channel mapping. Each inbound touchpoint is identified and assigned a trigger rule. For phone calls, a missed call detection webhook fires within seconds of a disconnect, sending an automated SMS and creating a CRM contact. For web forms, a submission hook pushes the data into the pipeline and sends an email acknowledgment. For chat widgets, an automated greeting initiates a qualification sequence. All of these triggers feed into a unified workflow engine that routes each contact based on source, intent, and availability. The system runs continuously without human supervision.
Without automation, each inbound channel requires a human to monitor, respond, and log the interaction. This creates inconsistency in response time, data quality, and follow-through. Automated capture replaces this with a deterministic system that performs identically at 2am on a Sunday as it does at 10am on a Monday. The difference is not incremental — it is structural.
Implementing the Opportunity Capture mechanism requires connecting each inbound channel to a workflow automation platform such as GHL (GoHighLevel), which DealLogic uses as its operational backbone. Each trigger is configured with a response template, a routing rule, and a pipeline stage assignment. Once all channels are connected, the system runs autonomously. DealLogic reviews trigger performance weekly to ensure no channel has gone dark or is experiencing routing failures.
Trigger drift is the primary mechanical risk — a trigger that was working correctly can break when underlying software updates change API behavior or field mappings. Regular automated testing of each trigger prevents silent failures from degrading capture performance.
Trigger drift is the primary mechanical risk — a trigger that was working correctly can break when underlying software updates change API behavior or field mappings. Regular automated testing of each trigger prevents silent failures from degrading capture performance.
Future capture mechanisms will incorporate AI intent classification at the point of contact, allowing the system to not only capture and route but also score and prioritize each inbound signal in real time based on behavioral and contextual data.