AI Automation Helps PlumbersSEO Slash Manual Call-Tagging Time by 70% via a Unified Analytics System

PlumbersSEO faced significant operational inefficiencies as call volumes increased across client campaigns. Manual call tagging required teams to listen to recordings and classify each interaction individually, creating a slow, labor-intensive workflow that was prone to human error. This not only reduced efficiency but also delayed the availability of actionable insights.

At the same time, the lack of a unified data system created fragmented visibility between marketing and operations teams. Without a centralized source of truth, it became difficult to accurately evaluate call quality, campaign performance, and lead conversion trends. As the agency continued to scale and onboard more clients, these limitations became increasingly restrictive, preventing the business from handling growing data volumes effectively.

Athena AI developed a fully automated call analytics platform designed to process, classify, and visualize call data in real time. The system eliminates manual intervention by automating the entire data pipeline, from audio transcription and metadata ingestion to AI-driven classification and dashboard reporting.

To ensure seamless data flow, the platform integrates multiple systems, including real-time transcription services, call metadata APIs, and cloud-based streaming infrastructure. Structured data is stored in scalable databases that support high-volume analytics while maintaining low-latency access to key insights.

Advanced AI models were implemented to classify call intent, service type, and lead quality with high accuracy. Through iterative refinement, the system achieved consistent and reliable tagging, enabling downstream analytics to be both accurate and actionable. In parallel, automated dashboards were deployed to generate client-facing reports, updating daily without manual input and providing both individual and aggregated performance visibility.