One of the largest multi-line insurers in the United States, this organization provides a comprehensive range of auto, home, life, and specialty insurance products. With over 21,000 employees and a national network of 48,000 agents, the company serves more than 10 million households across all 50 states.
Their objective: implement a structured and scalable approach to triage inbound email volume and improve customer response outcomes while laying the groundwork for broader automation opportunities across the enterprise.
To modernize operations within its Service Operations team, the insurer partnered with Ashling to explore how intelligent automation and language processing could reduce triage time, surface customer insights, and create a scalable foundation for enterprise-wide transformation.
At the outset, the Service Operations team managed four high-volume shared inboxes tied to various brands and product lines. They were manually triaging an estimated 412,000 service request related emails each year, with a portion of the volume predicted to be ongoing inquiries. Two full-time employees were solely dedicated to routing messages into Salesforce queues, with limited visibility into the nature of requests or emerging risk patterns.
The insurer’s goal was clear:
Ashling launched with a detailed discovery process, mapping the full email triage flow and applying natural language processing techniques to label, classify, and analyze inbox content.
What began as a simple automation request revealed surprising complexity. Despite the initial estimate of 412,000 annual emails for new service requests, the reality was more nuanced. Only 7% of emails (25.5K) were for new service requests, while 93% (386.5K) were ongoing conversations related to existing cases. Within those, Ashling uncovered 15–20 communication patterns strongly associated with churn risk, including dissatisfaction with rates, poor customer experience, and service cancellations.
With new visibility into customer communications, Ashling built a series of intelligent automation solutions to improve both efficiency and service quality.
To streamline the handling of email requests, Ashling introduced an automated reconciliation process. This system utilized unique identifiers, such as Exchange Message IDs, to match incoming emails with existing records in Salesforce's Service Request Management (SRM) system. Unmatched emails were flagged as new or for manual review, while matched emails were linked to existing cases with work already underway, ensuring no request was overlooked.
The team developed a classification model that accurately labeled incoming emails into 32 distinct categories. These labels were then used to automatically route service requests to the appropriate sub-queues within SRM, such as Cancellations, Coverage Questions, or Billing Inquiries. This replaced manual sorting with intelligent, rules-based automation.
For predictable requests with low complexity, Ashling implemented an automated solution to close service requests without the need for human intervention. This included setting up Management Information (MI) reporting to track the performance of these automated closures, ensuring transparency and continuous improvement.
Ashling delivered custom dashboards to monitor KPI's, volumes, response trends, and automation performance. These dashboards also helped surface new areas for automation by spotlighting recurring communication patterns.
The pilot implementation delivered immediate and measurable impact:
With the pilot a success, the insurer is now scaling these solutions across the enterprise. Service Operations is exploring new use cases with Ashling, such as routing cancellation-related inquiries straight through for automated processing using intelligent document processing (IDP).
Leadership is evaluating how inbox automation can support broader goals: reducing agent churn, improving service SLAs, and applying the same classification and insight framework across their top 25 shared inboxes.
Ashling remains a strategic partner in this journey, supporting the expansion of language-based automation, building governance frameworks, and ensuring a sustainable roadmap for transformation.
These outcomes were made possible through the application of inbox automation, natural language processing, and advanced analytics, delivered in part through UiPath Communications Mining™ and Ashling’s automation expertise.