Transforming Customer Interactions with Smart Email Scoring

Date:

April 14, 2025

Client:

Category:

Results & Impact

The system analyzed 50,000+ emails, delivering comprehensive coverage and actionable analytics.

Key results included:

  • 20% increase in customer satisfaction scores through higher-quality, standardized communications.
  • 25–30% reduction in training costs and QA effort via automated scoring and coaching insights.
  • Real-time guidance for agents, resulting in measurable improvements in consistency and efficiency.
  • A future-ready support model that enables continuous learning and performance refinement.
With Digile’s Gen-AI solution, the client transformed its enquiry management into a faster, smarter, and more scalable system - driving both customer experience and operational efficiency.

Challenge

This premier Banking & Insurance company needed to improve the quality and consistency of its customer email support. Manual review processes were slow, inconsistent, and resource-intensive - leading to variability in service quality and higher QA costs. Training agents and maintaining performance standards at scale was becoming increasingly difficult, and customer satisfaction scores reflected the gaps. The organization sought an AI-driven solution to automate email evaluation, enhance support interactions, and enable continuous improvement.

Solution

Digile deployed a Gen-AI powered smart email scoring system built on Microsoft Azure, Python, and LangChain.

The solution included:
  • AI-driven scoring system trained on historical emails and communication guidelines.
  • Automated quality checks with SLA and compliance alignment for accurate tracking.
  • Integration with internal knowledge systems to dynamically update and refine evaluation guidelines.
  • Real-time feedback and analytics, providing instant scoring insights and trend reports to address quality gaps.

This AI-powered approach reduced manual effort, improved consistency, and provided actionable insights to uplift service quality across the support function.

Technology Used

The following technologies were utilized in the managed services and integration solution:

  1. Microsoft Azure
  2. Python
  3. Qdrant
  4. Langchain
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