Driving Utility CX Through Metrics, Insights, and Technology

‍‍Turning customer data, journey insights, and emerging technologies into actionable strategies for utility customer experience

E Source has a mission is to help utilities make and implement better data-driven decisions that positively impact their customers, their bottom line, and the planet.

Project Snapshot

Role: CX Insights & Strategy Analyst, E Source
Scope: Assisted multiple utility clients in improving customer experience by:

  • Analyzing key CX metrics (CES, FCR, VOC)
  • Designing self-service journeys to deflect calls
  • Identifying non-survey-based methods to capture VOC
  • Exploring AI tools like ChatGPT for internal and customer service applications

Outcome: Increased self-service adoption, improved first-contact resolution, captured richer customer insights, and recommended AI integration strategies — all while reducing operational costs and enhancing satisfaction

The Challenge

Utilities face several CX obstacles:

  1. High contact center volume — live calls are expensive, and customers want faster solutions.
  2. Declining survey participation — traditional VOC methods are becoming less effective.
  3. Complex customer journeys — multiple touchpoints, from billing to service requests, often create friction.
  4. Emerging AI integration — utilities need guidance on safely adopting AI while maintaining accuracy and trust.

The Approach

‍1. Call Deflection & Self-Service Optimization

  • Analyzed CES and FCR to identify high-effort interactions.
  • Designed self-service flows (bill payments, reporting outages, start/transfer service).
  • Implemented strategies to promote high-bill alerts and chatbots (e.g., Watt at Con Edison).
  • Used data and journey mapping to identify bottlenecks and reduce repeat calls.
Self‑service flows and proactive tools like high‑bill alerts and chatbots reduced effort and repeat calls.

2. Capturing VOC Without Surveys

  • Leveraged employee CX councils to surface trends from front-line staff.
  • Used speech analytics and natural language processing on call transcripts to detect pain points and self-service opportunities.
  • Monitored social media, online reviews, and community platforms like Nextdoor.
  • Supported qualitative programs such as customer panels and video testimonials.
Expanded VOC insights by combining employee councils, speech analytics, social listening, and qualitative panels

3. Exploring AI (ChatGPT & LLMs) for Utility Operations

  • Identified internal applications first: enabling CSRs, field-service staff, and content teams.
  • Recommended AI for automating repetitive tasks, summarizing call transcripts, generating internal content, and supporting social media/email campaigns.
  • Emphasized the importance of controlled, internal knowledge training to minimize hallucinations and inaccuracies.
  • Proposed phased rollout: internal adoption → monitored customer-facing tools, only when AI outputs can be trusted.
Phased AI adoption framework prioritized safe internal applications before expanding to customer‑facing tools.

Solution

Deliverables / Outputs

Impact

  • Reduced call center volume: Optimized self-service options and high-bill alert programs deflected thousands of calls
  • Improved FCR and CES: Data-driven insights enabled smoother first-contact resolution
  • Enhanced VOC capture: Utilities gained richer understanding of customer pain points despite survey fatigue
  • Early AI adoption guidance: Structured approach for safely leveraging ChatGPT internally, boosting employee productivity without risking misinformation

Key Skills Demonstrated

  • CX metrics analysis (CES, FCR, VOC)
  • Customer journey mapping and self-service design
  • Non-survey VOC capture methods (employee councils, speech analytics, social monitoring, qualitative programs)
  • AI strategy and risk mitigation for utility operations
  • Cross-departmental collaboration and actionable reporting