Aviation & Logistics · Customer Care Analytics
Customer Care Analytics: Centralized Self-Service Insight for a Loyalty Program
Giving support teams a clearer way to analyze member issues and improve service decisions
The Client · A major US airline
Overview
A major US airline engaged Taller through a staffing partner in March 2023, with work spanning applied AI and core modernization. Taller ran six pods across AI/data and .NET/Angular rebuilds, with multi-year extensions confirmed.
The Problem
The airline’s customer-care function faced a familiar economic problem: a high volume of repetitive member inquiries that did not require an agent’s attention but used up their hours. Without a self-service option, every additional loyalty-program member translated directly into more contact-center cost.
The Solution
A four-person Taller team stood up an analytics workflow in Tibco Spotfire, a business-analytics and visualization platform, in under three weeks, centralizing customer-care data that had been scattered across separate operational systems. The team built Python and SQL pipelines against Oracle and SQL Server sources to feed normalized data into Spotfire’s analytical layer. Standing up an analytics workflow rather than a customer-facing app first was deliberate: it let the operations team validate self-service ideas before rebuilding the product surface, with the same data spine then powering the chat-based case-creation experience that reduced inbound volume.
The Impact
The analytics workflow became the data spine for the self-service and chat-based case-creation surfaces that followed, which cut agent dependency 30% across the affected categories.
