The assignment was broad, but we rose to the challenge, focusing on the following three key areas:
Customer experience management
We extracted, and rationalized structured and unstructured customer interaction data. We then mapped customer behavior across channels and functions. Applying a predictive customer satisfaction model, we studied 100% of customers' conversations as well as other channels. Then, our proprietary analytics algorithm measured the customer experience across multiple touch points and compiled the results into a customer effort score. In doing so, we discovered that web crossovers and repeat calls were the biggest problems. So we gave agents additional training to improve first call resolution and reduce call handling times. As a result, satisfaction scores improved in just four months!
Agent performance optimization
We centralized all KPIs into a single digital agent performance management platform. We then used our AI-powered automated call quality assessment tool to generate the Agent Performance Index — a single metric directly linked to cost savings and revenue enhancement opportunities. By ranking agents within and across sites, products, and teams, we identified targeted training needs.