A complaint-reduction juggernaut for a financial services major

If the customer is always right, this financial services firm was almost always wrong. Clients were bombarding the firm with criticism, especially about its co-branded credit card business. Grievances poured in about payments, charges, fees, fraud — even promotional programs. Judging by complaints and satisfaction scores, the customer experience was getting steadily worse year over year. Inefficient internal operations and ineffective customer interactions added to the pain. So the bank turned to Genpact to design, build, and implement an analytics-led transformation program for customer service operations.

The bank's leadership knew that to make customers happier, it needed a detailed understanding of their preferences and pain points in order to improve strategic and operational decision making. The bank had invested in some new technologies, such as voice-to-text, but it hadn't realized any benefits. The main reason: Only a few people had the training to use these tools and the firm hadn't collected any analytics to determine if the technologies were working well.

We'd provided data support for the bank in the past, but now it asked us to take on a much larger role. It wanted us to design, build, and implement an analytics-led transformation program for inbound customer service operations. We had specific goals for the new system, affecting 25 consumer finance/retail portfolios in the bank's co-branded credit card market:

• Develop a data-driven method of measuring customer experience that spanned all interaction channels: agent, interactive voice response, e-service, chat, and social media
• Quickly detect sub-par agent performance and best-practice sharing opportunities across 15+ sites to improve service efficiency and identify cross-sell opportunities
• Use the existing voice-to-text technology platform to accurately capture customer complaints and uncover the reasons behind their frustrations
• Offer technical and advisory support for projects, measure post-roll out performance, and recommend timely solutions by collaborating across client teams

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.

Advanced speech analytics

We used text mining to study over 2,500 call transcripts. We also used speech tuning and automated capture and classification to sort complaints. We found more than 15 categories of complaints in all, including payment, fraud, charges/fees, and promotion. Based on what we learned, we gave agents training to proactively handle customer concerns. That resulted in more than a 10% lift in complaint capture accuracy and a 15% reduction in overall complaints. Customer satisfaction scores improved by more than 300 basis points.

Overall, agent productivity and efficiency skyrocketed. But perhaps the greatest impact was in the customer experience across all channels:

• 20%-25% reduction in customer effort
• More than 15% reduction in customer complaints
• Greater than 5% improvement in customer satisfaction scores

Improved productivity and effectiveness produced about $3 million in annual savings. What's more, the bank experienced:

• A decrease in agent handling time by 10%-15
• An improvement in first call resolution rate by 8%-10
• The elimination of manual complaint capture process
• Fewer manual audits, improved QA coverage and reduced sample bias

The bank also enjoyed greater revenue, with up to 10% improvement in offer and net sales rates across sites.

Thanks to our expertise, the bank later replicated these solutions across other banking functions, moving us up the client's value chain from data support to key decision influencer!