Transforming Customer Support with Data-Driven Insights: A Case Study of an Online Restaurant Reservation Platform
In the highly competitive financial services landscape, customer experience is the critical driver of success. The customer, a financial services provider, is a prominent player in this sector, committed to securing the financial future of middle-income Americans. They offer a wide array of services, such as life and health insurance, annuities, financial services, and workforce benefits solutions.
The Challenge: Repetitive Inquiries and Customer Satisfaction Concerns
Despite their unwavering commitment to customer service, they faced a substantial challenge – 30% of their customer calls were repetitive inquiries. Addressing the same questions repeatedly was costly and detrimental to achieving First-Call Resolution (FCR), a key customer service goal. Furthermore, these repeated calls were indicative of broader customer satisfaction concerns, revealing that customers were not satisfied, often leading to customer frustration, cancellations, or attrition.
Moreover, they lacked the ability to gain deeper insights into agent behavior, report on crucial trends, and provide the granular reporting needed to enhance their training and management processes. This deficiency in their existing systems hampered their ability to optimize agent performance and achieve the desired operational efficiency.
In search of a solution, the company turned to a well-known name in the industry. However, this choice brought its own set of challenges. The vendor’s product was hosted on-premises, therefore limiting scalability, accessibility, and flexibility. The frustrations with this vendor included transcription errors, outdated software, time-consuming reporting processes, employee difficulties in adapting to the platform, segmented call recording, lack of custom reporting capabilities, and insufficient training for employees.
Objectives: A Roadmap to Enhanced Customer Service
To overcome these challenges, the customer defined its objectives, which encompassed:
Customer Journey Insight: They wanted to gain deeper insights into customer inquiries and experiences by enhancing system reporting and trend analysis.
Compliance Tracking: They sought to implement a compliance and process adherence tracking mechanism to avoid hefty fines.
Improve First-Call Resolution: A pivotal goal was to prioritize the reduction of repeat calls to improve the FCR and, hence, control added costs with each call.
Enhance Agent Coaching: They aimed to identify the factors leading to upset callers and broader performance drivers to create a coaching plan on those insights.
Understand Transfer Rates: They aimed to accurately identify and measure transfers/escalations rates to improve customer experience.
Furthermore, the company’s analytical needs were equally clear, including:
- Easier Reporting: Simplified and more efficient reporting processes.
- Data Sharing with Leadership: Sharing data with leadership to inform decision-making.
- Understanding Short Calls: Identification of the reasons for calls lasting 30 seconds or less. Existing reporting methods were inadequate in providing these insights.
- Trends in Quality Assurance (QA): The need to recognize trends within the QA center.
- Integration with Salesforce: Seamless integration with Salesforce was crucial for holistic data analysis.
The Level AI Solution? In-Depth Customer Insights to Master First-Call Resolution
The customer sought a tool that could help identify the root causes of their challenges and provide insights into call reasons and patterns. Collaborating with Level AI, the customer found the perfect solution to address their challenges –
- First-Call Resolution Excellence: They successfully achieved their main goal of enhancing FCR by identifying the factors behind repeated calls. They also provided targeted one-on-one coaching to equip agents with the knowledge and skills needed to meet customers’ requirements during their initial call.
- In-Depth Customer Intent Analysis: The reports through Level AI’s analytics module helped them gain comprehensive insights into customer intent, especially concerning transfers and escalations, allowing them to provide more focused and effective assistance.
- Call Cause Identification: They have successfully pinpointed the causes of calls lasting less than 30 seconds, including determining whether it was the customer or agent who disconnected the call first.
- Voice of the Customer (VOC) Mastery: With Level AI, they now benefit from Voice of the Customer (VOC) insights on every call, granting access to comprehensive data on customer trends and challenges that were previously inaccessible. This eliminates the need for manual call listening and reporting, taking on-call surveys, and streamlining their customer service operations.
With all the information at palm, the financial services provider now has a better understanding of why calls are disconnected and why sales didn’t close. The impact of Level AI on their operations is significant, resulting in improved First-Call Resolution, cost savings, and an enhanced customer experience. The platform facilitated the analysis of short calls, customer intent, transfers, and escalations while providing critical Voice of the Customer (VoC) insights.
Conclusion: Revolutionizing Customer Service with the Power of Modern Contact Center Technology
The partnership with Level AI showcased how Generative AI and advanced analytics can revolutionize customer service, reduce operational costs, and elevate business performance. This journey serves as a compelling case study of how the right technology solution can drive excellence in customer service within the financial services industry.
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