Contact Center Automation and VoC Utilization with Generative AI Agents

We greatly reduced after-call work (ACW) and improved products through Voice of the Customer (VoC) analysis. The implementation of AI agents transformed a contact center from a cost center to a profit center.

Business Process Reform (BPR)
Retail & Distribution

Contact Center Automation and VoC Utilization with Generative AI Agents

ISSUE
- Maintaining clear and accurate interaction records required a significant amount of time due to manual, labor-intensive ACW.
- Data was being accumulated in the form of correspondence histories, but there were no systems to utilize it.
SOLUTION
- We developed a platform for automatic call summarization and quality assessment utilizing a generative AI agent .
- We designed a knowledge codification and sales-driving model utilizing VoC.
RESULT
- ACW was reduced significantly, and operator productivity was improved.
- A system was built to utilize call data and correspondence histories as the VoC and feed it back to customer understanding and product improvement.

ISSUE

Moving away from Operations Reliant on Human Operator Responses

A major retail chain was under increasing pressure to enhance efficiency without compromising service quality as inquiry volumes grew. ACW tasks such as call summarization, CRM registration, and response quality assessment placed a heavy burden on operators, underscoring the need to transform a highly human-dependent operating model.
SOLUTION

Creation of a System for Automating Operations and Utilizing Knowledge using Generative AI Agents

We supported the client’s contact center transformation by enabling operational automation and knowledge utilization through generative AI agents. First, we integrated the cloud-based CTI system with a generative AI platform to automatically transcribe, summarize, evaluate, and register call content. By allowing AI agents to handle post-call processing automatically, operator ACW was significantly reduced.
The solution generates two types of summaries: structured summaries designed for supervisors, and summaries that preserve customers’ own words. This not only improved operational efficiency but also enabled more accurate understanding of customer intent, allowing the insights to be applied to complaint handling and product improvement. In addition, response quality evaluation was automated using generative AI, accelerating continuous improvement through immediate feedback.
RESULT

Significant ACW Reduction and Evolution to a Profit Center through VoC Utilization

Following implementation, the time required for ACW was significantly reduced, and the time spent on response quality assessment was cut in half. This reduced the workload for both operators and administrators, allowing resources to be reallocated to higher-value-added tasks. We also built a system to accumulate and analyze call data as the VoC. Inquiries are categorized and summarized using generative AI and then fed back to the marketing and product development departments, leading to product improvements and the creation of new sales opportunities based on customer feedback. Going forward, trend analysis based on vectorized VoC data is planned, supporting efforts to evolve the contact center from a cost center into a profit center.