Background

As a North American end-to-end logistics service provider, the logistics platform of this company currently relies on an outsourcing team to handle all-channel logistics inquiries and complaints. There are issues such as inaccurate responses, low efficiency, and high operational costs, which urgently require the company to address these problems. To enhance operational efficiency and service experience, the company plans to deploy a multi-channel intelligent customer service platform, integrate multiple entry business flows, and achieve real-time logistics status inquiries, automatic follow-up for abnormal items, and standardized handling of complaint suggestions, providing a key support for its competition in the North American logistics market.

Business Pain Points

Currently, non-professional outsourcing teams have limited understanding of the logistics business and their manual capabilities are also limited. This results in insufficient response accuracy and slow efficiency when handling logistics inquiries, complaints, and abnormal items, which negatively impacts customer satisfaction. As a consequence, the company's performance has significantly declined, and its profit margin has been severely squeezed. With the growth in end-point logistics demand, the workforce size has also expanded simultaneously. However, under the outsourcing model, service efficiency and costs have reached their limits. The return on investment efficiency has continued to decline. The company urgently needs a professional customer service team with high efficiency, high accuracy, and low cost to support its business development needs.

At the same time, during the promotional season, the volume of logistics consultation requests has increased by 300%, and the average waiting time for customers exceeds 20 minutes. It is difficult to meet the requirements for service quality and response timeliness with temporary additional manpower, and a team integration period is required, making it difficult to control the work efficiency and costs during this period.

solutions: Instadesk - Live Chat reshapes the new path of agent services

1.Intelligent IVR

It can accurately understand the conversational instructions of inbound users through technologies such as natural language processing, speech recognition, and machine learning, conduct multi-round conversations, and automatically handle or categorize issues such as logistics inquiries, reducing the proportion of transfers to human agents. This significantly improves the service efficiency and response accuracy of a certain logistics platform in North America. While enhancing service efficiency and response accuracy, this system can also integrate service cases, learn solutions to form an efficient service response program template, deeply addressing the inefficiencies caused by the diversity of customer service work.

2.Intelligent Text + Email Robots

Text robots enable users to query independently. In case of complex issues, they will guide users to manual processing and create work orders. Meanwhile, in the Instadesk—Call Centert, the background algorithms accurately identify the customer's language and tone or emotions, enabling corresponding emotional handling. This significantly reduces the customer complaint rate, improves the resolution efficiency and customer satisfaction, laying the foundation for attracting repeat customers for the company.

Email robots automatically handle all user emails, achieving automatic creation of work orders and intelligent responses. They have a powerful corpus output model that truly replicates the real language tone. At the same time, the email language is ensured to be concise and clear, effectively solving customer problems. By providing unified service standards through the robots, duplicate issues are intercepted, overall improving the resolution efficiency, reducing the pressure on human resources, and achieving cost reduction and efficiency improvement. The background models record typical cases and conduct intelligent learning, enriching the response methods, and enhancing customer satisfaction.

3.Ticket  System

Users generate work orders for complex issues and have them assigned to the second line for handling. The system automatically provides feedback. This shortens the waiting time for users and resolves problems. At the same time, it offers both human and intelligent customer service, complementing each other to solve difficult issues, ensuring high quality and efficiency while also enabling mutual learning and contributing to the company's development.

Solution Cycle

The work order tracks the request throughout the process → standardized processing flow → automatic feedback to ensure consistency. Service quality is monitored in real time, reducing operational costs and improving customer satisfaction.

Business Results

The daily call center receives an average daily volume of (incoming calls) over 4,000 per day. It successfully resolves the issues of insufficient customer service supply during the North American promotion season, expands the customer service team, and improves the service level. The efficiency of the customer service center has increased by 30%. The working mode of human + Instadesk—Live Chat can efficiently solve similar simple problems. When encountering difficult issues that intelligent customer service cannot solve, it transfers to human service to improve the efficiency of human processing and reduce time loss. The effective reception rate of the agents is 93%. With the improvement of processing speed, the reception rate naturally increases. The improvement of the effective reception rate also leads to higher customer satisfaction and evaluation, laying a good reputation for the company.