Leverage Futong's Auto Intelligence VOC platform to identify and uncover potential operational risks, such as product quality issues and high-frequency customer complaints. Through risk event identification and early warning, push notifications, and effect tracking, the platform creates a PDCA (Plan-Do-Check-Act) closed-loop process for addressing risk-related issues within the company. This helps business departments stay informed of potential risks and prepare countermeasures, preventing the occurrence of brand reputation risks.
Leverage big data and artificial intelligence to address customer issues with the voice of the customer, creating a digital, intelligent, and shared VOC (Voice of Customer) management platform. The VOC system aims to further implement the strategic goal of 'customer-centricity' by actively listening to all internal and external customer feedback in real-time. Through the process of hearing, understanding, and analyzing, it resolves issues related to products, complaints, services, marketing, and strategies. The platform enables the use of customers' own voices to address their pain points and problems, achieving a complete closed-loop VOC management system.
The automotive company aims to collect and analyze unstructured natural language data from users, converting it into structured, actionable insights. These insights will guide brand actions, helping the brand understand user perceptions and interactions with the brand, products, and services across all touchpoints throughout the entire customer lifecycle. This will enable the company to identify and address issues, ultimately providing a better user experience.
The automotive company seeks to implement a customer feedback management system to centralize the collection, management, and analysis of customer feedback data from both internal and external sources. This will help address customer pain points, proactively prevent issues, identify sales opportunities, and boost customer loyalty.
To define strategic investment priorities and goals, the automaker needed to quickly implement an enterprise-level consumer feedback system. This system would centralize the collection, management, and analysis of consumer input to better understand the Chinese market, competitor strategies, and consumer needs, aiming to mitigate risks, uncover sales opportunities, and improve consumer experience and loyalty.
The automaker aims to leverage data to identify blue ocean markets, conduct precise customer segmentation, and uncover unmet needs. This will guide product enhancements, pinpoint opportunities, and support product planning, ultimately boosting competitiveness and expanding market share.
Due to the increasing specialization of outpatient departments and the lack of sufficient medical knowledge among patients, there is a common experience of “knowing the symptoms but not the disease, knowing the disease but not the department, difficulty in making the right appointment, running back and forth during consultations, and long queues everywhere.” This significantly impacts the overall patient experience and satisfaction. The hospital aims to reduce the inefficiency caused by patients “misbooking appointments or blindly booking” leading to overcrowding in expert clinics, while simultaneously enhancing the patient experience and optimizing the utilization of internal medical resources.
Through this system, automatic time-limit checks are performed at the department level on medical record data, enabling common quality control alerts such as overdue warnings, unmet writing frequency, and missing key field entries. This reduces unnecessary medical record errors and subsequently improves record quality.
The hospital sees more than 5,000 outpatient visits daily, with a significant portion of patients coming from outside the region. Cases of incorrect appointments or patients not receiving appropriate care are prevalent, especially due to a lack of understanding about specialized and sub-specialized services. This results in low outpatient consultation efficiency. Auxiliary examination departments are overcrowded, with long appointment waiting times, and the service model urgently needs optimization.
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