About BELLE
Founded in 1992, BELLE is a large-scale fashion and sports industry group with businesses covering footwear, sports, and apparel. The company owns more than ten footwear brands, including BELLE, STACCATO, TATA, TEENMIX, and BASTO, as well as apparel brands such as INITIAL, MOUSSY, and SLY. BELLE is also a key retail partner for globally renowned sports brands like Nike and Adidas. As a large-scale enterprise in the real economy, BELLE has established a vertically integrated business model covering the entire supply chain, including merchandise planning, product research and development, manufacturing, marketing, logistics and warehousing, and retail distribution. BELLE operates 7 R&D and production bases, over 60 self-owned warehouses, and more than 14,000 self-operated stores, including over 8,000 for footwear and apparel, and over 6,000 for sports.
BELLE’s e-commerce department has established a deep partnership with Automa RPA to accelerate the digital transformation of its e-commerce business. In total, over 1,300 automation applications have been developed, covering a wide range of scenarios such as data acquisition, cross-application data flow, automated operations, as well as monitoring and reminders. These initiatives have brought multiple benefits to the company, including automated data integration, improved operational efficiency, and reduced labor costs. By leveraging automation technology, the company is better able to meet market demands, enhance business agility and response speed, and strengthen its brand’s competitive advantage.
Operational Statistics
The RPA project was jointly developed by two staff members from the Technology Center and the majority of personnel from various e-commerce brands and channels.
A total of over 1,300 RPA applications have been developed and deployed.
The cumulative execution time has exceeded 7,000 hours.
This is equivalent to saving more than 4,300 person-days.
Achieved Results
Automated data integration enables one-click access to multi-source data.
Enhanced RPA development capabilities among business personnel, allowing for rapid response to business needs.
Significant reduction in repetitive manual tasks, improving the sense of value and job satisfaction among frontline staff.
Covered Teams
E-commerce Department, Finance Department
Covered Scenarios
Data Acquisition Applications: Collecting various types of logistics information, compensation data, order details, traffic statistics, etc.
Cross-application Data Flow: Integrating and transferring information across different systems and interfaces.
Automated Operation Applications: Setting up promotional activities and offers across multiple sales channels.
Monitoring and Alert Applications: Retrieving store ratings from various platforms and monitoring key performance indicators.
E-commerce operations require extensive data collection and processing, including logistics information, order information, and compensation data. Manual processing is inefficient and prone to errors.
By implementing RPA for automated data collection and processing, various types of data can be automatically captured, integrated, and handled, greatly improving efficiency and accuracy.
Event specialists are responsible for bulk campaign registrations across multiple platforms and brand stores. Manual operations are tedious, time-consuming, and prone to mistakes.
By using Automa RPA to automate the setup of promotional campaigns across multiple platforms and brand stores, registration efficiency and accuracy are significantly improved.
Transferring content from Xiaohongshu to other major platforms manually is inefficient and error-prone.
By building an RPA-based content migration application, content can be automatically transferred and published, improving migration efficiency and accuracy while reducing labor costs.

