Using RPA for End-to-End E-Commerce Data Analysis Increases Efficiency by Up to 96 Times

"For developers, before Automa RPA, we used pure coding to address business needs, which was costly and resulted in long development cycles. Now, with Automa RPA, we can directly call a vast number of pre-built commands to solve most business requirements, and it also supports the integration of Python modules. This makes the entire development process highly efficient, even replacing some of our previous development logic and ways of thinking, allowing our technical team to focus on fulfilling business logic requirements."

Eira Lennox·E-commerce Technology Leader at GIANT BIOGENE

About GIANT BIOGENE

Founded in 2000, Giant Biogene is a high-tech enterprise rooted in scientific aesthetics. Focusing on three major industrial directions—efficacy-based skincare products, medical devices, and functional foods as well as foods for special medical purposes—the company is committed to the mission of "biotechnology serving beauty and health." Upholding an unwavering pursuit of innovative technologies and product research and development for natural beauty and health, Giant Biogene is dedicated to bringing technology from the laboratory into daily life, striving to become a leading enterprise in the field of beauty and health.

Giant Biogene faced similar hurdles as its e-commerce operations grew. The company turned to Automa RPA, with its low-code "drag-and-drop" tools, giving frontline staff the ability to build RPA solutions themselves. This automated cross-department data analysis—freeing up tons of staff time—and opened the door to more automation: e-commerce management, financial reconciliation, customer service replies—boosting both operational and team efficiency big time.

Automa Deliverables

Challenge 1

Massive Data Collection and Analysis: E-commerce data is difficult to obtain, making data collection and retention challenging. Inconsistent data across different systems further complicates analysis and reporting.

→

Solution 1

Utilize Automa RPA to build automated data extraction, aggregation, and cleansing workflows.

Automa RPA integrated with BI toolsAutomated daily data reports

Challenge 2

Multiple and Closed Systems, Difficult Collaboration: Enterprises often use various e-commerce platforms, ERP systems, and proprietary systems, making system integration and data exchange challenging.

→

Solution 2

Integrate systems using Automa RPA to enable efficient data flow.

Multi-system report exportsAutomated multi-system operations

Challenge 3

Labor-intensive and Repetitive Business Processes: Departments such as operations, finance, and data management face numerous repetitive and rule-based tasks, while the cost of developing automation solutions is often too high.

→

Solution 3

Automa RPA’s intuitive drag-and-drop interface allows any team member to quickly build automation applications, enabling rapid implementation of business requirements.

Financial reconciliationOperations automationData cleansingAutomated reporting

Operational Statistics:

3 specialists participated in project development
Built over 1,100 applications
Accumulated more than 15,000 operating hours
Saved approximately 9,551 man-days of labor

Covered Teams:

Including e-commerce operations, customer service center, finance, etc.

Covered Scenarios:

Operations: Bundle generation, product monitoring, multi-channel data downloads, order and product reporting, etc.
Customer Service: Removal of inactive customers in WeCom, full WeCom customer data updates, automatic generation of daily customer service data reports, etc.
Finance: Omnichannel sales data retrieval, automatic reconciliation, automatic invoicing, etc.

Achieved Results :

Fully automated enterprise operational data analysis, enabling every employee to obtain scenario-specific data analysis reports with one click.
Frontline staff have acquired RPA development skills, reducing reliance on IT development and enabling rapid fulfillment of business needs.
Significantly reduced repetitive mechanical tasks, greatly improving the sense of value, job stability, and talent density among entry-level staff.

PreviousNext