Detailed explanation of cross-border e-commerce enterprise data analysis and customer service functions

In today’s globalized market environment, cross-border e-commerce companies are facing unprecedented opportunities and challenges. In order to better respond to market changes, companies not only need a strong customer service team to promote sales, but also need efficient data analysis capabilities to guide decision-making.

Customer service’s promotional function

In the field of cross-border e-commerce, if customer service can give full play to its subjective initiative, it can also create huge sales results for enterprises and teams. For example, when a customer takes a photo of a product but has not yet paid, customer service can facilitate the transaction in the following ways:

• Emphasize the biggest selling point of the product: “The item you selected is of high quality one with competitive price. You would like it.”
• Remind the importance of immediate payment to avoid short of stock: “Instant payment can ensure earlier arrangement to avoid short of stock.”

At the same time, customer service can also identify potential long-term customers by sorting out buyer transaction data and recommend high-quality products in a targeted manner.

Data analysis function

General functions

• Marketing: including SEM, advertising, alliances, new media, etc.
• Operation: Involves the daily operation and maintenance management of the website.
• Purchasing: Focus on product procurement.
• Sales: Responsible for product sales.
• Logistics: Logistics distribution and management.
• Warehouse: Product inventory management.
• Customer Service: Customer service and maintenance.

System operation and maintenance

• Maintain data systems.
• Ensure the correct deployment of traffic systems.
• Provide system deployment solutions.
• Cooperate with the implementation of technical solutions.
• Develop a daily delivery plan.

Data architecture

• Plan the big data system.
• Build a metadata management system.
• Clear model and data standard definitions.

Data management

• Maintain data warehouse.
• Optimize data warehouse performance.
• Establish a data management system.

Products

• Develop data products.
• Assist in data analysis and data mining.
• Implement logical planning.

Data analysis

• Support business activity effectiveness evaluation.
• Support abnormal analysis of business activities.
• Establish an early warning mechanism.
• Uncover the intrinsic value of the business.

Data mining

• Study data mining algorithms.
• Maintain the data mining module.
• Optimize the personalized recommendation module.

Market strategy

• Develop mid- to long-term development plans.
• Collect industry information.
• Understand user needs.

To sum up, both customer service and data analysis play an extremely important role in cross-border e-commerce companies, and they jointly promote the growth and development of the company.