In today's globalized business environment, many companies operate overseas stores to cater to international customers. To effectively manage customer relationships and provide seamless service, companies often integrate their customer relationship management (CRM) systems across different locations. However, ensuring the data quality of overseas store service CRM system integration can be a challenging task. Data cleaning and verification are essential processes to address this challenge and maintain the integrity of the integrated CRM system. Data cleaning involves identifying and correcting errors, inconsistencies, and inaccuracies in the data. This process is crucial for ensuring that the data used in the CRM system is reliable and accurate. In the context of overseas store service CRM system integration, data cleaning may involve consolidating customer information from different sources, standardizing data formats, and removing duplicate records. By cleaning the data, companies can prevent issues such as incorrect customer information, duplicate entries, and outdated records, which can negatively impact the effectiveness of the CRM system. Verification is another critical step in ensuring data quality. This process involves validating the accuracy and completeness of the data through various methods, such as cross-referencing with external sources, conducting data audits, and implementing data validation rules. In the context of overseas store service CRM system integration, verification may involve confirming customer details, such as contact information, purchase history, and preferences, to ensure that the integrated CRM system contains reliable and up-to-date data. To effectively ensure the data quality of overseas store service CRM system integration through data cleaning and verification, companies can follow several best practices. Firstly, they should establish clear data quality standards and guidelines to govern the integration process. This includes defining data cleaning and verification procedures, as well as roles and responsibilities for managing data quality. Secondly, companies should invest in data quality tools and technologies to automate the data cleaning and verification processes. These tools can help identify and resolve data issues more efficiently, reducing the manual effort required and minimizing the risk of human error. Additionally, companies should regularly monitor and maintain data quality after the integration is complete. This involves implementing data governance practices, conducting periodic data audits, and addressing any emerging data quality issues promptly. In conclusion, ensuring the data quality of overseas store service CRM system integration through data cleaning and verification is essential for maintaining the effectiveness of the integrated CRM system. By following best practices and leveraging data quality tools, companies can effectively address data issues and maintain reliable and accurate customer data across different locations. This, in turn, enables them to provide seamless service and build strong customer relationships in the global marketplace.