Lazada data analysis: full process guide from collection to application
Lazada platform data analysis is an important tool to help merchants understand the market, optimize operations and formulate strategies. By utilizing big data, companies can mine useful information from large amounts of data and provide scientific basis for decision-making. This article will introduce in detail how to perform data analysis on the Lazada platform and discuss its specific application in actual operations.
Data collection
Data analysis on the Lazada platform first needs to start with collecting data. This includes collecting various key data indicators such as sales, order quantity, user behavior, etc. through APIs or other data acquisition methods provided by the Lazada platform. In addition, it can also be combined with other databases, such as market survey data, competitor data, etc., to obtain a more comprehensive data perspective.
Data cleaning and summary
After collecting the data, the next step is to clean and summarize the data. This step requires the elimination of abnormal data and duplicate data to ensure the authenticity and reliability of the data. Using tools such as Excel to organize and convert data helps in better analysis and mining.
Data analysis methods
The data analysis methods of the Lazada platform mainly include descriptive analysis and trend analysis. Descriptive analysis can understand the basic characteristics of the data through indicators such as the mean, median, and standard deviation of statistical data. Trend analysis draws line charts or column charts to observe the changing trends of data, such as sales and order quantity, and find hidden patterns.
In addition, Lazada also provides data analysis tools and dashboards such as Lazada Seller Center and Lazada Business Advisor to help sellers conduct data analysis and monitoring more conveniently.
Data application examples
Develop planning form
Merchants should use the form to analyze from the perspectives of traffic, conversions, products, promotions, services, etc., and fill in the forms based on the results of planning and implementation. Specific steps include formulating planning forms, covering annual, quarterly, monthly, weekly plans, etc., and assessing planned sales, actual completion amount, and completion rate.
Detailed statistics
Then formulate the target content of the plan form and set detailed statistics, including assigning the responsible person. For example, statistics on the effectiveness of store promotion tools can also be tracked and analyzed by people.
Competitor store tracking
In terms of tracking competing product stores, you can lock in the other party’s flash sale prices and big sale prices. These prices are often the bottom price of commodity retail. In addition, you can also track competitors’ supply chain systems, including production capacity, supply efficiency, logistics timeliness, etc.
Customer service management
In terms of customer service, merchants should use two forms: one is a statistical form of customer service’s daily work; the other is a form for maintaining old customers. Although not all customers will cooperate in providing effective information, there are still some customers who are willing to interact and communicate, and are more likely to become loyal fans.
Conclusion
In summary, data analysis on the Lazada platform is an important and complex task that requires a combination of multiple methods and techniques. Using big data, companies can not only gain a deeper understanding of their brands and markets, but also optimize operational strategies and achieve business growth. Therefore, data analysis plays a vital role for both merchants and the Lazada platform itself.