In addition to manually analyzing the data and writing analysis reports, the e-commerce review analysis system collects a large amount of review data and extracts the information contained in it, so as to provide support for brands to understand products and consumers comprehensively and accurately. , so as to make targeted optimization adjustments in a timely manner. Compared with the two, the use of system analysis will be more accurate and comprehensive than manual analysis.
The evaluation and analysis process of machine e-commerce is basically as follows: 1. Data collection. Capture information through big data collection technology; 2. Data cleaning. Automatically remove junk information through page structure and other technologies, and manually check; 3. Data coding. Standardize the unified coding of text data to form structured data; 4. Data analysis. Intelligent machine learning, classifying data, and using statistical models to analyze and calculate brand mentions, products, prices, services, etc.; 5. Report writing. Write an analysis report based on the data results, send the report to the customer, or upload it to the backend of the system, and watch it as needed.
The above e-commerce evaluation process is reproduced in the general process of antuodata, and the detailed operations in it should be detailed according to the actual situation of the company.