After the Internet gradually enters the era of big data, it will inevitably bring a series of changes and reshaping to the behavior of enterprises and consumers. The biggest change is that all the behaviors of consumers seem to be "visual" in front of enterprises. With the in-depth research and application of big data technology, enterprises are increasingly focusing on how to use big data services for precise marketing, so as to deeply tap the potential business value. Thus, the concept of "user portrait" came into being. What is a user portrait, that is, the tagging of user information, means that enterprises perfectly abstract a user's business panorama after collecting and analyzing the data of consumers' social attributes, living habits, consumption behaviors and other major information, which can be regarded as the basic way for enterprises to apply big data technology. User portraits provide enterprises with sufficient information base, which can help enterprises quickly find more extensive feedback information such as accurate user groups and user needs. The code-detecting big data collection system collects consumer big data, and outlines that the core of accurate marketing of user portraits is user portraits, and the core of user portraits is labels. The focus of user portrait is to label the user. A label is usually a highly refined feature identification, such as age, gender, region, user preferences and so on. Finally, you can comprehensively view all the tags of the user, and basically outline a three-dimensional "portrait" of a user. The most important thing in creating user portraits is user data collection. Next, we will show you the process of collecting, processing and modeling user data through code detection: collecting user online browsing behavior data, including data browsed by users on portals and even other e-commerce websites. It mainly includes user data, behavior data, consumption data, commodity data, behavior data and customer service data, and any data related to users can be used as a data source. This part of the data source may involve "data exchange", that is, obtaining the required data from other websites and other channels through certain methods. Then there is the data management platform. The core of the management platform is label management, including definition, editing, review, query, and corresponding analysis tools. On this basis, various models are established, including user purchasing power model, group portrait model, purchase interest model, promotion sensitivity model and so on. The result obtained through the series model is the user's label, including the user's DNA, category preference, brand preference, promotion preference and price preference. Code measurement technology marketing big data acquisition system is customer-centered, relying on powerful database resources, and accurately analyzing and positioning customers through data integration, helping enterprises to provide the required products to accurate customers at the right time, at the right place and at the right price through the right marketing channels, so as to maximize enterprise benefits. Code detection big data acquisition system builds a data lake for the industry. Code detection technology extracts structured and unstructured data from data sources through web data collection and factory equipment data collection. Through data labeling/cleaning, data conversion and data management, the extracted data is processed, and finally the data is quickly output to build a data lake. Break the data island mode, realize business intelligence through machine learning and artificial intelligence technology, strengthen the utilization of internal data, and promote collaborative office. There is a centralized data center that can store data, track data information and ensure consistency, track data usage to support agile data production process, and support interactive big data analysis. Provide access to the most advanced big data SQL engine and its extended functions to help organizations or enterprises make more flexible decisions on enterprise development. The data collection process of the code detection data lake defines the data requirements: because the customers are in different industries, the requirements are also different. Therefore, first of all, it is necessary to clarify the final use of data by customers and determine customer needs. After communicating with customers according to the data information they need to collect, summarize the fields that need to be collected. survey data