Mr. Cai's discussion on big data (17th): Universal Mobilization

Data-based operation discussion (3)

In 2010 and 2013, they proposed their respective strategies for data-based operation. The big data operation era has come, and how to integrate massive data becomes a key task.

In the industry, the definition of data-based operations is different, but the core and elements are the same, that is, "using big data analysis and mining as the foundation to support enterprises with more refined operation systems and strategies ".

The implementation is specific to the online and offline data analysis support for operation, sales, and customer service departments. For example, in Internet enterprises, the Operation Department needs to refine its operation through quantitative, subdivision, and prediction methods such as "log monitoring", "Traffic Monitoring Analysis", "target user behavior monitoring analysis", and "user feedback information analysis.

Data-based operations should be normalized and systematic within an enterprise (data collection and application systems), and relevant procedures should also be formulated for each department and position of an enterprise, they must truly operate their own jobs from the perspective or height of data, and consciously use simple or complex analysis tools in their work. Instead of dealing with data only by data engineers, everyone should get used to communicating with data, cultivate data awareness, and avoid the impact of human factors on decision-making. The level and level of data used by employees in their daily work determine the data-driven operation level of the enterprise. Enterprises that implement data-based operations should pay more attention to and deepen data than traditional enterprises.

Data will be used for pre-operation preparation, interim control, and later correction. Customer Service not only meets the needs of existing users, but also discovers new needs of users through data, through data analysis and mining, sales staff can be more targeted and precise in marketing. The most important thing is that data technicians should promote and popularize internal data technologies and tools.

Enterprise leaders must be aware that full data mining is the most valuable and data-driven operation is the core of future competition.

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