? With the rapid development of big data, AI and other fields, as well as the addition of blockchain technology, many industries closely associated with it, have ushered in a new period of change. When we enter the era of big data, enterprises in the operation has also changed accordingly, from the initial rough operation gradually transitioned to refined operation. How to realize the refined operation of the enterprise?

Refined operations

One of the four prerequisites for refined data operations

?1.Getting the data you need for your operations in a timely manner

? Clearly what data should be obtained, such as orders, registration, reading, page visits, visit length, etc.; accessible to the data, not all data can be accessed, only the pre-buried and can be captured data can be accessed; timely access to data, the operation of many companies can not directly access to the data, generally have to communicate with the technology to clarify the needs of the scheduling as well. And a lot of data is time-sensitive. For example, during the campaign period, we didn't get the id of the potential buyer in time, which led to the delay of sending the offer information, and the user purchased the goods in other channels.

2. Reasonable definition of dimensions and metrics for data analysis

The closer the definition of dimensions and metrics is to the needs of the business, the more the true value of the data can be realized. However, many companies have a vague division of data, and even if it can be reasonably defined during analysis, it is impossible to analyze it because the data for these dimensions is not collected in the early stages.

3. Select and use efficient data analysis tools

? Good data analysis tools, not only to meet the current stage of business data analysis, but also to meet the development process of the enterprise data volume growth and business changes after the data analysis.

? Therefore, Excel, SPSS, SAS, SQL, Clementine, R, Rapid-miner and other tools may be used. Mastering these tools is too much to ask of an operations person, and the financial resources and effort to train an operations person at such a standard is equivalent to training a data analyst.

4.? Have a strong data analysis ability, can be combined with the actual work

? Data analysis ability, in short, can find problems from the complicated data, summarize the law, and can give optimization plan. This requires not only an in-depth understanding of the business, but also the ability to analyze the data logically in order to integrate the data with the actual business.

Second, fine-tuning the operation of how to achieve user growth

?1. event analysis

? The application field of event analysis method is very wide, and different scholars have elaborated on it from the perspective of this field. Event research is a quantitative analysis method that uses specific techniques to measure the impactfulness of an event based on the statistics of information before and after the event.

?2. Funnel Analysis

? The value of the marketing funnel model is that it quantifies the efficiency of each link in the marketing process and helps to find weak links. That is to say, the link of marketing refers to a sub-link in the whole process from acquiring users to the final conversion into a purchase, and the conversion rate of the neighboring links refers to the use of data indicators to quantify the performance of each step. So the whole funnel model is to split the entire purchase process into steps, and then use the conversion rate to measure the performance of each step, and finally through the abnormal data indicators to find out the problematic links, so as to solve the problem, optimize the step, and ultimately achieve the purpose of improving the overall purchase conversion rate, the overall funnel model can be summarized as the core idea of decomposition and quantification.

3. Retention analysis

? Retention analysis is an analytical model used to analyze user engagement/activity by examining how many of the users who perform an initial action will perform subsequent actions. This is an important method used to measure how valuable the product is to the user.

? How to make users continue to be active, retained rather than after a period of activity into a dormant stage or even direct loss, is the entire user operation process is a solid foundation. If the user can not be retained, and then more users have to lose the day, only have enough retention, only subsequent to the continuous excavation of the value of the user. At this stage, the key behaviors of users that should be paid attention to are: continuous login and continuous activity, and the corresponding operational indicators are: next day retention, 7-day retention, 30-day retention.

? In the era of dataization, the era of continuous forward development of business, technology is changing, the marketing model is changing, the user demand is constantly upgrading. As a business, it is more important to keep up with the times and fine-tune operations to achieve user growth in order not to be abandoned by your users and not to be eliminated by the market.