The optimization scheme for designing products in this way is not rigorous bulk sms service and lacks data support. 3. The effect evaluation is unscientific Under the traditional model, the evaluation of the effect of product iterations is mostly extensive, lacking a comprehensive and objective evaluation index system, and the analysis of the effect of the revision is not in-depth and thorough enough to form an accurate and fair judgment. The reason for these problems in the bulk sms service closed loop of product operation under the traditional model is that, on the one hand, the leadership and product managers lack a data-driven mind, and on the other hand, it may be limited by the lack of data collection methods for the behavior of users using products.
Based on these problems and deficiencies in the bulk sms service closed-loop operation of products in the traditional mode, data-driven closed-loop operation of products emerges from time to time. The data-driven closed loop of product operation can make product demand more accurate, product optimization plan more reliable, and effect evaluation more reasonable. Compared with traditional routines, data-driven product operations have no major differences in product development, testing, and release. The main difference lies in the starting and ending points of product bulk sms service requirements. The traditional model of product closed-loop operation starts with demand analysis and ends with effect verification; while data-driven product closed-loop operation starts with data analysis and ends with data verification.
The core logic of data-driven closed-loop operation of bulk sms service products is: data comes from product problems, and the data eventually returns to the verification of the effect of product problem solving. 2. How data drives product operations The role of data in the closed loop of product operations can be summarized into five key words: monitoring, insight, diagnosis, inspection and evaluation. They are using the indicator system to monitor the entire operation bulk sms service process, using data analysis to gain insight into users' product needs, using abnormal indicators to diagnose product "obstacles", using the retention analysis curve to test the effect of new functions, and using data to evaluate the effect of product revisions. 1. Monitoring: Use the indicator system to monitor the entire operation process