標題: The case is relatively simple and the [打印本頁] 作者: HongKongPhone 時間: 2024-3-9 18:33 標題: The case is relatively simple and the Place orders, B-side customers confirm orders, select services, use services, and service experience. The formula of the growth model is: average daily order volume = total order size * proportion of orders from different rows * service display rate * service order rate * service completion rate. Based on the above summary, Xiaobai summarized and analyzed the existing data, and also supplemented the contract performance experience data of relevant three-party transportation capacity. following data are fictitious, please note that readersConclusion: Through data analysis, Xiaobai found that first of all, the exposure rate of this service product in the three industries is very low.
The main reason is that the service product currently requires merchants to sign separate contracts, and the current signing rate is low. Xiaobai needs to solve the problem. Contract signing rate Hong Kong Phone Number or use other methods to solve the problem of service exposure. For example: you can purchase and use it without signing a contract. Secondly, the service order rate is low. Xiaobai needs to further visit customers and ask about the specific reasons for not placing orders, and then further determine which strategy should be adopted to increase the order rate, and at the same time pay attention to the customer retention rate. Finally, the fulfillment experience provided by some capacity companies is poor and needs to be
further improved. Step Three: Start a Growth Experiment Next, when Xiaobai conducted growth experiments, he prioritized the specificity of goals and the clarification of measurement standards. She ensures that each experiment goal is clear and measurable, and sets precise metrics for them. Subsequently, Xiaobai systematically carried out a series of growth experiments according to the logical framework of "guess-execution-verify". During this process, Xiaobai made detailed planning and execution of prioritization, experimental design, and
