Jun 14, 2022
In Welcome to the Forum
Generally, the data is divided into three parts: macro, passengers, and drivers. The macro data includes indicators such as scale, transaction rate, and average subsidy. Do a day-to-day and week-on-year analysis of the indicators, and then use the Whatsapp Database relationship between the indicators to find problems, generally affecting the scale of the Whatsapp Database average subsidy, passenger funnel conversion rate, dispatch distance, product optimization, etc.; at the same time, pay attention to experience and income. Indicators include passenger NPS, driver income, etc. 2. User Lifecycle Operation According to the user's stage of using the product, the user's habits and psychology, plan activities. Pull new main sub-scenarios for brand exposure and material exhibition, such as cross-industry cooperation with shopping malls, schools, and Whatsapp Database hotels, there can be large-screen and offline material brand activity promotion, starting and ending bus coupons, etc. Scenarios where users are always present, attracting attention and Whatsapp Database promoting order completion. The basic idea of user operation in the later stage is to conduct special activities for tiered users on a weekly basis. Continuous activities promote the development of users' taxi habit. Conversion on the platform. Users who complete the first order can continue to lower the user threshold and give 2 coupons for immediate discount; for active users, Whatsapp Database according to the budget, formulate activities such as calling coupons during peak periods, targeting users to increase frequency, and paying coupons and other activities; For silent users, Whatsapp Database the churn node is generally 7 days away from the last order. Find this churn node and recall users hierarchically according to the RFM model.