This is a user activation strategy I made in the AI ​​industry from operations to products. At that time, the task was urgent. I thought about it in less than a week and compiled a report.
Of course, some sensitive content in it has been filtered and deleted; I b2c email list mainly want to share my user operation methods and experience of robot products, as well as supporting apps or small programs, and this type of tool product with my friends. Hope it helps you.
1. Project Description
1. Background
The marketing model of food delivery robots is mainly based on business leases for catering scenarios. The core task is to expand the rental rate and renewal rate of robots; around core indicators, the company continuously optimizes the robot chassis, navigation, vision, voice and other hardware performance, and software functions.
In addition to the iterative maintenance of the robot body, the robot applet can help merchants use robots efficiently and add a premium to b2c email list the use value of robots, thereby promoting brand promotion and increasing rental renewal rates.
2. Standards
The definition of user activity varies depending on the nature of the product and usage habits. The trial period of the food delivery robot is 15 to 30 days, and the formal lease starts from 3 months; we first define the applet according to the usage of the b2c email list food delivery robot in the restaurant The user's activity standard is: as long as each administrator logs into the applet once, it will be recorded as 1 activity. If 10 users log in 100 times, the number of active users is 100, and the number of active users is 10, that is, the difference between pv and uv.
The calculation logic of the active rate is: the ratio of the number of active users to the cumulative number of users within 7 days.
An example is as follows: Take 7 days as the statistical period——
The number of new users=A, the number of old users=B, the number of accumulated users=C; then C=A+B;
The active number of new users=E, the active number of old users=F, and the cumulative active number of users=G; then G=E+F;
New user activity rate = E/A, old user activity rate = F/B, cumulative user activity rate = G/C;
3. Goals
By formulating some promotion strategies and carrying out regular and irregular fun activities, we can wake up the silent users who have used Mini Programs among private domain users to be more willing to log in and use the "Robot Mini Program" more frequently, and also stimulate and Guide the administrator who has not used the applet to log in and use it.
Give full play to the practicality and convenience of Mini Programs. We initially set active goals:
The weekly activity rate of robot mini-program users increased to 80% within 7 days (statistics based on the last 7 days).
2. Status Quo
1. The problem was found to be unresolved or insufficiently resolved
Inspection, pre-sale, the product itself, and the direct demand from customers reflect some of the problems in the use of food delivery robots in the field; these intuitive problems have been reviewed and confirmed, and basically solved one by one.
But why the market sales are not optimistic, the rental rate is low, the opening rate of the applet is low, the activity rate is low, and the page traffic is not high; all the unsightly data are indirect reactions or problems.
Other tools are derived around the functions of the robot itself, in order to create a good reputation, portray a high-quality and profound brand impression, and increase the rental rate and renewal rate of the robot.
Therefore, to solve the insufficient problem, four measures should be taken:
From the use of Mini Programs, sort out and discuss and confirm important user behavior data indicators;
Embedding these indicators, from the WeChat native platform, can be automatically exported by products or operators;
Track user behavior data in stages, and gradually form data analysis reports, which are helpful for refined operations;
Efforts should be made to promote user activation and recall lost users, and try to grasp user attributes, behavior attributes, and data indicators as accurately as possible.