HUAWEI Analytics Kit allows you to identify users in your app by user ID or device. If you want to analyze the data of the same account on different devices and platforms, or analyze the behavior of users who have signed in, you can choose to identify users by user ID.
The following example illustrates the calculation logic of the user ID function:
Assume that there are two devices: X and Y. The reported event details are as follows:
Events reported by device X: A user opened the app and performed a series of operations (steps 1 to 3) without sign-in. Then, the user used account B to sign in on the device and performed a series of operations (steps 4 to 7). Finally, the user provided device X to another user, who used account C to sign in to the device, performed a series of operations (steps 8 to 11), signed out, and used the device for a period of time (steps 12 to 13) without sign-in.
Events reported by device Y: A user opened the app on a new mobile phone and performed a series of operations (steps 14 to 16) without sign-in. Then, the user used account B to sign in on the mobile phone and performed a series of operations (steps 17 to 19).
The following table lists the event details reported by devices X and Y.
| No. | Device | Event | Reported Device ID (AAID) | Reported Account ID (User ID) | User Identifier in the System | Sign-In Identifier |
|---|---|---|---|---|---|---|
1 | X | App installation | A | NULL | A | FALSE |
2 | X | App opening | A | NULL | A | FALSE |
3 | X | App operation | A | NULL | A | FALSE |
4 | X | App sign-in | B | NULL | A | FALSE |
5 | X | App operation | B | B | B | TRUE |
6 | X | App operation | B | B | B | TRUE |
7 | X | App sign-out | B | B | B | TRUE |
8 | X | App sign-in using another account | C | C | C | TRUE |
9 | X | App operation | C | C | C | TRUE |
10 | X | App operation | C | C | C | TRUE |
11 | X | App sign-out | C | C | C | TRUE |
12 | X | App operation | A | NULL | A | FALSE |
13 | X | App operation | A | NULL | A | FALSE |
14 | Y | App installation | D | NULL | D | TRUE |
15 | Y | App opening | D | NULL | D | TRUE |
16 | Y | App operation | D | NULL | D | TRUE |
17 | Y | App sign-in | B | B | B | TRUE |
18 | Y | App operation | B | B | B | TRUE |
19 | Y | App operation | B | B | B | TRUE |
The calculation logic of the user ID function is as follows:
The system determines that the operations in the same session are performed by the same user. If the operations of steps 1 to 7 listed in the preceding table are performed in the same session, the system automatically supplements the AAID before sign-in with the user ID after sign-in. The supplemented user ID is used as the primary key for all subsequent metrics statistics.
The following table lists the event details after supplementation.
| No. | Device | Event | Reported Device ID (AAID) | Reported Account ID (User ID) | User Identifier in the System | Sign-In Identifier |
|---|---|---|---|---|---|---|
1 | X | App installation | A | NULL | A-->B | FALSE |
2 | X | App opening | A | NULL | A-->B | FALSE |
3 | X | App operation | A | NULL | A-->B | FALSE |
4 | X | App sign-in | B | NULL | A-->B | FALSE |
5 | X | App operation | B | B | B | TRUE |
6 | X | App operation | B | B | B | TRUE |
7 | X | App sign-out | B | B | B | TRUE |
8 | X | App sign-in using another account | C | C | C | TRUE |
9 | X | App operation | C | C | C | TRUE |
10 | X | App operation | C | C | C | TRUE |
11 | X | App sign-out | C | C | C | TRUE |
12 | X | App operation | A | NULL | A | FALSE |
13 | X | App operation | A | NULL | A | FALSE |
14 | Y | App installation | D | NULL | D-->B | TRUE |
15 | Y | App opening | D | NULL | D-->B | TRUE |
16 | Y | App operation | D | NULL | D-->B | TRUE |
17 | Y | App sign-in | B | B | B | TRUE |
18 | Y | App operation | B | B | B | TRUE |
19 | Y | App operation | B | B | B | TRUE |
According to the statistics result, there are three users (A, B, and C), among which two users (B and C) have signed in.