Criteria & Action structure
Overview :
Segmentation of a platform involves dividing users into separate groups based on similar trait.
Segmentation can be of following types:
a) Demographic (Mostly involves Gender , Age, Occupation etc) - Ignored coz it constitues PII
b) Geographic Segmentation - Districts, States
c) Technographic Segmentation - Mobile Devices, Software, OS, Technologies
d) Behavioral Segmentation - Consumption Habits, BMGS Preferences, Collections Enrolled.
Existing System :
Existing System provides us the data to understand the segmentation. However, the system can be aided with actionable segments running a specific solution,ui, content or notification. This helps the core platform to enable/implement the features in more intelligent way.
Proposed System :
Intent is to have some server controlled configuration (called as Criteria Structure) to enable certain behavioural characteristics on the user’s device with appropriate Notification to user.
There are two parts to Proposed System:
a)Criteria Structures : There are fundamentally three criteria structures defined:
a) VERSION_COMMAND : Generally has specific version/list of versions targeted
b) SEGMENT_COMMAND : Generally has segment of users targeted
c) DEVICE_COMMAND : Generally has device / list of devices targeted
b) Actions : Resultant Function to be executed on client. The Below Table explains different control functions we intend to define:
Scenario | Action Type | ACTION_TYPE_ENUM | Execution Description |
|---|---|---|---|
App Update | Command to warn the users on app update if the current version is not the latest version | APP_UPDATE | App Intimates the client on app update to be done and asks for consent. |
Clear Sync Data (Telemetry Data, Course Update Data) | Command to clear all the sync table entries. | SYNC_UPDATE | Intent is to stop sync module to keep hitting servers with old requests |
Experimentation Track (A/B Test) | Command to take users to experimentation track on Mobile app | EXPERIMENT_TRACK | Intent is to leverage existing infrastructure to use Mobile App users to be part of A/B testing |
Local Notification Generation (Without Firebase) | Command to generate the local notification to the user | LOCAL_NOTIF | Intent is to generate local notification to the user similar to 7 PM notification. |
Remote Enabling of Debuggability | Switch the levels of Telemetry Logging Based on config passed from server | REMOTE_DEBUG | Intent is to generate telemetry @ levels determined by server |
Solution :
Levels | Use cases | Illustration |
|---|---|---|
App Version : (NUKE) |
| VERSION_COMMAND |
“Command Control“ can be enabled @ targeted app version. | a) FORCE UPGRADE all the users of particular app version using online(playstore) or offline(blob download) mechanism.
b) Send a local notification to users of particular app version.
c) A/B Test based on the version of the app
| {
"commandId": "timeStampInLong",
"expiresAfter": "timeStampInLong",
"commandType": "VERSION_COMMAND",
"targetVersion": ["2.10","3.0","3.1"],
"targetDeviceIds": null,
"tagFilters": null,
"tagFilterUpto": null,
"controlFunction": "APP_UPDATE"
}{
"commandId": "timeStampInLong",
"expiresAfter": "timeStampInLong",
"commandType": "VERSION_COMMAND",
"targetVersion": ["2.10","3.0","3.1"],
"targetDeviceIds": null,
"controlFunction": "LOCAL_NOTIF",
"tagFilters": null,
"tagFilterUpto": null,
"controlFunctionPayload": {Notification Payload}
}{
"commandId": "timeStampInLong",
"expiresAfter": "timeStampInLong",
"commandType": "VERSION_COMMAND",
"targetVersion": ["2.10","3.0","3.1"],
"targetDeviceIds": null,
"tagFilters": null,
"tagFilterUpto": null,
"controlFunction": "EXPERIMENT_TRACK",
"controlFunctionPayload": {payload which has trackId}
}
|
“Command Control“ once enabled targeted versions will execute the “Control Function” |
|
|
“Command Control“ can be enabled @ segmented devices/ Group of devices by deviceId. | Enabling scenarios a) to e) in above table by hand-coded deviceIds in response. |
|
Segmentation of Users : |
| SEGMENT_COMMAND |
”Command Control” can be enabled @ framework category level. | Enabling scenarios a) to e) in above table by creating multiple tags. Tags can effectively be handled as “AND“ function (or) “OR“ FUNCTION. |
|
a) “Board“ : #CBSE | All CBSE users | |
b) “Board + Medium“ : #CBSE #ENGLISH | All CBSE English Medium Users | |
c) “Board + Medium + Grade“: #CBSE #ENGLISH #CLASS7 | All CBSE English Medium Class 8 Users | |
d) “Board + Medium + Grade + Role“: #CBSE #ENGLISH #CLASS7 #TEACHER | All CBSE English Medium Class 8 Teachers | |
e) “Board + Medium + Grade + Role + Location“: #CBSE #ENGLISH #CLASS7 #TEACHER #KARNATAKA | All CBSE English Medium Class 8 Teachers of Karnataka State and Mysuru District | |
f) Consumers with failed QR code attempts | All Failed QR Code Attempts | |
g) Consumers of Course | Do_ID to be part of filters |
|
“Command Control“ once enabled targeted users/ Group of devices will execute the “Control Function” |
|
|
Role of Consumption Clients:
Maintains a simple list of tags on following attributes:
Currently the list can be capped to 250 tags.Implement an interface for control function to invoke
Persist the commandId and use it for reference against further queries
Attributes | PreFix | Example |
|---|---|---|
| UP_ | Ex: UP_English |
| UA_ |
|
| UA_ |
|
| UP_ |
|
| UA_ |
|
| UA_ |
|
| UA_ |
|
| UA_ |
|
| US_ |
|
| QR_ |
|
| CA_<do_id> |
|