Article summary
Interpret WA/WS gender and age task fields, missing values, coverage and profile boundaries without turning observations into verified identity.
A WhatsApp gender-and-age check returns task fields, not an identity-verified demographic record. Age, gender and avatar values may be missing, stale or unavailable. The defensible use is to disclose coverage, preserve unknowns and restrict these observations to an approved, low-risk analysis.
Begin with the actual export schema
| Field | Reasonable interpretation | It cannot prove |
|---|---|---|
| Phone | The number associated with this run | Permanent identity |
| Age and gender | Profile-related values returned by the task | Documented age or legal gender |
| Avatar | A picture-related result observed by the task | Identity, occupation or income |
| WhatsApp mapped phone | A clue for controlled reconciliation | A universal collision-free key |
Calculate coverage before distribution
If age is returned for 2,000 records in a 10,000-row file, report the 20% coverage before describing the age mix. Saying that one band is “the largest” without showing 8,000 unknowns creates a misleading profile. Measure non-missing, unknown, error and conflict rates separately for age, gender, avatar and mapped phone.
Four blank states should remain distinct
| State | Meaning |
|---|---|
| missing | No value was returned |
| not_visible | Visibility conditions prevented an observation |
| unknown | No definitive interpretation is available |
| error | A format or task exception occurred |
Do not convert all four to “none” or “false” simply to make a clean chart.
Do not infer demographics from the avatar
An avatar may show a logo, several people, a pet, an old image or someone other than the account holder. Manual guessing and AI vision should not fill unknown age or gender. The picture is also unsuitable as identity verification, a denial-of-service feature or sensitive targeting evidence.
The minimum TXT-to-Excel workflow
- Select phones with documented provenance and processing authority.
- Normalize and export one phone per line as TXT.
- Do not upload names, orders, addresses or the entire CRM.
- Select WS Gender and Age in AIPUSH.
- Download Excel into staging and reconcile rows, blanks and collisions.
AIPUSH accepts TXT only; Excel is the post-task export.
Do not confuse this task with WS Full Format
WS Gender and Age centers on phone, age, gender, avatar and mapped phone. WS Full Format adds a broader set including activity time, active days, skin tone, avatar type and business-account fields. When the decision does not require those columns, a wider task is unnecessary.
Keep the CRM master record clean
Reconnect through contact_id and store task_name, batch_id, checked_at and the original returned value in a separate observation domain. Stop automatic promotion when mapped phones create one-to-many or many-to-one collisions. Retain earlier observations and expose a dated view rather than overwriting customer-provided data.
Appropriate and inappropriate business questions
The fields may support an approved coverage study, data-quality review or reconciliation of an already-known customer record. They should not be used to “find high-value people,” predict purchasing power, prove identity or replace contact permission. Messaging decisions still depend on subscription, relationship and opt-out evidence.
A qualified report discloses definitions, coverage, unknown rate, collision count and observation date. WhatsApp profile analysis becomes explainable only when it documents what the task could not know as clearly as what it returned.
