Article summary
Learn which fields a Viber gender and age check can return, how to measure coverage by layer, and how to preserve missing values honestly.
A Viber gender and age check returns more than two demographic columns. The current schema also covers the phone number, nickname, activity and offline signals, mid, avatar source, and image characteristics. Separating these layers prevents an analytical output from being presented as a verified identity attribute.
Map the export into five field layers
| Layer | Fields | Acceptance focus |
|---|---|---|
| Input join | Phone number | Reconcile with the normalized TXT number |
| Account profile | Nickname, mid | Preserve raw values; do not treat nickname as a legal name |
| Status | Active days, offline time | Attach a task date and avoid permanent labels |
| Image source | Avatar | Distinguish no image from an inaccessible image |
| Image analysis | Skin color, gender, age, people count, avatar type | Interpret as analysis and retain blanks |
Confirm the current service on the Viber product page and find related guides in the Viber gender and age hub.
Phone number joins the source; mid belongs to the result
The phone number connects an Excel row to the submitted TXT and the authorized source record. Mid is a returned account field, so one should never overwrite the other. Add source_row_id before normalization and retain a map when deduplicating. One checked number can then be returned to every legitimate source row without repeating the service call.
Nickname and activity signals have narrow meanings
A nickname may be an alias, business label, symbol, or blank; it is not automatically a verified name. Active days and offline time describe the observation available when the task ran. They do not prove purchasing intent, lead value, or permission to contact. Store checked_at and append later observations rather than silently replacing history.
Avatar characteristics do not authenticate a person
Skin color, gender, age, people count, and avatar type are derived from avatar analysis. They describe visual presentation or a model classification, not self-declared or verified account-holder data. Cartoons, scenery, group photos, obstruction, and low-resolution images can leave fields blank or make analysis unsuitable.
Use evidence-aware wording: “the task returned this avatar-analysis value” is more accurate than “the user is.” The first identifies the source and uncertainty; the second invents certainty.
Measure missingness separately for every layer
A missing row, absent avatar, unavailable image analysis, and one blank analytical field are different events. Add an internal review_status column while leaving the original export unchanged. Calculate mid, nickname, avatar, and analysis coverage independently instead of compressing them into one completeness percentage.
- No avatar returned: this run contains no image source.
- Analysis unavailable: an image exists but some derived fields are blank.
- Task exception: several account and image fields are absent and require status review.
Move from TXT input to governed Excel delivery
- Upload TXT only, one normalized phone number per line.
- Record original, unique, and invalid row counts.
- Reconcile phone coverage before reviewing other columns.
- Retain an untouched export, governed working table, and field dictionary.
- Provide only purpose-necessary fields to authorized recipients.
Broader task-selection guidance is available in the Viber research hub.
Frequently asked questions
Do blank gender and age fields mean there is no Viber account?
No. They only mean those analysis values were not returned and cannot replace a Viber registration result.
Does a people count of zero mean there is no avatar?
Not necessarily. An image may exist without a detectable suitable person. Review the avatar, avatar type, and task status together.
Can nickname be the unique customer identifier?
It should not. Nicknames can repeat, change, or remain blank. Preserve the phone and source relationship for reconciliation.
Can I upload the Excel file directly?
The current input is TXT. Excel is the result export and downstream review format.
Coverage is useful when every value remains traceable
Keeping source keys, profile data, status, image source, and analysis in separate layers makes provenance visible. Missing values and timestamps are part of that evidence and should not be replaced with guesses for cosmetic completeness.
