national_id | id_type | names_1.name | names_1.last_seen | names_2.name | names_2.last_seen | names_3.name | names_3.last_seen | gender | dob | addresses_1.address | addresses_1.postcode | addresses_1.last_seen | addresses_2.address | addresses_2.postcode | addresses_2.last_seen | addresses_3.address | addresses_3.postcode | addresses_3.last_seen | phones_1.phone | phones_1.type | phones_1.last_seen | phones_2.phone | phones_2.type | phones_2.last_seen | phones_3.phone | phones_3.type | phones_3.last_seen | emails_1.name | emails_1.last_seen | emails_2.name | emails_2.last_seen | emails_3.name | emails_3.last_seen |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
xxxxxxxxxxxxxxxx | xxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxx | xxxxxxxxxx |
xxxxxxxxxxxxxxxx | xxx | xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxx | xxxxxxxxxx |
xxxxxxxxxxxxxxxx | xxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxx | xxxxxxxxxx |
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xxxxxxxxxxxxxxxx | xxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxx | xxxxxxxxxx |
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xxxxxxxxxxxxxxxx | xxx | xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxx | xxxxxxxxxx |
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xxxxxxxxxxxxxxxx | xxx | xxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxx | xxxxxxxxxx |
xxxxxxxxxxxxxxxx | xxx | xxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxxx | xxxx | xxxxxxxxxx | xxxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxx | xxxxxxxxxx |
Attribute | Type | Example |
---|---|---|
national_id | Integer | 8009094425214905 |
id_type | String | NIK |
names_1.name | String | Calista A. |
names_1.last_seen | DateTime | 2024-12-15T00:00:00+00:00 |
names_2.name | String | Calista Ardianto |
names_2.last_seen | DateTime | 2024-11-15T00:00:00+00:00 |
names_3.name | String | Cal. Ardianto |
names_3.last_seen | DateTime | 2024-01-15T00:00:00+00:00 |
gender | Boolean | f |
dob | DateTime | 1950-01-08T00:00:00+00:00 |
addresses_1.address | String | Gg. Jamika No. 832 Malang, JK 82470 |
addresses_1.postcode | Integer | 82470 |
addresses_1.last_seen | DateTime | 2024-06-15T00:00:00+00:00 |
addresses_2.address | String | Jalan Jend. Sudirman No. 24 Pangkalpinang, JK 96575 |
addresses_2.postcode | Integer | 96575 |
addresses_2.last_seen | DateTime | 2024-04-15T00:00:00+00:00 |
addresses_3.address | String | Gang Jakarta No. 210 Surakarta, JK 53000 |
addresses_3.postcode | Integer | 53000 |
addresses_3.last_seen | DateTime | 2024-01-15T00:00:00+00:00 |
phones_1.phone | Float | 7079278744.0 |
phones_1.type | String | HOME |
phones_1.last_seen | DateTime | 2024-12-15T00:00:00+00:00 |
phones_2.phone | Integer | 620266181764 |
phones_2.type | String | HOME |
phones_2.last_seen | DateTime | 2024-11-15T00:00:00+00:00 |
phones_3.phone | Integer | 625129425711 |
phones_3.type | String | HOME |
phones_3.last_seen | DateTime | 2024-01-15T00:00:00+00:00 |
emails_1.name | String | skywalker866@email.com |
emails_1.last_seen | DateTime | 2024-11-15T00:00:00+00:00 |
emails_2.name | String | calista0108@email.com |
emails_2.last_seen | DateTime | 2024-09-15T00:00:00+00:00 |
emails_3.name | String | calista1950@email.com |
emails_3.last_seen | DateTime | 2024-01-15T00:00:00+00:00 |
Description
Living Identity™ Southeast Asia (Demographic Data): Verified Identity and Lifestyle Intelligence Across 5 High-Growth Markets Living Identity™ Southeast Asia provides access to 401 million verified consumer profiles across five of the fastest-growing Southeast Asian economies. Combining structured identity verification with rich lifestyle, location, and demographic data, this multi-country dataset is purpose-built for marketing strategy, audience analytics, KYC, and consumer intelligence applications. Key Features: • Volume: 401,000,000 verified records • Coverage: 5 strategic Southeast Asian countries • Historical Depth: 6 months of current, refreshed data • Attributes: Full name, address, phone, email, government ID (where available), geo-coded location, lifestyle behaviors, consumer interests • Location Precision: Geo-coded at high accuracy Data Storage: Fully on-premise, with secure, compliant architecture What’s Inside: Profiles are structured around core identity data and enhanced with mobility, lifestyle segmentation, demographic classification, and public sector insights. This enables real-world, cross-channel consumer targeting, onboarding, and marketing optimization. Primary Use Cases: • Marketing Strategy and Data-Driven Campaign Design • Location-Based Audience Analytics • Consumer Intelligence for Product and Market Expansion • Real-Time KYC and Identity Verification • Cross-Sell/Upsell Strategy Based on Lifestyle and Affluence Indicators Ideal For: • Marketing and Media Agencies • Retailers, E-Commerce Platforms, and Payment Companies • Customer Intelligence and Analytics Teams • Audience Modeling and Predictive Analytics Specialists • Financial Services Firms Targeting Southeast Asia Data Quality and Compliance: Living Identity™ Southeast Asia is built with regulatory alignment to GDPR, LGPD, PDPA, and relevant national frameworks, ensuring lawful data sourcing, privacy-first practices, and operational security. Pricing and additional samples available upon request.
Country Coverage
(5 countries)Data Categories
- Demographic Data
- Location Data
- Consumer Behavior Data
- Geodemographic Data
- Identity Data
Pricing
Volumes
- Records
- 401M
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