West Africa AdTech Consumer Database: 1.12M Verified Mobile Users (Nigeria, Ghana, Kenya Focus)
Emerging market mobile-first consumer dataset with 1.12M identities, operator-level intelligence, and female-skewed demographics. Ideal for CPG, fintech, telco, and mobile commerce targeting.
Description
Verified consumer dataset from mobile advertising platform registrations across Nigeria, Ghana, Kenya, Tanzania, and emerging markets. Designed for programmatic advertising campaigns, DMP audience segmentation, and carrier-level mobile targeting in high-growth African economies.
Dataset Overview
This database contains 1,120,526 user records from mobile-first AdTech platform registrations spanning 2019-2024. Nigeria dominates with 521,850 records (46.6%), followed by India (79,850), Ghana (70,677), United States (64,185), Kenya (46,795), Indonesia (30,358), Tanzania (29,963), and South Africa (25,627). Records include verified email addresses, mobile operator detection via MCC-MNC codes, phone numbers (where provided), full demographic attributes, and geographic identifiers.
Strategic Value for African Markets
The dataset exhibits an 84.5% female skew—distinctive in AdTech and particularly valuable for CPG, beauty, household goods, and family-targeted campaigns in African markets where women drive purchasing decisions. The 26-45 age bracket represents 82.1% of dated records, capturing prime consumer spending demographics across Nigeria and West Africa.
Operator-level granularity enables MTN, Airtel, Glo, Safaricom, and AirtelTigo-specific targeting without requiring phone number matches, supporting carrier billing integration and network-level advertising strategies essential for mobile-first African markets. The 390,230 phone-verified records (34.8%) provide high-value targets for SMS and WhatsApp outreach campaigns.
Technical Specifications
Email coverage: 100% (1,120,526 records).
Operator detection: 69.8% (781,941 records) via network infrastructure data.
Phone verification: 34.8% (390,230 records).
Birth date coverage: 100% with standardized YYYY-MM-DD formatting.
Language identification: 86.6% English, enabling standardized creative across Anglophone Africa.
Country codes: ISO 3166-1 alpha-2 format.
Operator codes: Standard MCC-MNC mobile network codes.
Operator detection: 69.8% (781,941 records) via network infrastructure data.
Phone verification: 34.8% (390,230 records).
Birth date coverage: 100% with standardized YYYY-MM-DD formatting.
Language identification: 86.6% English, enabling standardized creative across Anglophone Africa.
Country codes: ISO 3166-1 alpha-2 format.
Operator codes: Standard MCC-MNC mobile network codes.
Unlike generic consumer lists, this dataset enables:
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Multi-channel activation (Email / SMS / Telco-level targeting)
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Emerging market campaign reach
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Female-skewed consumer targeting (84% female)
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Operator-resolved segmentation for carrier-aware campaigns
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Primary coverage includes:
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Nigeria (core market)
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Ghana
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Kenya
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India
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Southeast Asia
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Core demographic concentration:
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Ages 26–45
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Mobile-first users
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Lower-middle to mass-market consumers
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Highly responsive to FMCG, fintech, mobile commerce, and entertainment offers
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This audience is particularly effective for:
✔ Consumer packaged goods (CPG)
✔ Mobile money & fintech
✔ E-commerce expansion
✔ Telco partnerships
✔ NGO / public sector outreach
✔ Mass-market digital services
With:
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1.12M total identities
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390K phone-verified users
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782K operator-resolved users
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This is not just contact data — it is an activation-ready emerging market consumer audience.
DATA SPECIFICATIONS
Column Completeness
| Field | Coverage | Field | Coverage | |
|---|---|---|---|---|
| id | 100.0% | 100.0% | ||
| bdate | 100.0% | sex | 100.0% | |
| lang | 100.0% | country | 100.0% | |
| operator | 69.8% | phone | 34.8% |
Phone Number Analysis
| Category | Count | % | Category | Count | % | |
|---|---|---|---|---|---|---|
| With phone | 390,230 | 34.8% | Without phone | 730,296 | 65.2% | |
| Operator + phone | 339,234 | — | Operator only | 442,707 | 56.6% |
Phone Country Codes (Top 10)
| Country | Records | % | Country | Records | % | |
|---|---|---|---|---|---|---|
| Nigeria | 356,540 | 91.4% | Unknown | 6,879 | 1.8% | |
| Kenya | 6,028 | 1.5% | Ghana | 5,885 | 1.5% | |
| India | 5,279 | 1.4% | Zambia | 1,675 | 0.4% | |
| Uganda | 1,591 | 0.4% | Lithuania | 1,363 | 0.3% | |
| Bangladesh | 1,112 | 0.3% | South Africa | 726 | 0.2% |
Email Domains (Top 12)
| Domain | Records | % | Domain | Records | % | |
|---|---|---|---|---|---|---|
| gmail.com | 769,034 | 68.6% | yahoo.com | 320,770 | 28.6% | |
| ymail.com | 12,029 | 1.1% | outlook.com | 5,288 | 0.5% | |
| live.com | 3,342 | 0.3% | rediffmail.com | 1,823 | 0.2% | |
| icloud.com | 706 | 0.1% | yandex.com | 684 | 0.1% | |
| mail.com | 498 | 0.0% | qq.com | 123 | 0.0% | |
| rediff.com | 114 | 0.0% | protonmail.com | 96 | 0.0% |
Mobile Operators by Code (Top 20)
| MCC-MNC | OP | Records | % | MCC-MNC | OP | Records | % | |
|---|---|---|---|---|---|---|---|---|
| 62130 | MTN Nigeria | 172,904 | 15.4% | 62120 | Airtel Nigeria | 122,281 | 10.9% | |
| 62150 | Glo Nigeria | 90,051 | 8.0% | 62160 | 9mobile Nigeria | 51,608 | 4.6% | |
| 63902 | Safaricom Kenya | 19,768 | 1.8% | 62001 | MTN Ghana | 18,599 | 1.7% | |
| 62002 | Vodafone Ghana | 16,345 | 1.5% | 40402 | Airtel India | 12,263 | 1.1% | |
| 73406 | Other (73406) | 11,339 | 1.0% | 53703 | Other (53703) | 10,826 | 1.0% | |
| 64304 | Other (64304) | 9,800 | 0.9% | 62003 | AirtelTigo Ghana | 8,139 | 0.7% | |
| 234MBR | Other (234MBR) | 8,066 | 0.7% | 40401 | Vodafone India | 7,158 | 0.6% | |
| 64004 | Tigo Tanzania | 7,098 | 0.6% | 51010 | Telkomsel | 6,762 | 0.6% | |
| 64901 | Other (64901) | 6,479 | 0.6% | 40404 | Other (40404) | 6,231 | 0.6% | |
| 62124 | Other (62124) | 6,015 | 0.5% | 65510 | MTN SA | 5,693 | 0.5% |
Mobile Operators by Name (Top 20)
| Operator | Records | % | Operator | Records | % | |
|---|---|---|---|---|---|---|
| MTN Nigeria | 172,904 | 15.4% | Airtel Nigeria | 122,281 | 10.9% | |
| Glo Nigeria | 90,051 | 8.0% | 9mobile Nigeria | 51,608 | 4.6% | |
| Safaricom Kenya | 19,768 | 1.8% | MTN Ghana | 18,599 | 1.7% | |
| Vodafone Ghana | 16,345 | 1.5% | Airtel India | 12,997 | 1.2% | |
| AirtelTigo Ghana | 12,186 | 1.1% | Other (73406) | 11,339 | 1.0% | |
| Other (53703) | 10,826 | 1.0% | Other (64304) | 9,800 | 0.9% | |
| Vodafone India | 8,846 | 0.8% | Other (234MBR) | 8,066 | 0.7% | |
| Tigo Tanzania | 7,098 | 0.6% | Telkomsel | 6,762 | 0.6% | |
| Other (64901) | 6,479 | 0.6% | Other (40404) | 6,231 | 0.6% | |
| Other (62124) | 6,015 | 0.5% | MTN SA | 5,693 | 0.5% |
Countries (Top 20)
| Code | Country | Records | % | Code | Country | Records | % | |
|---|---|---|---|---|---|---|---|---|
| ng | Nigeria | 521,850 | 46.6% | in | India | 79,850 | 7.1% | |
| gh | Ghana | 70,677 | 6.3% | us | United States | 64,185 | 5.7% | |
| ke | Kenya | 46,795 | 4.2% | id | Indonesia | 30,358 | 2.7% | |
| tz | Tanzania | 29,963 | 2.7% | za | South Africa | 25,627 | 2.3% | |
| ve | Venezuela | 19,765 | 1.8% | pg | Papua New Guinea | 16,980 | 1.5% | |
| mz | Mozambique | 15,255 | 1.4% | lt | Lithuania | 14,373 | 1.3% | |
| br | Brazil | 12,568 | 1.1% | na | Namibia | 12,516 | 1.1% | |
| cr | Costa Rica | 10,902 | 1.0% | zm | Zambia | 9,022 | 0.8% | |
| ug | Uganda | 8,805 | 0.8% | vn | Vietnam | 8,718 | 0.8% | |
| pk | Pakistan | 7,406 | 0.7% | eg | Egypt | 7,011 | 0.6% |
Languages (Top 15)
| Lang | Records | % | Lang | Records | % | |
|---|---|---|---|---|---|---|
| en | 970,053 | 86.6% | es | 34,684 | 3.1% | |
| id | 29,917 | 2.7% | pt | 28,271 | 2.5% | |
| fr | 16,936 | 1.5% | lt | 14,476 | 1.3% | |
| ar | 13,506 | 1.2% | vi | 8,656 | 0.8% | |
| bn | 2,873 | 0.3% | hi | 811 | 0.1% | |
| ro | 119 | 0.0% | rs | 76 | 0.0% | |
| th | 49 | 0.0% | cn | 33 | 0.0% | |
| ru | 21 | 0.0% |
Gender Distribution
| Gender | Records | % | Gender | Records | % | |
|---|---|---|---|---|---|---|
| Female | 946,472 | 84.5% | Male | 174,052 | 15.5% |
Age Group Distribution
| Age Group | Records | % | Age Group | Records | % | |
|---|---|---|---|---|---|---|
| 26-35 | 463,818 | 41.8% | 36-45 | 446,290 | 40.3% | |
| 46-55 | 126,721 | 11.4% | 55+ | 61,765 | 5.6% | |
| 18-25 | 10,070 | 0.9% | Under 18 | 53 | 0.0% |
Birth Year Distribution (Top 15)
| Year | Count | % | Age | Year | Count | % | Age | |
|---|---|---|---|---|---|---|---|---|
| 1990 | 84,555 | 7.6% | 36 | 1992 | 77,114 | 7.0% | 34 | |
| 1993 | 65,928 | 5.9% | 33 | 1994 | 64,774 | 5.8% | 32 | |
| 1995 | 60,867 | 5.5% | 31 | 1989 | 57,248 | 5.2% | 37 | |
| 1988 | 56,670 | 5.1% | 38 | 1991 | 55,082 | 5.0% | 35 | |
| 1996 | 48,736 | 4.4% | 30 | 1987 | 48,293 | 4.4% | 39 | |
| 1985 | 47,720 | 4.3% | 41 | 1986 | 46,471 | 4.2% | 40 | |
| 1997 | 35,750 | 3.2% | 29 | 1984 | 33,889 | 3.1% | 42 | |
| 1980 | 33,573 | 3.0% | 46 |
Sample data:
| id | phone | operator | bdate | sex | lang | country | |
|---|---|---|---|---|---|---|---|
| 12580132 | [email protected] | 62120 | 1980-07-05 | F | en | ng | |
| 19821162 | [email protected] | 46689 | 1989-03-19 | F | en | tw | |
| 13131225 | [email protected] | 2349092728065 | 1988-10-01 | F | en | ng | |
| 23869037 | [email protected] | 1996-10-22 | M | en | tz | ||
| 25959772 | [email protected] | 2348111029284 | 62130 | 1984-08-25 | F | en | ng |
| 13158194 | [email protected] | 62150 | 1969-03-02 | F | en | ng | |
| 23994560 | [email protected] | 233266295006 | 1994-11-10 | M | en | gh | |
| 10001211 | [email protected] | 2349092158991 | 62160 | 1977-09-16 | F | en | ng |
| 24838218 | [email protected] | 62130 | 1991-02-14 | F | en | ng | |
| 13423917 | [email protected] | 63903 | 1995-08-30 | F | en | ke | |
| 18150088 | [email protected] | 62120 | 1985-07-17 | F | en | ng | |
| 25588836 | [email protected] | 1989-11-21 | M | en | us | ||
| 19284366 | [email protected] | 40402 | 1992-09-06 | F | en | in | |
| 11989256 | [email protected] | 2347034866144 | 62130 | 1986-02-17 | F | en | ng |
| 2545711 | [email protected] | 2348182490595 | 62120 | 1990-11-14 | F | en | ng |
| 18350644 | [email protected] | 2348182708789 | 62160 | 1996-05-08 | F | en | ng |
| 2534344 | [email protected] | 2349022053605 | 62120 | 1996-03-12 | F | en | ng |
| 21366453 | [email protected] | 2349083944569 | 62130 | 1996-12-22 | F | en | ng |
| 23472222 | [email protected] | 1998-03-25 | F | en | ke | ||
| 23167141 | [email protected] | 1993-06-15 | F | en | ke | ||
| 19968215 | [email protected] | 61001 | 1992-06-12 | F | fr | ml | |
| 19940862 | [email protected] | 2348087578497 | 1989-06-14 | F | en | ng | |
| 12446774 | [email protected] | 62130 | 1987-05-07 | F | en | ng | |
| 20928723 | [email protected] | 40404 | 1988-01-11 | F | en | in | |
| 26198683 | [email protected] | 1999-06-25 | F | en | ng | ||
| 6637836 | [email protected] | 1987-06-28 | F | en | in | ||
| 24235118 | [email protected] | 256777248708 | 64110 | 1992-10-06 | F | en | ug |
| 23418865 | [email protected] | 233261340924 | 62001 | 1992-03-04 | F | en | gh |
| 3803445 | [email protected] | 2348037619490 | 1987-04-23 | F | en | ng |
🔄 Last updated / records refreshed: October 2026
💰 Pricing Tiers
| Tier | Description | Price |
|---|---|---|
| Phone Verified Segment | 390K users with validated mobile numbers suitable for SMS, WhatsApp, and direct-response messaging campaigns. | $1,995 |
| Nigeria Female Core | 310K female mobile-first consumers (ages 26–45) in Nigeria — ideal for FMCG, retail, beauty, and household product targeting. | $1,495 |
| Operator-Resolved Audience | 782K users mapped to mobile carriers, enabling telco-aware targeting and network-level campaign segmentation. | $2,495 |
| Full Emerging Market Audience | 1.12M complete activation-ready identities including email, demographics, and telecom operator intelligence. | $3,995 |
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