Our data · ad tech
Global Ad Tech file
Built from our global contact database, email exhaust exchange, and company crawler network, the Global Ad Tech file nearly doubles the reach of the contact database alone. While personally identifiable information has been removed, the file retains key B2B targeting attributes such as job title, department, industry, company size, and revenue.
197,417,818 records across 252 countries, keyed on a hashed personal email address rather than a name — built for audience onboarding and programmatic targeting, not for prospecting a named individual.
Attributes on the file
25 fields. The count is the number of records carrying that attribute.
| Attribute | Type | Description | Records |
|---|---|---|---|
| personal_email_md5_hash | string | The personal email address of the contact hashed in lowercase MD5 format | 197,417,818 |
| web_source_url | string | Webpage where email address was identified | 35,590,168 |
| is_decision_maker | boolean | TRUE if contact has decision making authority | 67,091,573 |
| job_title_level picklist | string | The level of the contact's Job Title | 45,881,399 |
| job_function picklist | string | The function or department of the contact's Job Title | 92,281,514 |
| interests | array(string) | The inferred interests of the contact (top 250) | 21,773,494 |
| skills | array(string) | The inferred business skills of the contact (top 250) | 66,782,442 |
| gender | string | The inferred gender of the contact: M / F | 118,595,173 |
| personal_country picklist | string | The country where the contact works | 163,789,585 |
| personal_region picklist | string | The region / state / province where the contact works | 126,406,472 |
| personal_city | string | The city where the contact works | 149,012,504 |
| metro_area picklist | string | The US metro area where the contact works in City, State format | 12,504,348 |
| company_name | string | The name of the contact's current employer | 143,769,318 |
| company_domain | string | The website of the contact's current employer | 103,878,145 |
| company_sector picklist | string | The sector of the contact's current employer | 100,245,233 |
| company_industry picklist | string | The industry of the contact's current employer | 101,047,305 |
| company_naics_code_6_2022 picklist | string | The 2022 6 digit NAICS code of the contact's current employer | 100,539,265 |
| company_city | string | The city where the contact's current employer is headquartered | 99,529,320 |
| company_region picklist | string | The region / state / province code where the contact's current employer is headquartered | 77,403,133 |
| company_region_code picklist | string | The region / state / province where the contact's current employer is headquartered | 68,644,333 |
| company_country picklist | string | The country where the contact's current employer is headquartered | 94,164,259 |
| company_employee_size_range picklist | string | The estimated range of employees of the contact's current employer | 86,461,891 |
| company_revenue_range picklist | string | The estimated annual revenue range of the contact's current employer in US dollars | 86,321,314 |
| education_level picklist | string | The highest level of education of the contact | 0 |
| personal_email_sha256_hash | string | The personal email address of the contact hashed in lowercase SHA 256 format | 197,417,818 |
The key is a hashed personal email address. No name, no plain-text email, no phone number. That is what makes the file usable for audience onboarding while keeping personally identifiable information out of it.
Where the records are
Top 20 of 252 countries by record count.
| Country | Records | Decision makers | With job function | With company name |
|---|---|---|---|---|
| United States | 88,397,052 | 25,523,181 | 27,326,495 | 53,200,503 |
| India | 11,861,563 | 4,133,980 | 3,794,120 | 6,345,982 |
| Brazil | 7,660,701 | 2,374,766 | 672,313 | 3,624,269 |
| United Kingdom | 5,827,036 | 2,040,563 | 1,828,657 | 3,757,301 |
| Canada | 4,277,388 | 1,413,315 | 1,046,349 | 2,801,389 |
| France | 3,787,298 | 1,442,882 | 388,765 | 2,406,385 |
| Italy | 3,398,175 | 1,440,883 | 475,777 | 1,773,834 |
| Germany | 2,460,595 | 1,533,481 | 312,317 | 1,907,351 |
| Netherlands | 2,451,191 | 712,144 | 483,398 | 1,808,264 |
| Mexico | 2,444,622 | 1,299,976 | 286,138 | 749,840 |
| Australia | 2,374,148 | 858,304 | 749,097 | 1,492,772 |
| Spain | 2,357,135 | 823,765 | 421,355 | 1,297,920 |
| Indonesia | 1,343,699 | 727,833 | 257,662 | 613,102 |
| China | 1,041,107 | 501,540 | 320,278 | 656,924 |
| South Africa | 1,002,495 | 400,546 | 261,707 | 520,643 |
| Belgium | 967,451 | 357,253 | 184,846 | 614,565 |
| Russia | 960,478 | 801,965 | 72,329 | 824,310 |
| Argentina | 923,896 | 604,744 | 81,433 | 465,904 |
| Poland | 882,904 | 619,978 | 112,433 | 535,915 |
| Turkey | 863,796 | 446,719 | 133,530 | 514,030 |
Controlled vocabularies
Fourteen of the attributes are picklisted, so a segment means the same thing every time it is built.
19
Job functions
15
Title levels
4
Education levels
384
Metro areas
71
Regions
434
Industries and sectors
7
Revenue ranges
8
Employee size ranges
374
2022 NAICS codes
Industries, sectors and NAICS align with the taxonomies used across the rest of the platform — see the 2022 NAICS lookup and the industry counts.
How it is built
Three sources feed the file: the global contact database, the email exhaust exchange, and the company crawler network. Combining them reaches records that the contact database alone does not hold.
Personally identifiable information is stripped before delivery. What remains is the B2B targeting frame — seniority, function, employer, firmographics and location — against a hashed key you can match to your own audience.
Delivered as a flat file on an annual subscription with monthly updates. See pricing, or ask for a count against the segment you actually target.
Start with the number.
Tell us the segment you actually sell to and we will send the exact count, the fill rates for that slice, and a sample — before anyone asks you for a budget.