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Documentation Index

Fetch the complete documentation index at: https://docs.revenuebase.ai/llms.txt

Use this file to discover all available pages before exploring further.

The organizations table contains organization-level records with firmographic data. Use it for account targeting, ICP filtering, segmentation, and enriching your CRM with organization-level attributes. One row per organization; join to contacts and insights via RBID.

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Where data comes from

Organization records are built from public profiles, websites, regulatory filings, and third-party data providers. Industry and size are normalized for consistent filtering. Location and financials are updated with each release; fill rates for revenue and funding are higher for public and venture-backed organizations.

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Organization counts by region

The map below shows current organization counts by country. Use it to understand coverage and plan account-based campaigns by region.

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Table stats

MetricValue
Total recordsSee map above; updated with each release
Update frequencyMonthly (new delivery on the 1st of each month)
Primary keyRBID
Main foreign keyVELOCITY_BASE_UNLIMITED_LATEST.rbid_org and INSIGHTS_LATEST.rbid_org join here

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Data dictionary

Fill rate is the percentage of rows where a field is non-null. Rates vary by segment (e.g. US and public organizations often have higher fill rates for financials and industry).

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Identifiers

FieldDescriptionExample
RBIDRevenueBase’s unique identifier for an organization. The same value is placed in a field RBID_ORG of people datasetrb-oacksydgz
DOMAINDomain of the organization’s websitecompany.com
WEBSITEOrganization URLhttps://www.company.com
LINKEDIN_URLLinkedIn URL for the organizationhttps://www.linkedin.com/company/company_name
LINKEDIN_URL_IDLinkedIn unique identifier for the organization76647045

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Organization basics

FieldDescriptionExample
COMPANY_NAMEName of the organizationDell Technologies
COMPANY_NAME_LANGUAGEThe language the name of the organization is writtenen
ABOUT_USDescription of the organizationUpstream Fullvision is a full service design firm in Honolulu Hawaii. Specializing in homes and small business design, 3D rendering/virtual tour, graphic design and beyond. Upstream Fullvision will provide the best service to turn your concept into reality.
COMPANY_ENTITY_TYPELegal entity type of the organizationPrivately Held
COMPANY_LEGAL_TYPELegal type of the organization[ ""Corporation"" ]
FOUNDEDYear of the organization’s founding1997
PHONEContact phone number for the organization+1 972-000-0000
IS_LINKEDIN_URL_CLAIMEDIndicates if the LinkedIn URL is claimed by the organizationTRUE
IS_WEBSITE_FOR_SALEIndicates if the website is listed for saleFALSE

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Industry & classification

FieldDescriptionExample
INDUSTRY_LINKEDINIndustry description from LinkedIn[ ""Software Development"" ]
INDUSTRY_NAICS_CODENAICS Code[ ""484121"", ""541512"", ""541511"", ""561499"" ]
INDUSTRY_NAICS_DESCRIPTIONNAICS Description[ ""General Freight Trucking, Long-Distance, Truckload"", ""Computer Systems Design Services"", ""Custom Computer Programming Services"", ""All Other Business Support Services"" ]
INDUSTRY_SIC_CODEStandard Industrial Classification code[ ""7373"" ]
INDUSTRY_SIC_DESCRIPTIONStandard Industrial classification description[ ""Computer systems design"" ]
SPECIALTIESSpecialties or key areas of focus of the organization[ ""technology"", ""education and implementation"", ""data synchornization"", ""product data management"", ""advisory services"", ""innovation"", ""data quality analytics"" ]

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Size & financials

FieldDescriptionExample
EMPLOYEE_COUNT_MINMinimum number of employees5001
EMPLOYEE_COUNT_MAXMaximum number of employees10000
EMPLOYEE_COUNT_RANGERange of employee count5001 to 10000
EMPLOYEE_PROFILES_ON_LINKEDINNumber of employee profiles in LinkedIn7196
REVENUE_MINMinimum revenue of the organization1000000
REVENUE_MAXMaximum revenue of the organization9999999
REVENUE_RANGERange of the organization’s revenue$50M to <$100M
LINKEDIN_FOLLOWERSNumber of LinkedIn followers for the organization2039

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Addresses

FieldDescriptionExample
LOCATION_STREETStreet address of the organization’s location2440 Sand Hill Rd 300
LOCATION_CITYCity where the organization is locatedNew York
LOCATION_STATE_NAMEState name of the organization’s locationCalifornia
LOCATION_STATE_CODEState code of the organization’s locationCA
LOCATION_POSTCODEPostal code of the organization’s location94612
LOCATION_COUNTRY_NAMECountry name of the organization’s locationUnited States
LOCATION_COUNTRY_CODECountry code of the organization’s locationUS
LOCATION_COUNTRY_REGIONRegion of the organization’s locationNORAM
LOCATION_CONTINENTContinent of the organization’s locationNorth America
LOCATION_IS_PRIMARYIndicates if the location is the primary oneTRUE
LOCATION_COUNTNumber of locations associated with the organization1
HEADQUARTERS_CITYCity where the organization’s HQ is locatedNew York
HEADQUARTERS_STATE_NAMEState where the organization’s HQ is locatedNY
HEADQUARTERS_COUNTRY_NAMECountry where the organization’s HQ is locatedUnited States
Location vs. Headquarters: For small organizations, location and HQ fields may point to the same address. For organizations with multiple branches, the LOCATION_* fields represent one of the locations listed on the organization’s LinkedIn page, while HEADQUARTERS_* fields are derived from the headquarters information on the LinkedIn organization page.

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Metadata

FieldDescriptionExample
RBIDRevenueBase internal key for cross-table joinsrb-oacksydgz

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Joining this table

Join org_latest to per_latest on RBID = RBID_ORG to attach firmographics to people. Join to insights_latest on RBID = RBID_ORG to attach buying signals and technographics.

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Organization + Person (accounts with decision-makers)

SELECT
    co.RBID,
    co.COMPANY_NAME,
    co.DOMAIN,
    co.INDUSTRY_LINKEDIN,
    co.EMPLOYEE_COUNT_MAX,
    COUNT(c.RBID) AS contact_count
FROM RELEASE.ORG_LATEST co
JOIN RELEASE.PER_LATEST c ON c.RBID_ORG = co.RBID
WHERE co.INDUSTRY_LINKEDIN LIKE '%Software%'
  AND co.EMPLOYEE_COUNT_MAX BETWEEN 50 AND 500
GROUP BY co.RBID, co.COMPANY_NAME, co.DOMAIN, co.INDUSTRY_LINKEDIN, co.EMPLOYEE_COUNT_MAX
HAVING COUNT(c.RBID) >= 1;

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Organization + Insights (firmographics + signals)

SELECT
    co.COMPANY_NAME,
    co.DOMAIN,
    co.INDUSTRY_LINKEDIN,
    co.EMPLOYEE_COUNT_MAX,
    i.CRM_TECH_ORG,
    i.SALES_ROLE_COUNT_ORG,
    i.HAS_CIO_ORG,
    i.LAST_FUNDING_AMOUNT_ORG
FROM RELEASE.ORG_LATEST co
LEFT JOIN RELEASE.INSIGHTS_LATEST i ON co.RBID = i.RBID_ORG
WHERE co.EMPLOYEE_COUNT_MAX BETWEEN 100 AND 1000;

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How to calculate fill rates

Use this pattern to compute fill rates for any field or segment. Replace the sample fields with the columns you care about. 
SELECT
    COUNT(*) AS total_records,
    ROUND(COUNT(DOMAIN) * 100.0 / COUNT(*), 1) AS domain_fill_pct,
    ROUND(COUNT(INDUSTRY_LINKEDIN) * 100.0 / COUNT(*), 1) AS industry_fill_pct,
    ROUND(COUNT(EMPLOYEE_COUNT_MAX) * 100.0 / COUNT(*), 1) AS employee_count_fill_pct,
    ROUND(COUNT(HEADQUARTERS_COUNTRY_NAME) * 100.0 / COUNT(*), 1) AS hq_country_fill_pct
FROM RELEASE.ORG_LATEST;

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Sample queries

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Find target accounts by ICP (mid-size software in the US)

What you’re finding: Organizations that match your ideal customer profile so you can build an account list or sync to a CRM. Why these fields: industry and employee_count define ICP; revenue_range adds budget signal. hq_city and hq_state support territory or regional campaigns. We select only the columns you’d need for account creation or routing. Logic: Filter by industry, size band, country, and revenue band. Order by employee_count to prioritize larger accounts within the band. 
SELECT
    COMPANY_NAME,
    DOMAIN,
    INDUSTRY_LINKEDIN,
    EMPLOYEE_COUNT_MAX,
    REVENUE_RANGE,
    HEADQUARTERS_CITY,
    HEADQUARTERS_STATE_NAME,
    HEADQUARTERS_COUNTRY_NAME,
    HEADQUARTERS_COUNTRY_CODE
FROM RELEASE.ORG_LATEST
WHERE 
(INDUSTRY_LINKEDIN LIKE '%Software%' OR INDUSTRY_LINKEDIN LIKE '%Information Technology%')
  AND EMPLOYEE_COUNT_MAX BETWEEN 50 AND 500
  AND HEADQUARTERS_COUNTRY_CODE = 'US'
  AND REVENUE_RANGE IN ('$10M to <$50M')
ORDER BY EMPLOYEE_COUNT_MAX DESC NULLS LAST;

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Normalize LinkedIn URN

What you’re finding: The LINKEDIN_URL_ID field contains LinkedIn’s numeric organization identifier. Some integrations (e.g. LinkedIn Ads, Sales Navigator APIs) require the full URN format (urn:li:organization:<id>) rather than the raw ID or URL. Why these fields: LINKEDIN_URL_ID is the source value; the query constructs the URN by prepending the standard LinkedIn organization URN prefix. Rows without a LINKEDIN_URL_ID are excluded. 
SELECT
    RBID,
    COMPANY_NAME,
    LINKEDIN_URL,
    LINKEDIN_URL_ID,
    'urn:li:organization:' || LINKEDIN_URL_ID AS LINKEDIN_URN
FROM RELEASE.ORG_LATEST
WHERE LINKEDIN_URL_ID IS NOT NULL;

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Check fill rates for a segment

What you’re finding: How complete key fields are for a subset (e.g. one industry or region) so you know what to expect when building lists. Why these fields: Same as the global fill-rate query, but with a WHERE clause so percentages reflect only the segment you care about. 
SELECT
    COUNT(*) AS total_records,
    ROUND(COUNT(DOMAIN) * 100.0 / COUNT(*), 1) AS domain_fill_pct,
    ROUND(COUNT(INDUSTRY_LINKEDIN) * 100.0 / COUNT(*), 1) AS industry_fill_pct,
    ROUND(COUNT(EMPLOYEE_COUNT_MAX) * 100.0 / COUNT(*), 1) AS employee_count_fill_pct,
    ROUND(COUNT(REVENUE_MAX) * 100.0 / COUNT(*), 1) AS revenue_fill_pct
FROM RELEASE.ORG_LATEST
WHERE HEADQUARTERS_COUNTRY_NAME = 'United States'
  AND INDUSTRY_LINKEDIN LIKE '%Software%';