Every field in the Investor Interest Signals, its type, and what it means.
All 29 fields of the Investor Interest Signals, grouped by category.
Names are the Parquet field names; the CSV delivery uses its own column
headers, listed under CSV column names.
Every field may be null unless marked required. Today strategic_signal_id is guaranteed.
Under each type is the column’s Parquet type, as DuckDB names it: VARCHAR is
a string, BIGINT a 64-bit integer, DOUBLE a 64-bit float, and [] a list.
Each category ends with its full Parquet schema, ready to copy.
Signal score from Specter’s proprietary algorithm, 1 to 10, with 10 the highest. Based on signal source, signal strength and company performance.
source_type
string VARCHAR
Based on signal source. A signal with several sources lists each, separated by ; . One of venture capital, insider, private equity, investment bank, angel, journalist, influencer.
signal_type
string VARCHAR
Whether the signal is about a company or a person. One of Talent, Company.
signal_source
string VARCHAR
The VC firm, corporation, or individual that is the source of the signal.
signal_summary
string VARCHAR
Brief on the investor activity and what the company does.
Name of the company or person the signal is about.
website
string VARCHAR
Company website URL or LinkedIn personal profile URL in case of a Signal Type = Talent.
screenshot
string VARCHAR
Company website screenshot.
hq_location
string VARCHAR
City-level location of the company’s headquarters.
hq_region
string VARCHAR
Region the company’s headquarters sits in. One of Africa, Asia, Oceania, Canada, Europe, LATAM, MENA, United States, Russia.
growth_stage
string VARCHAR
Stage the company has reached in its growth. One of Pre-Launch, Bootstrapped, Early Stage, Growth Stage, Late Stage.
company_linkedin_url
string VARCHAR
URL of the company’s LinkedIn page.
twitter_url
string VARCHAR
URL of the company’s X (Twitter) profile.
talent_github_url
string VARCHAR
GitHub profile URL (only available when Signal Type = Talent)
contact_email
string VARCHAR
Recommended contact email address for the person behind the signal.
company_description
string VARCHAR
Short description of what the company does.
company_founded_year
integer SMALLINT
Company founded date.
customer_focus
string VARCHAR
This data point categorizes companies based on their primary and secondary customer engagement models. One of B2B, B2C, B2B,B2C, B2C,B2B.
specter_industry
array<string> VARCHAR[]
Classifies companies by their economic activity — the market they serve and the products or services they deliver. E.g: Construction, Utilities, Wholesale There is one industry per company, with up to three levels.
specter_tech_verticals
array<array<string>> VARCHAR[][]
Classifies companies by the technology domain they operate in — the technical capability or space they’re building around. E.g: AI & Machine Learning, Cybersecurity, FinTech. There can be up to 5 tech verticals per company, with 2 levels each.
is_industry_estimated
boolean BOOLEAN
True if new position industry and tech verticals are estimated.
The CSV delivery carries the same fields under the headers below. Parquet,
JSONL and the API all use the field name.
Field
CSV column
strategic_signal_id
Specter - Strategic Signal ID
specter_person_id
Specter - Person ID
company_id
Specter - Organization ID
signal_date
Signal Date
signal_score
Signal Score
source_type
Source Type
signal_type
Signal Type
signal_source
Signal Sources
signal_summary
Signal Summary
name
Name
website
Website
screenshot
Screenshots
hq_location
HQ Location
hq_region
HQ Region
growth_stage
Growth Stage
company_linkedin_url
LinkedIn - URL
twitter_url
Twitter - URL
talent_github_url
GitHub - URL
contact_email
Email
company_description
Description
company_founded_year
Founded
customer_focus
Customer Focus
specter_industry
Industry
specter_tech_verticals
Tech Verticals
is_industry_estimated
Is Industry Estimated
company_funding_amount_usd
Total Funding Amount (in USD)
company_last_funding_date
Last Funding Date
company_last_funding_amount_usd
Last Funding Amount (in USD)
company_investors
Investors
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screenshot.`})]}),_jsxs(_components.tr,{children:[_jsx(_components.td,{children:_jsx(_components.code,{children:`hq_location`})}),_jsxs(_components.td,{children:[_jsx(_components.code,{children:`string`}),_jsx(`br`,{}),_jsx(`code`,{className:`parquet-type`,children:`VARCHAR`})]}),_jsx(_components.td,{children:`City-level location of the company’s headquarters.`})]}),_jsxs(_components.tr,{children:[_jsx(_components.td,{children:_jsx(_components.code,{children:`hq_region`})}),_jsxs(_components.td,{children:[_jsx(_components.code,{children:`string`}),_jsx(`br`,{}),_jsx(`code`,{className:`parquet-type`,children:`VARCHAR`})]}),_jsxs(_components.td,{children:[`Region the company’s headquarters sits in. One of `,_jsx(_components.code,{children:`Africa`}),`, `,_jsx(_components.code,{children:`Asia`}),`, `,_jsx(_components.code,{children:`Oceania`}),`, `,_jsx(_components.code,{children:`Canada`}),`, `,_jsx(_components.code,{children:`Europe`}),`, `,_jsx(_components.code,{children:`LATAM`}),`, `,_jsx(_components.code,{children:`MENA`}),`, `,_jsx(_components.code,{children:`United States`}),`, `,_jsx(_components.code,{children:`Russia`}),`.`]})]}),_jsxs(_components.tr,{children:[_jsx(_components.td,{children:_jsx(_components.code,{children:`growth_stage`})}),_jsxs(_components.td,{children:[_jsx(_components.code,{children:`string`}),_jsx(`br`,{}),_jsx(`code`,{className:`parquet-type`,children:`VARCHAR`})]}),_jsxs(_components.td,{children:[`Stage the company has reached in its growth. 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One of `,_jsx(_components.code,{children:`B2B`}),`, `,_jsx(_components.code,{children:`B2C`}),`, `,_jsx(_components.code,{children:`B2B,B2C`}),`, `,_jsx(_components.code,{children:`B2C,B2B`}),`.`]})]}),_jsxs(_components.tr,{children:[_jsx(_components.td,{children:_jsx(_components.code,{children:`specter_industry`})}),_jsxs(_components.td,{children:[_jsx(_components.code,{children:`array\u003cstring>`}),_jsx(`br`,{}),_jsx(`code`,{className:`parquet-type`,children:`VARCHAR[]`})]}),_jsx(_components.td,{children:`Classifies companies by their economic activity — the market they serve and the products or services they deliver. 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There can be up to 5 tech verticals per company, with 2 levels each.`})]}),_jsxs(_components.tr,{children:[_jsx(_components.td,{children:_jsx(_components.code,{children:`is_industry_estimated`})}),_jsxs(_components.td,{children:[_jsx(_components.code,{children:`boolean`}),_jsx(`br`,{}),_jsx(`code`,{className:`parquet-type`,children:`BOOLEAN`})]}),_jsx(_components.td,{children:`True if new position industry and tech verticals are estimated.`})]})]})]}),`\n`,_jsx(Accordion,{title:`Parquet schema: Company / Personal Data`,icon:`code`,id:`parquet-schema-company-personal-data`,children:_jsx(CodeBlock,{filename:`Company / Personal Data`,numberOfLines:`18`,language:`sql`,children:_jsx(_components.pre,{className:`shiki shiki-themes github-light-default 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Delivered as a string of digits, without a currency symbol or separators.`})]}),_jsxs(_components.tr,{children:[_jsx(_components.td,{children:_jsx(_components.code,{children:`company_last_funding_date`})}),_jsxs(_components.td,{children:[_jsx(_components.code,{children:`date`}),_jsx(`br`,{}),_jsx(`code`,{className:`parquet-type`,children:`DATE`})]}),_jsx(_components.td,{children:`Date of the company’s most recent funding round.`})]}),_jsxs(_components.tr,{children:[_jsx(_components.td,{children:_jsx(_components.code,{children:`company_last_funding_amount_usd`})}),_jsxs(_components.td,{children:[_jsx(_components.code,{children:`string`}),_jsx(`br`,{}),_jsx(`code`,{className:`parquet-type`,children:`VARCHAR`})]}),_jsx(_components.td,{children:`Amount of the company’s most recent funding round, in USD. 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