LinkedIn Datasets
Profiles, companies and hiring signals are the three tables most GTM, talent and research teams actually build on. Every one of them filterable in Data Explorer before you spend a credit.
Data can be accessed via
The catalogue
Pick the LinkedIn dataset you need
Three tables that combine into prospecting, ABM, talent and research workflows.
LinkedIn Company Dataset
60M+ records · 52 fields
idcompany_namecompany_domain+49 moreAll 52 fieldsscrollidcompany_namecompany_domaincompany_linkedincompany_descriptionspecialitiesindustrynaicscodes_v5naics_descriptionsiccodes_v5sic_descriptioncompany_entity_typecompany_legal_type_textheadcount_rangeemployee_on_linkedinemployee_on_linkedin_growth_raterevenue_rangeyear_foundedcompany_hq_countrycompany_hq_stateheadquarters_citycompany_countrycompany_statecompany_citycompany_addresspostcodecountry_regionlocation_countcompany_phonetotal_funding_amountlast_funding_amountlast_funding_datelast_funding_typefunding_round_num_investorslead_investorscompany_technologiesmonthly_google_adspendengineer_role_countdevops_role_countit_role_countit_open_roles_countsecurity_role_countnetwork_infrastructure_role_countqa_role_countmobile_dev_role_countios_dev_role_countandroid_dev_role_countsales_role_countaccount_executive_open_roles_countbusiness_development_role_countmarketing_role_countcustomer_success_role_countBusiness · Global coverage
LinkedIn Profile Dataset
250M+ records · 74 fields
idfull_namelinkedin_url+71 moreAll 74 fieldsscroll_idfull_namefirstnamemiddlenamelastnamelinkedin_urllinkedin_headlinejob_titlejob_descriptionsenioritydepartmentaboutSkillsSpecialitiesbusiness_emailemail_statussecondary_emailcell_phonecountrystatecitycountry_regioncontinentcompany_namecompany_domaincompany_linkedincompany_descriptioncompany_legal_typecompany_entity_typecompany_name_languagecompany_countrycompany_statecompany_citycompany_addresspostcodecompany_phonecompany_hq_countrycompany_hq_statecompany_hq_citylocation_countlinkedin_industrysic_codessic_descriptionnaics_codesnaics_descriptionheadcount_rangerevenue_rangeyear_foundedemployee_on_linkedinemployee_on_linkedin_growth_ratetechnologiesCompany Technologiesmonthly_google_adspendtotal_monthly_trafficmonthly_organic_trafficmonthly_paid_trafficit_open_roles_countbusiness_development_open_roles_countcustomer_success_open_roles_countdemand_generation_open_roles_countdevops_open_roles_countgrc_open_roles_countmarketing_open_roles_countaccount_executive_open_roles_countnetwork_infrastructure_open_roles_countoperations_open_roles_countsales_open_roles_countsecurity_open_roles_countlead_investorstotal_funding_amountlast_funding_amountlast_funding_datefunding_round_num_investorslast_funding_typeBusiness · Popular
LinkedIn Jobs Dataset
32 fields
idjob_titlecompany_name+29 moreAll 32 fieldsscrollidjob_titlecompany_namecompany_linkedin_urlcompany_descriptioncompany_specialitiescompany_industriesheadcount_rangejob_descriptioncompany_hq_country_namecompany_hq_citycompany_hq_streetcompany_hq_state_namecompany_hq_postalcodecompany_locationformatted_employment_statussource_domainformatted_experience_leveljob_locationcompany_apply_urlformatted_job_functionscompensation_typemax_salarymin_salarypay_periodoriginal_posted_timelisted_atexpire_atformatted_industriesindustriesjob_statework_remote_allowedBusiness · Hiring intent
How it works
From first call to working data in four steps
It starts with a short call. You see the row count and the price before you commit. From there, filter and export your dataset in Data Explorer, query it through the API, or have it sent to your own cloud.
Tell us your segment
Industry, geography, seniority, company size, whoever you are trying to reach.
We check our coverage
A specialist checks what Kipplo actually holds for that segment and tells you how many rows match, so you know the data is there before you go any further.
Get your quote
Row count and price, before you commit.
Open your dataset
You get the complete dataset in Data Explorer and through the API, and filter it down yourself. Need it inside your own stack instead? On request we send it to your preferred cloud.
Access
How your team gets the data
Data Explorer and the API are the two ways in, and both read the identical underlying tables. If your team would rather not log in at all, we can send your filtered dataset to your own cloud on request.
Data Explorer
Data Explorer is where your team actually works with the data. Open a dataset in the grid, see the real fields and what is in them, filter down to the rows you want, then export as CSV, Excel, JSON, XML or SQL.
API access
The Kipplo API is the same data without the interface. Query records with the same filters you would use in the grid, and pull the results straight into your own product or workflow.
Delivery to your cloudOn request
Delivery is the exception, not the default route. If your team would rather not log in at all, we send your filtered dataset to your preferred cloud storage, once or on a schedule, in whatever format and structure you already work with.
Use cases
What teams build with it
Three LinkedIn datasets that combine into prospecting, ABM, talent and research workflows.
Prospecting and Lead Generation
Build lists that match your ICP using profiles and firmographics together, then export them with verified contact data already attached.
Account-Based Marketing
Rank your target accounts by headcount, industry and tech stack, then use their open job postings to decide which ones to reach out to now.
Talent Sourcing
Search candidates by job title and department, and see which competitors are hiring for the same roles.
Market and Competitive Research
Size a market by role, industry or geography, and track how it moves quarter over quarter.
Before you ask sales
A Kipplo LinkedIn dataset is a table of company profiles, job postings or people profiles that is already built for you, from public and licensed sources. You get the complete dataset, filter it down to your segment in Data Explorer, and export the rows you need. Filtering and previewing cost nothing. Credits are charged only for the rows you export.
From 50+ verified public and licensed business sources. Every record is publicly available or licensed at the point of collection, never taken from behind a login. The catalogue is maintained in line with GDPR and CCPA, including opt-out handling and an audited DSAR removal pipeline. Our GDPR and CCPA pages carry the detail your legal team will ask for.
Yes. Filtering and previewing in Data Explorer is completely free. Credits are charged when you export rows.
Yes, and that is the normal way to buy. Narrow by industry, headcount, revenue band, geography, seniority, department, technology or posted date, and pick only the columns you need. You see the exact row count and price before you commit to anything.
Continuously. Companies, job postings and profiles are all re-crawled and re-validated on an ongoing basis, so firmographics, hiring signals and role changes stay current.
We measure 95%+ field accuracy. Every record is deduplicated, AI-validated and human-reviewed before it ships, and we publish the real fill rate for every field, including the low ones.
Pricing is row-based, not per data point. Credits are charged per row delivered, so an email or phone attached to a row you already exported costs nothing extra.
Talk to our data experts
Every dataset starts with a short call. Tell us what you are building and a data specialist comes back within one business day.