Revelio Labs alternatives for workforce data

Workforce data answers two questions that are easy to confuse. Supply: who works at a company, in which roles, and how many joined or left. Demand: which roles the company is trying to fill now. Revelio Labs models supply from online professional profiles and holds demand in a postings dataset. It is built for headcount by role, attrition, talent flows and the pay of people already employed. Fokals is built for demand: hiring data recorded daily from each company's own careers pages, every role labelled by job function and seniority, on the same company ID as technographic, intent and announcement data.

This page describes what Revelio Labs offers, why some teams look further, which measure comes from which kind of source, and four alternatives. Statements about other companies were checked against their own pages on 4 October 2026 and are linked. Fokals is delivered direct, by REST API and as bulk files, which you load into your own warehouse.

What Revelio Labs offers

Revelio Labs calls itself a workforce research and data company. Its company page says it uses data science and statistical modelling to turn public employment records into workforce data, drawing on public profiles, job postings, sentiment reviews and layoff notices.

Its data page lists six datasets.

• Workforce Dynamics. Headcount with inflows and outflows for each position at each company, cut by role, seniority, geography, salary, education, skills, gender and ethnicity.
• Transitions. Moves of employees between companies and industries.
• Job Postings. COSMOS, a postings dataset drawn from employer websites, the major job boards and the boards of staffing firms, with duplicates removed.
• Sentiment. Employee reviews, with ratings and text.
• Layoff Notices. Notices of mass layoffs and plant closures registered under the WARN Act.
• Individual. The work history of each individual: roles, skills, salary, education and demographics.

The methods are published in its data dictionary. Because some occupations and places are more likely than others to appear in profiles, it weights the sample to correct for occupation and location. Because people can be slow to update a profile after a move, a nowcasting model estimates recent inflows and outflows. A salary model predicts the pay of each position, gender is predicted from first names, and ethnicity from names and location.

Delivery takes three forms, according to its FAQ: an API that answers by request, a data feed delivered monthly, and the Revelio Terminal, its interface for insights. The FAQ gives the usual delivery day as the 15th of the month, for the month before. The Terminal page says the data goes back to 2008. Revelio Labs also publishes Revelio Public Labor Statistics, a free monthly release on the US labour market.

Why a team looks for an alternative

The reasons are about fit, and each is a question to put to any vendor, Fokals included.

• A different kind of data. The question is demand: which roles are open this week, by function and country. Postings answer that directly, and a model of the existing workforce answers a different question.
• Company-level data. Some teams work with company-level records only, whatever the source, and want a dataset that is company-level throughout.
• Observed or modelled. A research process may require inputs that are counts of things observed, each with its source and its observation time.
• Delivery. The pipeline wants daily datasets through a REST API, or the opposite: a monthly panel loaded once.
• Licence fit. The data is going into a product or on to clients, and the agreement has to name that use.

Revelio Labs and Fokals side by side

Each cell restates what the vendor says publicly.

What each is built for

• The composition of a workforce. Revelio Labs measures headcount with inflows and outflows for each position at each company, and follows the moves of employees between companies and industries.
• A long monthly panel. Its Terminal page says the data goes back to 2008, and its FAQ describes a data feed delivered monthly.
• Sentiment and layoff notices. Employee reviews and notices registered under the WARN Act are datasets of their own on its data page.
• Demand as the company publishes it. Fokals records every role a company publishes on its own careers pages and delivers daily counts of open, new and closed postings for each company, written once after the day closes and never revised.
• Labels ready for analysis. Each posting is labelled by job function, seniority and ten role flags, with its location, work mode, advertised pay on one annual US-dollar scale and the tools it names. The labels are produced under named, frozen versions, so a series built on them stays comparable from week to week.
• The sales organisation in detail. Sales Team Metrics gives weekly metrics on each company's sales organisation, and Sales Pay Benchmarks gives pay quartiles for sales roles by role and country.
• One company index. Hiring joins to Technology Stack, Intent Scores, Company News and Employee Headcount on the same company ID, and a listed company carries its ticker, MIC, ISIN, LEI and share-class FIGI.

Which measure comes from which source

Most disagreements between a workforce dataset and a postings dataset come from asking one for the other's measure. Workforce Dynamics, Transitions and Sentiment are the Revelio Labs measures of the people a company employs: headcount by role and seniority, joiners and leavers, where leavers go, and employee sentiment. The table sets out the measures of size, demand, pay and restructuring that both sources carry. The Revelio Labs column uses the names its data page and data dictionary give. The Fokals column names datasets in the hiring dataset and its neighbours.

A worked measure: hiring intensity

Open postings mean most when they are set against the size of the company. With a profile-based source you divide by modelled headcount. With Fokals you divide by the latest stated count in Employee Headcount, which carries the date each count refers to. The query keeps to one kind of stated count so that every company is measured alike, takes the latest count for each company and sets Hiring Activity beside it on a closed day of your choice.

with latest as (
  select
    company_id,
    employees,
    as_of,
    row_number() over (partition by company_id order by as_of desc) as rn
  from company_headcounts
  where source = 'sec_10k'
)
select
  h.company,
  h.open_postings,
  l.employees,
  l.as_of,
  round(100.0 * h.open_postings / l.employees, 1) as open_per_100_employees
from company_hiring_daily h
join latest l
  on l.company_id = h.company_id
 and l.rn = 1
where h.day = :as_of
  and l.employees > 0
order by open_per_100_employees desc;

Acme Robotics, an illustrative company with 2,000 employees stated at its last year end and 90 open postings, shows 4.5 open roles per 100 employees. Read the figure with the date of the count beside it: each count is a stated fact as of its own date, so the ratio rests on two dated observations that a reviewer can check. Whether 4.5 is high depends on the company's own past and on its sector, which the weekly Market Series give on same-store cohorts.

Two points decide how to read the result. A posting records an intention to hire, so the series measures demand as the company itself publishes it, and it tends to move before headcount does. Pay is the pay an employer advertises, set on one annual US-dollar scale so that roles compare across countries; the guide to benchmarking pay and talent demand puts it to work.

The data is company-level throughout. A posting is the record of a role, and a leadership change in Company News is recorded by the role concerned. The sourcing statement is the document for a compliance review.

Other sources of workforce and hiring data

None of these was tested for this guide: each line says only what the vendor states on its own site.

• Lightcast. Lightcast describes labour market data built from job postings, professional profiles and government statistics, delivered by API, cloud storage, data shares and SFTP.
• LinkUp. LinkUp sells job market data collected from employer websites, with job records its product page dates from 2007. The guide to LinkUp alternatives covers it.
• Coresignal. Coresignal describes company, employee and job posting records collected from the public web, by API or as datasets. The guide to Coresignal alternatives covers it.
• People Data Labs. People Data Labs documents bulk person datasets licensed by the year and delivered to cloud storage, beside its Person Enrichment API and Company Enrichment API. The guide to People Data Labs alternatives covers it.

Choosing by the question

Frequently asked questions

The queries and code on this page are examples to adapt. Test them in your own environment before you rely on them.

What this page says about the products it names was checked against their public documentation on 4 October 2026. Product and company names are trademarks of their owners. Fokals is not affiliated with them or endorsed by them.