Titles

LinkedIn uses machine learning to classify the over 60 million unique job titles entered by members in their profile into standardized titles to make them searchable in Talent Insights. There are more than 25,000+ different standardized titles in our “titles taxonomy” that are searchable in Talent Insights.

For example, Software Engineers on LinkedIn might input their titles as a Software Engineer, SWE, Software Eng. or Software Developer. In this example, all of these member-input titles would roll into the standardized job title “Software Engineer”.

Talent Insights groups related standardized job titles. When searching for a job title such as “Software Engineer” we automatically expand the search to include all related standardized job titles such as “Senior Software Engineer” and “Freelance Software Engineer”.

See diagram below for an example of our “title taxonomy” for Software Engineers.

Skills 

LinkedIn standardizes member-input skills into 35,000+ different standardized searchable skills in our “skills taxonomy”. New skills, technologies, aliases and language translations are added every month to our standardized skills that are searchable in Talent Insights.

The skills you see in Talent Insights reflect explicit, implicit and inferred skills based on member profiles.

• Explicit: Skills that members list within the “skills” section of their member profiles.
• Implicit: Through the application of natural-language processing technology, we are able to read and extract skills from other parts of the member profile including the job title, job descriptions and profile summary. 

Member endorsement of skills are not included in Talent Insights.

Function

LinkedIn determines members’ functions based on their job titles which are mapped to Functions in our “titles taxonomy”. In the Company Report, Talent Insights users are able to see which Titles map to a particular Function by adding a Function to the Company Report search query and then selecting the “Titles” tab.

Companies

Company information on Talent Insights captures data from more than 26 million company profiles on LinkedIn. Basic Company information - such as industry, headquarters location, year of founding and whether the a company private vs. public  - are based on self-reported data within Company LinkedIn pages. All workforce data - including hires, departures (attrition), skills, job titles - are based on member profile information indicating current or past employment at a given company.

Industries

Each company within Talent Insights is mapped to one of 148 different industries. The industry of a company is determined by the industry on the company’s LinkedIn Company Page. Industries for companies are based on the industry a company lists on their LinkedIn Company page.


Industry data surfaced in Talent Insights reflects the industry of company associated with the member’s current position on their profile. For example, a salesperson, software engineer, office manager and accountant that currently work for Microsoft would all map to the Industry “Computer Software” which is the industry of their employer, Microsoft. Members who are not mapped to a company or to a company without an industry, are associated with their self-selected  industry on their profile.

Locations

LinkedIn determines a members’ location using the zipcode/postal code, city, or country that a member provides on their LinkedIn profile.

Members are then mapped into the geo-levels above the level provided. For example, if a member provides a postal code, we can map them to the city that contains that postal code, the Market Area that contains the city and the country that contains the Market Area.

Market Areas are defined using government definitions of a city region. Market Areas are highly integrated economically, culturally, and share the same workers.

City or Market Area data is only available when the majority of LinkedIn members from a given country selects a zipcode/postal code or city as their profile location. For example, in Ireland the majority of members previously selected their location as “Ireland” and have not provided details on the city in which they live in Ireland. We therefore, do not show city or Market Area data in this location.

Professional counts

Company workforce data in Talent Insights is based on the member profiles associated with that Company on LinkedIn.com.

Employee counts reflect the number of active members with a full-time position at the company selected on their LinkedIn profiles. The Full-Time employment type filter will be selected by default, meaning that any members who have listed themselves as part-time, freelance, contractors, students, or interns are excluded by default. See employment type for more detail. All calculations in the Company Report -- including hires, departures, attrition and growth rates, etc. - also reflect this methodology and exclude part-time or non-active members.

Because LinkedIn Talent Insights employee counts represent active, full-time employees, member counts on LinkedIn Talent Insights Company Reports and LinkedIn.com may differ.

The counts in the Company Report can be viewed at either the parent company or individual company level. For example, searching for Microsoft will include all employees currently working at Microsoft. If all Microsoft's affiliated companies are added to the search, the count will include all employees working at either Microsoft or any of the affiliated companies such as Skype or LinkedIn.

Employee growth rates

The growth rate is the percentage change in the number of employees at a company compared to the number of employees at a company one year ago. The change in employees includes hires, departures and internal promotions and transfers at a company.

Recent graduates

Globally, there are more than 46 million students and recent college graduates on LinkedIn.

Recent graduates are defined by default as members who have listed a degree end date on their LinkedIn profile that is within the past four years. You can access more specific “Recent Grads” data by editing the time since graduation, e.g. the last two years, the last four, or even a specific date range by customizing your settings, available behind your profile image in the top right.

Talent flows

Talent Insights provides data on the movement of talent across a number of dimensions. Everytime a member changes roles and updates their profile, we capture information about their prior role and their new role such as company, location and industry. In cases where the member ends their current position and does not create a new position record, they will be counted as a departure but not as a ‘talent flow’ to another company.

When viewing talent flows and comparing hires/departures between two company reports, you may see cases where the talent flow from Company A to Company B does not equal the offsetting talent flow from Company B to Company A. This can occur for the following reasons:

1. Members can have a time gap between the month when they departed Company A and the month when they joined Company B. This means the month in which the member left their previous company is outside the timeframe shown in the talent flows, and the month in which they joined a company is inside the timeframe. In our data, we observed that members commonly have a 0-2 month gap between the end month of one position and the start month of the next position. To better reflect this in the Talent Flows of a company, the departure window is two months longer than the hires window. Instances will still exist where members take extended leave between positions such as for parental leave, non-compete clauses and sabbaticals.
   
   
2.  [If you have filters applied] Anytime a filter is applied on the left rail of your search, the talent flows will reflect hires and departures within the search criteria. This means that any talent movement between search facets will be shown in the hires of one company and not in the departures of another.

For example:

When viewing the company report with a title filter such as "Account Executive", the talent flows will show you where you have hired Account Executives from and where Account Executives have left your company to go. In a scenario where a member's job title at their previous company was "Relationship Manager", the member would count as a hire for your company and would not count as a departure for the previous company (when looking at both company reports with the title filter Account Executive).

Employment type

Within Company Reports in Talent Insights, you can filter by employment type.

We identify employment type based on explicit wording in LinkedIn member job titles (e.g. titles containing words like “Contractor”, “Part-time”, or “Intern”). We call this “explicit employment type”, which means that the exact word (or a variation of the word) must be used in a member’s job title for us to recognize that member as belonging to one of our employment type categories. Full-time members are identified through the absence of any of these words.

You can filter by one or more of the following employment type categories:

• Full-time

• Intern/student

• Contract, part-time, & self-employed

Examples:

• “Sales Intern” → categorized as “Intern / Student”
• “Recruiter (contract)” → categorized as “Contract / Part-time / Self-employed”
• “Independent Photographer” → categorized as “Contract / Part-time / Self-employed”
• “Sales Manager” → “Full-time”

Control options:

• By default Company Report searches will be filtered to include only full-time employees so that intern,  student, part-time, temp, and contractor employees do not inflate attrition numbers and total employee count.

• You have the option to also add or focus exclusively on the intern & student population.

• You can decide whether or not to also members we can identify as contractors, part-time, or self-employed. Because we rely on member titles to classify this population, it’s likely that this population is underrepresented as not everyone includes words like “contract”, “part-time”, or “self-employed” in their titles.

Movement among Industries

Within the Industry tab of the Talent Pool report, the talent flow data reflects the movement of talent from one industry to another. Industry is based on the industry of the company the member departed from and the industry of the company the member subsequently joined.

Geographic migration


Migration talent flows between cities, market areas, and countries or territories can be found on the Location tab of the Talent Pool report.

These flows show movement of professionals between the selected location and the specified locations listed. When a member updates their location on their profile, LinkedIn captures the location they departed from and the location they moved to.

Data Availability:

Data in this module is only available for member geographical movements since November 2018. LinkedIn adopted a new geo taxonomy to provide greater transparency and granularity into geo data, and it is not backwards compatible. Market areas are defined using government defined borders and are not exactly the same as the regions in the previous taxonomy.

Attrition

Attrition in Talent Insights reflects the number of members who departed a company over the past 12 months plus the days of the current month as of the day the report is being run divided by the average number of employees over the last 12 months (“Average headcount”) full months. Average headcount is calculated by taking the average of current employees and employees 12 months ago.

A member is considered to have departed a company only if they have added a position with a new company on their LinkedIn profile and provided an end date for their position record at the company. at their previous company.

Contractors and other non-full-time employees are excluded from this calculation.

Attrition is only displayed if the average number of employees in the past 12 full months is at least 15. Attrition estimates in LinkedIn Talent Insights may under or overstate actual attrition due to the time-lag between when professionals begin a new position at a company and when they update their LinkedIn profiles.

Gender representation

Availability:

• Talent Pool: Gender representation metrics in the Talent Pool Report are available globally.

• Company Report: Gender benchmarking data in the Company Report is available globally for your company’s workforce where we have sufficient coverage. To view gender representation data of your affiliated companies, you need to get permission from the companies. Contact your sales representative if you want access to the data. They will help you get started on the process.

  • See “View gender coverage by location” within the gender tab of your Company Report to see which countries have sufficient coverage.

We currently infer gender based on members’ first names from their LinkedIn profile (NOT their LinkedIn profile picture). In Talent Insights, we will showcase gender representation insights when:

• (1) there are at least 50 professionals in a given talent pool; and

• (2) we have at least 67% coverage (i.e., we can infer at least 67% of members’ gender).

If LinkedIn cannot infer a member’s gender, we do not factor the member data into the gender insights for their talent pool. In LinkedIn Talent Insights tool tips, we disclose the inferred gender coverage percentage for any given report. Gender data coverage represents the number of members within the selected talent pool for which gender (male or female) can be inferred with a high degree of confidence.

Gender inference metrics to know:

• LinkedIn’s coverage for inferred gender insights is ~79% globally.

• In the U.S., our gender inference accuracy is over 95%.

Gender insights are non-personally identifiable and do not reveal the gender attribution for individual members.

Aggregated gender insights in Talent Insights are currently binary; they either show the representation of men or women. We know that not all members identify as male or female, and are enabling members based in the U.S. with the option of privately sharing with LinkedIn how they identify (e.g., male, female or another gender identity) via their account Settings. So far, fewer than 1% of U.S. respondents have identified as “another gender identity.”

Job posts

At 20 million+ active daily job posts, LinkedIn is one of the largest jobs ingesters in the world. The jobs data includes both jobs posted directly on LinkedIn via LinkedIn Jobs as well as and jobs ingested from over 40,000 sources including company websites, applicant tracking systems, job boards, aggregators and job feeds. LinkedIn has developed advanced algorithms to identify and remove duplicate job posts from ingested sources. This robust process ensures the insights reflect the current state of the job market.  

LinkedIn standardizes job posts by extracting the title, location, employer, employment type, description, and industry information. Natural language processing and machine learning models are used to extract skills from job post descriptions and standardized job post titles to make them searchable.

Job posts data within LinkedIn Talent Insights reflects the number of current open jobs matching the search criteria.

Salary insights

Source of salary insights:

LinkedIn Talent Insights provides compensation data for talent pools using LinkedIn Salary data collected from LinkedIn members. The compensation data is inferred based on a blend of factors, including similar roles, companies, industries, company size, years of experience, and location.

Learn more about how LinkedIn Salary data is collected and how data is inferred.

How and when data is displayed:

• Salary insights  in Talent Insights are currently available for Canada, US and UK talent pools. Data is displayed only for searches within a single country and when compensation can be inferred for at least 10% of professionals in the talent pool. Data for additional countries will be available as we collect more data and improve our inference models.
• Compensation data is shown in the Talent Pool Report on the overview page and within the industry, company, and location tabs.

Access Settings, behind your profile image in the top right header, to customize how salary insights appear. You can specify currency and whether to see average total compensation or base salary by default.

Member privacy & GDPR

The privacy of our members is a top priority for LinkedIn. LinkedIn’s mission is to connect the world’s professionals to allow them to be more productive and successful. Central to this mission is our commitment to be transparent about the data we collect about our members, how it is used and with whom it is shared.

Data within LinkedIn Talent Insights honors the privacy settings our members have chosen. Members have control over what level of information is presented through their account settings, and we encourage our members to regularly check their preferences to make sure they feel comfortable on LinkedIn.

LinkedIn Talent Insights can be used in a GDPR-compliant manner. LinkedIn provides members with control over their personal data and is transparent about how it’s used.

For more information, see the LinkedIn privacy policy.