Global Demand Tiers

In order to improve expectation management and ease communication with prospects, we have divided all countries into ‘tiers’ for Global by data availability and granularity. Whilst there are regional differences within countries we have opted to only provide this information at the national level.

Link

Please find the current global tier list per country here; Lightcast Global DataSet Summary

Open

Fields

A great place to find the current supported fields in Global is to reference the API documentation or the Snowflake documentation.

Tier Descriptions

Tier 1 - Full Capability

These are the top-tier countries, with the best demand data we have available. They have a long history of use, great normalization and extensive vetting. These countries are the United States, the United Kingdom, and Canada. Customers can use this data for any purpose they see fit.

Tier 2 - Low Level Analysis

These countries have a rich depth of data and can be used to understand labor markets in-depth. With a solid mix of all occupations and key employers covered, analysis done in this tier can be really thorough. It lacks in some of the locally relevant enrichments compared to Tier 1 and might now have quite the same breath of data. The use cases for this tier are very broad, from analyzing skill trends to understanding local markets.

Tier 3 - High Level Analysis

Countries in this tier have good coverage of most occupations and postings by large employers, with data going back 1-2 years. However, they may have less localized enrichments and no localized taxonomies. We try to address customer feedback within 12 weeks. Examples include India, Brazil and Mexico and examples of use cases are understanding high-level trends at the market level, investigating large employers, and trying to understand the skills landscape at a high level.

Tier 4 - Near raw data

These countries have not yet been worked on, and the data is presented "as is". There are large gaps in employer and occupation coverage, but the data can still be used for broad research purposes or investigating large multinationals. Any customer feedback will be stored to be processed at a later date.

Enrichments

Skill

Skills are a foundational translation layer that enables a standardized way to compare and evaluate job requirements across different languages and cultures, allowing for accurate talent matching and identification of skill gaps. Skills are generally updated every 2 weeks.

Tier 1: Full localized support major and minor languages
Tier 2: Support major languages
Tier 3: Support major language
Tier 4: Where language support available (see language support)

Occupation

Occupation groups are a useful tool to group workers into buckets of adjacent work. There are 2 Lightcast occupation classifications in the Global data; LOT and Global Occupation.

LOT is fully supported for English postings in Tier 1 countries and the data is presented ‘as-is’ for English postings in all other tiers in Snowflake.

The Global Occupations are supported in Tiers 1, 2 and 3 but provide a lesser granularity than LOT.

Geography

All global postings support the ‘market’ regions definition, which is a broad classification system that attempts to divide the postings geographically to generally useful area’s that are comparable to MSA’s.

For tier 1 and tier 2 countries we are also continuously expanding our capability to tag postings with Lightcast Administrative Area coding (LAA’s) which are based on the same concept as NUTS2 levels.

Tier 1: Markets & LAA's & applicable local coding (Example; MSA's)
Tier 2: Markets & Lightcast Administrative Areas
Tier 3: Markets
Tier 4: Markets where available

Company and Industry

ACME is a proprietary system from Lightcast that codes all companies in the global dataset to easy to use normalized numbers and names. Example; is Deutsche Telekom AG, Deutsche Telekom Berlin or Deutsche Telekom S.A. are all coded to company: 93501333 and company_name: “Deutsche Telekom”.

Recall calculated on postings with a known employer, including staffing agencies excluding non-advertised employers.