On this page, we explain the different factors that make up our Compensation Calculator and its alignment to GitLab's values and Compensation Principles.
We source some of the information the calculator is based upon, including the San Francisco benchmark and location factors, from 3rd party, non-public sources. As a result, the full compensation calculator application itself cannot be made completely public.
Instead, consistent with our value of transparency but in line with our agreements regarding how we use data we have sourced, we provide information regarding the type of data we use to build the calculator and how that information helps us build as complete and accurate of a calculator as possible.
Team members can access the calculator at any time with their GitLab credentials. Applicants will be issued credentials and have access to the calculator during the interview process. The information from the calculator should only be shared with those who have access (GitLab team members and candidates).
You can use the calculator to determine the overall Total Rewards Package Offered by GitLab (Cash + Equity + Benefits). Internal team members can also use the following spreadsheet by making a copy and adding in your specific information to calculate the GitLab Total Rewards annual amount.
For any questions relating to the compensation calculator, reach out to Total Rewards.
As a natural extension of the Compensation Principles and our commitment to transparency, sharing, efficiency, directness, and boring solutions (see our values) we developed a Compensation Calculator. The compensation of executives and anyone on a quota is not set with the calculator. We use a Compensation Calculator because it helps us align compensation to our values:
The goals of the calculator are:
The calculator will output the amount as
base + variable = total target cash (TTC)
The compensation calculator is updated in December and June with the proper exchange rate, keeping compensation levels in line with local purchasing power.
The compensation calculator is a tool to assist the Total Rewards team in determining a compensation package for new and existing team members. The results of the calculator are not binding. Written correspondence through a contract or letter of adjustment specify all official compensation changes. We reserve the right to change the calculator at any point in time.
As with all things at GitLab, the compensation calculator is a constant work in progress. There are a few options for reporting a discrepancy if you find the calculator isn't outputting data that is true to market.
If you are an internal GitLab team member or external to GitLab:
If you prefer to remain anonymous:
Previously, our compensation calculator and processes (percentage changes from compensation review, relocations, currency fluctuations, etc.) produced numbers that were exact, sometimes down to the dollar and cents. To make the numbers more digestible, we are implementing a practice to round up compensation in the local currency to the nearest hundredth. This rounding practice applies to future compensation changes from July 2020 onwards.
SF benchmark is the team member compensation at a compa ratio of 1.0 at or above market for the role in San Francisco, which we determine using various sources of survey data: Radford, Comptryx.
Benchmarks are determined based on the following types: Individual Contributor (IC), Manager, Director, Senior Director. The Total Rewards team will add an entry for each type listed within the job family. For example:
ic_ttc: compensation: 100000 percentage_variable: 0 from_base: true manager_ttc: compensation: 140000 percentage_variable: 0 from_base: true director_ttc: compensation: 180000 percentage_variable: 0.15 from_base: true senior_director_ttc: compensation: 220000 percentage_variable: 0.15 from_base: true
Note: Where there is no variable component offered (ICs and Managers) GitLab runs the benchmark evaluation off of base salary only. Where there is a variable component offered, GitLab runs the benchmark evaluation off of Total Target Case (TTC).
Benchmarks are evaluated annually as part of the Annual Compensation Review process. Benchmarks can also be adjusted as needed throughout the year.
To analyze benchmarks:
Whenever a new role is established, a new benchmark must also be determined. The Total Rewards team is pinged on the merge request for a compensation review to start the process. The Total Rewards team should ensure that the request is not for a role that already exists and has a benchmark.
Compensation Benchmarking is the process of using internal job descriptions to match salary survey jobs in order to identify the external survey data for each benchmark positions. Compensation data can fluctuate from very high salary data to very low salary data for roles that have the same or similar job titles. Example would be Field Marketing Manager. A Field Marketing Manager at GitLab or another SaaS or Technology company salary benchmarks would and can be included with Field Marketing Manager for other Non Technology companies, as an example RedBull. Though they have the same "title" the role, scope and salaries for these roles are very different. Based on these variants in comp data we will look at the relevant comp data for each role and use the median for the benchmark.
To review the Compensation Benchmark process please refer to the New Roles Creation.
As stated in competitive rate we want to recruit and retain people who meet our requirements. If any one, or a combination of, the following statistics is met, a benchmark review can be requested to address any concerns around the benchmark:
Timing of requests for benchmark adjustments: Requests to review a benchmark adjustment can be requested between Feb 1 and Oct 1 of the fiscal year, with the latest effective date of the potential benchmark update being Nov 1. There will not be any benchmark adjustment reviews in Q4 due to the timing of the annual review of benchmarks in Q4.
Summary of the process: Once data has been collected, the Total Rewards team will review the compensation expectations. During this review, we will look at survey data and candidate expectations (specifically declines due to compensation) to recommend an adjustment to our SF benchmark and target percentile for the role. Total Rewards will coordinate with FP&A and the department leader to draft a business case to be presented to the egroup leader. The business case would include:
Please see the following for a full summary of the benchmark review process:
To automate the process of pulling survey data from Comptryx and Radford to review benchmarks, GitLab has mapped each job title with a corresponding job code. As a first iteration GitLab will use the job codes Radford has outlined. Each job family and level must have a unique job code. The following structure is used:
For example: Backend Engineer = 5163 Senior Backend Engineer = 5164 Distribution Engineer = 5163A Senior Distribution Engineer = 5164A
All current job codes can be found by the Total Rewards team in the "Job Codes" google sheet on the Final Job Code Tab.
Location Factor is calculated using multiple data sources to conduct a market analysis of compensation rates globally: Economic Research Institute (ERI), Comptryx, Radford. This is not a cost of living analysis, but instead a cost of market evaluation compared to San Francisco. The Total Rewards team will use their best judgement in determining the input per location based on our Compensation Principles.
The location factor depends on your geographical area. To determine geographical areas as it relates to compensation, we looked at what the United Nations outlines globally:
To determine your area:
Select your Metro Area if you live within a commutable one hour and forty-five minutes of a city listed.
If you are within a commutable one hour and forty-five minutes of more than one city, use the city with the shortest commute as your location. If not, select "Not Applicable."
If there are no additional boxes for State/Province and/or Metro Area for the country you select, this country has the same location factor regardless of the city you live in. Similarly, if there is no additional box for Metro Area after selecting a State/Province, this state or province has the same location factor regardless of the city you live in.
If the location of a metropolitan area is higher than the regional minimum, the metropolitan area's location factor is used for the calculation.
GitLab will gather and analyze the data for each location factor annually as part of annual compensation review. We will also iterate on location factors as needed throughout the year.
Level Factor is currently defined as:
The nomenclature can be adjusted for each job family to ensure the appropriate level to select is clear.
GitLab job grades aid in mapping a role for internal equity with respect to cash and equity. For example, if there is a stock option update, this mapping can act as a reference to update the compensation calculator for the various roles to ensure alignment. Job Grades can also provide an alternative path to finding the current number of options offered without having to fill out the compensation calculator.
Note: This table excludes Enterprise Sales, Commercial Sales, Channel Sales, and Sales Development. Grading can be seen in the table below.
|11||Senior Director||Senior Distinguished|
Senior Principal Product Manager
Group Manager, Product
Principal Product Manager
Senior Product Manager
Dual career tracks can be added to each job family (regardless of division) when supported by data. Each individual contributor level above senior (grade 7) will have links to market examples of that level in the relevant section of the job family.
Senior Manager (Sales)
|8||Manager (Demand Generation)||Enterprise|
|6||SMB/SDR Lead & Acceleration|
Compa Ratio is a term used internally in the Total Rewards team to evaluate Pay Equality.
The Compa Ratio where within the range spread a team member falls in the calculator. Specifically, the GitLab compensation calculator has a 40% spread (+/- 20% from the median). It is common to see range spreads up to 50%.