Table of Contents
- Product History and Overview
-
Pave's Real-Time Model
- How does Pave's real-time compensation benchmarking model work?
- What makes Pave's real-time model better than traditional compensation surveys?
- How often is Pave's real-time compensation database updated?
- Who can join Pave's real-time compensation database?
- I already use a traditional compensation survey. Why do I need an additional source like Pave?
-
Compensation Database Coverage
- Who is using Pave's real-time compensation database?
- What types of companies participate in Pave's real-time compensation database?
- What elements of compensation can I benchmark using Pave's Market Data product?
- What additional compensation insights can I access with Pave's Market Data Pro offering?
- What is Pave's Calculated Benchmarks feature and how does it work?
- What jobs can I benchmark using Pave's Market Data product?
- What locations can I benchmark using Pave's Market Data product?
- What market filters are available in Pave's Market Data product?
- Does Pave's Market Data product include industry-based market filters?
- Does Pave's Market Data product include peer group reporting capabilities?
- Pave Job Architecture
- Pave Job Matching
- Data Collection and Management Practices
- Data Consistency Labels, Data Sufficiency, and Safe Harbour
- Data Privacy and Security
Product History and Overview
In March 2021, Pave launched an innovative approach to compensation benchmarking using data collected directly from automated and persistent (i.e., real-time) connections to human resources (HR) platforms, including human resources information systems (HRIS), applicant tracking systems (ATS), and equity management systems (EMS).
Our real-time model, coupled with the use of sophisticated data science techniques and machine learning algorithms, provides customers with improved compensation benchmarks and a radically streamlined user experience.
Today, more than 8,500 companies—including more than 1,000 medium and large enterprises—use Pave's Market Data product as their primary or secondary compensation data source and enjoy significant advantages over companies that rely solely on traditional compensation surveys.
Depending on your company's stage of growth, we currently offer two options when using Pave's Market Data product—our Launch and Pro packages:
- Market Data Launch – We recommend our Launch package for business leaders, recruiters and HR generalists looking to access base salary and new hire equity benchmarks in one or two markets to launch and grow a new venture. To join for free today, sign up here.
- Market Data Pro – We recommend our Pro package for organizations with at least one compensation or total rewards professional looking to access detailed cash and equity compensation benchmarks in multiple markets to build formal pay processes and structures. To learn more, please contact our team.
If you would like to learn more about Pave's full compensation management platform, including market pricing, salary range management, compensation cycle planning, and total rewards communication tools, explore our platform here.
Pave's Real-Time Model
How does Pave's real-time compensation benchmarking model work?
As noted above, Pave's Market Data products deliver compensation benchmarks to customers using data collected directly from real-time connections to HR platforms, including HRIS, ATS, and EMS systems.
Once data is received by Pave, employee records are matched to Pave's job architecture system (i.e., job levels and job families) using a machine learning algorithm. Data for employees with a successful job match is then aggregated and de-identified before entering Pave's overall compensation database. These steps dramatically accelerate the speed with which data is collected, matched, and published, while protecting individual data privacy and maintaining the data confidentiality of participating organizations.
Additional layers of machine learning provide customers with value-added insights, including data quality information (e.g., data consistency labels) and the normalization of benchmarks in cases where raw market data is sparse (e.g., job families with low incumbent counts or markets with smaller concentrations of talent). Overall, this approach provides customers with improved benchmarks and a radically streamlined user experience.
What makes Pave's real-time model better than traditional compensation surveys?
Pave's Market Data products use data collected directly from real-time connections to HR platforms, which is further enhanced by a world-class data science team and a layer of sophisticated machine learning algorithms. As a result, Pave customers enjoy significant advantages, including:
- No stale data. Pave collects information continuously from HR platforms and publishes updated compensation benchmarks monthly. In contrast, traditional compensation surveys provide a point-in-time snapshot of pay that is, on average, six months old before it is published.
- No survey inputs. After a customer connects their HR platforms to Pave once—which can take as little as 15 minutes—they never have to complete a survey submission again. Many traditional survey providers ask customers to submit data annually using insecure and overly complex Excel-based input templates.
- No missing data. By virtue of collecting data directly from HR platforms, Pave can quickly gather comprehensive information on all employees. In contrast, traditional compensation surveys usually receive pay information covering approximately 70% to 80% of employees.
- Improved benchmarks. By virtue of collecting data directly from HR platforms, Pave can not only provide comprehensive base salary, bonus, and equity compensation insights (e.g., unvested equity holdings), but also tens of organizational benchmarks in real-time, including attrition rates, promotion rates, span of control insights, and workforce spend, among many others.
- Streamlined job matching. Pave uses a machine learning algorithm to accelerate job matching and allows customers to bypass manual job matching if desired. Our job matching algorithm is reviewed regularly by compensation experts to fine-tune results. This approach can save larger organizations hundreds of hours and tens of thousands of dollars on manual job matching efforts.
To learn more about the disruption of traditional compensation surveys, read our white paper: A New Era in Compensation Benchmarking is Here
How often is Pave's real-time compensation database updated?
Published compensation benchmarks in Pave's Market Data products are updated monthly, with new data releases typically scheduled for the first Monday of each month. Actual publication dates may vary.
At Pave, we use the term real-time to refer to how often data is collected from customers. Indeed, the automated and persistent connections we have to HR platforms generate new data daily. However, we choose to publish updated compensation benchmarks monthly to ensure the consistency and quality of the data we publish.
Who can join Pave's real-time compensation database?
Companies of all types—private and public, large and small—can join Pave's real-time compensation database.
Today, our database primarily includes technology companies (e.g., hardware, software, etc.) and technology-adjacent companies (e.g., FinTech, MedTech, etc.), but a growing number of energy, financial services, healthcare, life sciences, and manufacturing firms are joining Pave, among others.
Of the more than 8,500 companies using Pave, a majority are venture-backed private companies. However, more than 1,000 medium and large enterprises now use Pave, and 40% of all employees in our dataset come from companies with more than 1,000 employees. See the Compensation Database Coverage section of this guide for more details.
Depending on your company's stage of growth, we currently offer two options when using Pave's Market Data product—our Launch and Pro packages:
- Market Data Launch – We recommend our Launch package for business leaders, recruiters and HR generalists looking to access base salary and new hire equity benchmarks in one or two markets to launch and grow a new venture. To join for free today, sign up here.
- Market Data Pro – We recommend our Pro package for organizations with at least one compensation or total rewards professional looking to access detailed cash and equity compensation benchmarks in multiple markets to build formal pay processes and structures. To learn more, please contact our team.
If you have specific questions about the relevancy of Pave's dataset for your company, or the right Market Data package for you, we encourage you to contact our team.
I already use a traditional compensation survey. Why do I need an additional source like Pave?
If you already use one or more traditional compensation surveys, Pave's Market Data product can still add significant value to your organization. Here's why:
- Multiple data sources are a feature, not a bug. Different datasets have unique strengths and weaknesses and can be used to close gaps in data coverage. In particular, Pave's real-time model, coupled with our sophisticated data science and machine learning capabilities, allows us to capture, analyze, and provide certain datasets faster and more comprehensively than others. At the end of the day, compensation is often a company's single largest expense, so maximizing confidence in compensation decisions using multiple sources is time and money well spent.
- Traditional surveys have limitations. As noted above, traditional compensation surveys suffer from data lag, antiquated and time-consuming data submission processes, and limited equity compensation insights. Pave's model directly addresses these challenges. If you're going to add a new data source, pick a provider like Pave who makes your workload significantly lighter while closing data coverage gaps.
- Real-time data and insights will give you an edge. By virtue of collecting data directly from HR platforms in an automated and persistent fashion, Pave can not only provide comprehensive base salary, bonus and equity benchmarks, but also a wide range of value-added insights. These insights include benchmarks for unvested equity holdings, the ability to normalize annual vs. total equity grant values or toggle between indented (at grant) vs. actual (current) equity grant values, and information on equity burn rates and vesting schedules.
To learn more about the disruption of traditional compensation surveys, read our white paper: A New Era in Compensation Benchmarking is Here.
Compensation Database Coverage
Who is using Pave's real-time compensation database?
The full list of companies providing information to Pave's real-time compensation database is available inside our Market Data product. However, a select list of some of our largest participants by employee headcount includes:
Private Companies
- Anduril Industries
- Auctane
- Automation Anywhere
- BAL
- BambooHR
- BitSight Technologies
- Boomi
- Clio
- Commonwealth Fusion Systems
- Credit Karma
- Databricks
- Dialpad
- DocPlanner
- Emburse
- Extreme Reach
- fivestars
- GLOBO
- GOAT
- Gusto
- Industrious
- Mews
- Monzo
- Motive Technologies
- Navan
- Notion
- OpenAI
- OutSystems
- Pax8
- PayJoy
- Qualtrics
- Relativity Space
- Remote
- Rohlik Group a.s.
- Scale AI
- ServiceTitan
- Solidcore
- Sonder
- SpotOn
- Stripe
- SymphonyAI
- Tarro
- Tekion
- Tide
- Undefeated Tribe Operating Co.
- Verkada
- Virtual Business Partners
- Wealthsimple
- X
- Zinnia
- Zipline
Public Companies
- Affirm
- AppFolio
- Asana
- Atlassian
- Aurora
- Bill
- Block
- Braze
- Cloudflare
- Coinbase
- Confluent
- CSL Behring
- Doordash
- Dropbox
- Elastic
- Electronic Arts
- FanDuel
- Five9
- GitLab
- Grubhub
- HashiCorp
- Hims & Hers
- HubSpot
- Instacart
- Joby
- Klaviyo
- Lucid Motors
- MongoDB
- Nutanix
- Okta
- On Holding AG
- Procore
- Remitly
- RingCentral
- Rivian
- Roblox
- Samsara
- Silicon Labs
- Smartsheet
- Snowflake
- Sofi
- Squarespace
- Sweetgreen
- The RealReal
- Twilio
- Unity Technologies
- Zip Co
- Zoom
- Zscaler
- Zuora
What types of companies participate in Pave's real-time compensation database?
As of January 2025, more than 8,500 companies use Pave's Market Data products. The general makeup of our compensation database, by employee distribution, is as follows:
If you have specific questions about the relevancy of Pave's dataset for your company, or the right Market Data package for you, we encourage you to contact our team.
What elements of compensation can I benchmark using Pave's Market Data product?
Pave's Market Data products provide customers with real-time benchmarks for the following elements of compensation:
Broad-Based Employees
- Cash Compensation
- Base Salary
- Variable (or Bonus) Pay
- Total Cash Compensation
- Equity Compensation
- New Hire Equity Awards
- Ongoing (or Refresh) Equity Awards *
- Unvested Equity Holdings *
Executives (VP+ Roles)
- Cash Compensation
- Base Salary
- Variable (or Bonus) Pay
- Total Cash Compensation
- Equity Compensation
- Total Equity Awards
* Available with Market Data Pro only.
What additional compensation insights can I access with Pave's Market Data Pro offering?
Pave's Market Data Pro offering provides customers with additional real-time data and insights, including:
Advanced Equity Insights
Powered by real-time connections to EMS systems, we offer customers data on:
- Equity vehicle practices
- Equity vesting practices
- Equity burn rates
Offer Insights
Powered by our partnership with Greenhouse, we offer customers data on:
- New posting rates by job
- Offer acceptance rates by job
- Changes in posted salary ranges
Furthermore, by virtue of collecting line-by-line equity grant data from EMS systems, our Market Data Pro product allows customers to customize equity benchmarks as follows:
- Total vs. annualized equity grant values
- Intended (at grant) vs. actual (current) equity grant values
- 409A vs. Gross vs. Net equity valuation methodologies
What is Pave's Calculated Benchmarks feature and how does it work?
Pave's Calculated Benchmarks feature uses machine learning to identify patterns across our dataset that can be used to provide customers with more relevant, accurate, and timely equity compensation benchmarks. Using these patterns, we then apply a series of regression models to generate reliable results in places where robust data is often lacking (e.g., job families with low incumbent counts or markets with smaller concentrations of talent).
Prior to launch, our algorithm was tested extensively against real market data and by industry experts at multiple compensation consulting firms to validate outputs. In many ways, our approach emulates the manual data "smoothing" (or normalization) process already used by most compensation professionals.
To learn more, read our Calculated Benchmarks blog post.
What jobs can I benchmark using Pave's Market Data product?
As of January 2025, Pave's Market Data products deliver compensation benchmarks for more than 100 broad-based (or non-executive) job families, plus more than 40 executive job families. For more details, please see the Pave Job Architecture section of this guide for more details.
What locations can I benchmark using Pave's Market Data product?
As of January 2025, Pave's Market Data products deliver compensation benchmarks in more than 55 countries, including filters that allow users to examine pay in more than 75 major cities or metropolitan areas.
- Argentina
- Armenia
- Australia
- Austria
- Belgium
- Brazil
- Bulgaria
- Canada
- Chile
- China
- Colombia
- Costa Rica
- Croatia
- Czechia
- Denmark
- Estonia
- Finland
- France
- Germany
- Greece
- Hong Kong
- Hungary
- India
- Ireland
- Israel
- Italy
- Japan
- Kenya
- Malaysia
- Malta
- Mexico
- Morocco
- Netherlands
- New Zealand
- Nicaragua
- Norway
- Pakistan
- Peru
- Philippines
- Philippines
- Poland
- Portugal
- Romania
- Russia
- Serbia
- Singapore
- Slovakia
- South Africa
- South Korea
- Spain
- Sweden
- Switzerland
- Thailand
- Türkiye
- Ukraine
- United Kingdom
- United States
- Vietnam
Available United States (U.S.) market tiers and global cities or metropolitan areas include:
Tier 1 Grouping
- San Francisco Bay Area Metro
- Seattle, WA
- New York City Metro
Tier 3 Grouping
- All other United States metros not listed in Tier 1 and Tier 2
Tier 2 Grouping
- Austin, TX
- Boston, MA
- Chicago, IL
- Denver, CO
- Los Angeles, CA
- Philadelphia Metro
- Portland, OR
- Washington DC
- Sacramento, CA
- San Diego, CA
US Metros
- Albany, NY
- Atlanta, GA
- Austin, TX
- Baltimore, MD
- Boston, MA
- Charleston, SC
- Charlotte, NC
- Chicago, IL
- Cincinnati, OH
- Cleveland, OH
- Dallas/Fort Worth, TX
- Denver, CO
- Detroit, MI
- Houston, TX
- Indianapolis, IN
- Las Vegas, NV
- Los Angeles, CA
- Miami, FL
- Milwaukee, WI
- Nashville, TN
- New York City Metro
- Orlando, FL
- Philadelphia Metro
- Phoenix, AZ
- Pittsburgh, PA
- Portland & Vancouver Metro
- Research Triangle Metro
- Sacramento, CA
- Salt Lake City, UT
- San Diego, CA
- San Francisco Bay Area Metro
- Seattle, WA
- Tampa, FL
- Twin Cities Metro
- Washington, DC
International Metros
- Amsterdam
- Auckland
- Barcelona
- Bengaluru
- Berlin
- Bristol
- Buenos Aires
- Calgary
- Cape Town
- Chennai
- Dublin
- Edinburgh
- Edmonton
- Hyderabad
- Kitchener
- Lisbon
- London
- Madrid
- Melbourne
- Mexico City
- Montreal
- Munich
- Nairobi
- Ottawa
- Paris
- Prague
- Pune
- Santiago
- São Paulo
- Shanghai
- Sofia
- Sydney
- Tallinn
- Tel Aviv-Yafo
- Toronto
- Vancouver
- Warsaw
What market filters are available in Pave's Market Data product?
As of January 2025, Pave's Market Data products provide customers with the following filters to fine-tune compensation benchmarks:
Company-Based Filters
- Capital Raised
- Employee Headcount
- Market Capitalization (for Public companies)
- Ownership (Public vs. Private)
- Valuation (for Private companies)
- Revenue
Job-Based Filters
- Job Family
- Job Level
- Location
We are actively working on additional filtering options and plan to launch improved functionality throughout 2025.
Does Pave's Market Data product include industry-based market filters?
Currently, Market Data customers cannot filter compensation data by industry. We are actively developing this capability and plan to launch improved filtering functionality throughout 2025.
Does Pave's Market Data product include peer group reporting capabilities?
Currently, Market Data customers cannot create, save, and use custom peer groups. We are actively developing this capability and plan to launch improved peer group functionality throughout 2025.
In the meantime, customers can use existing market filters to define relevant cohorts of companies.
Pave Job Architecture
What are the core elements of Pave's job architecture system?
Pave currently organizes employees into job levels and job families based on job-related data (e.g., job title, functional area, reporting lines, span of control, tenure, etc.) collected by Pave's real-time connections to HR platforms as follows:
- Career Track – Based on job-related data, is the employee in Pave's Executive, Management or Professional Individual Contributor career track?
- Job Level – Based on job-related data, how senior is the employee, how experienced is the employee, and what is the employee's scope of responsibility within their assigned career track?
- Job Family – Based on job-related data, what business department or function, and specific job role should the employee be assigned to?
For additional information on how Pave places employees into job families, see the Pave Job Matching section of this guide for more details.
What career tracks and job levels are in Pave's job architecture system?
Pave's career tracks and job levels define a hierarchy of employees spanning professional individual contributor, management, and executive roles. Starting at the senior-most level of an organization, Pave's career tracks and job levels are as follows:
Executive Career Track:
- C-Level Jobs
- Senior Vice President (SVP) Level Jobs
- Vice President (VP) Level Jobs
Management Career Track:
- Senior Director Level Jobs
- Director Level Jobs
- Senior Manager Level Jobs
- Manager Level Jobs
Professional Individual Contributor Career Track:
- Principal Level Jobs
- Expert Level Jobs
- Senior Level Jobs
- Career Level Jobs
- Developing Level Jobs
- Entry Level Jobs
What broad-based (or non-executive) job families can I benchmark using Pave?
As of January 2025, Pave’s Market Data products deliver compensation benchmarks for more than 100 broad-based (or non-executive) job families, including:
Job Families | Sub Families | Description |
---|---|---|
Account Management | Cultivates and strengthens ongoing client relationships, focusing on revenue growth and client satisfaction. | |
Account Management - Generalist | Responsible for nurturing and expanding relationships with current clients by understanding client needs, identifying upselling opportunities, addressing customer concerns, providing excellent support, and achieving sales targets to maximize revenue from existing accounts. | |
Relationship Management | Responsible for nurturing client connections and fostering long-term partnerships by actively engaging with stakeholders, resolving issues promptly, identifying growth opportunities, and providing personalized support. | |
Accounting | Oversees financial activities of the company, from transactions to reporting, ensuring compliance and providing financial insights for decision-making. | |
Accounting - Generalist | Involves recording, analyzing, and reporting financial transactions. Responsibilities include preparing financial statements, reconciling accounts, managing budgets, ensuring compliance with regulations, and providing accurate financial insights for decision-making. | |
Accounts Payable / Receivable | Validates and assesses invoices to maintain financial databases, arrange payments to and from vendors and lenders, and generate reports. | |
Controller | Oversees the company's accounting and budgeting operations, provides upper management with financial data required for controlling business operations, and are ultimately accountable for financial and regulatory reporting. | |
Invoicing Operations | Carries out administrative tasks related to billing processes, like organizing, recording, and invoice preparation. | |
Payroll | Ensures the timely and precise distribution and accounting of salaries, wages, commissions, and bonus payments. | |
Revenue Recognition | Coordinates monthly financial closing activities, ensuring accurate and timely outcomes. This position requires thorough examination, analysis, and interpretation of revenue and margin reports, all in compliance with regulatory guidelines. | |
Tax | Minimizes tax obligations to improve impact on cash flow and guarantee adherence to reporting responsibilities from evolving tax legislation. | |
Administration | Manages organizational support activities, including office operations, facilities management, and travel coordination. | |
Aerospace Engineering | Designs and constructs vehicles and systems for air and space exploration. | |
Brand Marketing | Focuses on strategizing and executing marketing campaigns to enhance brand visibility and engagement with the target audience. | |
Event Marketing | Strategizes and implements marketing events, such as trade shows and field events. | |
Social Media Marketing | Defines and implements promotional strategy for products or services over social media channels. Responsible for growing social presence, community, reach, and brand awareness. | |
Business Development | Drives the organization's growth by identifying, evaluating, and capitalizing on strategic opportunities and partnerships. | |
Business Development - Generalist | Responsible for defining and pursuing growth opportunities by researching markets, prospecting potential clients, building relationships, creating proposals, and collaborating with teams to expand the organization's business and revenue. | |
Corporate Development | Responsible for identifying and evaluating strategic growth opportunities, conducting market research, analyzing financial data, and executing mergers, acquisitions, and partnerships to drive corporate expansion and success. | |
Business Operations | Optimizes business processes and workflows to improve organizational efficiency and align with strategic goals. | |
Business Operations - ERP | Focuses on identifying and assessing operational inefficiencies within the organization. They redesign existing business processes to enhance their effectiveness, streamline workflows, and optimize overall performance, with a particular emphasis on Enterprise Resource Planning (ERP) systems. | |
Business Operations - Generalist | Specializes in developing, defining, and implementing a systematic approach to enhance business processes for achieving improved efficiency and results. | |
Strategic Planning | Responsible for shaping organizational strategy by conducting market analysis, setting objectives, formulating plans, and ensuring alignment with long-term goals. | |
Communication and PR | Manages the organization's public image through strategic communication initiatives and media relations. | |
Community Operations | Nurtures and manages community relationships, ensuring a positive and collaborative environment for members. | |
Content Marketing | Develops and disseminates content to promote brand awareness, lead generation, and align with broader marketing objectives. | |
Copywriting | Crafts engaging content for various communication channels to convey brand messages and engage audiences. | |
Customer Success | Ensures customer satisfaction and retention by understanding their needs and enhancing their experience with the company's offerings. | |
Customer Success Engineering | Manages post-sales product customization, integration, and delivery to ensure customer satisfaction. | |
Implementation | Responsible for the post-sales customization, integration, and delivery of the product. | |
Solutions Engineering - Post-Sales | Responsible for ensuring successful post-sales implementation and support by collaborating with customers to understand their needs, designing tailored solutions, providing technical expertise, and offering guidance to deliver effective and efficient solutions that meet client requirements and drive customer satisfaction. | |
Customer Support | Handles client interactions concerning the company's products and services, addressing concerns, and enhancing product usage experience. | |
Customer Assistance | Initiates or receives calls from clients concerning pre- and post-sales services. This role necessitates keeping up-to-date with product information and understanding the company's customer service guidelines. They might also identify and develop potential business prospects based on these interactions. | |
Customer Training Development | Responsible for designing, creating, and updating training materials. This includes developing curriculum, crafting instructional content, incorporating multimedia elements, and ensuring courses meet learning objectives and enhance participants' skills. | |
Enterprise Account Services | Steers the execution of assistance and service functions for enterprise and strategic accounts. They are responsible for formulating the service delivery strategy, associated procedures, escalation protocols, and education initiatives. They also identify potential avenues for enhancing service delivery, reducing costs, and adding value for the customers. | |
Product Support | Focuses on aiding and resolving client complications associated with the company's product usage, including queries or challenges that arise during the setup, operation, upkeep, or usage in specific applications or integration scenarios. They notify the engineering and design teams about persistent or novel issues. | |
Customer Support Engineering | Offers specialized technical support, ensuring complex issues are addressed and customer satisfaction is maintained. | |
Data Engineering | Develops and maintains data infrastructure, ensuring data integrity and accessibility for analytical decision-making. | |
Analytics Engineering | Designs, implements, and maintains data models, dashboards, and reports to provide actionable insights. | |
Data Engineering - Generalist | Responsible for designing, building, and maintaining data systems. This includes collecting and processing data, creating data pipelines, implementing data models, and ensuring data integrity to support data-driven decision-making and analysis. | |
Data Science | Develops and maintains data infrastructure, ensuring data integrity and accessibility for analytical decision-making. | |
Business Intelligence | Responsible for analyzing data, designing and developing data models, creating reports and dashboards, and providing actionable insights to support data-driven decision-making and improve business performance. | |
Data Analyst | Leverages data modeling and statistical methods to collect, transform, and analyze data. | |
Data Science - Generalist | Interprets and communicates business insights generated by applying programming and analytical techniques to a variety of datasets. | |
DevOps Engineering | Streamlines software development processes through automation, continuous integration, and efficient software delivery. | |
Executive Assistance | Acts as a liaison between executives and partners, managing communications, schedules, and office needs. | |
Finance | Manages financial processes, credit collections, reporting structures, and risk assessment to ensure financial health and compliance. | |
Credits and Collections | Focuses on managing credit processes and collecting outstanding debts. Responsibilities include assessing creditworthiness, approving credit applications, negotiating payment plans, monitoring payment status, and resolving payment issues to ensure timely collections. | |
Financial Planning and Analysis | Manages and improves financial reporting structures to provide budget and forecast analysis and commentary on discrepancies, reports, and overviews. | |
Investors Relations | Responsible for engaging in communication with analysts and the financial media. | |
Regulatory Reporting | Generates reports and statements mandated by governmental and regulatory bodies, such as cash flow reports, earnings releases, and equity disclosures. | |
Risk Assessment | Involves the identification, evaluation, and reduction of risk. This might involve setting up risk management protocols and procedures to ensure compliance with company policies. | |
Growth Marketing | Conducts experiments to grow the business using paid and organic channels like email, social, and digital ads. | |
Demand Generation | Responsible for producing qualified leads for the sales pipeline by designing and implementing marketing initiatives. | |
Marketing Operations | Manages the processes and technology platforms that support the firm's marketing strategy, initiatives, and campaigns. | |
Hardware Engineering | Designs and tests electrical systems and components to meet project objectives and safety standards. | |
Industrial Design | Designs and specifies physical products to enhance both aesthetic and functional appeal. | |
IT | Manages the implementation, maintenance, and monitoring of networked systems and applications within a company. | |
Business Systems | Responsible for examining, assessing, adjusting, testing, and executing business systems like CRM's, HRIS's, and financial systems. Assesses different suggestions to fulfill projected requirements in terms of cost, schedule, and advantages. Devises and executes tests for system specifications using cutting-edge diagramming tools in alignment with business needs. | |
Information Systems Management | Responsible for planning, implementing, and maintaining IT infrastructure, ensuring data security, managing software applications, and providing technical support to meet the organization's information management needs. | |
IT Support | Involves managing and maintaining IT systems and infrastructure. Responsibilities include monitoring network performance, troubleshooting technical issues, managing hardware and software, implementing security measures, and ensuring efficient IT operations to support the organization's needs. | |
Project Management - IT | Plans, executes, and delivers IT projects. Responsibilities include defining project scope, managing resources, coordinating teams, monitoring progress, and ensuring successful implementation of information systems initiatives. | |
Legal | Focuses on managing contracts, delivering legal counsel, and ensuring organizational compliance with laws, regulations, and policies. | |
Contracts | Reviews, negotiates, and manages business contracts with the goal of protecting the organization's legal and business interests, ensuring compliance with laws and regulations, identifying potential risks, and working closely with various stakeholders to finalize contractual agreements. | |
General Counsel | Delivers legal counsel to the company by coordinating with other departments, external legal counsel, law firms, or online legal services as required. | |
Paralegal | Supports attorneys and legal counsels in carrying out legal transactions. Assists with procuring, preparing, composing, and handling legal documents. | |
Risk and Compliance | Responsible for ensuring adherence to regulatory and internal policies, conducting risk assessments, implementing risk management strategies, monitoring compliance, and providing recommendations to mitigate risks in the organization. | |
Machine Learning | Develops solutions using machine learning techniques, from research to model training and evaluation. | |
Manufacturing | Oversees manufacturing processes, from development to testing, to ensure quality, efficiency, and adherence to standards. | |
Manufacturing Engineering | Develops, implements, and optimizes manufacturing processes. The goal is to improve product quality, maximize efficiency, reduce production costs, and ensure worker safety, all while maintaining adherence to regulatory standards and specifications. | |
Manufacturing Production | Coordinates and manages manufacturing processes, ensuring optimal productivity and quality. Implements production plans, monitors performance, and troubleshoots issues. Maintains safety standards and implements improvements for increased efficiency. | |
Test Engineering - Manufacturing | Defines and implements methods to inspect and test the precision of manufacturing processes and completed goods. | |
Marketing | Manages the implementation, maintenance, and monitoring of networked systems and applications within a company. | |
Advertising | Creates, manages, and optimizes advertising campaigns, ensuring alignment to reach the target audience and drive customer engagement effectively. | |
Channel Marketing | Develops and implements effective marketing strategies for specific channels or partners. The role is tasked to align channel tactics with broader marketing objectives, enhance partner relationships, and maximize channel performance. | |
E-commerce Marketing | Responsible for strategizing and executing marketing campaigns for e-commerce sites and products. | |
Mechanical Engineering | Focuses on the creation and improvement of mechanical systems. Involves both design and testing procedures. | |
Media Production | Handles the creation and development of various media content, from conceptualization to final product. | |
Media Production - Generalist | Involves producing and creating multimedia content. Responsibilities include scripting, shooting, editing, and producing videos, audio recordings, graphics, and other media materials for various platforms and purposes. | |
Videography | Responsible for operating video recording tools within media projects, employing cinematic methods to seize and communicate a project's artistic concept, and refining footage for subsequent post-production or distribution. | |
Office Management | Oversees facilities operations and procurement, ensuring efficient space use, safety, and cost-effective sourcing. | |
Facilities Management | Coordinates facilities operations, including planning and executing maintenance, managing vendor relationships, optimizing space utilization, ensuring safety compliance, and providing a comfortable and efficient environment for occupants. | |
Office Supplies Procurement | Optimizes procurement of supplies by strategically sourcing goods and services, identifying cost-saving opportunities, and ensuring compliance with procurement policies and procedures. | |
People Operations | Manages human resource functions, from recruiting to compensation, ensuring employee growth, satisfaction, and alignment with business goals. | |
Compensation | Researches, analyzes, and recommends appropriate salary levels to ensure the company's compensation strategy is competitive. The role includes reviewing job classifications, assessing pay equity, and working with HR and management on salary, bonus, and benefits packages. | |
Diversity and Inclusion | Responsible for crafting, executing, and overseeing preemptive policies and initiatives aimed at advocating for the advantages of a diverse workforce. | |
HR Generalist | Supports various HR functions including recruiting, onboarding, conducting employee training, managing employee relations, administering HR policies, and ensuring compliance with labor laws to foster a positive work environment. | |
HRIS Analyst | Leverages data and statistical methods to derive insights about an organization's workforce, aiding in decision making related to hiring, employee engagement, performance, and retention, ultimately improving the company's overall effectiveness and efficiency. | |
Learning and Development | Implements strategies to facilitate employee growth and productivity. This includes creating training programs, facilitating workshops, identifying skill gaps, and developing career development plans to align with the organization's objectives. | |
People Business Partner | Collaborates closely with departments to align HR strategies with business objectives. Drives talent acquisition, employee development, performance management, and organizational effectiveness. Provides expert guidance on HR policies, ensuring compliance and fostering a positive work culture. Fosters employee engagement, resolves conflicts, and contributes to overall people operations excellence. | |
Total Rewards | Responsible for managing and administering the organization's compensation and benefits programs. | |
Product Design | Centers on crafting user-focused product experiences, from initial design sketches to final usability refinements. | |
Product Management | Guides the journey of a product from ideation to market release, ensuring alignment with market needs. | |
Product Marketing | Drives the positioning and promotion of products to ensure market relevance and customer adoption. | |
Professional Services | Offers specialized solutions to clients, focusing on technological integration, relationship management, and business strategy. | |
Client Relationship Management | Maintains and enhances relationships with clients. The goal is to understand client needs, provide relevant solutions, ensure client satisfaction, and foster long-term engagement. This role also seeks to manage client expectations and contribute to business growth. | |
Professional Services - Generalist | Delivers specialized assistance and solutions to clients. The goal is to understand client requirements, implement tailored solutions, provide guidance, and support their business objectives, ultimately enhancing client satisfaction and relationship longevity. | |
System Integration | Combines different computing systems and software applications physically or functionally. The goal is to streamline operations, improve workflow efficiency, reduce redundancies, and ensure interoperability among disparate systems, thus enhancing the organization's overall technological infrastructure. | |
Technology Consulting | Advises clients on how to best use technology to meet their business objectives. This involves assessing technology needs, implementing suitable technology solutions, optimizing existing systems, and providing strategic guidance to facilitate digital transformation and enhance operational efficiency. | |
Project/Program Management | Manages cross-functional projects, ensuring successful coordination, resource allocation, and timely delivery. | |
Project/Program Management - Non-technical | Oversees the coordination and management of projects, typically involving cross-functional teams. They collaborate with project teams and stakeholders to plan, execute, monitor, and control projects. The role involves managing resources, budget, timelines, quality, risks, and other project constraints to ensure successful project delivery. | |
Project/Program Management - Technical | Oversees technical projects or initiatives, typically within the research and development function. | |
QA Engineering | Ensures the quality and functionality of software or hardware systems through rigorous testing methods. | |
QA Engineering - Generalist | Specializes in conducting comprehensive testing of software products to meet the firm's quality standards. They utilize automated testing tools to identify and debug issues, ensuring the functionality and reliability of the programs. Collaborating closely with development engineers, they address and resolve any identified issues. | |
Test Engineering | Defines and executes cost-efficient strategies for testing and diagnosing software or hardware systems. They are responsible for creating testing and diagnostic programs, designing testing apparatus and equipment, and finalizing specifications and procedures for new products. | |
Recruiting | Manages the process of attracting, evaluating, and hiring suitable talent for the organization. | |
Research | Ensures the quality and functionality of software or hardware systems through rigorous testing methods. | |
Bioinformatics | Engages in scientific studies, specifically around biology and biochemistry, contributing to scientific advancements. | |
Protein Biochemistry | Responsible for studying and analyzing protein structures, functions, and interactions through experimental techniques, conducting assays, and interpreting data to contribute to scientific research and understanding in the field of biochemistry. | |
Restaurant Operations | Manages the various facets of restaurant functions, emphasizing service quality and operational efficiency. | |
Sales | Drives revenue through client engagement, selling products/services, and managing client relationships to support revenue growth. | |
Digital Ad Sales | Responsible for maximizing digital advertising revenue by identifying and engaging potential clients, creating compelling advertising proposals, negotiating contracts, and driving ad sales initiatives to achieve revenue targets and support business growth. | |
Sales - Generalist | Responsible for selling products and/or services to customers within a designated geographic area, industry, or product segment. | |
Sales - New Business | Responsible for prospecting and acquiring new clients by identifying potential customers, initiating contact, presenting solutions, addressing objections, negotiating contracts, and closing deals to expand the customer base and drive revenue growth. | |
Sales - Strategic Accounts | Responsible for managing key client relationships by identifying growth opportunities, developing account strategies, building strong partnerships, understanding client needs, and ensuring customer satisfaction to drive long-term success and revenue growth from strategic accounts. | |
Sales Development | Responsible for generating and qualifying leads for the sales team by prospecting, conducting research, reaching out to potential customers, nurturing relationships, and scheduling appointments to facilitate the sales process and contribute to revenue growth. | |
Sales Engineering | Merges technical expertise with sales strategies to enhance customer understanding and drive sales success. | |
Sales Operations | Optimizes the procedures and systems that bolster sales performance and growth. | |
Deal Desk Manager | Responsible for aiding commercial endeavors by shaping deals, composing and revising contracts for new ventures, evaluating pricing, offers, and approvals, managing contracts, and assisting field sales with quotes. Ensures adherence to internal and external policies/regulations. Utilizes quoting tools and/or CRM systems. | |
Sales Enablement | Responsible for empowering sales teams by developing and providing essential resources, training, and tools, enabling them to effectively engage customers, close deals, and meet sales targets. | |
Sales Operations - Generalist | Responsible for optimizing sales processes, managing sales data and analytics, implementing sales strategies, supporting sales teams with tools and systems, and ensuring efficient sales operations to drive productivity and revenue growth. | |
Security Engineering | Ensures the protection of digital assets through the design and management of security systems and practices, while identifying and mitigating risks. | |
Application Security Engineering | Defines and develops security features and posturing within the firm's products and services. | |
Cyber Forensics Engineering | Dedicated to identifying, preserving, extracting, and documenting digital evidence from diverse types of digital media. The role includes investigating cybersecurity incidents, assisting in litigation support, and striving to understand complex digital forensic issues, with the aim to protect and analyze the organization's digital information. | |
Security Engineering - Generalist | Designs, builds, and maintains robust security systems. They identify and mitigate risks, implement secure network solutions, respond to security breaches, and contribute to the organization's security policy while ensuring compliance with regulatory standards. | |
Security Operations | Aims to monitor and analyze the organization's security posture continuously. The role includes planning to identify, manage and mitigate security threats, responding to security incidents, and striving to ensure data integrity and network availability, with the goal of protecting the organization's digital assets. | |
Software Engineering | Focuses on the development, design, and integration of software applications, ensuring robust and efficient solutions. | |
Front-end Engineering | Specializes in the development of user interfaces for web-based applications. | |
Product Development Engineering | Drives technical activities related to new product development and innovation. They focus on various aspects such as hardware, software, and integrated hardware/software systems. They collaborate with cross-functional teams to ensure successful integration of hardware and software components, fostering continuous improvement and technological excellence throughout the development process. | |
Software Engineering - Generalist | Responsible for designing, developing, and testing software applications. Responsibilities include writing code, debugging, collaborating with cross-functional teams, and continuously improving software to deliver robust and efficient solutions. | |
System Architecture | Combines hardware and/or software infrastructures, systems and frameworks to define the foundational architecture to be utilized in one or more product solutions. | |
System Development | Integrates software, hardware, and mechanical elements of a product, system, or components to guarantee that the resulting functions align with client specifications. | |
Solutions Engineering | Designs and presents tailored solutions for customers, leveraging technical and product knowledge. | |
Supply Chain | Manages the end-to-end supply chain, from inventory management to sourcing and logistics, ensuring efficient product delivery. | |
Materials Engineering | Focuses on overseeing and optimizing inventory levels. This includes tracking, ordering, and receiving materials, coordinating with suppliers, managing stock levels, and ensuring timely availability of materials for production and distribution processes. | |
Supply Chain - Generalist |
Responsible for managing and optimizing the supply chain process by sourcing suppliers, negotiating contracts, coordinating logistics, managing inventory, and ensuring timely and efficient delivery of products and services to meet customer demands. |
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Additional job families are added on a regular basis as data sufficiency standards are met. Please note, benchmarks for some job families will not be available in all locations or market cuts due to data sufficiency standards.
What executive jobs can I benchmark using Pave?
As of January 2025, Pave's Market Data products deliver compensation benchmarks for the following executive jobs:
C-Level Jobs:
- Chief Customer Officer
- Chief Executive Officer
- Chief Financial Officer
- Chief Information Security Officer
- Chief Legal Officer
- Chief Marketing Officer
- Chief Medical Officer
- Chief of Staff
- Chief Operations Officer
- Chief People Officer
- Chief Product/Strategy Officer
- Chief Revenue Officer
- Chief Scientific Officer
- Chief Technology Officer
- SVP of Business Development
- SVP of Customer Success
- SVP of Data
- SVP of Engineering
- SVP of Finance
- SVP of HR
- SVP of Manufacturing
- SVP of Marketing
- SVP of Operations
- SVP of Product
- SVP of Sales
Vice President (VP) Level Jobs:
- VP of Business Development
- VP of Clinical/ Regulatory
- VP of Customer Success
- VP of Data
- VP of Design
- VP of Engineering
- VP of Finance
- VP of Growth
- VP of HR
- VP of Legal
- VP of Manufacturing
- VP of Marketing
- VP of Operations
- VP of Product/Strategy
- VP of Professional Services
- VP of Sales
Other Jobs:
- General Manager
- President
Additional executive jobs are added on a regular basis as data sufficiency standards are met. Please note, benchmarks for some executive jobs will not be available in all locations or market cuts due to data sufficiency standards.
Pave Job Matching
How does job matching work at Pave?
Pave uses a machine learning algorithm to streamline and accelerate the job matching process for customers. Our algorithm is regularly reviewed by internal and external compensation professionals to improve results over time.
To create strong training data for our job matching algorithm, we periodically ask select customers to manually match some of their employees to Pave's job architecture system. Patterns identified in this training data are then used by our job matching algorithm to assign job matches across our full database.
Our job matching algorithm uses many of the same signals that compensation professionals and consultants use for manual job matching, including:
- Job title
- Job function
- Reporting line
- Span of control
- Employee location
- Compensation history
- Company industry
Additionally, when customers provide us with their job matches to external survey providers, we can use this information to further enhance the accuracy of job matches.
Data Collection and Management Practices
Is connecting my HR platforms to Pave required to access Market Data?
Yes. Access to Pave's Market Data products is contingent upon customers agreeing to connect their HR platforms to Pave, including HRIS, ATS, and EMS systems.
What HRIS, ATS, and EMS systems connect to Pave?
Pave currently supports connections to the following HRIS, ATS, and EMS systems:
ATS, HRIS and Payroll:
- ADP
- Bamboo HR
- Ceridian Dayforce
- Charlie HR
- Deel
- Gusto
- Hibob
- Humaans
- Justworks
- Namely
- Paylocity
- Personio
- Rippling
- Sapling
- Sequoia One
- TriNet
- UKG Pro (Ultipro)
- Workday
- Zenefits
Cap Table / EMS:
- Capdesk
- Captable.io
- Carta
- E-Trade
- Fidelity
- Ledgy
- Pulley
- Shareworks Solium
- Shareworks Startu4p
We regularly build connections to new HRIS, ATS, and EMS systems, so if you use a tool not listed above, Pave can still work for you. We encourage you to contact our team to learn more about your options.
What information does Pave collect on customer employees?
Pave's Market Data products deliver compensation benchmarks to customers using data collected directly from real-time connections to HR platforms. Data collected on customer employees and candidates will vary based on customer needs and controls, but generally includes:
- Employee or candidate name
- Employee or candidate email address
- Location
- Job title
- Job level
- Manager
- Base salary
- Data related to variable (or bonus) compensation
- Data related to equity grants and holdings
Some of this information is used to power Pave's machine learning-based job matching algorithm. For customers who only use our Market Data product, and depending on the HRIS and EMS system you use, we may have options that allow you to connect to Pave without sharing employee names or email addresses.
See the Data Privacy and Security section of this guide to learn more about how Pave protects customer data.
What information does Pave collect on customer organizations?
For Pave's Market Data products, we ask customers to provide the following business information:
Private Companies
- Business name
- Headquarters location
- Funding sources
- Primary industry
- Secondary industry
- Employee headcount
- Revenue
- Valuation
- Capital Raised
- Current & Historical Share Prices
Public Companies
- Business name
- Headquarters location
- Primary industry
- Secondary industry
- Employee headcount
- Revenue
- Market capitalization
- Ticker symbol
- Listing exchange
Company demographic information is used to power filtering options in Pave's Market Data products. Some of the information above cannot be collected directly from HR platforms, so in these cases, account administrators will be asked to input and update information every six months.
See the Data Privacy and Security section of this guide to learn more about how Pave protects customer data.
Data Consistency Labels, Data Sufficiency and Safe Harbor
Why does Pave provide data consistency labels?
Pave's Market Data products include data consistency labels next to all compensation benchmarks. We provide this information because the way data is distributed within a compensation dataset has a significant impact on the reliability of compensation benchmarks. To help companies make well-informed compensation decisions, a benchmarking dataset must paint a complete picture of both sample size and data distribution patterns.
While most traditional compensation surveys only share sample size information, Pave's data consistency labels allow customers to assess both the size and statistical quality of a reported compensation benchmark.
How should customers use Pave's data consistency labels?
Data consistency labels should be used to guide decisions on when and how to utilize compensation benchmarks. A compensation benchmark labeled as "Very High Consistency" can be used at face value with a higher degree of confidence. This is because benchmarks with higher consistency levels indicate there is less variability in pay practices.
A compensation benchmark labeled as "Low Consistency" can still be used, but with an understanding that there is more variability in how the market compensates for this role. This means customers likely have more flexibility to pay slightly above or below the reported compensation benchmark depending on their specific compensation philosophy and existing pay ranges. However, it is important to note that data consistency labels are not intended to serve as a replacement for company-specific range spreads in compensation bands.
How are Pave's data consistency labels different from data confidence labels?
Pave's updated data consistency labels are very similar in concept and practice to the "data confidence labels" displayed in past versions of our Market Data products. However, when we launched updated data consistency labels, we expanded support to all compensation types (e.g., equity) and improved our methodology to provide more context to customers.
Why does my search have a large sample size but low consistency?
This may seem counterintuitive at first glance, but this is exactly why Pave introduced data consistency labels. Our goal is to help compensation professionals think differently about the data they use to make better decisions. In general, as sample sizes increase, data consistency decreases.
For example, if you benchmark compensation for a job using data across the entire United States, this will greatly increase your sample size (generally a good thing); however, there will be a lot of variation in your dataset because it is drawn from such a wide pool of employees (generally a bad thing). As we all know, pay varies widely by city, industry, company size, and company stage of development, etc.
In order to reduce variation in a dataset, compensation professionals typically apply market filters to hone in on more relevant information. However, as you add filters, your sample size will go down.
This is why we show both sample size and data consistency information; it helps compensation professionals fully understand the statistical quality of a reported compensation benchmark and the potential impact of selecting wider vs. narrower datasets.
Why does equity data tend to have lower consistency labels?
Generally speaking, there is a much higher degree of variation in how companies pay employees with equity compensation vs. cash compensation. Equity award sizes also vary widely across locations, job families, job levels, and company stages. Thus, our reported equity compensation benchmarks tend to have lower consistency labels.
Indeed, when comparing cash and equity compensation benchmarks, our data science team finds that it typically takes 10 times more equity data points than base salary data points to produce benchmarks with the same level of consistency.
How do data consistency labels apply to Pave's Calculated Benchmarks feature?
Pave's data consistency labels are applied to all compensation benchmarks in our Market Data products, including compensation benchmarks generated using raw data and our Calculated Benchmarks feature. In both cases, we take various factors, including sample size and data distribution, into account to give customers a view into how well a dataset represents market practices via a margin of error.
Why does a Calculated Benchmarks output have low consistency? Does this mean Pave isn't confident in its calculation?
Data consistency labels are intended to give customers context into how much variation there is in a dataset underlying a compensation benchmark. When there is a high degree of variation in how the market compensates employees for a given role, the consistency level of compensation benchmarks will be lower in order to provide customers with this context. This is true regardless of whether a compensation benchmark is calculated using raw data or other means.
In the case of Calculated Benchmarks outputs labeled as "Low Consistency," Pave is A) providing you with a compensation benchmark where one would otherwise not exist, and B) being transparent that there is a higher level of variation in how the market typically compensates employees for this role.
What are Pave's data sufficiency standards?
Pave's Market Data products require data from a minimum of three companies to generate a compensation benchmark. However, in cases where company and incumbent counts are very low, algorithms in our product often override the display of data. In some cases, our data consistency rules will block the display of data altogether, and in others, our Calculated Benchmarks feature will model results using more robust datasets.
What is Pave's approach to Safe Harbor?
For decades, guidance from the U.S. Department of Justice (DOJ) and U.S. Federal Trade Commission (FTC) trained HR professionals that aggregated compensation data must be at least three months old before being shared, among other considerations. However, in February 2023, the DOJ withdrew its 1996 Healthcare Safe Harbor statement, and in January 2025, the DOJ and FTC went further by withdrawing the 2016 Antitrust Guidance for Human Resource Professionals.
As a result, long-held beliefs about what is required to meet safe harbor guidelines are changing. Additionally, nothing about a real-time market data approach conflicts with the core intent of DOJ and FTC guidance, which is designed to prevent an agreement among competing employers to limit competition or the competitive process.
Pave's model, which aggregates and de-identifies data from thousands of companies, and adheres to all expected data sufficiency standards, meets this litmus test.
Data Privacy and Security
How does Pave protect privacy?
Pave aggregates and de-identifies compensation data from our customers, meaning the information we display in our Market Data products cannot be linked back to any specific customer or employee. In addition, we do not sell employee data. These protections are contractually guaranteed in Pave's agreements, including our:
Is Pave CCPA and GDPR compliant?
Pave adheres to the California Consumer Privacy Act (CCPA) and the European Union's General Data Protection Regulation (GDPR), ensuring that personal data is processed lawfully, transparently, and securely. We also work closely with customers in meeting their compliance requirements under these regulations.
Is Pave SOC 1 Type 2 compliant?
Yes. This attestation verifies that Pave has effective controls in place for financial reporting, ensuring the accuracy and reliability of financial data processed through its platform.
Is Pave SOC 2 Type 2 compliant?
Yes. This attestation confirms that Pave's systems are designed to keep customer data secure, available, and confidential over time, reflecting the company's commitment to ongoing operational excellence.
Is Pave ISO/IEC 27001:2022 certified?
Yes. Pave has achieved ISO/IEC 27001:2022 certification, demonstrating our adherence to international standards for information security management systems. This certification underscores Pave's dedication to systematically managing sensitive information and ensuring data integrity. To view Pave's certificate, click here.
Does Pave have a bug bounty program?
Yes. Pave operates a private bug bounty program.
How often does Pave undergo penetration testing?
The Pave application undergoes biannual penetration testing.
Does Pave use encryption to protect customer data?
Yes. Data is encrypted at rest and in transit. Pave data is encrypted in transit with TLS 1.2 and at rest with AES 256-bit encryption.
How does Pave manage encryption keys?
Pave relies on Google Key Management Service.
Does Pave collect PII from customers?
Yes. The collection of some Personally Identifiable Information (PII) is required for Pave to deliver services to customers. The amount and nature of PII collected by Pave will vary based on the products a customer uses. Typically, our Market Data products consume less PII than our compensation management tools. Customers can work directly with our team to control and adjust data flows as needed.
Who has access to customer data at Pave?
Pave enforces the principle of "Least Privilege," ensuring that employees have access only to the data necessary for their roles. This approach minimizes the risk of unauthorized data exposure and maintains strict confidentiality.
Does Pave have a security training program for employees?
Yes. Pave has a security training program that covers topics ranging from general security awareness for all employees, to more specialized training in secure design principles and other advanced topics for software engineers.
Where does Pave store customer data?
Pave stores data in the United States, utilizing enterprise-grade cloud storage solutions provided by Google Data Centers. We follow data storage best practices that comply with relevant regulations and industry standards.
What else does Pave do to protect customer data?
Pave's Market Data products only display aggregated and de-identified data, ensuring that individual identifying information is not utilized. This practice protects individual privacy and maintains data confidentiality.