Overview
Pave is a modern compensation platform providing real-time market data and sophisticated comp planning tools. Unlike traditional surveys updated annually, Pave provides continuously updated compensation benchmarks from thousands of companies. The platform helps organizations design equitable pay structures, plan compensation budgets, communicate comp philosophy, and ensure pay equity across the organization.
Pros & Cons
Pros
- ✓Real-time compensation data more current than annual surveys
- ✓Comprehensive data from thousands of tech companies
- ✓Beautiful, intuitive compensation planning tools
- ✓Strong pay equity and DEI analytics
- ✓Excellent customer support and implementation
- ✓Transparent total compensation statements for employees
Cons
- ✗Premium pricing limits access to mid-market companies
- ✗Best suited for tech companies (less data for other industries)
- ✗Requires data sharing to access benchmarks
- ✗Smaller dataset compared to traditional survey providers
Who Should Use This?
Best For
- →High-growth tech companies 100-2000 employees
- →Organizations doing regular compensation planning cycles
- →Companies prioritizing pay equity and transparency
- →Businesses competing for tech talent
- →HR and Finance teams collaborating on comp budgets
Not Ideal For
- →Small businesses under 50 employees
- →Traditional industries outside tech
- →Companies with static compensation structures
- →Organizations with limited HR budgets
- →Businesses not actively recruiting or adjusting compensation
Key Features
Implementation
Implementation takes 4-6 weeks with dedicated customer success support.
Get Pricing for Pave
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Quick Info
Custom enterprise pricing starting around $20,000-50,000 annually depending on company size.
📋 Implementation Guide
Step-by-step guide to implementing Compensation software
View Guide BelowOpen Full Guide PageImplementing Compensation Management Software
Modernize compensation planning, pay equity analysis, and salary benchmarking.
Implementation Steps
Build foundation with clean data and job leveling.
Key Tips:
- Collect all employee compensation data
- Define job families and levels
- Map employees to job levels
- Gather market data from compensation surveys
- Document current compensation philosophy
Common Mistakes to Avoid
- ×Inconsistent job leveling - leads to pay inequities
- ×Not training managers properly - poor compensation conversations
- ×Ignoring pay equity issues
- ×Making process too complex - analysis paralysis
- ×Not having clear compensation philosophy
Best Practices
- Start with clear compensation philosophy
- Involve managers early in process design
- Run pay equity analysis before finalizing changes
- Provide manager training on compensation conversations
- Be transparent about how pay is determined
- Continuously benchmark against market
Frequently Asked Questions About Pave
Common questions about Pave, including pricing, features, integrations, and who should use it.