📹 Watch now: How expensive is AI/ML talent?
Join comp experts from MongoDB, Nua Group, and Pave as they dig into trends in total comp, hiring, attrition, and more for top technical talent. View on-demand now ->

Efficiently Benchmark Jobs and Build Confidence in Your Ranges

Use Pave Market Pricing to analyze multiple datasets, put benchmarks into action, and create or update comp bands.
Request demo

TRUSTED BY THE WORLD’S MOST INNOVATIVE COMPANIES

What Pave Market Pricing delivers

data sources

Create a system of record for all your market data

Aggregate all your market data sources in one location, and reference current and past market data points to track changes. Plus, pull the latest Pave data with turnkey integration.
Market data mapping

Intuitively map market data to your job architecture

Store your job matches for repeatable benchmarking. Save elements that are unique to your programs, and pull the latest benchmarks based on your company’s compensation philosophy.
DATA GAP RESOLUTION

Intelligently & quickly fill data gaps

Apply survey and job code fallbacks where your primary cut is missing data, and leverage level progressions and geo differentials for data gaps. Your decisions are tracked in a sharable audit log.
BAND GENERATOR

Automate range generation & repricing

Build new bands in seconds, not hours. Model different scenarios and efficiently update your ranges so you can focus your time and energy on stakeholder engagement.
VISUALIZE & SHARE

Build confidence in your comp strategy

View where your employees fall within their compensation band, and set up granular permissions to share compensation bands with the right stakeholders. Share employee-specific salary band information in a personalized Total Rewards portal.

Get aligned. Stay aligned.

Aggregate Survey Data
Analyze multiple market data sources and understand which ones give you the best coverage.
Intelligently Benchmark Jobs
Highlight gaps in market data and apply fallbacks to get the best possible benchmarks.
Streamline Repricing
Automate range generation and repricing with one-click workflows and mass updates.

Trusted by innovative startups and the world’s leading enterprises

Pave's Market Pricing tool increased my confidence in explaining how our compensation bands were developed. Since the logic lives in Pave, it will be easy to apply it in the future.
Ben Dickens
Ben Dickens
Senior HR Manager, Snapdocs
Read case study
Pave's Market Pricing tool increased my confidence in explaining how our compensation bands were developed. Since the logic lives in Pave, it will be easy to apply it in the future.
Ben Dickens
Ben Dickens
Senior HR Manager, Snapdocs
Read case study
In previous cycles, we had to pull data into spreadsheets, aggregate it, and come up with complex, error-prone formulas to benchmark. Even small changes would take a lot of time. With Market Pricing from Pave, we can view all our market data and encode our comp philosophy, enabling us to reprice faster with more confidence.
Yvonne Liu
Yvonne Liu
Senior Manager, Compensation, Clio
Read case study

Learn more about
Pave Market Pricing

Sign up for freeRequest demo
Solutions
Market DataCompensation WorkflowsCommunication
Product
BenchmarkingMarket PricingCompensation PlanningTotal RewardsVisual Offer Letter
Resources
BlogPave Data LabWebinarsCase StudiesGuidesHelp CenterIntegrations
Company
PricingCustomersAboutCareersSecurity & PrivacyPress RoomContact Support
Legal
Privacy PolicyTerms of UseService Terms
Fulfillment PolicyMaster Subscription Agreement
Built in San Francisco, CA
© Copyright 2023

Pave's successful SOC 2 Type 2 report was issued by the Johanson Group and is actively monitored by Drata.

(function (h, o, t, j, a, r) { h.hj = h.hj || function () { (h.hj.q = h.hj.q || []).push(arguments) }; h._hjSettings = { hjid: 2412860, hjsv: 6 }; a = o.getElementsByTagName('head')[0]; r = o.createElement('script'); r.async = 1; r.src = t + h._hjSettings.hjid + j + h._hjSettings.hjsv; a.appendChild(r); })(window, document, 'https://static.hotjar.com/c/hotjar-', '.js?sv='); !function () { var analytics = window.analytics = window.analytics || []; if (!analytics.initialize) if (analytics.invoked) window.console && console.error && console.error("Segment snippet included twice."); else { analytics.invoked = !0; analytics.methods = ["trackSubmit", "trackClick", "trackLink", "trackForm", "pageview", "identify", "reset", "group", "track", "ready", "alias", "debug", "page", "once", "off", "on", "addSourceMiddleware", "addIntegrationMiddleware", "setAnonymousId", "addDestinationMiddleware"]; analytics.factory = function (e) { return function () { var t = Array.prototype.slice.call(arguments); t.unshift(e); analytics.push(t); return analytics } }; for (var e = 0; e < analytics.methods.length; e++) { var key = analytics.methods[e]; analytics[key] = analytics.factory(key) } analytics.load = function (key, e) { var t = document.createElement("script"); t.type = "text/javascript"; t.async = !0; t.src = "https://cdn.segment.com/analytics.js/v1/" + key + "/analytics.min.js"; var n = document.getElementsByTagName("script")[0]; n.parentNode.insertBefore(t, n); analytics._loadOptions = e }; analytics.SNIPPET_VERSION = "4.13.1"; analytics.load("0KGQyN5tZ344emH53H3kxq9XcOO1bKKw"); analytics.page(); } }(); $(document).ready(function () { $('[data-analytics]').on('click', function (e) { var properties var event = $(this).attr('data-analytics') $.each(this.attributes, function (_, attribute) { if (attribute.name.startsWith('data-property-')) { if (!properties) properties = {} var property = attribute.name.split('data-property-')[1] properties[property] = attribute.value } }) analytics.track(event, properties) }) }); var isMobile = /iPhone|iPad|iPod|Android/i.test(navigator.userAgent); if (isMobile) { var dropdown = document.querySelectorAll('.navbar__dropdown'); for (var i = 0; i < dropdown.length; i++) { dropdown[i].addEventListener('click', function(e) { e.stopPropagation(); this.classList.toggle('w--open'); }); } }