Launch Preview: Taking Pave's Compensation Benchmarks to the Next Level

At Pave, we're all about perfecting the art and science of pay. From compensation benchmarks to compensation workflows, our team is focused on developing a platform that empowers compensation professionals to make smarter, faster pay decisions with confidence.

Early on, this led us to ask a simple question: What if we could give customers better compensation intelligence by collecting real-time data directly from HR systems, and eliminate the pain of participating in traditional compensation surveys?

Four years—and 8,000+ customers later—it's safe to say the real-time compensation data revolution has arrived! Getting pay insights no longer requires spending three months on manual job matching, submitting stale data via insecure Excel files, and then waiting months for outdated benchmarks.

However, we know our work isn't done. To meet the needs of both startups and global enterprises in a rapidly changing labor market, our products must continue to evolve. This is why we're thrilled to preview the most significant set of enhancements to our Market Data products since Pave's launch.

With these updates, we're sending a clear message: No matter where you are on your growth journey, you deserve better compensation intelligence and a better customer experience.

See How We're Taking Market Data to the Next Level

Enterprise-grade job architecture

Our early Q3 release includes an expanded job architecture that improves our ability to handle data from complex organizations. We're adding a career track for individual contributors in support roles (job levels S1, S2, and S3), filling out our existing management career track with job level M2, and streamlining our leadership career track with VP, SVP, and C-Suite levels. Now, whether you're benchmarking pay for a Customer Success Manager at a 50-person SaaS company or a Director of Operations at a 5,000-person enterprise, you'll find more precise job levels aligned to your needs.

Expanded job catalog

At the same time, Pave's job catalog will grow to 200+ job families, allowing you to benchmark pay for more roles with greater granularity. Key areas of improvement include adding more AI, engineering, and G&A jobs, among others. We plan to fast-follow with more biotechnology jobs in October.

We aren’t adding jobs for the sake of it. We analyzed patterns in our dataset to ensure we only added jobs with meaningful distinctions between each other. Creating an overloaded job library with close to 1,000 job families that are hard to tell apart is not the goal. 

Please note, it will take time for some new job families and job levels to populate with data. We will publish benchmarks as soon as sufficient data becomes available.

Enhanced AI job matching

We're also releasing enhancements to our job leveling and matching algorithms to support the changes above. This brings us closer to eliminating fully manual job matching. Instead of spending hours debating whether your Senior Product Manager maps to P4 or P5, our AI model will consider job titles, organizational structures, internal levels, and many other data points from your HR systems, to handle matching for you with the same accuracy as human reviewers.

New industry filter

A new, modern industry filter also arrives in early Q3! For example, you’ll soon be able to examine compensation for AI engineers across different market segments, from AI to FinTech to Enterprise Software companies. We'll add more industries as data becomes available, but you can expect to see the following options on day one:

• Technology - Software Products & Services
  
  • Artificial Intelligence (AI)
  • Consumer Software
  • Ecommerce
  • Enterprise Software
  • FinTech
  • HealthTech
• Technology - Hardware & Devices
• Media, Entertainment & Gaming
• Life Sciences
• Commercial Products & Services (Non-tech)
• Consumer Products & Services (Non-tech)

Improved company demographic filters

We're also improving the granularity of our capital raised, headcount, revenue, and valuation filters, meaning you'll see more "buckets" to fine-tune how you benchmark pay. These changes include more options at the upper end of the scale to reflect the growing number of large companies using Pave.

Streamlined user experience

Finally, to ensure Pave remains easy to use for everyone, we're merging our employee and executive compensation benchmarking experiences into one seamless view. You'll be able to use our AI-powered search to find results for all job families and all job levels in one place and access the same filters and compensation types all the time.

We're also refining our ground-breaking Calculated Benchmarks feature, launched in January. This work will further expand our market-leading equity compensation coverage, bringing us closer to ensuring you never choose between data relevance and data coverage.

Keeping Our Promise to Companies at Every Stage of Growth

At Pave, we believe great compensation intelligence shouldn't be a luxury reserved for a handful of companies—every business deserves access to high-caliber, real-time data and insights. This is why every enhancement listed above will be available to both our free Market Data Launch and paid Market Data Pro customers.

Yes, hundreds of enterprise companies are turning to Pave to leave painful compensation surveys behind, but supporting emerging companies and the VC community remains core to our mission.

Supporting You Through this Launch

We know changes to the tools you rely on, even exciting ones, can feel disruptive. That's why we've timed these updates to occur ahead of prime benchmarking season. You'll have plenty of time to explore new job levels, job families, and filters heading into your 2026 planning cycle.

We also worked hard to ensure these updates fit intuitively into the benchmarking experience you already enjoy inside Pave. Plus, our customer success team will conduct outreach to assist users and host training webinars throughout Q3 and Q4. Stay tuned for more news soon!

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