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Connect Rippling to Pave to benchmark your compensation data against market peers so pay decisions are grounded in current data, not outdated surveys.
The Rippling–Pave integration connects Rippling's compensation and employee data with Pave's real-time compensation benchmarking platform. Employee comp data from Rippling feeds Pave's benchmarking analysis, giving HR and Total Rewards teams current market position visibility without manually preparing compensation files for survey submissions.
Pave provides real-time compensation benchmarking by aggregating live comp data from its participant network. Connecting Rippling ensures your compensation data is current in Pave's analysis, improving the accuracy of your market position assessment and compensation planning decisions.
Total Rewards teams often benchmark compensation using point-in-time salary survey data that's 12–18 months old, making decisions about offers and raises based on stale market comparisons. Pave's real-time benchmarking addresses this — but only if Rippling's compensation data is flowing in continuously rather than through periodic manual updates.
thePeopleStack configures the Rippling–Pave data connection, mapping Rippling's compensation, job title, department, and work location fields to Pave's benchmarking data requirements. We validate the data quality before activating Pave's benchmarking reports.
Pave's benchmarking data is primarily US-focused, with some international coverage. For thePeopleStack clients with Canadian employees, Rippling's Canadian comp data can be included in the Pave data feed, though Canadian benchmarking depth varies by market and role.
Pave is a real-time compensation benchmarking and total rewards platform that provides market pay data from a live participant network, replacing traditional point-in-time salary surveys for HR and Total Rewards teams.
Rippling's employee compensation fields — base salary, equity, bonus, and total comp — sync to Pave alongside job title, department, work location, and seniority, enabling Pave to position each role against current market benchmarks.
Pave aggregates comp data anonymously across its participant network. Individual company data is not disclosed to other participants; participants see only aggregated market benchmarks, not competitor-specific compensation structures.
Pave's data is refreshed continuously from its live participant network, providing more current benchmarks than traditional annual salary surveys. Connecting Rippling ensures your contribution to the network is equally current.
Configuration takes 2–3 hours including compensation field mapping and data quality validation.
