Ramp Spend Share Index

Methodology

The Ramp Business Spend Index is constructed from aggregated, anonymized transaction data across more than 50,000 U.S. businesses that use Ramp's corporate card and bill pay platform. The index is designed to measure real changes in business spending activity across the broader economy — not Ramp's own growth or platform adoption.

To isolate genuine economic signals, we apply a multi-step statistical pipeline. First, we use machine learning models to identify and remove spending patterns attributable to a company's lifecycle on the Ramp platform, including onboarding ramp-ups and churn-related declines. We train separate models for card and bill pay channels, as well as for individual spending categories and industries, to account for differences in adoption behavior across these dimensions. Second, we construct the index using a same-store methodology — only comparing businesses active in consecutive months — and weight observations using a Törnqvist index, a standard approach in economic measurement. Third, we apply size-group caps so that no segment of businesses by size disproportionately influences the overall index.

The result is a timely, high-frequency indicator of U.S. business spending trends, broken out by sector and spending category. Sub-indices allow for analysis of where growth or contraction is concentrated — whether in technology, retail, construction, travel, or other areas.

Important: The Ramp Business Spend Index is not a measure of Ramp's financial or business performance. The statistical controls described above are specifically designed to remove Ramp-specific platform dynamics. The index values, trends, and growth rates presented cannot be used to infer, estimate, or reverse-engineer Ramp's transaction volumes, revenue, net dollar retention, or any other internal business metric.