S&P Global (SPGI) Return on Sales [ROS] (2009 - 2026)
S&P Global's Return on Sales [ROS] came in at 43.70% for Q2 2026, up 2.40 percentage points from 41.30% a year earlier but down 4.29 percentage points from the prior quarter.
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Analysis
S&P Global (SPGI) Return on Sales [ROS] (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, S&P Global reported Return on Sales [ROS] of 44.43%, up 4.48 percentage points year-over-year; for FY2025, it came in at 42.24%, up 2.97 percentage points from FY2024.
- Return on Sales [ROS] carries a five-year change of -6.36 percentage points (FY2020 to FY2025).
- Going back by year, Return on Sales [ROS] was 39.27% in FY2024 (+7.11 pp), 32.17% in FY2023 (-12.05 pp), 44.22% in FY2022 (-6.66 pp) and 50.87% in FY2021 (+2.27 pp).
- The five-year range for quarterly Return on Sales [ROS] is 24.38% (Q4 2022) to 79.20% (Q1 2022).
- Year-over-year, Return on Sales [ROS] has increased for 12 consecutive quarters, with an average year-over-year change of +4.24 percentage points over the last eight quarters.
- The fastest year-over-year change in Return on Sales [ROS] over five years came in Q1 2022 (a gain of 25.58 percentage points), and the weakest in Q1 2023 (a drop of 42.99 percentage points).
- Business Quant data shows SPGI's Return on Sales [ROS] at 48.00% (Q1 2026), 42.75% (Q4 2025) and 43.08% (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Msci | 236.00 Bn | 234.48 Bn | 739.80 Mn | 56.29% |
| 2 | S&P Global | 137.30 Bn | 132.50 Bn | 2.64 Bn | 53.18% |
| 3 | Moodys | 87.63 Bn | 80.69 Bn | 1.50 Bn | 44.78% |
| 4 | Verisk Analytics | 26.66 Bn | 22.85 Bn | 567.00 Mn | 45.15% |
| 5 | Equifax | 22.03 Bn | 21.43 Bn | 940.10 Mn | 20.99% |
| 6 | TransUnion | 15.46 Bn | 12.30 Bn | - | 20.36% |
| 7 | Factset Research Systems | 11.73 Bn | 10.58 Bn | 308.40 Mn | 24.68% |
| 8 | Morningstar | 9.14 Bn | 7.03 Bn | 431.40 Mn | 24.91% |
| 9 | Mastercard | 572.29 Bn | 532.37 Bn | - | 59.77% |
| 10 | Cme | 113.65 Bn | 101.99 Bn | 359.20 Mn | 65.70% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 53.18% |
| Jun 30, 2026 | 43.70% |
| Mar 31, 2026 | 48.00% |
| Dec 31, 2025 | 38.36% |
| Sep 30, 2025 | 45.19% |
| Jun 30, 2025 | 41.30% |
| Mar 31, 2025 | 41.78% |
| Dec 31, 2024 | 36.44% |
| Sep 30, 2024 | 40.11% |
| Jun 30, 2024 | 40.91% |
| Mar 31, 2024 | 39.67% |
| Dec 31, 2023 | 28.24% |
| Sep 30, 2023 | 34.82% |
| Jun 30, 2023 | 29.38% |
| Mar 31, 2023 | 36.20% |
| Dec 31, 2022 | 24.38% |
| Sep 30, 2022 | 29.81% |
| Jun 30, 2022 | 49.52% |
| Mar 31, 2022 | 79.20% |
| Dec 31, 2021 | 43.30% |
API Access
S&P Global Return on Sales [ROS] API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=return-on-sales-%5Bros%5D&ticker=SPGI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "SPGI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=return-on-sales-%5Bros%5D&ticker=SPGI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();