Specificity (SPTY) Return on Sales [ROS] (2021 - 2026)
Specificity's Return on Sales [ROS] was -19.36% in Q2 2026, up 5.91 percentage points from -25.27% a year earlier and up 34.77 percentage points from the prior quarter.
Powered by 
Analysis
Specificity (SPTY) Return on Sales [ROS] (2021 - 2026) Analysis & Trends
On a trailing twelve-month basis, Specificity's Return on Sales [ROS] was -33.91% through Jun 30, 2026, up 42.04 percentage points year-over-year; for FY2025, it was -34.02%, up 17.00 percentage points from FY2024.
- Return on Sales [ROS] has now increased for three consecutive years, with a five-year change of +46.28 percentage points (FY2020 to FY2025).
- In earlier years, Return on Sales [ROS] was -51.02% in FY2024 (+19.59 pp), -70.61% in FY2023 (+244.52 pp), -315.13% in FY2022 (-3.86 pp) and -311.26% in FY2021 (-230.97 pp).
- The Q2 2026 figure marks the highest quarterly Return on Sales [ROS] since Q2 2024.
- Compared with a year earlier, Return on Sales [ROS] was higher in three of the last eight quarters, with an average year-over-year change of -6.23 percentage points.
- The best year-over-year quarter for Return on Sales [ROS] over five years was Q1 2023 (a gain of 381.20 percentage points); the worst was Q4 2024 (a drop of 131.64 percentage points).
- Per Business Quant data, SPTY's Return on Sales [ROS] in the three quarters before Q2 2026 was -54.13% (Q1 2026), -46.78% (Q4 2025) and -19.81% (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 464.51 Bn | 433.46 Bn | 1.64 Bn | 47.12% |
| 2 | Oracle | 372.69 Bn | 244.82 Bn | - | 34.78% |
| 3 | Sap Se | 277.22 Bn | 205.00 Bn | 8.40 Bn | 26.76% |
| 4 | Salesforce | 199.46 Bn | 155.33 Bn | 8.70 Bn | 20.55% |
| 5 | ServiceNow | 158.92 Bn | 137.38 Bn | 2.82 Bn | 4.06% |
| 6 | Automatic Data Processing | 122.73 Bn | 104.85 Bn | 2.51 Bn | -33.33% |
| 7 | Intuit | 95.03 Bn | 74.38 Bn | 3.44 Bn | 10.91% |
| 8 | Relx | 73.93 Bn | 73.02 Bn | - | - |
| 9 | Thomson Reuters | 54.54 Bn | 51.32 Bn | - | 28.56% |
| 10 | Specificity | 4.98 Mn | 4.93 Mn | 118,436.00 | -19.36% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -19.36% |
| Mar 31, 2026 | -54.13% |
| Dec 31, 2025 | -46.78% |
| Sep 30, 2025 | -19.81% |
| Jun 30, 2025 | -25.27% |
| Mar 31, 2025 | -42.85% |
| Dec 31, 2024 | -203.92% |
| Sep 30, 2024 | -99.10% |
| Jun 30, 2024 | -15.36% |
| Mar 31, 2024 | 8.92% |
| Dec 31, 2023 | -72.28% |
| Sep 30, 2023 | -11.51% |
| Jun 30, 2023 | -97.88% |
| Mar 31, 2023 | -107.48% |
| Dec 31, 2022 | -383.21% |
| Sep 30, 2022 | -95.11% |
| Jun 30, 2022 | -95.11% |
| Mar 31, 2022 | -488.68% |
| Dec 31, 2021 | -354.59% |
| Sep 30, 2021 | -73.67% |
API Access
Specificity 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=SPTY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "SPTY", "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=SPTY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();