Expensify (EXFY) Return on Sales [ROS] (2020 - 2026)
Expensify (EXFY) reported Return on Sales [ROS] of -8.63% for Q2 2026, up 20.28 percentage points from -28.91% a year earlier but down 2.82 percentage points from the prior quarter.
Expensify (EXFY) Return on Sales [ROS] (2020 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Expensify's Return on Sales [ROS] came in at -8.03%, down 0.35 percentage points year-over-year; for FY2025, it came in at -12.68%, down 12.09 percentage points from FY2024.
- Return on Sales [ROS] has a five-year change of -19.12 percentage points (FY2020 to FY2025).
- By year, Return on Sales [ROS] came in at -0.59% in FY2024 (+21.41 pp), -22.00% in FY2023 (-13.01 pp), -8.99% in FY2022 (-1.81 pp) and -7.18% in FY2021 (-13.62 pp).
- Five-year quarterly Return on Sales [ROS] spans a low of -50.63% in Q4 2021 and a high of 1.26% in Q4 2024.
- Year over year, Return on Sales [ROS] gained in four of the last eight quarters, with an average year-over-year change of +3.81 percentage points.
- The high point for year-over-year Return on Sales [ROS] in five years was Q4 2022 (a gain of 49.02 percentage points); the low point was Q4 2021 (a drop of 67.69 percentage points).
- Per Business Quant data, the three quarters before Q2 2026 came in at -5.81% (Q1 2026), -11.19% (Q4 2025) and -6.44% (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 407.96 Bn | 372.79 Bn | 1.93 Bn | 46.89% |
| 2 | Oracle | 352.42 Bn | 224.55 Bn | - | 34.78% |
| 3 | Sap Se | 276.89 Bn | 204.29 Bn | 8.64 Bn | 28.53% |
| 4 | Salesforce | 176.49 Bn | 132.36 Bn | 8.70 Bn | 20.55% |
| 5 | Automatic Data Processing | 121.63 Bn | 108.43 Bn | 2.53 Bn | -30.06% |
| 6 | ServiceNow | 107.67 Bn | 86.93 Bn | 2.90 Bn | 9.38% |
| 7 | Intuit | 93.37 Bn | 72.72 Bn | 3.44 Bn | 10.91% |
| 8 | Relx | 73.28 Bn | 72.37 Bn | - | - |
| 9 | Strategy | 50.66 Bn | 37.80 Bn | 89.63 Mn | 16,670.89% |
| 10 | Expensify | 169.79 Mn | -89.33 Mn | 14.93 Mn | -8.10% |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | -8.10% |
| Jun 30, 2026 | -8.63% |
| Mar 31, 2026 | -5.81% |
| Dec 31, 2025 | -11.19% |
| Sep 30, 2025 | -6.44% |
| Jun 30, 2025 | -28.91% |
| Mar 31, 2025 | -4.12% |
| Dec 31, 2024 | 1.26% |
| Sep 30, 2024 | 0.81% |
| Jun 30, 2024 | 0.66% |
| Mar 31, 2024 | -5.35% |
| Dec 31, 2023 | -17.00% |
| Sep 30, 2023 | -40.82% |
| Jun 30, 2023 | -24.59% |
| Mar 31, 2023 | -6.74% |
| Dec 31, 2022 | -1.61% |
| Sep 30, 2022 | -13.45% |
| Jun 30, 2022 | -9.21% |
| Mar 31, 2022 | -11.99% |
| Dec 31, 2021 | -50.63% |
Expensify 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=EXFY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "EXFY", "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=EXFY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();