Sprinklr (CXM) Operating Expenses (2020 - 2026)
Sprinklr (CXM) posted Operating Expenses of $129.23 million for fiscal Q2 2027 (quarter ended Jul 31, 2026), up 0.7% from $128.33 million a year earlier but down 2.4% from the prior quarter.
Sprinklr (CXM) Operating Expenses (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jul 31, 2026, Operating Expenses at Sprinklr was $526.25 million, down 2.8% year-over-year; for FY2026 (ended Jan 31, 2026), it was $537.54 million, down 2.4% from FY2025.
- Annual Operating Expenses shows a five-year compound annual growth rate of 13.1% (FY2021 to FY2026).
- In prior fiscal years, Sprinklr's Operating Expenses was $550.67 million in FY2025 (+6.1%), $519.01 million in FY2024 (+2.6%), $505.69 million in FY2023 (+13.8%) and $444.31 million in FY2022 (+53.0%).
- Quarterly Operating Expenses has run from a low of $113.12 million in fiscal Q3 2022 to a high of $144.62 million in fiscal Q1 2026 over five years.
- On a year-over-year basis, Operating Expenses increased in four of the last eight quarters, with an average decline of 0.8%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q4 2022, with growth of 68.2%; the weakest was fiscal Q2 2026, with a decline of 10.5%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $132.42 million (Q1 2027), $130.66 million (Q4 2026) and $133.94 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 449.27 Bn | 418.33 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 417.01 Bn | 289.56 Bn | - | 12.62 Bn |
| 3 | Sap Se | 258.97 Bn | 180.05 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 185.51 Bn | 141.38 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 134.41 Bn | 112.87 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 71.93 Bn | 51.28 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 60.47 Bn | 57.43 Bn | - | - |
| 9 | Strategy | 54.44 Bn | 47.43 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Sprinklr | 1.14 Bn | 395.28 Mn | 139.19 Mn | 129.23 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 129.23 Mn |
| Apr 30, 2026 | 132.42 Mn |
| Jan 31, 2026 | 130.66 Mn |
| Oct 31, 2025 | 133.94 Mn |
| Jul 31, 2025 | 128.33 Mn |
| Apr 30, 2025 | 144.62 Mn |
| Jan 31, 2025 | 133.27 Mn |
| Oct 31, 2024 | 134.95 Mn |
| Jul 31, 2024 | 143.33 Mn |
| Apr 30, 2024 | 139.12 Mn |
| Jan 31, 2024 | 128.20 Mn |
| Oct 31, 2023 | 126.69 Mn |
| Jul 31, 2023 | 129.51 Mn |
| Apr 30, 2023 | 134.62 Mn |
| Jan 31, 2023 | 127.82 Mn |
| Oct 31, 2022 | 121.33 Mn |
| Jul 31, 2022 | 130.15 Mn |
| Apr 30, 2022 | 126.39 Mn |
| Jan 31, 2022 | 131.66 Mn |
| Oct 31, 2021 | 113.12 Mn |
Sprinklr Operating Expenses 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=operating-expenses&ticker=CXM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CXM", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=CXM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();