Netscout Systems (NTCT) Operating Expenses (2010 - 2025)
Netscout Systems (NTCT) reported Operating Expenses of $140.34 million for fiscal Q3 2026 (quarter ended Dec 31, 2025), down 2.3% from $143.69 million a year earlier and down 1.8% from the prior quarter.
Netscout Systems (NTCT) Operating Expenses (2010 - 2025) Analysis & Trends
Over the twelve months ended Dec 31, 2025, Netscout Systems' Operating Expenses came in at $572.55 million, down 46.1% year-over-year; for FY2025 (ended Mar 31, 2025), it came in at $1.01 billion, up 27.7% from FY2024.
- Operating Expenses has increased for four consecutive fiscal years, with a five-year compound annual growth rate of 9.9% (FY2020 to FY2025).
- By fiscal year, Operating Expenses came in at $791.87 million in FY2024 (+29.0%), $613.77 million in FY2023 (+3.5%), $592.76 million in FY2022 (+3.6%) and $572.06 million in FY2021 (-9.5%).
- Five-year quarterly Operating Expenses spans a low of $127.46 million in fiscal Q2 2024 and a high of $593.52 million in fiscal Q1 2025.
- Year over year, Operating Expenses gained in four of the last eight quarters, with growth averaging 16.9%.
- The high point for year-over-year Operating Expenses in five years was fiscal Q1 2025 (growth of 258.8%); the low point was fiscal Q1 2026 (a decline of 74.7%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $142.92 million (Q2 2026), $149.89 million (Q1 2026) and $139.4 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 499.67 Mn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | - |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 4.17 Bn |
| 10 | Netscout Systems | 2.82 Bn | 526.09 Mn | - | - |
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 140.34 Mn |
| Sep 30, 2025 | 142.92 Mn |
| Jun 30, 2025 | 149.89 Mn |
| Mar 31, 2025 | 139.40 Mn |
| Dec 31, 2024 | 143.69 Mn |
| Sep 30, 2024 | 134.93 Mn |
| Jun 30, 2024 | 593.52 Mn |
| Mar 31, 2024 | 190.08 Mn |
| Dec 31, 2023 | 308.90 Mn |
| Sep 30, 2023 | 127.46 Mn |
| Jun 30, 2023 | 165.44 Mn |
| Mar 31, 2023 | 155.51 Mn |
| Dec 31, 2022 | 148.99 Mn |
| Sep 30, 2022 | 149.04 Mn |
| Jun 30, 2022 | 160.23 Mn |
| Mar 31, 2022 | 151.85 Mn |
| Dec 31, 2021 | 146.27 Mn |
| Sep 30, 2021 | 148.11 Mn |
| Jun 30, 2021 | 146.53 Mn |
| Mar 31, 2021 | 142.38 Mn |
Netscout Systems 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=NTCT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NTCT", "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=NTCT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();