Marketwise (MKTW) Operating Expenses (2020 - 2026)
Marketwise's Operating Expenses was $80.06 million in Q2 2026, up 22.9% from $65.14 million a year earlier and up 2.5% from the prior quarter.
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Analysis
Marketwise (MKTW) Operating Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Marketwise's Operating Expenses was $291.85 million through Jun 30, 2026, up 4.1% year-over-year; for FY2025, it came in at $265.53 million, down 16.9% from FY2024.
- Operating Expenses has now declined for four consecutive years, with a five-year compound annual growth rate of -21.7% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $319.71 million in FY2024 (-19.3%), $396.38 million in FY2023 (-6.8%), $425.12 million in FY2022 (-72.0%) and $1.52 billion in FY2021 (+68.0%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses since Q2 2024.
- Compared with a year earlier, Operating Expenses was higher in two of the last eight quarters, with an average decline of 10.1%.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2021 (growth of 210.5%); the worst was Q1 2022 (a decline of 83.7%).
- Per Business Quant data, MKTW's Operating Expenses in the three quarters before Q2 2026 was $78.13 million (Q1 2026), $70.21 million (Q4 2025) and $63.45 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 12.62 Bn |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 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 | 72.30 Bn | 51.65 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Marketwise | 309.79 Mn | -130.29 Mn | 64.70 Mn | 80.06 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 80.06 Mn |
| Mar 31, 2026 | 78.13 Mn |
| Dec 31, 2025 | 70.21 Mn |
| Sep 30, 2025 | 63.45 Mn |
| Jun 30, 2025 | 65.14 Mn |
| Mar 31, 2025 | 66.73 Mn |
| Dec 31, 2024 | 73.28 Mn |
| Sep 30, 2024 | 75.28 Mn |
| Jun 30, 2024 | 83.71 Mn |
| Mar 31, 2024 | 87.44 Mn |
| Dec 31, 2023 | 110.92 Mn |
| Sep 30, 2023 | 95.11 Mn |
| Jun 30, 2023 | 94.73 Mn |
| Mar 31, 2023 | 95.63 Mn |
| Dec 31, 2022 | 102.89 Mn |
| Sep 30, 2022 | 98.21 Mn |
| Jun 30, 2022 | 104.64 Mn |
| Mar 31, 2022 | 119.38 Mn |
| Dec 31, 2021 | 117.41 Mn |
| Sep 30, 2021 | 513.73 Mn |
API Access
Marketwise 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=MKTW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MKTW", "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=MKTW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();