Blackline (BL) Operating Expenses (2015 - 2026)
Blackline's Operating Expenses came in at $131.69 million for Q2 2026, up 8.1% from $121.86 million a year earlier but down 0.9% from the prior quarter.
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Analysis
Blackline (BL) Operating Expenses (2015 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Blackline reported Operating Expenses of $521.8 million, up 8.1% year-over-year; for FY2025, it was $501.49 million, up 6.1% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 10.6% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $472.84 million in FY2024 (+10.3%), $428.86 million in FY2023 (-4.6%), $449.75 million in FY2022 (+22.7%) and $366.45 million in FY2021 (+21.1%).
- The five-year range for quarterly Operating Expenses is $79.01 million (Q3 2021) to $132.92 million (Q1 2026).
- Year-over-year, Operating Expenses has increased for nine consecutive quarters, with growth averaging 7.2% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2022 (growth of 56.0%), and the weakest in Q2 2023 (a decline of 17.3%).
- Business Quant data shows BL's Operating Expenses at $132.92 million (Q1 2026), $130.91 million (Q4 2025) and $126.29 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 470.71 Bn | 439.66 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 382.66 Bn | 254.79 Bn | - | 12.62 Bn |
| 3 | Sap Se | 270.42 Bn | 198.20 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 197.21 Bn | 153.08 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 155.58 Bn | 134.04 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 117.58 Bn | 99.70 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 91.99 Bn | 71.34 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 72.77 Bn | 71.86 Bn | - | - |
| 9 | Thomson Reuters | 51.52 Bn | 48.30 Bn | - | -1.21 Bn |
| 10 | Blackline | 1.83 Bn | -802.97 Mn | 142.68 Mn | 131.69 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 131.69 Mn |
| Mar 31, 2026 | 132.92 Mn |
| Dec 31, 2025 | 130.91 Mn |
| Sep 30, 2025 | 126.29 Mn |
| Jun 30, 2025 | 121.86 Mn |
| Mar 31, 2025 | 122.43 Mn |
| Dec 31, 2024 | 121.83 Mn |
| Sep 30, 2024 | 116.44 Mn |
| Jun 30, 2024 | 117.95 Mn |
| Mar 31, 2024 | 116.62 Mn |
| Dec 31, 2023 | 105.30 Mn |
| Sep 30, 2023 | 114.99 Mn |
| Jun 30, 2023 | 89.54 Mn |
| Mar 31, 2023 | 119.03 Mn |
| Dec 31, 2022 | 103.32 Mn |
| Sep 30, 2022 | 123.26 Mn |
| Jun 30, 2022 | 108.25 Mn |
| Mar 31, 2022 | 114.93 Mn |
| Dec 31, 2021 | 103.54 Mn |
| Sep 30, 2021 | 79.01 Mn |
API Access
Blackline 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=BL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BL", "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=BL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();