Procore Technologies (PCOR) Operating Expenses (2020 - 2026)
Procore Technologies (PCOR) posted Operating Expenses of $295.47 million for Q2 2026, up 3.1% from $286.45 million a year earlier but down 2.6% from the prior quarter.
Procore Technologies (PCOR) Operating Expenses (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Procore Technologies was $1.21 billion, up 4.3% year-over-year; for FY2025, it came in at $1.18 billion, up 8.6% from FY2024.
- Annual Operating Expenses has increased for six consecutive years, with a five-year compound annual growth rate of 24.9% (FY2020 to FY2025).
- In prior years, Procore Technologies' Operating Expenses was $1.08 billion in FY2024 (+9.2%), $991.23 million in FY2023 (+15.0%), $862.24 million in FY2022 (+22.8%) and $702.44 million in FY2021 (+81.4%).
- Quarterly Operating Expenses has run from a low of $158.85 million in Q3 2021 to a high of $322.5 million in Q4 2025 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last nine quarters, with growth averaging 10.2% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2022, with growth of 85.4%; the weakest was Q2 2022, with a decline of 15.7%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $303.46 million (Q1 2026), $322.5 million (Q4 2025) and $285.12 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 178,646.00 |
| 2 | Veeva Systems | 50.19 Bn | 22.44 Bn | 695.95 Mn | 420.93 Mn |
| 3 | Samsara | 23.08 Bn | 19.85 Bn | 392.58 Mn | 387.71 Mn |
| 4 | Ptc | 22.13 Bn | 20.95 Bn | 490.47 Mn | 323.96 Mn |
| 5 | Toast | 18.36 Bn | 11.03 Bn | 516.00 Mn | 364.00 Mn |
| 6 | Trimble | 13.91 Bn | 12.97 Bn | 674.90 Mn | 542.90 Mn |
| 7 | Manhattan Associates | 13.13 Bn | 12.13 Bn | 168.33 Mn | 231.56 Mn |
| 8 | Costar | 12.81 Bn | 6.76 Bn | 728.00 Mn | 652.00 Mn |
| 9 | Bentley Systems | 10.98 Bn | 10.44 Bn | 336.74 Mn | 248.13 Mn |
| 10 | Procore Technologies | 8.49 Bn | 5.79 Bn | 299.80 Mn | 295.47 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 295.47 Mn |
| Mar 31, 2026 | 303.46 Mn |
| Dec 31, 2025 | 322.50 Mn |
| Sep 30, 2025 | 285.12 Mn |
| Jun 30, 2025 | 286.45 Mn |
| Mar 31, 2025 | 281.95 Mn |
| Dec 31, 2024 | 311.46 Mn |
| Sep 30, 2024 | 277.43 Mn |
| Jun 30, 2024 | 251.02 Mn |
| Mar 31, 2024 | 242.61 Mn |
| Dec 31, 2023 | 249.54 Mn |
| Sep 30, 2023 | 254.13 Mn |
| Jun 30, 2023 | 244.96 Mn |
| Mar 31, 2023 | 242.59 Mn |
| Dec 31, 2022 | 236.69 Mn |
| Sep 30, 2022 | 220.46 Mn |
| Jun 30, 2022 | 207.77 Mn |
| Mar 31, 2022 | 197.32 Mn |
| Dec 31, 2021 | 190.79 Mn |
| Sep 30, 2021 | 158.85 Mn |
Procore Technologies 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=PCOR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PCOR", "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=PCOR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();