Crocs (CROX) Operating Expenses (2010 - 2026)
Crocs' Operating Expenses came in at $415.03 million for Q2 2026, up 4.2% from $398.24 million a year earlier and up 28.9% from the prior quarter.
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Analysis
Crocs (CROX) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Crocs reported Operating Expenses of $1.49 billion, up 2.5% year-over-year; for FY2025, it was $1.47 billion, up 7.7% from FY2024.
- Operating Expenses has increased in each of the last six years, with a five-year compound annual growth rate of 23.3% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $1.36 billion in FY2024 (+17.2%), $1.16 billion in FY2023 (+15.3%), $1.01 billion in FY2022 (+36.9%) and $737.16 million in FY2021 (+43.2%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses in data going back to Q2 2010.
- Year-over-year, Operating Expenses has increased for 24 consecutive quarters, with growth averaging 8.4% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 1.1% in Q1 2026 to 60.5% in Q1 2022.
- Business Quant data shows CROX's Operating Expenses at $322.1 million (Q1 2026), $377.27 million (Q4 2025) and $375.35 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 | Nike | 53.94 Bn | 19.93 Bn | 5.39 Bn | 4.08 Bn |
| 2 | Tapestry | 22.74 Bn | 18.69 Bn | 1.56 Bn | 1.12 Bn |
| 3 | Ralph Lauren | 21.47 Bn | 13.57 Bn | 1.44 Bn | 1.10 Bn |
| 4 | Deckers Outdoor | 11.15 Bn | 4.02 Bn | - | - |
| 5 | Lululemon Athletica | 10.72 Bn | 4.97 Bn | 1.46 Bn | 1.01 Bn |
| 6 | Levi Strauss | 7.64 Bn | 4.29 Bn | 979.10 Mn | 856.90 Mn |
| 7 | Gildan Activewear | 6.52 Bn | 5.51 Bn | 459.76 Mn | 283.86 Mn |
| 8 | Birkenstock Holding | 6.06 Bn | 4.37 Bn | 493.89 Mn | -37.80 Mn |
| 9 | Crocs | 5.89 Bn | 5.30 Bn | 700.71 Mn | 415.03 Mn |
| 10 | V F | 5.67 Bn | 2.29 Bn | 917.04 Mn | 1.75 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 415.03 Mn |
| Mar 31, 2026 | 322.10 Mn |
| Dec 31, 2025 | 377.27 Mn |
| Sep 30, 2025 | 375.35 Mn |
| Jun 30, 2025 | 398.24 Mn |
| Mar 31, 2025 | 318.58 Mn |
| Dec 31, 2024 | 373.01 Mn |
| Sep 30, 2024 | 363.51 Mn |
| Jun 30, 2024 | 356.18 Mn |
| Mar 31, 2024 | 295.65 Mn |
| Dec 31, 2023 | 311.90 Mn |
| Sep 30, 2023 | 307.78 Mn |
| Jun 30, 2023 | 302.82 Mn |
| Mar 31, 2023 | 241.44 Mn |
| Dec 31, 2022 | 276.27 Mn |
| Sep 30, 2022 | 277.24 Mn |
| Jun 30, 2022 | 249.77 Mn |
| Mar 31, 2022 | 206.25 Mn |
| Dec 31, 2021 | 212.04 Mn |
| Sep 30, 2021 | 196.73 Mn |
API Access
Crocs 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=CROX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CROX", "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=CROX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();