Chewy (CHWY) Operating Expenses (2018 - 2026)
Chewy (CHWY) posted Operating Expenses of $919.2 million for fiscal Q2 2027 (quarter ended Aug 2, 2026), up 5.4% from $872.5 million a year earlier and up 4.1% from the prior quarter.
Chewy (CHWY) Operating Expenses (2018 - 2026) Analysis & Trends
For the trailing twelve months through Aug 2, 2026, Operating Expenses at Chewy was $3.58 billion, up 3.1% year-over-year; for FY2026 (ended Feb 1, 2026), it came in at $3.5 billion, up 4.3% from FY2025.
- Annual Operating Expenses has increased for eight consecutive fiscal years, with a five-year compound annual growth rate of 12.9% (FY2021 to FY2026).
- In prior fiscal years, Chewy's Operating Expenses was $3.36 billion in FY2025 (+5.3%), $3.19 billion in FY2024 (+14.7%), $2.78 billion in FY2023 (+13.0%) and $2.46 billion in FY2022 (+28.7%).
- The fiscal Q2 2027 figure stands as the highest quarterly Operating Expenses since fiscal Q4 2025.
- On a year-over-year basis, Operating Expenses increased in seven of the last eight quarters, with growth averaging 5.7%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q4 2022, with growth of 28.1%; the weakest was fiscal Q4 2026, with a decline of 2.0%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $882.9 million (Q1 2027), $917.2 million (Q4 2026) and $863 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 139.34 Bn | 90.80 Bn | - | - |
| 2 | Mondelez International | 80.33 Bn | 73.60 Bn | 3.99 Bn | 2.01 Bn |
| 3 | Hershey | 33.19 Bn | 29.44 Bn | 1.26 Bn | 628.91 Mn |
| 4 | Kraft Heinz | 26.86 Bn | 13.28 Bn | 2.03 Bn | 8.46 Bn |
| 5 | General Mills | 17.22 Bn | 14.87 Bn | 1.49 Bn | 853.60 Mn |
| 6 | J M Smucker | 13.01 Bn | 12.79 Bn | 979.60 Mn | 411.10 Mn |
| 7 | Mccormick | 12.02 Bn | 11.09 Bn | 794.90 Mn | 436.40 Mn |
| 8 | Hormel Foods | 10.90 Bn | 7.56 Bn | 471.52 Mn | 323.50 Mn |
| 9 | Chewy | 8.45 Bn | 5.74 Bn | 1.01 Bn | 919.20 Mn |
| 10 | Lamb Weston Holdings | 7.28 Bn | 6.91 Bn | 266.50 Mn | 184.30 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 2, 2026 | 919.20 Mn |
| May 3, 2026 | 882.90 Mn |
| Feb 1, 2026 | 917.20 Mn |
| Nov 2, 2025 | 863.00 Mn |
| Aug 3, 2025 | 872.50 Mn |
| May 4, 2025 | 846.90 Mn |
| Feb 2, 2025 | 935.70 Mn |
| Oct 27, 2024 | 818.30 Mn |
| Jul 28, 2024 | 811.70 Mn |
| Apr 28, 2024 | 789.40 Mn |
| Jan 28, 2024 | 820.02 Mn |
| Oct 29, 2023 | 791.58 Mn |
| Jul 30, 2023 | 805.38 Mn |
| Apr 30, 2023 | 768.12 Mn |
| Jan 29, 2023 | 747.32 Mn |
| Oct 30, 2022 | 720.61 Mn |
| Jul 31, 2022 | 661.14 Mn |
| May 1, 2022 | 649.00 Mn |
| Jan 30, 2022 | 681.97 Mn |
| Oct 31, 2021 | 616.77 Mn |
Chewy 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=CHWY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CHWY", "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=CHWY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();