Bark (BARK) Operating Expenses (2020 - 2026)
Bark's Operating Expenses was $57.27 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), down 20.9% from $72.43 million a year earlier and down 13.8% from the prior quarter.
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Analysis
Bark (BARK) Operating Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Bark's Operating Expenses was $266.9 million through Jun 30, 2026, down 18.1% year-over-year; for FY2026 (ended Mar 31, 2026), it was $282.06 million, down 16.3% from FY2025.
- Operating Expenses has now declined for four consecutive fiscal years, though with a five-year compound annual growth rate of 2.7% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $337.14 million in FY2025 (-3.0%), $347.67 million in FY2024 (-6.5%), $371.95 million in FY2023 (-1.2%) and $376.29 million in FY2022 (+52.6%).
- The fiscal Q1 2027 figure marks the lowest quarterly Operating Expenses since fiscal Q2 2021.
- Compared with a year earlier, Operating Expenses has declined for six straight quarters, with an average decline of 11.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q2 2022 (growth of 63.3%); the worst was fiscal Q3 2026 (a decline of 22.9%).
- Per Business Quant data, BARK's Operating Expenses in the three fiscal quarters before Q1 2027 was $66.47 million (Q4 2026), $70.55 million (Q3 2026) and $72.62 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 133.59 Bn | 108.95 Bn | - | - |
| 2 | Mondelez International | 75.71 Bn | 69.03 Bn | 3.99 Bn | 2.01 Bn |
| 3 | Hershey | 32.64 Bn | 28.88 Bn | 1.26 Bn | 628.91 Mn |
| 4 | Kraft Heinz | 27.82 Bn | 14.35 Bn | 2.03 Bn | 8.46 Bn |
| 5 | General Mills | 18.09 Bn | 15.75 Bn | 1.49 Bn | 853.60 Mn |
| 6 | Mccormick | 13.03 Bn | 12.90 Bn | 778.20 Mn | 441.80 Mn |
| 7 | J M Smucker | 12.89 Bn | 12.68 Bn | 979.60 Mn | 411.10 Mn |
| 8 | Hormel Foods | 10.92 Bn | 7.61 Bn | 471.52 Mn | 323.50 Mn |
| 9 | Chewy | 7.33 Bn | 4.62 Bn | 1.01 Bn | 919.20 Mn |
| 10 | Bark | 81.88 Mn | -38.60 Mn | 57.33 Mn | 57.27 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 57.27 Mn |
| Mar 31, 2026 | 66.47 Mn |
| Dec 31, 2025 | 70.55 Mn |
| Sep 30, 2025 | 72.62 Mn |
| Jun 30, 2025 | 72.43 Mn |
| Mar 31, 2025 | 79.97 Mn |
| Dec 31, 2024 | 91.51 Mn |
| Sep 30, 2024 | 81.81 Mn |
| Jun 30, 2024 | 83.86 Mn |
| Mar 31, 2024 | 82.68 Mn |
| Dec 31, 2023 | 91.21 Mn |
| Sep 30, 2023 | 86.74 Mn |
| Jun 30, 2023 | 87.04 Mn |
| Mar 31, 2023 | 84.57 Mn |
| Dec 31, 2022 | 101.94 Mn |
| Sep 30, 2022 | 89.49 Mn |
| Jun 30, 2022 | 95.95 Mn |
| Mar 31, 2022 | 98.87 Mn |
| Dec 31, 2021 | 105.46 Mn |
| Sep 30, 2021 | 85.31 Mn |
API Access
Bark 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=BARK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BARK", "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=BARK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();