Bark (BARK) Other Operating Expenses (2020 - 2026)
Bark's Other Operating Expenses came in at $9.5 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), down 37.4% from $15.18 million a year earlier and down 24.4% from the prior quarter.
Bark (BARK) Other Operating Expenses (2020 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Bark reported Other Operating Expenses of $53.53 million, down 31.8% year-over-year; for FY2026 (ended Mar 31, 2026), it came in at $59.21 million, down 29.3% from FY2025.
- Other Operating Expenses carries a five-year compound annual growth rate of -2.4% (FY2021 to FY2026).
- Going back by fiscal year, Other Operating Expenses was $83.76 million in FY2025 (+5.6%), $79.28 million in FY2024 (+15.2%), $68.81 million in FY2023 (-7.5%) and $74.42 million in FY2022 (+11.0%).
- The fiscal Q1 2027 figure represents the lowest quarterly Other Operating Expenses in data going back to fiscal Q1 2021.
- Year-over-year, Other Operating Expenses has declined for six consecutive quarters, with an average decline of 17.9% over the last eight quarters.
- The fastest year-over-year change in Other Operating Expenses over five years came in fiscal Q2 2022 (growth of 31.8%), and the weakest in fiscal Q3 2026 (a decline of 41.3%).
- Business Quant data shows BARK's Other Operating Expenses at $12.57 million (Q4 2026), $16.07 million (Q3 2026) and $15.4 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Unilever | 132.43 Bn | 107.80 Bn | - |
| 2 | Mondelez International | 73.80 Bn | 67.12 Bn | 3.99 Bn |
| 3 | Hershey | 31.86 Bn | 28.11 Bn | 1.26 Bn |
| 4 | Kraft Heinz | 26.96 Bn | 13.49 Bn | 2.03 Bn |
| 5 | General Mills | 17.20 Bn | 14.85 Bn | 1.49 Bn |
| 6 | J M Smucker | 12.70 Bn | 12.49 Bn | 979.60 Mn |
| 7 | Mccormick | 12.49 Bn | 12.36 Bn | 778.20 Mn |
| 8 | Hormel Foods | 10.97 Bn | 7.66 Bn | 471.52 Mn |
| 9 | Chewy | 7.31 Bn | 4.59 Bn | 1.01 Bn |
| 10 | Bark | 84.17 Mn | -36.31 Mn | 57.33 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.50 Mn |
| Mar 31, 2026 | 12.57 Mn |
| Dec 31, 2025 | 16.07 Mn |
| Sep 30, 2025 | 15.40 Mn |
| Jun 30, 2025 | 15.18 Mn |
| Mar 31, 2025 | 17.30 Mn |
| Dec 31, 2024 | 27.36 Mn |
| Sep 30, 2024 | 18.67 Mn |
| Jun 30, 2024 | 20.43 Mn |
| Mar 31, 2024 | 18.76 Mn |
| Dec 31, 2023 | 25.09 Mn |
| Sep 30, 2023 | 17.81 Mn |
| Jun 30, 2023 | 17.62 Mn |
| Mar 31, 2023 | 15.37 Mn |
| Dec 31, 2022 | 21.75 Mn |
| Sep 30, 2022 | 15.33 Mn |
| Jun 30, 2022 | 16.36 Mn |
| Mar 31, 2022 | 13.36 Mn |
| Dec 31, 2021 | 26.83 Mn |
| Sep 30, 2021 | 17.08 Mn |
Bark Other 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=other-operating-expenses&ticker=BARK&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-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=other-operating-expenses&ticker=BARK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();