Bark (BARK) Return on Sales [ROS] (2020 - 2026)
Bark (BARK) posted Return on Sales [ROS] of 0.08% for fiscal Q1 2027 (quarter ended Jun 30, 2026), up 8.20 percentage points from -8.12% a year earlier and up 14.16 percentage points from the prior quarter.
Bark (BARK) Return on Sales [ROS] (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Return on Sales [ROS] at Bark was -8.57%, down 1.58 percentage points year-over-year; for FY2026 (ended Mar 31, 2026), it was -10.18%, down 2.92 percentage points from FY2025.
- Annual Return on Sales [ROS] shows a five-year change of -4.73 percentage points (FY2021 to FY2026).
- In prior fiscal years, Bark's Return on Sales [ROS] was -7.26% in FY2025 (+2.03 pp), -9.29% in FY2024 (+2.64 pp), -11.92% in FY2023 (+6.64 pp) and -18.56% in FY2022 (-13.12 pp).
- The fiscal Q1 2027 figure stands as the highest quarterly Return on Sales [ROS] since fiscal Q1 2021.
- On a year-over-year basis, Return on Sales [ROS] increased in five of the last eight quarters, with an average year-over-year change of +0.19 percentage points.
- The strongest year-over-year quarter for Return on Sales [ROS] in the past five years was fiscal Q4 2023, with a gain of 16.89 percentage points; the weakest was fiscal Q4 2022, with a drop of 23.56 percentage points.
- According to Business Quant data, Return on Sales [ROS] for the three prior fiscal quarters was -14.07% (Q4 2026), -9.13% (Q3 2026) and -9.96% (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 130.23 Bn | 105.59 Bn | - | - |
| 2 | Mondelez International | 74.27 Bn | 67.59 Bn | 3.99 Bn | 20.80% |
| 3 | Hershey | 32.39 Bn | 28.63 Bn | 1.26 Bn | 23.06% |
| 4 | Kraft Heinz | 26.34 Bn | 12.87 Bn | 2.03 Bn | -102.70% |
| 5 | General Mills | 17.12 Bn | 14.77 Bn | 1.49 Bn | 14.43% |
| 6 | J M Smucker | 12.52 Bn | 12.30 Bn | 979.60 Mn | 23.05% |
| 7 | Mccormick | 12.03 Bn | 11.67 Bn | 794.90 Mn | 10.72% |
| 8 | Hormel Foods | 11.14 Bn | 7.83 Bn | 471.52 Mn | 3.75% |
| 9 | Chewy | 7.29 Bn | 4.58 Bn | 1.01 Bn | 2.76% |
| 10 | Bark | 80.59 Mn | -39.89 Mn | 57.33 Mn | 0.08% |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 0.08% |
| Mar 31, 2026 | -14.07% |
| Dec 31, 2025 | -9.13% |
| Sep 30, 2025 | -9.96% |
| Jun 30, 2025 | -8.12% |
| Mar 31, 2025 | -5.73% |
| Dec 31, 2024 | -9.68% |
| Sep 30, 2024 | -4.52% |
| Jun 30, 2024 | -9.11% |
| Mar 31, 2024 | -5.31% |
| Dec 31, 2023 | -11.17% |
| Sep 30, 2023 | -9.02% |
| Jun 30, 2023 | -11.61% |
| Mar 31, 2023 | -10.16% |
| Dec 31, 2022 | -16.19% |
| Sep 30, 2022 | -6.36% |
| Jun 30, 2022 | -15.35% |
| Mar 31, 2022 | -27.05% |
| Dec 31, 2021 | -19.21% |
| Sep 30, 2021 | -12.84% |
Bark Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=BARK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "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=return-on-sales-%5Bros%5D&ticker=BARK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();