1 800 Flowers Com (FLWS) Total Liabilities (2011 - 2026)
1 800 Flowers Com (FLWS) reported Total Liabilities of $493.34 million for fiscal Q4 2026 (quarter ended Jun 28, 2026), down 2.2% from $504.34 million a year earlier but up 1.2% from the prior quarter.
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Analysis
1 800 Flowers Com (FLWS) Total Liabilities (2011 - 2026) Analysis & Trends
Dating back to fiscal Q4 2011, 1 800 Flowers Com's Total Liabilities record includes 56 quarters.
- Total Liabilities has declined for four consecutive fiscal years, with a five-year compound annual growth rate of -2.8% (FY2021 to FY2026).
- By fiscal year, Total Liabilities came in at $504.34 million in FY2025 (-10.9%), $566.31 million in FY2024 (-2.3%), $579.59 million in FY2023 (-1.0%) and $585.48 million in FY2022 (+3.1%).
- Five-year quarterly Total Liabilities spans a low of $487.41 million in fiscal Q3 2026 and a high of $756.38 million in fiscal Q1 2022.
- Year over year, Total Liabilities has now declined in each of the last three quarters, with an average decline of 4.4% over the last eight quarters.
- The high point for year-over-year Total Liabilities in five years was fiscal Q3 2024 (growth of 9.4%); the low point was fiscal Q3 2025 (a decline of 11.9%).
- Per Business Quant data, the three fiscal quarters before Q4 2026 came in at $487.41 million (Q3 2026), $603.36 million (Q2 2026) and $622.99 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,659.84 Bn | 2,176.54 Bn | 104.83 Bn | 544.07 Bn |
| 2 | Home Depot | 287.59 Bn | 280.83 Bn | 16.12 Bn | 92.77 Bn |
| 3 | Tjx Companies | 147.38 Bn | 124.93 Bn | 5.07 Bn | 26.46 Bn |
| 4 | Lowes Companies | 105.03 Bn | 97.99 Bn | 8.58 Bn | 63.32 Bn |
| 5 | Ross Stores | 74.93 Bn | 57.86 Bn | 2.12 Bn | 9.24 Bn |
| 6 | Target | 71.05 Bn | 65.64 Bn | 8.94 Bn | 43.39 Bn |
| 7 | O Reilly Automotive | 70.25 Bn | 69.33 Bn | 2.52 Bn | 19.22 Bn |
| 8 | Carvana | 69.96 Bn | 61.56 Bn | 1.38 Bn | 9.41 Bn |
| 9 | Autozone | 46.92 Bn | 45.82 Bn | 2.52 Bn | 23.70 Bn |
| 10 | 1 800 Flowers Com | 166.17 Mn | -96.98 Mn | 101.81 Mn | 493.34 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 493.34 Mn |
| Mar 29, 2026 | 487.41 Mn |
| Dec 28, 2025 | 603.36 Mn |
| Sep 28, 2025 | 622.99 Mn |
| Jun 29, 2025 | 504.34 Mn |
| Mar 30, 2025 | 488.49 Mn |
| Dec 29, 2024 | 642.66 Mn |
| Sep 29, 2024 | 601.21 Mn |
| Jun 30, 2024 | 566.31 Mn |
| Mar 31, 2024 | 554.66 Mn |
| Dec 31, 2023 | 688.35 Mn |
| Oct 1, 2023 | 608.46 Mn |
| Jul 2, 2023 | 579.59 Mn |
| Apr 2, 2023 | 506.79 Mn |
| Jan 1, 2023 | 656.47 Mn |
| Oct 2, 2022 | 738.95 Mn |
| Jul 3, 2022 | 585.48 Mn |
| Mar 27, 2022 | 594.86 Mn |
| Dec 26, 2021 | 756.38 Mn |
| Sep 26, 2021 | 599.51 Mn |
API Access
1 800 Flowers Com Total Liabilities 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=total-liabilities&ticker=FLWS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "FLWS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=FLWS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();