Designer Brands (DBI) Return on Sales [ROS] (2010 - 2026)
Designer Brands (DBI) recorded Return on Sales [ROS] of 7.49% in fiscal Q2 2027 (quarter ended Aug 1, 2026), up 3.96 percentage points from 3.53% a year earlier and up 4.78 percentage points from the prior quarter.
Designer Brands (DBI) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
On a TTM basis, Designer Brands' Return on Sales [ROS] came in at 3.53% as of Aug 1, 2026, up 3.01 percentage points year-over-year; for FY2026 (ended Jan 31, 2026), it came in at 1.65%, up 0.49 percentage points from FY2025.
- Annual Return on Sales [ROS] has a five-year change of +27.89 percentage points (FY2021 to FY2026).
- Across earlier fiscal years, Return on Sales [ROS] came in at 1.16% in FY2025 (-1.19 pp), 2.35% in FY2024 (-3.30 pp), 5.65% in FY2023 (-0.77 pp) and 6.42% in FY2022 (+32.66 pp).
- The fiscal Q2 2027 figure is the highest quarterly Return on Sales [ROS] since fiscal Q2 2024.
- On a year-over-year basis, Return on Sales [ROS] has increased for four consecutive quarters, with an average year-over-year change of +1.26 percentage points over the last eight quarters.
- Peak year-over-year performance for Return on Sales [ROS] in the last five years was a gain of 21.20 percentage points in fiscal Q3 2022, against a drop of 5.05 percentage points in fiscal Q4 2024 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at 2.71% (Q1 2027), -1.99% (Q4 2026) and 5.67% (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,712.14 Bn | 2,228.84 Bn | 104.83 Bn | 13.69% |
| 2 | Home Depot | 282.27 Bn | 275.52 Bn | 16.12 Bn | 14.29% |
| 3 | Tjx Companies | 146.16 Bn | 123.70 Bn | 5.07 Bn | 13.09% |
| 4 | Lowes Companies | 101.42 Bn | 94.39 Bn | 8.58 Bn | 13.67% |
| 5 | Ross Stores | 73.06 Bn | 55.98 Bn | 2.12 Bn | 17.62% |
| 6 | Target | 70.86 Bn | 65.45 Bn | 8.94 Bn | 9.65% |
| 7 | Carvana | 70.11 Bn | 61.71 Bn | 1.38 Bn | 9.22% |
| 8 | O Reilly Automotive | 69.29 Bn | 68.38 Bn | 2.52 Bn | 20.15% |
| 9 | Autozone | 45.61 Bn | 44.51 Bn | 2.52 Bn | 19.08% |
| 10 | Designer Brands | 262.51 Mn | 58.60 Mn | 365.36 Mn | 7.49% |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 7.49% |
| May 2, 2026 | 2.71% |
| Jan 31, 2026 | -1.99% |
| Nov 1, 2025 | 5.67% |
| Aug 2, 2025 | 3.53% |
| May 3, 2025 | -1.15% |
| Feb 1, 2025 | -3.62% |
| Nov 2, 2024 | 2.94% |
| Aug 3, 2024 | 3.70% |
| May 4, 2024 | 1.26% |
| Feb 3, 2024 | -4.77% |
| Oct 28, 2023 | 3.58% |
| Jul 29, 2023 | 7.66% |
| Apr 29, 2023 | 2.64% |
| Jan 28, 2023 | 0.27% |
| Oct 29, 2022 | 7.46% |
| Jul 30, 2022 | 7.87% |
| Apr 30, 2022 | 6.40% |
| Jan 29, 2022 | 2.73% |
| Oct 30, 2021 | 12.22% |
Designer Brands 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=DBI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "DBI", "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=DBI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();