Dine Brands Global (DIN) Return on Sales [ROS] (2010 - 2026)
Dine Brands Global (DIN) posted Return on Sales [ROS] of 4.86% for Q2 2026, down 3.33 percentage points from 8.19% a year earlier and down 0.83 percentage points from the prior quarter.
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Analysis
Dine Brands Global (DIN) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 28, 2026, Return on Sales [ROS] at Dine Brands Global was 2.75%, down 4.35 percentage points year-over-year; for FY2025, it was 3.56%, down 6.56 percentage points from FY2024.
- Annual Return on Sales [ROS] shows a five-year change of +1.47 percentage points (FY2020 to FY2025).
- In prior years, Dine Brands Global's Return on Sales [ROS] was 10.12% in FY2024 (-2.78 pp), 12.90% in FY2023 (+2.39 pp), 10.51% in FY2022 (-1.78 pp) and 12.29% in FY2021 (+10.20 pp).
- Quarterly Return on Sales [ROS] has run from a low of -5.72% in Q4 2025 to a high of 14.70% in Q2 2024 over five years.
- On a year-over-year basis, Return on Sales [ROS] increased in two of the last eight quarters, with an average year-over-year change of -4.95 percentage points.
- The strongest year-over-year quarter for Return on Sales [ROS] in the past five years was Q4 2021, with a gain of 9.49 percentage points; the weakest was Q4 2024, with a drop of 10.61 percentage points.
- According to Business Quant data, Return on Sales [ROS] for the three prior quarters was 5.68% (Q1 2026), -5.72% (Q4 2025) and 5.86% (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 164.13 Bn | 158.95 Bn | 6.42 Bn | 47.02% |
| 2 | Starbucks | 107.97 Bn | 95.60 Bn | - | 10.52% |
| 3 | Chipotle Mexican Grill | 41.04 Bn | 37.02 Bn | - | 15.70% |
| 4 | Yum Brands | 37.16 Bn | 34.04 Bn | 1.47 Bn | 30.20% |
| 5 | Restaurant Brands International | 24.42 Bn | 21.52 Bn | 1.38 Bn | 28.41% |
| 6 | Darden Restaurants | 22.67 Bn | 21.77 Bn | 1.68 Bn | 9.98% |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 28.41% |
| 8 | Yum China Holdings | 13.79 Bn | 8.16 Bn | 537.00 Mn | 11.09% |
| 9 | Texas Roadhouse | 10.24 Bn | 9.60 Bn | - | 8.50% |
| 10 | Dine Brands Global | 379.50 Mn | -118.40 Mn | 91.20 Mn | 4.86% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 4.86% |
| Mar 29, 2026 | 5.68% |
| Dec 28, 2025 | -5.72% |
| Sep 30, 2025 | 5.86% |
| Jun 29, 2025 | 8.19% |
| Mar 30, 2025 | 5.54% |
| Dec 29, 2024 | 1.60% |
| Sep 30, 2024 | 13.29% |
| Jun 30, 2024 | 14.70% |
| Mar 31, 2024 | 10.98% |
| Dec 31, 2023 | 12.21% |
| Sep 30, 2023 | 12.41% |
| Jun 30, 2023 | 12.66% |
| Mar 31, 2023 | 14.23% |
| Dec 31, 2022 | 6.63% |
| Sep 30, 2022 | 10.44% |
| Jun 30, 2022 | 11.98% |
| Mar 31, 2022 | 12.62% |
| Dec 31, 2021 | 11.02% |
| Sep 30, 2021 | 11.36% |
API Access
Dine Brands Global 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=DIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "DIN", "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=DIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();