Reynolds Consumer Products (REYN) Return on Sales [ROS] (2019 - 2026)
Reynolds Consumer Products' Return on Sales [ROS] came in at 14.62% for Q2 2026, up 0.76 percentage points from 13.86% a year earlier and up 3.44 percentage points from the prior quarter.
Reynolds Consumer Products (REYN) Return on Sales [ROS] (2019 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Reynolds Consumer Products reported Return on Sales [ROS] of 14.63%, up 0.17 percentage points year-over-year; for FY2025, it came in at 14.30%, down 0.56 percentage points from FY2024.
- Return on Sales [ROS] carries a five-year change of -4.55 percentage points (FY2020 to FY2025).
- Going back by year, Return on Sales [ROS] was 14.86% in FY2024 (+1.23 pp), 13.63% in FY2023 (+2.21 pp), 11.42% in FY2022 (-2.39 pp) and 13.81% in FY2021 (-5.04 pp).
- The five-year range for quarterly Return on Sales [ROS] is 5.72% (Q1 2023) to 20.48% (Q4 2023).
- Year-over-year, Return on Sales [ROS] has increased for three consecutive quarters, with an average year-over-year change of -0.34 percentage points over the last eight quarters.
- The fastest year-over-year change in Return on Sales [ROS] over five years came in Q3 2023 (a gain of 5.23 percentage points), and the weakest in Q3 2021 (a drop of 8.81 percentage points).
- Business Quant data shows REYN's Return on Sales [ROS] at 11.17% (Q1 2026), 17.79% (Q4 2025) and 14.39% (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Procter & Gamble | 336.76 Bn | 292.75 Bn | 10.28 Bn | 18.63% |
| 2 | Colgate Palmolive | 67.18 Bn | 62.24 Bn | 3.30 Bn | 18.95% |
| 3 | Estee Lauder Companies | 33.32 Bn | 21.40 Bn | 2.74 Bn | -1.08% |
| 4 | Kenvue | 33.09 Bn | 28.70 Bn | 2.30 Bn | 17.67% |
| 5 | Kimberly Clark | 31.38 Bn | 28.71 Bn | 1.60 Bn | 15.11% |
| 6 | Church & Dwight | 22.37 Bn | 20.90 Bn | 693.90 Mn | 18.07% |
| 7 | Clorox | 9.72 Bn | 8.16 Bn | 804.00 Mn | 24.33% |
| 8 | e.l.f. Beauty | 6.17 Bn | 5.15 Bn | 398.84 Mn | 21.37% |
| 9 | Reynolds Consumer Products | 4.71 Bn | 4.37 Bn | 245.00 Mn | 14.62% |
| 10 | Interparfums | 3.65 Bn | 3.46 Bn | 223.53 Mn | 14.35% |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 14.62% |
| Mar 31, 2026 | 11.17% |
| Dec 31, 2025 | 17.79% |
| Sep 30, 2025 | 14.39% |
| Jun 30, 2025 | 13.86% |
| Mar 31, 2025 | 10.39% |
| Dec 31, 2024 | 17.65% |
| Sep 30, 2024 | 15.16% |
| Jun 30, 2024 | 15.05% |
| Mar 31, 2024 | 10.80% |
| Dec 31, 2023 | 20.48% |
| Sep 30, 2023 | 14.33% |
| Jun 30, 2023 | 12.87% |
| Mar 31, 2023 | 5.72% |
| Dec 31, 2022 | 15.63% |
| Sep 30, 2022 | 9.10% |
| Jun 30, 2022 | 10.14% |
| Mar 31, 2022 | 10.06% |
| Dec 31, 2021 | 14.97% |
| Sep 30, 2021 | 11.60% |
Reynolds Consumer Products 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=REYN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "REYN", "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=REYN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();