Maison Solutions (MSS) Cost of Revenue (2022 - 2026)
Maison Solutions (MSS) reported Cost of Revenue of $22 million for fiscal Q3 2026 (quarter ended Jan 31, 2026), down 12.9% from $25.27 million a year earlier but up 3.9% from the prior quarter.
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Analysis
Maison Solutions (MSS) Cost of Revenue (2022 - 2026) Analysis & Trends
Over the twelve months ended Jan 31, 2026, Maison Solutions' Cost of Revenue came in at $94.88 million, up 16.4% year-over-year; for FY2025 (ended Apr 30, 2025), it was $97.87 million, up 110.8% from FY2024.
- Cost of Revenue has increased for three consecutive fiscal years, with a three-year compound annual growth rate of 42.7% (FY2022 to FY2025).
- By fiscal year, Cost of Revenue came in at $46.42 million in FY2024 (+8.1%), $42.95 million in FY2023 (+27.5%) and $33.7 million in FY2022.
- Five-year quarterly Cost of Revenue spans a low of $9.1 million in fiscal Q1 2023 and a high of $31.09 million in fiscal Q4 2025.
- Year over year, Cost of Revenue gained in six of the last eight quarters, with growth averaging 58.1%.
- The high point for year-over-year Cost of Revenue in five years was fiscal Q3 2025 (growth of 142.8%); the low point was fiscal Q3 2026 (a decline of 12.9%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $21.17 million (Q2 2026), $20.61 million (Q1 2026) and $31.09 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 827.17 Bn | 789.87 Bn | 49.13 Bn | 138.80 Bn |
| 2 | Costco Wholesale | 408.32 Bn | 337.62 Bn | 9.01 Bn | 61.52 Bn |
| 3 | Sysco | 37.11 Bn | 31.36 Bn | 4.13 Bn | 17.99 Bn |
| 4 | Kroger | 34.86 Bn | 21.01 Bn | 7.86 Bn | 26.76 Bn |
| 5 | Dollar General | 26.24 Bn | 20.91 Bn | 3.68 Bn | 7.61 Bn |
| 6 | Caseys General Stores | 22.83 Bn | 20.83 Bn | 1.24 Bn | 4.44 Bn |
| 7 | Dollar Tree | 21.05 Bn | 17.67 Bn | 2.10 Bn | 2.79 Bn |
| 8 | US Foods Holding | 20.97 Bn | 20.76 Bn | 1.92 Bn | 8.61 Bn |
| 9 | Tractor Supply | 16.22 Bn | 15.39 Bn | 1.68 Bn | 2.86 Bn |
| 10 | Maison Solutions | 943,996.47 | -3.93 Mn | 7.54 Mn | 22.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jan 31, 2026 | 22.00 Mn |
| Oct 31, 2025 | 21.17 Mn |
| Jul 31, 2025 | 20.61 Mn |
| Apr 30, 2025 | 31.09 Mn |
| Jan 31, 2025 | 25.27 Mn |
| Oct 31, 2024 | 21.47 Mn |
| Jul 31, 2024 | 20.04 Mn |
| Apr 30, 2024 | 14.72 Mn |
| Jan 31, 2024 | 10.41 Mn |
| Oct 31, 2023 | 10.64 Mn |
| Jul 31, 2023 | 10.65 Mn |
| Apr 30, 2023 | 11.13 Mn |
| Jan 31, 2023 | 11.63 Mn |
| Oct 31, 2022 | 11.08 Mn |
| Jul 31, 2022 | 9.10 Mn |
API Access
Maison Solutions Cost of Revenue 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=cost-of-revenue&ticker=MSS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "ticker": "MSS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=cost-of-revenue&ticker=MSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();