Cracker Barrel Old Country Store (CBRL) Operating Expenses (2009 - 2026)
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Analysis
Cracker Barrel Old Country Store (CBRL) Operating Expenses (2009 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 199.73 Bn | 194.55 Bn | 6.42 Bn | 3.76 Bn |
| 2 | Starbucks | 124.84 Bn | 112.47 Bn | - | 8.42 Bn |
| 3 | Chipotle Mexican Grill | 45.68 Bn | 42.18 Bn | - | 2.84 Bn |
| 4 | Yum Brands | 44.27 Bn | 41.15 Bn | 1.47 Bn | 1.51 Bn |
| 5 | Restaurant Brands International | 27.05 Bn | 22.84 Bn | 1.40 Bn | 1.83 Bn |
| 6 | Darden Restaurants | 26.14 Bn | 25.23 Bn | 1.68 Bn | 2.88 Bn |
| 7 | Restaurant Brands International Limited Partnership | 24.67 Bn | 20.46 Bn | 1.40 Bn | 1.83 Bn |
| 8 | Yum China Holdings | 17.37 Bn | 11.02 Bn | 537.00 Mn | 2.79 Bn |
| 9 | Texas Roadhouse | 12.53 Bn | 11.87 Bn | - | 1.54 Bn |
| 10 | Cracker Barrel Old Country Store | 1.49 Bn | 1.41 Bn | 605.13 Mn | 65.18 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 65.18 Mn |
| May 1, 2026 | 49.39 Mn |
| Jan 30, 2026 | 48.05 Mn |
| Oct 31, 2025 | 47.96 Mn |
| Aug 1, 2025 | 50.17 Mn |
| May 2, 2025 | 46.03 Mn |
| Jan 31, 2025 | 61.67 Mn |
| Nov 1, 2024 | 59.64 Mn |
| Aug 2, 2024 | 51.27 Mn |
| Apr 26, 2024 | 54.52 Mn |
| Jan 26, 2024 | 52.54 Mn |
| Oct 27, 2023 | 48.74 Mn |
| Jul 28, 2023 | 37.58 Mn |
| Apr 28, 2023 | 45.05 Mn |
| Jan 27, 2023 | 45.52 Mn |
| Oct 28, 2022 | 45.95 Mn |
| Jul 29, 2022 | 32.90 Mn |
| Apr 29, 2022 | 40.16 Mn |
| Jan 28, 2022 | 43.46 Mn |
| Oct 29, 2021 | 40.91 Mn |
API Access
Cracker Barrel Old Country Store Operating Expenses 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=operating-expenses&ticker=CBRL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CBRL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=CBRL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();