Starbucks (SBUX) Buildings (2009 - 2014)
Starbucks' (SBUX) quarterly Buildings came in at $277.9 million in Q1 2014, up 12.88% year-over-year from $246.2 million in Q1 2013, and down 0.5% quarter-over-quarter from $279.3 million in Q4 2013.
Starbucks (SBUX) Buildings (2009 - 2014) Analysis & Trends
Starbucks (SBUX) has reported Buildings for 6 consecutive years, with $277.9 million the latest figure, recorded in Q1 2014.
- On a quarterly basis, Buildings rose 12.88% year-over-year to $277.9 million in Q1 2014; TTM through Mar 2014 was $277.9 million, a 12.88% increase from a year earlier, with the FY2013 full-year figure at $259.6 million, up 15.28% from the prior year.
- Buildings was $277.9 million for Q1 2014 at Starbucks, down from $279.3 million in the prior quarter.
- Over five years, Buildings peaked at $279.3 million in Q4 2013 and troughed at $218.5 million in Q4 2011.
- A 5-year average of $249.6 million and a median of $259.1 million in 2013 frame the typical range for Buildings.
- Across the five-year window, Buildings fell 18.26% in 2012 and gained 23.64% in 2013, its largest moves.
- Over 5 years, Buildings stood at $265.7 million in 2010, then retreated by 17.76% to $218.5 million in 2011, then climbed by 3.39% to $225.9 million in 2012, then grew by 23.64% to $279.3 million in 2013, then slipped by 0.5% to $277.9 million in 2014.
- The last three Buildings figures came in at $277.9 million (Q1 2014), $279.3 million (Q4 2013), and $259.6 million (Q3 2013), per Business Quant data.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 168.67 Bn | 167.85 Bn | 6.42 Bn |
| 2 | Starbucks | 107.32 Bn | 103.72 Bn | 6.49 Bn |
| 3 | Chipotle Mexican Grill | 41.40 Bn | 40.73 Bn | 2.35 Bn |
| 4 | Yum Brands | 38.39 Bn | 37.72 Bn | 1.47 Bn |
| 5 | Restaurant Brands International | 25.02 Bn | 25.51 Bn | 1.89 Bn |
| 6 | Darden Restaurants | 24.39 Bn | 24.17 Bn | 3.68 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 15.95 Bn | 1.89 Bn |
| 8 | Yum China Holdings | 14.09 Bn | 13.41 Bn | 2.22 Bn |
| 9 | Texas Roadhouse | 10.81 Bn | 10.63 Bn | 1.44 Bn |
| 10 | Dominos Pizza | 9.81 Bn | 9.60 Bn | 478.23 Mn |
Historic Data
| Date | Value |
|---|---|
| Mar 30, 2014 | 277.90 Mn |
| Dec 29, 2013 | 279.30 Mn |
| Sep 29, 2013 | 259.60 Mn |
| Jun 30, 2013 | 258.60 Mn |
| Mar 31, 2013 | 246.20 Mn |
| Dec 30, 2012 | 225.90 Mn |
| Sep 30, 2012 | 225.20 Mn |
| Jul 1, 2012 | 222.60 Mn |
| Apr 1, 2012 | 221.60 Mn |
| Jan 1, 2012 | 218.90 Mn |
| Oct 2, 2011 | 218.50 Mn |
| Jul 3, 2011 | 270.10 Mn |
| Apr 3, 2011 | 269.80 Mn |
| Jan 2, 2011 | 267.80 Mn |
| Oct 3, 2010 | 265.70 Mn |
| Jun 27, 2010 | 265.30 Mn |
| Sep 27, 2009 | 231.50 Mn |
Starbucks Buildings 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=buildings&ticker=SBUX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "buildings", "ticker": "SBUX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=buildings&ticker=SBUX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();