U.S. company-operated
16,944 stores
Largest profit pool; Rewards + mobile order densest here
Play →Afternoon reset + mobile throughput are the priority levers
Business Analytics · 2026 · 4-week sprint
Starbucks
Sales intelligence hidden inside every cup
A business analytics case study built from Starbucks public filings — daypart strategy, Rewards economics, and product mix — so every claim can be traced to a disclosure.
FY2025–Q2 FY2026 public filings · IR loyalty dashboard · daypart strategy notes
10-K / 8-K analysisExcelPower BIPythonTableauratio analysistrend analysisscenario modelingsegment mixloyalty KPIs
10-K / 8-K analysisExcelPower BIPythonTableauratio analysistrend analysisscenario modelingsegment mixloyalty KPIs
10-K / 8-K analysisExcelPower BIPythonTableauratio analysistrend analysisscenario modelingsegment mixloyalty KPIs
10-K / 8-K analysisExcelPower BIPythonTableauratio analysistrend analysisscenario modelingsegment mixloyalty KPIs
The brief
What do Starbucks' own filings say is broken — and fixable?
This case is a secondary-data analysis. I did not pull private POS extracts. I structured FY2025–Q2 FY2026 investor disclosures into an analyst brief a professor can interrogate.
The sharp question: under the “Back to Starbucks” turnaround, which publicly disclosed levers — afternoon daypart, Rewards economics, and beverage/food mix — actually explain where growth can come from next?
Success = a short list of actions tied to named sources — not a fake 48-store dataset, and not a 40-slide archaeology report.
TheThemorningmorningrushrushownsownsthethebrandbrandstory.story.TheTheafternoonafternoonownsownsthethegrowthgrowthagenda.agenda.
Pipeline
From raw POS noise to decisions you can defend
Every insight on this page traces back to a reproducible path — tables joined, dayparts standardized, cohorts stress-tested — so the critique can challenge method, not magic.
- 01Ingest 10-K, earnings, loyalty IR dashboards
- 02Normalize KPIs into a comparable metric sheet
- 03Explore segments, mix, Rewards, and daypart narrative
- 04Recommend actions tied to named sources
Analytics loop
Method
A repeatable analytics loop, not a one-off report
Walk the four steps used on this case — from framing the question to validated recommendations.
Step 1 of 4
Frame the question
Asked what public disclosures reveal about growth levers: daypart opportunity, loyalty economics, and product mix — especially under the “Back to Starbucks” turnaround.
Disclosed company metrics · FY2025 / Q2 FY2026
$0B
FY2025 consolidated net revenue
0
Global stores (Q2 FY2026)
0M
U.S. 90-day active Rewards
0%
Rewards share of U.S. tender
Signal feed
What kept lighting up in the disclosures
A reel of the public signals that shaped the brief — useful when a professor asks “what did the filings actually say?”
Afternoon traffic accelerating
DaypartCompany: visits after 2 PM rising; strongest growth between 3–5 PM
Insights
Three findings that changed the recommendation
01 — Daypart
Afternoon is the growth gap management is chasing
Starbucks has long been a morning brand. Company data shared in 2026 shows visits after 2 PM rising, with the strongest growth between 3–5 PM — and executives call building the afternoon daypart “tremendous upside.” Midday-and-after sales after 11 AM are described as an ~$11B pool.
3–5pm
fastest-growing afternoon traffic window (U.S., 2026 company data)
Illustrative curve aligned with disclosed afternoon momentum (strongest growth 3–5 PM) · not proprietary POS
- Beverages73%
- Food23%
- Other4%
02 — Loyalty
Rewards already own the majority of U.S. spend
As of Q4 FY2025, Starbucks reported 34.2 million 90-day active Rewards members in the U.S., with Rewards accounting for 58% of tender dollars in U.S. company-operated stores. Mobile order was 31% of transactions — loyalty and digital are the operating system, not a side program.
58%
of U.S. company-operated tender dollars via Rewards
03 — Product mix
Beverages still dominate — food is the attach lever
FY2025 company-operated retail mix was 73% beverages, 23% food, and 4% other. Refreshers are now the #2 beverage platform behind espresso (~$2B franchise), which is exactly how Starbucks is trying to win non-morning occasions.
73%
beverage share of company-operated retail sales (FY2025)
Source: Starbucks FY2025 segment disclosures · $ billions
Grounded in filings
Every headline number is traceable to a disclosure
0
Global store footprint
Company-operated + licensed · Q2 FY2026
0%
Company-operated revenue mix
Share of FY2025 consolidated net revenue
0%
Mobile order share
Of U.S. company-operated transactions · Q4 FY2025
Strategic levers
Toggle the plays management is already signaling
These are not invented POS lifts — they are decision levers grounded in disclosed KPIs and the afternoon / Rewards strategy. Toggle them to structure a class critique.
Priorities selected
4 / 4
Win the 3–5 PM reset · Scale Refreshers platform · Lift afternoon food attach · Deepen Rewards tender
Store clusters
One playbook never fits 41,000+ coffeehouses
Q2 FY2026 store counts by operating model. Recommendations change when you move from U.S. company-operated denseness to licensed international breadth.
China company-operated
7,991 stores
Second-largest market; competitive cold-beverage dayparts
Play →Localize afternoon beverages without diluting brand espresso core
North America licensed
7,263 stores
Partner-operated; less direct control of labor & food replenishment
Play →Playbook + digital menu standards, not heavy corporate labor shifts
International licensed
12,309 stores
Breadth over depth; format and assortment vary by market
Play →Protect hero SKUs; localize cold / tea occasions by region
Actions
Recommendations a district manager can argue from the filings
- 01
Staff and merchandise for the 3–5 PM reset
Management says afternoon traffic is rising fastest between 3 and 5 PM. Align labor, digital menu boards, and cold-beverage features to that window — not only the morning peak.
- 02
Treat Refreshers as a second hero platform
Refreshers are disclosed as the #2 beverage platform (~$2B). Build afternoon occasions around cold, customizable drinks instead of discounting espresso to chase volume.
- 03
Raise food attach where replenishment allows
Food is already 23% of company-operated mix, but afternoon attach is constrained when stores are not on daily replenishment. Prioritize protein / snackable items in stores that can keep food fresh.
- 04
Defend and deepen Rewards economics
With 34.2M active U.S. members and 58% of tender, loyalty is the growth flywheel. Focus on same-day return visits and mobile order quality rather than one-off promo spikes.
Deliverables
- ▸Metric sheet from 10-K / earnings / IR dashboards
- ▸Segment & mix dashboard (Power BI / Tableau)
- ▸Afternoon opportunity brief (1-pager)
- ▸Scenario levers for class critique
- ▸Source appendix + assumption log
Oral defense
Questions a sharp professor will ask
Pre-loaded answers for critique — so you sound prepared, not rehearsed.
No — this is a secondary-data case. All KPIs come from investor disclosures (10-K, earnings, loyalty IR dashboard) and company daypart communications. Charts labeled illustrative show patterns those disclosures describe.
Because management itself frames afternoon as under-penetrated upside. Public commentary highlights post-2 PM visit growth, especially 3–5 PM, plus Refreshers as the cold-occasion engine.
No. It’s share of tender dollars in U.S. company-operated stores — a spend concentration metric. Member count (34.2M 90-day actives) is the separate scale metric.
If subsequent earnings showed afternoon traffic stalling, Refreshers growth fading, or Rewards tender falling while comps stayed weak — I’d shift toward morning retention and pricing before daypart expansion.
Close
Built to stand out in a room full of slide decks
Clear question. Rigorous method. Visual proof. Actions with owners. Present it live — toggle the levers, walk the segments, defend the sources.
Starbucks Sales Analysis · Business Analytics Case Study · 2026