us restaurants phone to table: digitizing restaurants

US Restaurants Phone To Table: Digitizing Restaurants Initiation of Coverage

DISCLOSURE APPENDIX AT THE BACK OF THIS REPORT CONTAINS IMPORTANT DISCLOSURES, ANALYST CERTIFICATIONS, LEGAL ENTITY

DISCLOSURE AND THE STATUS OF NON-U.S ANALYSTS. U.S. Disclosure: Credit Suisse does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the Firm may have a conflict of interest that could affect the objectivity of this report. Investors should

consider this report as only a single factor in making their investment decision.

25 June 2019

Research Analyst

Lauren Silberman, CFA, CPA

+1 212 325 2720 [email protected]

Equity Research US

mailto:[email protected]



2

Table of Contents

Executive Summary

US Restaurants Industry Overview

Company Summaries

Key Themes

Disclosures

Delivery Digital

M&A

Unit Growth

4

16

34

141

112

3

Accompanying Company-Specific Reports

Source: Credit Suisse estimates

CMG: Guac is Worth the Extra Charge and So Is Growth; Initiate Outperform

DNKN: Shares Hot on Luke Warm Outlook; Initiate Underperform

DPZ: Time to Get A Piece of This Pie; Initiate Outperform

JACK: Waiting for JACK to Come Out of the Box; Initiate Underperform

MCD: Hamburglar Positioned to Steal Share; Initiate Outperform

PZZA: Not An Easy Layup; Initiate Neutral

QSR: Maintains Claim To Throne; Initiate Outperform

SBUX: A Gold Star in Restaurants; Initiate Outperform

SHAK: Premium Burger Deserves Premium Multiple; Initiate Outperform

WEN: Can’t Find Catalysts As Fresh As The Beef; Initiate Neutral

YUM: Can’t Find Más Upside; Initiate at Neutral

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4

Executive Summary

5

Coverage & Ratings 6 Outperform, 2 Underperform, 3 Neutral

Source: Company data, FactSet, Credit Suisse estimates

Ticker Company CS RatingMarket Cap

($MM)

Current

Price

CS Target

Price

Upside/

Downside

NTM

EV/EBITDANTM P/E CS Thesis

CMG Chipotle Outperform $20,302 $727 $870 19.7% 25.6x 53.0xHigh convinction in 10%+ top-line growth generating margin leverage with attractive flow-

through. Earnings growth supports premium multiple.

SHAK Shake Shack Outperform $2,531 $67 $77 15.4% 28.2x 113.8xUnique concept with unit growth potential of 20%+. Upside exists from better-than-

expected top-line & margins. Traffic & SSS stabilization should improve sentiment.

DPZ Domino's Pizza Outperform $11,606 $280 $320 15.1% 20.4x 29.0x

High convinction in ~10% top-line growth supporting global market share gains. Third-

party delivery concerns appear overblown. SSS outperformance should improve

sentiment & upside to base case.

MCD McDonald's Outperform $156,155 $204 $230 14.9% 18.0x 24.8x

We're bullish on MCD's outlook, with traction against sales initiatives supporting upside

to SSS and EPS near & long-term. Healthy global SSS, defensive characteristics,

ongoing transition to ~95% franchise-mix & increased digital focus should provide

support for the current valuation premium.

QSRRestaurant

Brands Intl. Outperform $32,685 $70 $78 14.3% 17.5x 25.5x

Confident in long-term growth with international network of master franchisees. Menu

innovation at BK US and innovation/digital enhancements at TH Canada should support

SSS acceleration. Valuation is reasonable relative to the peer group.

SBUX Starbucks Outperform $100,433 $84 $92 11.5% 17.4x 29.0x

High-single-digit rev growth, modest margin expansion & repurchases support EPS

growth of 10%+ going forward. Americas & CAP sales leverage, improved performance

in China & strategic optionality represent upside. A more focused growth strategy &

enhanced capital structure support the premium valuation to history.

WEN Wendy's Neutral $4,480 $19 $20 5.3% 15.0x 30.3x

Improved fundamentals and a more consistent FCF profile appear to be reflected in

shares. We're cautious on a meaningful acceleration in unit growth given recent

challenges & lack of international infrastructure, and risks to long-term targets could

weigh on valuation.

PZZA Papa John's Neutral $1,557 $44 $45 3.4% 15.7x 36.8x

Brand is still in recovery mode and implementation of strategic plan is in the works. While

we believe there is risk to numbers and elevated valuation, activist involvement, high

short interest, potential value unlock & potential M&A keep us Neutral.

YUM Yum! Brands Neutral $33,263 $110 $106 -2.3% 20.1x 28.3x

Solid asset-light business with a strong unit growth outlook and diversified portfolio

across brands and geographies. But at ~21x EV/EBITDA, valuation is rich and we would

wait for a better entry point before becoming constructive on shares.

DNKN Dunkin' Brands Underperform $6,617 $80 $70 -10.1% 18.3x 26.4x

We like the stability of the business model, experienced mgmt team & recent initiatives.

But at ~18x EV/EBITDA, DNKN is trading at a significant premium to its history & peers,

and we see downside risk from lower growth prospects & an elevated multiple.

JACK Jack in the Box Underperform $2,229 $85 $75 -10.1% 12.1x 19.1x

Flat SSS, elevated closures, geographic concentration, margin pressure & penetrated

burger segment represent headwinds to unit growth (flat over last decade). A lackluster

sales plan is unlikely to drive a sustainable SSS inflection. Risk to LT targets exist and

could weigh on valuation.

US Restaurants Coverage

6

Initiating Coverage of the Restaurants Sector Value Creation


Leverage the box (increase in-store sales)

– New product innovation, marketing/advertising, improved operations, effective

value messaging, etc.

Expand global footprint

– Grow units domestically and internationally

– Work with franchisees and licensed partners

Improve margins

– Top-line drives scale and efficiencies

– Cost savings

7

Initiating Coverage of the Restaurants Sector Evolution of Digital and Delivery


Leverage the box (increase in-store sales) – Demand for convenience

– Unlock incremental sales through digital channels (mobile order & pay, delivery,

loyalty incentives); increase throughput

Expand global footprint – Increase real estate site potential

– New formats increase addressable market

– Increase number of access points

Improve margins – Generate leverage and cost saves

– Increased capacity/throughput supports margin leverage (not constrained to

three meals)

– Cost savings (i.e. labor)

– But digital also comes at a cost (i.e. infrastructure, delivery fees)

Volume Increases ~10-15%

Volume

Increases ~20-30%

Delivery

8

Digital Supports Incremental Sales Volumes Adding Convenience Not Seen Since the Drive-Thru


AUV*

Traditional

QSR

Drive-Thru

~50-70%

Sales Mix

Mobile Order

Drive-Thru

~20%

Sales Mix

Drive-thru orders tend to generate higher avg tickets relative to in-store orders (multiple people in car)

Digital channels support an additional layer of sales and orders generally 1.5-2x higher than an in-store order (group orders; suggestive sell; more time to browse)

*Average unit volume

9

Technology Comes At A Cost Corporate Level

Source: Company data, Credit Suisse estimates

Technology is a perpetual cost restaurants must incur to maintain their digital ecosystems

All companies across all restaurant segments are increasing investments in digital and the majority are partnering with third-party aggregators for delivery

Select companies are also making big investments in outside firms as they seek to gain a competitive advantage against peers (accelerate digital innovation, access to talent, etc.)

February 2018: $200MM in Grubhub July 2018: Acquires license for CardFree December 2018: Acquires QuikOrder for $77MM February 2019: $25MM digital investment, including $15MM for Accenture partnership March 2019: $100MM investment in Venture Fund that invests in food & retail startups March 2019: $300MM to acquire Dynamic Yield startup & $5MM investment in Plexure

10

Technology Comes At A Cost Restaurant Level


Infrastructure, Equipment and Software – Back of house/front of house technology and equipment, maintenance fees, support, etc. (annual & one time fees)

Technology/Digital Transaction Fees – Franchisees generally pay fees on every digital order

Credit Card Processing Fees – Digital orders generally transacted with credit/debit cards

Mobile offers and loyalty programs – Many restaurant companies are offering mobile-specific deals to encourage utilization and loyalty programs, with both discounts at the cost of the restaurants

Delivery Fees – Incremental costs: 1) commission costs for third-party delivery; 2) proprietary delivery infrastructure

– Delivery commission costs average ~15-30% of average tickets

11

Delivery is Expensive for Restaurants and Customers


Incremental delivery costs weigh on margins, though higher average tickets and incrementality support better delivery order profitability

Customers pay higher prices for delivery through delivery fees, service fees and inflated menu prices

In-Store

Avg Check

Delivery

1.5x Avg

Check

Delivery

2x Avg

Check

Delivery

1.5x Avg

Check

Delivery

2x Avg

Check

Average Ticket $7.00 $10.50 $14.00 $10.50 $14.00

Food & Paper 28.5% 29.0% 29.0% 29.0% 29.0%

Labor 28.0% 18.7% 14.0% 14.0% 10.5%

Royalty 4.0% 4.0% 4.0% 4.0% 4.0%

Advertising 4.0% 4.0% 4.0% 4.0% 4.0%

Other Operating 12.0% 8.0% 6.0% 6.0% 4.5%

Rent 12.0% 12.0% 12.0% 12.0% 12.0%

Commission 0.0% 20.0% 20.0% 20.0% 20.0%

EBITDA per order 11.5% 4.3% 11.0% 11.0% 16.0%

EBITDA $ per order $0.81 $0.45 $1.54 $1.16 $2.24

Cost of Delivery - Restaurant Level

Assumes IncrementalityNo Incrementality

In-Store

Avg Check

Delivery

1.5x Avg

Check

Delivery

2x Avg

Check

Delivery

1.5x Avg

Check

Delivery

2x Avg

Check

Average Ticket $7.00 $10.50 $14.00 $10.50 $14.00

% Menu Price Adjustment 20% 20%

Adjusted Average Ticket $12.60 $16.80

Delivery Fee $1.99 $1.99 $1.99 $1.99

Service Fee 15.0% 15.0% 15.0% 15.0%

Small Order Fee (if appicable) $2.00 $2.00 $2.00 $2.00

Order Cost to Customer $7.00 $14.07 $18.09 $16.48 $21.31

Cost of Delivery - Customer Level

No Menu Price Adj. Menu Price Adj.

12

Restaurants are trading at ~12x NTM EV/EBITDA, nearly ~2x above the 10-yr average of ~10.3x and at a P/E of ~20x earnings, relatively in-line with the 10-yr average

Restaurants trade at premium valuations driven by: higher unit growth opportunities, international exposure, lower inventory risk, lower impact from digital/online shift

– Within restaurants, companies with heavily franchised business models and strong unit growth prospects trade at higher valuations

Restaurant Valuation

Source: FactSet, Credit Suisse estimates

NTM P/E NTM EV/EBITDA

6.0x

7.0x

8.0x

9.0x

10.0x

11.0x

12.0x

13.0x

14.0x

May-

09

May-

10

May-

11

May-

12

May-

13

May-

14

May-

15

May-

16

May-

17

May-

18

May-

19

NTM

EV

/EB

ITD

A

NTM EV/EBITDA 10-yr Avg +1 Std Dev -1 Std Dev

10.0x

12.0x

14.0x

16.0x

18.0x

20.0x

22.0x

24.0x

26.0x

28.0x

30.0x

May-

09

May-

10

May-

11

May-

12

May-

13

May-

14

May-

15

May-

16

May-

17

May-

18

May-

19

NTM

P/E

NTM P/E 10-yr Avg +1 Std Dev -1 Std Dev

CMG

DPZYUMDNKN

MCDQSR SBUX

PZZAWEN

JACK

10.0x

12.0x

14.0x

16.0x

18.0x

20.0x

22.0x

24.0x

26.0x

28.0x

0.0% 2.0% 4.0% 6.0% 8.0%

NTM

EV

/EB

ITD

A

3-yr Unit CAGR (2019-2021)

WENPZZA

DPZ

YUM

DNKNMCD

QSR

JACK

10.0x

12.0x

14.0x

16.0x

18.0x

20.0x

22.0x

85% 90% 95% 100%

NTM

EV

/EB

ITD

A

% Franchised

13

Credit Suisse Coverage Valuation

Source: Company data, FactSet, Consensus Metrix, Credit Suisse estimates

EV/EBITDA vs 3-yr Unit CAGR

EV/EBITDA vs SSS

EV/EBITDA – Current vs 3-yr Historical

EV/EBITDA vs % Franchised

SHAK

CMG

DPZYUM

DNKN MCDQSR SBUX

PZZAWEN

JACK

10.0x

12.0x

14.0x

16.0x

18.0x

20.0x

22.0x

24.0x

26.0x

28.0x

30.0x

0.0% 2.0% 4.0% 6.0% 8.0%

NTM

EV

/EB

ITD

A

3-yr SSS Avg (2019-2021)

10.0x

12.0x

14.0x

16.0x

18.0x

20.0x

22.0x

24.0x

26.0x

28.0x

30.0x

SH

AK

CM

G

DP

Z

YU

M

DN

KN

MC

D

QS

R

SB

UX

PZ

ZA

WE

N

JA

CK

NTM

EV

/EB

ITD

A

Current NTM EV/EBITDA 3-yr Avg NTM EV/EBITDA

14

Restaurants Coverage Summary


Current Mkt Ent. EV/EBITDA P/E Net Short

CS CS Price Cap Value 3-yr 3-yr Div. Debt/ Int. as %

Ticker Company Rating PT 6/21/19 ($BN) ($BN) Avg Avg Yield EBITDA of Float

Quick Service Restaurants

DNKN Dunkin' Brands U $70 $80 $6.6 $9.1 18.3x 15.7x 26.4x 23.3x 1.9% 5.1x 6%

DPZ Domino's Pizza O $320 $280 $11.8 $15.3 20.4x 19.2x 29.0x 25.9x 0.9% 4.8x 9%

JACK Jack in the Box U $75 $85 $2.2 $3.4 12.1x 11.9x 19.1x 17.6x 1.9% 4.3x 15%

LOCO El Pollo Loco - - $11 $0.4 $0.5 7.7x 8.6x 15.2x 16.7x 0.0% 1.0x 14%

MCD McDonald's O $230 $204 $157.6 $188.8 18.0x 14.5x 24.8x 21.7x 2.3% 2.8x 1%

PZZA Papa John's International N $45 $44 $1.4 $1.7 17.1x 14.7x 36.8x 37.3x 1.8% 2.7x 30%

QSR Restaurant Brands International O $78 $70 $32.7 $42.2 17.1x 17.3x 25.5x 23.8x 2.9% 4.0x 4%

SBUX Starbucks Corporation O $92 $84 $104.8 $110.1 17.5x 14.1x 29.0x 25.1x 1.7% 0.9x 2%

WEN The Wendy's N $20 $19 $4.6 $6.8 15.0x 14.0x 30.3x 26.4x 2.0% 5.0x 7%

YUM Yum! Brands N $106 $110 $34.7 $44.7 20.1x 16.4x 28.3x 24.8x 1.5% 4.7x 2%

Average 16.3x 14.6x 26.4x 24.3x 3.5x

Fast Casual Restaurants

CMG Chipotle Mexican Grill O $870 $727 $20.4 $20.1 25.8x 19.5x 53.0x 47.7x 0.0% -0.4x 7%

FRGI Fiesta Restaurant Group - - $13 $0.3 $0.4 6.5x 8.0x 21.0x 19.0x 0.0% 1.1x 5%

HABT The Habit Burger Grill - - $10 $0.2 $0.2 5.9x 7.5x 83.7x 90.9x 0.0% -0.8x 9%

NDLS Noodles & Company - - $7 $0.3 $0.3 9.1x 9.7x 43.7x 49.5x 0.0% 1.0x 13%

PBPB Potbelly Corporation - - $5 $0.1 $0.1 4.1x 6.9x 338.7x 36.0x 0.0% -0.6x 8%

SHAK Shake Shack O $77 $67 $2.5 $2.5 28.4x 23.4x 113.8x 84.2x 0.0% -0.7x 17%

WING Wingstop - - $92 $2.7 $3.0 47.1x 30.9x 119.8x 72.1x 0.4% 4.9x 13%

Average 18.1x 15.1x 110.5x 57.1x 0.6x

Casual Dining Restaurants

BJRI BJ's Restaurants - - $43 $0.9 $1.0 7.3x 8.4x 18.5x 22.1x 1.2% 0.6x 11%

BLMN Bloomin' Brands - - $19 $1.7 $2.7 6.6x 7.1x 11.4x 13.4x 2.2% 2.4x 5%

CAKE Cheesecake Factory - - $44 $2.0 $2.0 9.0x 9.3x 16.4x 17.3x 3.0% 0.2x 24%

CBRL Cracker Barrel Old Country Store - - $168 $4.0 $4.3 10.7x 10.0x 18.3x 16.8x 3.1% 0.6x 16%

CHUY Chuy's Holdings - - $23 $0.4 $0.4 8.6x 9.7x 23.9x 22.9x 0.0% -0.4x 12%

DFRG Del Frisco's Restaurant Group - - $7 $0.2 $0.5 9.1x 7.2x -28.0x -76.4x 0.0% 5.7x 26%

DIN Dine Brands Global - - $95 $1.7 $3.0 10.7x 10.4x 13.0x 12.6x 2.9% 4.6x 10%

DRI Darden Restaurants - - $121 $15.2 $15.7 11.9x 10.4x 18.9x 17.3x 3.0% 0.4x 6%

EAT Brinker International - - $38 $1.4 $2.7 7.2x 7.9x 9.4x 10.8x 4.0% 3.3x 32%

PLAY Dave & Buster's Entertainment - - $40 $1.5 $1.9 7.6x 8.5x 13.0x 14.9x 1.5% 1.3x 19%

RRGB Red Robin Gourmet Burgers - - $31 $0.4 $0.6 9.7x 6.2x 25.6x 18.9x 0.0% 1.2x 32%

RUTH Ruth's Hospitality Group - - $22 $0.7 $0.7 9.8x 10.1x 15.7x 17.3x 2.3% 0.5x 4%

TXRH Texas Roadhouse - - $52 $3.8 $3.6 11.7x 11.9x 22.1x 23.5x 2.3% -0.6x 8%

Average 9.2x 9.0x 13.7x 10.1x 1.5x

NTM NTM

15

Credit Suisse Relative Rankings


Digital DeliveryProduct

InnovationValue Domestic International

Sales

Leverage

Cost

Savings

CMG O

SHAK O

DPZ O

MCD O

QSR O

SBUX O

WEN N

PZZA N

YUM N

DNKN U

JACK U

SSSStrategic

Optionality

Credit

Suisse

Rating

Global Whitespace

OpportunityMargin Prospects

16

US Restaurants Overview

17

US Consumers Spend ~$1.6 Trillion On Food Annually

Source: USDA, Credit Suisse estimates

Food Away From Home Food At Home

$311BN

$869BN

$436BN

$747BN

$314BN $5BN$36BN

$203BN

$172BN $15BN

$124BN

Full Service

Restaurants

Limited

Service

Restaurants

Drinking

Places

Hotels &

Motels

Other Food Away

From Home

Grocery Warehouse

Clubs & Mass

Merchants

Convenience

Stores

Other Stores &

Foodservice

Food At

Home

18

Source: USDA, Credit Suisse estimates

Food Share Shifting Away From Home

US Food Expenditures – Food At Home vs Food Away From Home

US Food Expenditures – Composition

Consumers spend more money are increasingly eating more meals away from home, with food away from home now representing a greater share of overall food spend

Restaurants have gained ~6pp of stomach share over the last 20 years, relative to grocery which has lost ~11pp of share

0%

10%

20%

30%

40%

50%

60%

70%

80%

19

49

19

53

19

57

19

61

19

65

19

69

19

73

19

77

19

81

19

85

19

89

19

93

19

97

20

01

20

05

20

09

20

13

20

17

% F

ood E

xpenditu

res

Food At Home Food Away From Home

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

% F

ood E

xpenditu

res

Grocery Warehouse Clubs & Mass Merchants Restaurants

19

Source: US Census Bureau, Credit Suisse estimates

Restaurants Are Gaining Consumer Wallet Share

US Restaurants As % of Retail Wallet Share

US Restaurants & Retail Sales Growth

Restaurants represent ~11% of consumer retail wallet spend, an increase of ~250bps over the last 20 years

Restaurant sales growth has outpaced overall retail sales and accelerated in recent years

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

20-yr CAGR 5-yr CAGR 1-yr Growth

% G

row

th

Restaurant Sales Retail & Foodservice Sales

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

Jan-9

9

Dec-

99

Nov-

00

Oct

-01

Sep-0

2

Aug-0

3

Jul-04

Jun-0

5

May-

06

Apr-

07

Mar-

08

Feb-0

9

Jan-1

0

Dec-

10

Nov-

11

Oct

-12

Sep-1

3

Aug-1

4

Jul-15

Jun-1

6

May-

17

Apr-

18

Mar-

19

% W

alle

t S

hare

Full Service Restaurants Limited Service Restaurants

20

Source: US Bureau of Labor Statistics, US Census Bureau, Credit Suisse estimates

Structural Changes Women At Work

Female Labor Participation Rate & % Share of Food Expenditures

Women’s Age at First Marriage & % Food Away From Home Expenditure

The increase of women in the labor force over the last several decades has been a notable factor in driving an increase in food away from home stomach share…

…with delayed marriages (and families) likely to maintain “younger generational trends” longer than prior generations

20%

30%

40%

50%

60%

70%

80%

19

50

19

54

19

58

19

62

19

66

19

70

19

74

19

78

19

82

19

86

19

90

19

94

19

98

20

02

20

06

20

10

20

14

20

18

Female Labor Participation Rate % FAFH % FAH

Correlation: 0.96

R2: 0.92

16

18

20

22

24

26

28

30

32

20%

25%

30%

35%

40%

45%

50%

55%

60%

19

50

19

54

19

58

19

62

19

66

19

70

19

74

19

78

19

82

19

86

19

90

19

94

19

98

20

02

20

06

20

10

20

14

20

18

Media

n A

ge a

t Firs

t M

arr

iage

% F

ood A

way

Fro

m H

om

e (

FA

FH

)

% FAFH Women's age at first marriage Men's age at first marriage

Correlation: 0.97

R2: 0.93

21


Structural Changes Living Arrangements

% Adults 25-34 Years Old Living At Home

% Adults 18+ Years Old Living Alone

Adults are moving out of their parents’ houses later, with ~17% of adults 25-34 years old still living at home, the highest in history

There are also more adults living alone than ever before

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

19

98

20

00

20

02

20

04

20

06

20

08

20

10

20

12

20

14

20

16

20

18

% A

dults

25

-34 L

ivin

g A

t H

om

e

8.0%

9.0%

10.0%

11.0%

12.0%

13.0%

14.0%

15.0%

19

70

19

73

19

76

19

79

19

82

19

85

19

88

19

91

19

94

19

97

20

00

20

03

20

06

20

09

20

12

20

15

20

18

% A

dults

18+

Liv

ing A

lone

22


Structural Changes Household Composition

Single-Person Households in US

Median Age of Homeowner

The number of single-person households continues to rise, now representing ~28% of total households …

… and Americans are buying houses later, with the median age of homeowners now at the highest level in more than 50 years

42

44

46

48

50

52

54

19

60

19

63

19

66

19

69

19

72

19

75

19

78

19

81

19

84

19

87

19

90

19

93

19

96

19

99

20

02

20

05

20

08

20

11

20

14

20

17

Media

n A

ge o

f H

om

eow

ner

10%

12%

14%

16%

18%

20%

22%

24%

26%

28%

30%

0

20

40

60

80

100

120

140

19

60

19

63

19

66

19

69

19

72

19

75

19

78

19

81

19

84

19

87

19

90

19

93

19

96

19

99

20

02

20

05

20

08

20

11

20

14

20

17

% S

ingle

-Pers

on H

ouse

hold

s

# S

ingle

-Pers

on H

ouse

hold

s (0

00s)

# Single-Person Households % Single-Person Households

23

Source: Prodco, Bloomberg, Forrester, Credit Suisse estimates

Shifts In Consumption Trends Shopping

Retail Traffic Trends

E-commerce as % of Retail Sales

It’s no surprise retail traffic trends are down, which is likely a headwind for restaurants overall…

…as consumers increasingly shop online

-10.0%

-8.0%

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

1Q

11

3Q

11

1Q

12

3Q

12

1Q

13

3Q

13

1Q

14

3Q

14

1Q

15

3Q

15

1Q

16

3Q

16

1Q

17

3Q

17

1Q

18

3Q

18

1Q

19

Reta

il Tra

ffic

Retail traffic continues to trend negative as consumers

shift online

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

E-C

om

merc

e a

s %

of

Reta

il S

ale

s

E-commerce now

represents ~13-14% of

retail sales, with

penetration that has more

than doubled over the last

decade

24

Source: eMarketer, Credit Suisse estimates

Shifts In Consumption Trends Content

Cord Cutters & Penetration

Subscription Over-the-Top (OTT) Video Service Users & Penetration

Consumers are increasingly shifting to alternative providers for content, forgoing pay-TV for other subscription services (i.e. Netflix, Hulu, HBO Now, Amazon Video, YouTube Red, etc.)

Subscription service providers often offer creative content, customization, engagement with audiences and increased convenience (i.e. streaming direct through phone/tablet vs TV)

25

33

39

45

50

55

0%

5%

10%

15%

20%

25%

0MM

10MM

20MM

30MM

40MM

50MM

60MM

2017 2018 2019 2020 2021 2022

% P

opula

tion

Cord

Cutters

Cord Cutters (MM) % Population

153

170

182 188

193 198

44%

46%

48%

50%

52%

54%

56%

58%

60%

62%

100MM

120MM

140MM

160MM

180MM

200MM

220MM

2017 2018 2019 2020 2021 2022

% P

opula

tion

Subsc

riptio

n O

TT V

ideo S

erv

ice U

sers

Subscription OTT Video Service Users % Population

25

Source: Euromonitor, Credit Suisse estimates

Shift in Consumption Trends Restaurant Ordering

Digital Sales as % of Limited Service Restaurant Sales

Delivery as % of Limited Service Restaurant Sales

Industry estimates suggest digital ordering will comprise ~12% of limited service restaurant sales by 2022 (which could even be conservative)

Delivery is estimated to represent ~11% of limited service restaurant sales over the next four years (and estimates have continued to increase)

2%2% 3%

4%

6%7%

8%

10%

11%12%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

20

13

20

14

20

15

20

16

20

17

20

18

20

19E

20

20E

20

21E

20

22E

Dig

ital as

% o

f LS

R S

ale

s

7%8%

8%8%

9%

9%

10%10%

10%11%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

11.0%

12.0%

20

13

20

14

20

15

20

16

20

17

20

18

20

19E

20

20E

20

21E

20

22E

Deliv

ery

as

% o

f S

ale

s

26

Source: US Census Bureau, US Bureau of Labor Statistics, Credit Suisse estimates

Restaurants Sales Growth ~5% Over Last 20 Years Contribution from ~3% SSS & ~2% Unit Growth

US Restaurants Sales US Restaurants Sales SSS & Unit Growth

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Rest

aura

nts

Sale

s G

row

th

20-yr Avg: 5%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Rest

aura

nts

Sale

s G

row

th

SSS Unit Growth

60% of restaurant sales growth has come from SSS and 40% of growth generated from unit growth

27

Source: US Bureau of Labor Statistics, Credit Suisse estimates

Consumers Allocate “Food Budget” Differently by Age

Share of Food Away From Home Meals by Age Food & Food Away From Home Expenditures as % of Total by Age

Consumers across age groups spend ~12-14% of their budgets on food

Younger consumers:

– Spend more of their “food budget” on food away from home

– Spend more on fast food, takeout & delivery

The younger the consumer, the more is spent away from home and off-premise, highlighting the importance of resonating with younger generations

7.0%

6.2%

6.2%

5.6%

5.0%

5.1%

14.2%

13.4%

13.6%

12.5%

12.2%

12.8%

<25 years old

25-34 years old

35-44 years old

45-54 years old

55-64 years old

65+ years old

% Average Expenditures

Food Away From Home Food At Home

56%

51%

48%

44%

42%

33%

37%

44%

46%

51%

54%

65%

<25 years old

25-34 years old

35-44 years old

45-54 years old

55-64 years old

65+ years old

% Food Away From Home Spend

Fast Food/Takeout/Delivery Full Service RestaurantsVending Machines Employer & School Cafeterias

28

Source: US Bureau of Labor Statistics, Credit Suisse estimates

Food Away From Home Gaining Share Across Age Groups

Change in Share of Food Away From Home Meals by Age (2017vs 2010) Change in Food Away From Home Share by Age (2017 vs 2010)

Consumers are spending more on meals away from home across age groups

Fast food/takeout/delivery has gained the most incremental share from consumers <25 years old

Fast food/takeout/delivery is gaining share among younger and older consumers

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

<25 years

old

25-34

years old

35-44

years old

45-54

years old

55-64

years old

65+ years

old

Chg in

Food A

way

Fro

m H

om

e S

hare

-8.0%

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

<25 years

old

25-34

years old

35-44

years old

45-54

years old

55-64

years old

65+ years

old

Chg in

% S

hare

of

FA

FH

Meals

Fast food/takeout/delivery Full service restaurants

Vending machines Employer & school cafeterias

29

Source: Conference Board, Bureau of Labor Statistics, Credit Suisse estimates

Macro Trends Largely Favorable For Restaurant Growth

Disposable Income Growth

Average Hourly Earnings Growth

Consumer Sentiment

Unemployment Rate

0

20

40

60

80

100

120

140

160

Jan-0

0S

ep-0

0M

ay-

01

Jan-0

2S

ep-0

2M

ay-

03

Jan-0

4S

ep-0

4M

ay-

05

Jan-0

6S

ep-0

6M

ay-

07

Jan-0

8S

ep-0

8M

ay-

09

Jan-1

0S

ep-1

0M

ay-

11

Jan-1

2S

ep-1

2M

ay-

13

Jan-1

4S

ep-1

4M

ay-

15

Jan-1

6S

ep-1

6M

ay-

17

Jan-1

8S

ep-1

8M

ay-

19

Consu

mer

Confidence

Index

US Consumer

Confidence approaching

peak levels

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

11.0%

1Q

00

1Q

01

1Q

02

1Q

03

1Q

04

1Q

05

1Q

06

1Q

07

1Q

08

1Q

09

1Q

10

1Q

11

1Q

12

1Q

13

1Q

14

1Q

15

1Q

16

1Q

17

1Q

18

1Q

19

Unem

plo

yment

Rate

Unemployment is

at its lowest levels

since 2000 &

expected to

remain below

historical levels

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

1Q

00

1Q

01

1Q

02

1Q

03

1Q

04

1Q

05

1Q

06

1Q

07

1Q

08

1Q

09

1Q

10

1Q

11

1Q

12

1Q

13

1Q

14

1Q

15

1Q

16

1Q

17

1Q

18

1Q

19

Dis

posa

ble

Inco

me G

row

th

Disposable income has been

strong in recent years, a

positive for restaurant

spend

1.5%

1.7%

1.9%

2.1%

2.3%

2.5%

2.7%

2.9%

3.1%

3.3%

3.5%

Feb-1

3

Jul-13

Dec-

13

May-

14

Oct

-14

Mar-

15

Aug-1

5

Jan-1

6

Jun-1

6

Nov-

16

Apr-

17

Sep-1

7

Feb-1

8

Jul-18

Dec-

18

May-

19

Ave

rage H

ourly

Earn

ings

Gro

wth

Average hourly earnings

growth has continued to

accelerate

30

Source: Bureau of Economic Analysis, Energy Information Administration, USDA, Credit Suisse estimates

Backdrop is Largely Stable or Improving

Gas Prices

Personal Savings Rates

Personal Consumption Expenditures (PCE)

Food At Home/Food Away From Home CPI Inflation Gap

$1.50

$2.00

$2.50

$3.00

$3.50

$4.00

Jan-1

3

Jun-1

3

Nov-

13

Apr-

14

Sep-1

4

Feb-1

5

Jul-15

Dec-

15

May-

16

Oct

-16

Mar-

17

Aug-1

7

Jan-1

8

Jun-1

8

Nov-

18

Apr-

19

Sep-1

9

Feb-2

0

Jul-20

Dec-

20

$/G

allo

n

Gas prices are expected to

remain at relatively similar

levels over the next 18

months-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

1Q

00

1Q

01

1Q

02

1Q

03

1Q

04

1Q

05

1Q

06

1Q

07

1Q

08

1Q

09

1Q

10

1Q

11

1Q

12

1Q

13

1Q

14

1Q

15

1Q

16

1Q

17

1Q

18

1Q

19

PC

E G

row

th

Total PCE Food Services & Accomodations

PCE growth and food

service & accomdations

growth remain strong

-6.0%

-5.0%

-4.0%

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

Jan-0

0

Dec-

00

Nov-

01

Oct

-02

Sep-0

3

Aug-0

4

Jul-05

Jun-0

6

May-

07

Apr-

08

Mar-

09

Feb-1

0

Jan-1

1

Dec-

11

Nov-

12

Oct

-13

Sep-1

4

Aug-1

5

Jul-16

Jun-1

7

May-

18

Apr-

19

FA

H/F

AFH

CP

I G

ap

FAH/FAFH CPI

inflation gap remains

elevated, making

restaurants relatively

more expensive than

grocery

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

Mar-

00

Mar-

01

Mar-

02

Mar-

03

Mar-

04

Mar-

05

Mar-

06

Mar-

07

Mar-

08

Mar-

09

Mar-

10

Mar-

11

Mar-

12

Mar-

13

Mar-

14

Mar-

15

Mar-

16

Mar-

17

Mar-

18

Mar-

19

Pers

onal S

avi

ngs

Rate

The savings rate has been

relatively stable though still

slightly above the ~6% average

31

Source: Black Box, USDA, Credit Suisse estimates

CPI Inflation Gap Remains Elevated Restaurants More Expensive Relative to Grocery

2.2%

2.7%

2.1%

1.4%

0.7%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

1-yr Avg 3-yr Avg 5-yr Avg 10-yr Avg 20-yr Avg

FA

H/F

AFH

CP

I In

flatio

n G

ap

Food At Home/Food Away From Home CPI Inflation Gap Over Time FAH/FAFH CPI Inflation Gap vs Restaurant Traffic

The Food At Home (FAH)/Food Away From Home (FAFH) CPI Inflation gap has remained

elevated, making restaurant prices relatively more expensive than grocery

– Over the last year, the gap has narrowed (1-yr avg 2.2% vs 3-yr avg 2.7%), though is 2x as wide as the 10-yr avg (1.4%)

Restaurant traffic has exhibited a relatively strong relationship with the CPI inflation gap over time

-7.0%

-6.0%

-5.0%

-4.0%

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

Apr-

12

Sep-1

2

Feb-1

3

Jul-13

Dec-

13

May-

14

Oct

-14

Mar-

15

Aug-1

5

Jan-1

6

Jun-1

6

Nov-

16

Apr-

17

Sep-1

7

Feb-1

8

Jul-18

Dec-

18

Black Box Restaurant Traffic FAH/FAFH CPI Gap

Correlation Since 2012: 0.6

Correlation Since 2014: 0.7

32

Source: Black Box, Credit Suisse estimates

SSS are primarily being driven by price increases, rather than traffic growth

Black Box Traffic & Average Check Black Box SSS

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

Jan-1

2

May-

12

Sep-1

2

Jan-1

3

May-

13

Sep-1

3

Jan-1

4

May-

14

Sep-1

4

Jan-1

5

May-

15

Sep-1

5

Jan-1

6

May-

16

Sep-1

6

Jan-1

7

May-

17

Sep-1

7

Jan-1

8

May-

18

Sep-1

8

Jan-1

9

May-

19

Rest

aura

nt

Indust

ry S

SS

-8.0%

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

Jan-1

2

May-

12

Sep-1

2

Jan-1

3

May-

13

Sep-1

3

Jan-1

4

May-

14

Sep-1

4

Jan-1

5

May-

15

Sep-1

5

Jan-1

6

May-

16

Sep-1

6

Jan-1

7

May-

17

Sep-1

7

Jan-1

8

May-

18

Sep-1

8

Jan-1

9

May-

19

Rest

aura

nt

Indust

ry S

SS

Traffic Avg Check

33

Source: Company data, Consensus Metrix, Credit Suisse estimates

Restaurant Industry SSS Expectations Imply Acceleration in 2019 & 2020

Restaurant Industry SSS Consensus Estimates Restaurant Industry SSS 20-yr Historical

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

1Q

14

3Q

14

1Q

15

3Q

15

1Q

16

3Q

16

1Q

17

3Q

17

1Q

18

3Q

18

1Q

19

3Q

19

E

1Q

20

E

3Q

20

E

Rest

aura

nt

Indust

ry S

SS

Consensus estimates a ~50bps SSS acceleration

in 2019 to 2.6%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

1Q

98

1Q

99

1Q

00

1Q

01

1Q

02

1Q

03

1Q

04

1Q

05

1Q

06

1Q

07

1Q

08

1Q

09

1Q

10

1Q

11

1Q

12

1Q

13

1Q

14

1Q

15

1Q

16

1Q

17

1Q

18

1Q

19

Rest

aura

nt

Indust

ry S

SS

20-yr Avg: 3%

34

Key Themes

35

Delivery

36

Source: Euromonitor, Technomic, Credit Suisse estimates

Delivery channel small & growing

Off-premise

~$300BN

Total Restaurant Industry

~$600BN

Delivery represents ~$35BN of US restaurant sales, though is expected to outpace overall restaurant growth over the next several years as consumers increase utilization, awareness increases, restaurants expand offerings and third party partnerships expand coverage

Restaurant Industry

~$600BN

Off-premise $300BN

Delivery

$35BN

37


Are Delivery Sales Incremental? Yes…for now

On average, restaurant companies have indicated delivery is ~65-70% incremental

– Majority of delivery sales appear to be generated in afternoon/late night during underutilized dayparts and can likely offset lost sales during inclement weather

Incrementality generated from both increased order sizes and transaction growth

– Average Check – more group orders; add-ons (avg check ~1.5-2x size of traditional in-store order)

– Transactions – replacing cooking; gaining share from restaurants not offering delivery

Some operators appear to be skeptical delivery is truly incremental to the business against a backdrop of relatively flat to negative traffic and sales

– But delivery is both an offensive & defensive strategy

Over time, we expect the incrementality of delivery to decrease as the channel grows and more restaurants/alternative food providers offer delivery – the winners will be restaurants enhancing operations and building an infrastructure to support sustainable channel

38

Source: Credit Suisse survey

Delivery Is Taking Share Away From Home Convenience driving delivery growth

Delivery is incremental to the restaurant industry – 50% of consumers are eating delivery more often because they are cooking less

Convenience is driving demand for delivery (in an industry based on convenience) – 60% of consumers are eating delivery more often because they don’t feel like cooking; 50% of consumers are eating delivery more often because they don’t have time to cook

Consumers Eating Delivery MORE Often Consumers Eating Delivery MORE Often

Both eating at

restaurants &

cooking less

33%

Cooking less

49%

Eating at

restaurants less

18%

If you said you have been eating restaurant food delivery

MORE often, are you:

60%

49%

31%

10%

0%

10%

20%

30%

40%

50%

60%

70%

Don't feel like

cooking

Don't have time to

cook

Don't feel like

going out to a

restaurant

Cheaper than

grocery

shopping/cooking

% R

esp

odents

If you said you have been eating restaurant food delivery

MORE often, what are the reasons?

Survey conducted among ~1,200 consumers in March 2019.

39

Source: Restaurant Research Journal, Credit Suisse survey

Majority of Delivery During Underutilized Dayparts

Delivery transactions are largely occurring at underutilized dayparts – 82% of consumers indicated they are ordering delivery at dinner; majority of QSR sales are during breakfast and lunch

– Commentary from restaurant companies also suggests most delivery orders are coming in during underutilized times (dinner, late night, weekends)

Average QSR Daypart Mix Delivery by Daypart

Breakfast

11%

Lunch

43%Dinner

31%

Late

Night/Snack

17%

3%

13%9%

82%

13%

4%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Morn

ing

(7-1

1A

M)

Lunch

(11A

M-1

PM

)

Aft

ern

oon

(1-4

PM

)

Din

ner

(4-9

PM

)

Late

Nig

ht

(9P

M-1

2A

M)

Very

Late

Nig

ht

(A

fter

12

AM

)

% R

esp

ondents

What part of the day do you usually order delivery?


40


Delivery Utilization Growing Across All Markets

Consumers order delivery the most in urban markets –70% of consumers in urban markets indicated they order delivery at least 1-2x per month (vs. ~50% of consumers on average)

But delivery is growing across ALL markets – from our surveys conducted in March 2019 relative to our July 2018 survey, a greater percentage of consumers across urban, suburban and rural neighborhoods indicated they order delivery at least 1-2x per month (meaning there are less consumers that have never ordered delivery as availability increases)

Delivery Order Frequency by Neighborhood – March 2019 vs July 2018 Delivery Order Frequency by Neighborhood

Survey conducted among ~1,200 consumers in March 2019 & ~1,200 consumers in July 2018.

37% 30% 35%

57%

41%42%

44%

30%

16% 21% 16%9%

6% 7% 6% 4%

0%10%20%30%40%50%60%70%80%90%

100%

Average Urban Suburban Rural

Neighborhood

% R

esp

ondents

How often do you order restaurant food delivery

at home per month?

Never 1-2 times per month 3-4 times per month 5 or more times per month

59%

48%

39%

70%65%

43%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Urban Suburban Rural

Neighborhood

% R

esp

ondents

How often do you order restaurant food delivery at home

per month? "1-5+ Times Per Month"

July 2018 March 2019

41


Delivery Should Continue to Grow Across All Markets

Consumers in all neighborhoods expect to order delivery more – more than 50% of consumers in all neighborhoods are likely to order delivery over the next 12 months

Delivery intent is growing – from our surveys conducted in March 2019 to July 2018, more consumers across urban, suburban and rural neighborhoods indicated they are likely to order delivery over the next 12 months (i.e. 79% of consumers in urban markets were likely to order delivery over the NTM in our March 2019 survey vs 66% in our July 2018 survey)

Delivery Order Intent Over Next 12 Months – March 2019 vs July 2018 Delivery Order Intent Over Next 12 Months


79%72%

56%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


% R

esp

ondents

What is the likelihood you order restaurant food delivery

over the next 12 months?

Very likely Somewhat likely

66%60%

51%

79%72%

56%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


% R

esp

ondents


over the next 12 months? "Very likely/Somewhat likely"

July 2018 March 2019

42


Delivery Pervasive Across All Age Groups

Consumers across all age groups are ordering delivery – 65% of consumers order delivery at least 1-2x per month

The majority of consumers across age groups are likely to order delivery going forward – 70%+ of consumers 18-60 years old are likely to order delivery over the next 12 months

Delivery Order Intent Over Next 12 Months by Age Delivery Order Frequency by Age


35% 32%23%

34%

60%

42%39%

45%

48%

28%

17%20% 22%

15% 8%6% 9% 9% 4% 5%

0%10%20%30%40%50%60%70%80%90%

100%

Average 18-29 30-44 45-60 60+

Age

% R

esp

ondents

How often do you order restaurant food delivery

at home per month?

Never 1-2 times per month 3-4 times per month 5 or more times per month

73%78%

73%

50%

0%10%20%30%40%50%60%70%80%90%

100%

18-29 30-44 45-60 60+

Age

% R

esp

ondents


over the next 12 months?

Very likely Somewhat likely

43


How Do You Get People to Order Delivery MORE Often?

Potential Delivery Demand Drivers – “Free Delivery” Potential Delivery Demand Drivers

Reducing delivery costs could be the best way to drive delivery growth – consumers indicated free delivery, special discounts and loyalty points/rewards as top factors that would get them to order delivery more (65% free delivery, 40% special discounts, 38% loyalty points/rewards)

Free delivery is the #1 way to increase delivery orders across age groups & frequency levels – “Free delivery” was indicated as the top factor that would drive increased delivery demand across every age and delivery frequency level


65%

40%

38%

33%

31%

18%

9%

Free delivery

Special discounts only for delivery

Loyalty points/rewards

More restaurant/cuisine options

Favorite restaurant starts to offer delivery

LTOs available only for delivery

Nothing

% Respondents

What would get you to eat restaurant food delivery

MORE often?

62%

67%

63%

67%71%

67%62%

53%

Never 1-2 times 3-4 times 5+ times 18-29 30-44 45-60 60+

Delivery Frequency Per Month Age


MORE often? - "Free Delivery"

44 Source: Credit Suisse survey

Younger Consumers Want Delivery – But They Don’t Want the Cost

Potential Delivery Demand Drivers – “Free Delivery” Potential Delivery Demand Drivers – 18-29 Year Olds vs Average

Younger consumers would have a greater response to reduced delivery costs than the

average consumer – more consumers 18-29 years old indicated free delivery, loyalty/rewards and special discounts would lead them to order delivery more often relative to the average consumer

Non-delivery users would be even more incentivized to order delivery with free delivery and

special discounts – 78% of consumers 18-29 years old that don’t order delivery indicated free delivery would get them to order delivery more often; this compares to 67% of 18-29 year olds that order delivery at least 1-2x per month


78%

54%

48%

29%

28%

17%

3%

67%

53%

49%

35%

26%

28%

2%

Free delivery




Favorite restaurant offers delivery


Nothing

% Respondents


MORE often?

Age 18-29 Non-Delivery Users Age 18-29 Delivery Users

-6%

7%

-4%

1%

11%

13%

7%

Nothing






Free delivery

% Respondents


MORE often (Age 18-29 vs Average)?

45

Source: PitchBook, Sensor Tower, Credit Suisse estimates

Third-Party Delivery Platforms Friend or Foe?

Third-party platforms have expanded coverage, customer acquisition and restaurant acquisition over the last couple of years, which we view as largely complementary to restaurant industry sales growth

Over the last few years, there has been meaningful growth in the number of deals in the restaurant delivery/ordering platform space

Delivery apps are growing at a much faster rate than the pizza segment (digital app leaders), indicative of increasing demand and expanding geographical coverage

Pizza vs Delivery Apps Download Share Restaurant Delivery & Ordering Platform Deals

Note: Pizza apps include 10 of the largest national pizza chains. Delivery apps

include 9 of the largest national delivery/digital restaurant service providers.

0

10

20

30

40

50

60

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

# D

eliv

ery

/Ord

ering P

latf

orm

Deals

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Jan-

12

Jun-1

2

Nov

-12

Apr-

13

Sep-

13

Feb-

14

Jul-

14

Dec-

14

May

-15

Oct

-15

Mar

-16

Aug-

16

Jan-

17

Jun-1

7

Nov

-17

Apr-

18

Sep-

18

Feb-

19

Dig

ital A

pp D

ow

nload

Sha

re

Pizza Apps Delivery Apps

46

Are Large Chains Positioned to Win on Delivery? In Our View, Yes

Delivery platforms help level the playing field for regional chains & locals to compete against the larger chains

– Opportunity for virtual and ghost kitchens, requiring minimal upfront costs & benefits from shared services

– But high commission costs and little negotiating power could turn delivery orders into unprofitable orders for some smaller restaurant chains

Most large restaurant chains are currently rolling out delivery through partnerships with third-party providers and more favorable deal terms (relative to smaller restaurant companies)

Increasing competition among delivery aggregators and their strategies to acquire large chain restaurants sets a favorable backdrop going forward, with restaurants likely to gain more power

Overall, we believe restaurants that view delivery as a long-term growth driver and integrate digital/delivery across operations will generate higher levels of delivery sales, incremental profit and optimize operations


47

Large Chains Helping to Drive Delivery Aggregator Growth QSR chain partnerships are generating accelerating digital downloads for third-party aggregators,

highlighting the demand and value of chains on aggregator platforms

We expect QSR chains could get more favorable rates from aggregators near-term as they (1) recognize the value they bring to the platform and (2) competition among delivery aggregators to attract QSR chains increases

Source: Sensor Tower, Credit Suisse estimates

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1Q

15

2Q

15

3Q

15

4Q

15

1Q

16

2Q

16

3Q

16

4Q

16

1Q

17

2Q

17

3Q

17

4Q

17

1Q

18

2Q

18

3Q

18

4Q

18

1Q

19

% D

ow

nload

Sha

re Uber Eats

Caviar

DoorDash

Postmates

Delivery.com

Grubhub/Seamless

Uber Eats download share accelerated in 2017 following its announced partnership with McDonald’s

DoorDash downloads are

growing at the fastest rate

relative to competitors –

DoorDash has established more partnerships with large chains

relative to competitors

48


Top Delivery Considerations

Economics

– High commission costs pressuring margins

– Restaurants increasingly shifting incremental costs to customer

Data

– Limited access to customer data transacted through third-party platforms

Increasing Competition

– Decreases barriers to entry (ghost kitchens without physical address; pop up shops)

Customer Shifting

– Restaurant customers shifting to third-party platform customers

Quality

– Restaurants lose quality control with last mile, including the customer experience

Operations

– Integration with POS system and digital app, store layouts, alternative solutions

– Increase restaurant complexity

Delivery Drivers

– Ability to acquire and retain delivery drivers is challenging and delivery driver networks need to be sufficient to fulfill demand

49

Future of Delivery– Restaurants Gaining Power Change is Coming Economics

– (1) more favorable commission rates between third-party aggregators and QSR chains going forward as QSRs realize the growth they bring to the platform; (2) higher delivery prices relative to in-store; and (3) costs to increasingly shift to the customer (delivery fees, service fees, small order fees)

Data

– We expect an increased focus on capturing customer data, with integration of delivery into digital apps likely near-term, and limited expectations for data sharing from delivery aggregator to restaurant

Operations

– We expect restaurants will modify layouts with an omni-channel focus & explore alternative formats

Exclusivity

– Commentary from restaurant companies suggest presence on multiple third-party platforms is complementary within a still fragmented market, and we expect most chains to work with multiple aggregators

Marketing Support

– Partnerships with chains has generated significant customer acquisition for delivery aggregators, and we expect large QSR chains to demand greater marketing support (i.e. funding of free delivery campaigns)


50


Economics pressuring margins and profitability of delivery orders Third-party commission costs of ~20-30% drive significant margin pressure and source of concern

among restaurant operators

– Commissions are customer acquisition costs to some extent, but they are perpetual

But, delivery economics may not be as bad as they seem at face value

1) May not require incremental costs, making delivery orders more profitable assuming they are at least partially incremental sales (i.e. unused labor capacity, rent & other fixed costs)

2) Operators may not offer same in-store deals/discounts

3) Generally higher average ticket and could be higher dollar profit, even if margins as a percentage of sales is lower

Restaurants are increasingly shifting delivery costs to customers and improving profitability through:

1) Increased menu prices

2) Delivery fees

3) Service fees

4) Small order fees

Economics

51

Source: Wendy’s App, DoorDash, Seamless App, Credit Suisse estimates

Shifting Delivery Costs to the Customer Increased Menu Prices, Delivery Fees & Service Fees

Wendy’s delivery menu prices ~5-15%

higher than mobile order & pay

YUM charges an additional service fee of 12.5% on

delivery orders to cover commission

Higher Menu Prices: Wendy’s Digital App vs DoorDash Delivery Seamless Additional Service Fee Charged on Taco Bell Delivery

Economics

Wendy’s App DoorDash App

52


Delivery is Expensive for Customers

Economics

In-Store

Avg Check

Delivery

1.5x Avg

Check

Delivery

2x Avg

Check

Delivery

1.5x Avg

Check

Delivery

2x Avg

Check

Average Ticket $7.00 $10.50 $14.00 $10.50 $14.00

% Menu Price Adjustment 20% 20%

Adjusted Average Ticket $12.60 $16.80

Delivery Fee $1.99 $1.99 $1.99 $1.99

Service Fee 15.0% 15.0% 15.0% 15.0%

Small Order Fee (if appicable) $2.00 $2.00 $2.00 $2.00

Order Cost to Customer $7.00 $14.07 $18.09 $16.48 $21.31

Cost of Delivery - Customer Level

No Menu Price Adj. Menu Price Adj.

Restaurants are adjusting

menu prices on platforms to offset the cost of delivery

Restaurants and platforms are increasingly shifting costs to the customer

53


Can Delivery Be Margin Accretive? Yes – requires higher average checks and incrementality

Third-party commission costs represent a headwind, but higher average checks and incrementality support margin leverage

– Delivery orders tend to generate average checks 1.5-2x the size of a traditional in-store order

– Restaurants indicate delivery is ~65-70% incremental

Increasing delivery menu prices to cover the incremental costs of delivery should be at least margin neutral (and likely accretive)

Assume slightly higher

packaging costs

Assume leverage from partially fixed labor and operating costs

Economics

In-Store

Avg Check

Delivery

1.5x Avg

Check

Delivery

2x Avg

Check

Delivery

1.5x Avg

Check

Delivery

2x Avg

Check

Average Ticket $7.00 $10.50 $14.00 $10.50 $14.00

Food & Paper 28.5% 29.0% 29.0% 29.0% 29.0%

Labor 28.0% 18.7% 14.0% 14.0% 10.5%

Royalty 4.0% 4.0% 4.0% 4.0% 4.0%

Advertising 4.0% 4.0% 4.0% 4.0% 4.0%

Other Operating 12.0% 8.0% 6.0% 6.0% 4.5%

Rent 12.0% 12.0% 12.0% 12.0% 12.0%

Commission 0.0% 20.0% 20.0% 20.0% 20.0%

EBITDA per order 11.5% 4.3% 11.0% 11.0% 16.0%

EBITDA $ per order $0.81 $0.45 $1.54 $1.16 $2.24

Cost of Delivery - Restaurant Level

Assumes IncrementalityNo Incrementality

54


The Cost of Convenience Customer Willingness to Pay Delivery Fees

80% of customers indicated they are willing to pay a delivery fee across age groups

On average, 1 in 5 customers are not willing to pay a delivery fee – Among those that don’t order delivery, 1 in 3 customers are not willing to pay a delivery fee –

highlighting incremental costs of delivery as a headwind to attracting new users

Customer Willingness to Pay Delivery Fee – “No Delivery Fee” Customer Willingness to Pay Delivery Fee by Age

Economics


30%

17%

10%13%

17%19% 19%

33%



What is the most you are willing to pay for a delivery fee?

"No Delivey Fee"

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

18-29 30-44 45-60 60+

% R

esp

ondents

by

Age

What is the most you are willing

to pay for a delivery fee?

$1-$1.99 $2-2.99 $3-3.99 $4-4.99 $5+

65%

40%

38%

33%

31%

18%

9%

Free delivery






Nothing

% Respondents


MORE often?

55


The Cost of Convenience The Impact of Delivery Fees

“Free delivery” and “Special discounts” were the top factors that would drive increased delivery order intent, highlighting opportunities to increase utilization and customer acquisition

– 65% of customers indicated “free delivery” would incentivize them to order delivery more often

“Free delivery” was the number one way to incentivize consumers across every age group and delivery frequency level to order delivery more often

Potential Demand Drivers – “Free Delivery” Potential Delivery Demand Drivers - Average

Economics


62%

67%

63%

67%71%

67%62%

53%




MORE often? - "Free Delivery"

-6%

7%

-4%

1%

11%

13%

6%

Nothing






Free delivery

% Respondents


MORE often (Age 18-29 vs Average)?

2%

25%

27%

33%

48%

54%

71%

Nothing






Free delivery

% Respondents


MORE often (Ages 18-29)?

56


Appealing to Younger and Frequent Delivery Users Free Delivery & Loyalty/Rewards

Younger consumers are more receptive to free delivery and special discounts to drive

purchase behavior – 71% of consumers 18-29 years old indicated “free delivery” would incentivize them to order delivery MORE often vs 65% on average

Loyalty and rewards are more important to younger consumers – 54% of consumers 18-29 years old indicated “loyalty points/rewards” would increase delivery intent (vs 40% on average) – the greatest difference among all factors considered

– Delivery growth should unlock increased digital utilization, especially among younger consumers

Potential Delivery Demand Drivers – Ages 18-29 vs Average Potential Delivery Demand Drivers – Ages 18-29

Economics


57

Source: Uber Eats, Credit Suisse estimates

Who Owns the Data? Restaurants vs Third-Party Platforms

Third-party platforms own the customer data through their platforms – NOT the restaurants,

underscoring the importance for restaurants to integrate delivery through their own

branded websites/apps

Data is arguably the most important element of increased digital utilization (including delivery) to better forecast demand, personalize offers, segment customers and influence behavior

Most significant risk: third-party platforms use the rich customer data to launch their own food offerings based on demand & trends

– Increasing availability of turnkey solutions (virtual & ghost kitchens), reducing capital requirements and barriers to entry

Data

When searching “McDonald’s” in Uber Eats, the pop-up shop was the first option

Uber Eats selectively offers food

through pop-up shops in the form of virtual kitchens

58

Source: Kitchen United website, Cloud Kitchens website, Credit Suisse estimates

Increasing Competition Virtual Kitchens Launch of virtual and ghost kitchens lowers the barriers to entry by reducing upfront capital

requirements and ability to leverage shared services

Emerging virtual kitchen competitors have targeted aggressive growth potential

– Kitchen United has identified opportunities to build out 400 Virtual Kitchen Centers & install 5K kitchens across the US, including 18 centers & 13 new markets in 2019

Strong management team, many with former restaurant operator backgrounds

– Cloud Kitchens has multiple locations with expectations for additional expansion

Founder & CEO is former Uber CEO Travis Kalanick

Competition

Cloud Kitchens Benefits: Lower Costs & Faster Expansion Kitchen United Expected Openings – Virtual Kitchen Centers

59

Source: Grubhub Transcript, Credit Suisse estimates

Opportunity Cost of Shifting Customers to Third-Party Platforms As restaurants partner with third-party providers and encourage customers to order through the

platforms, they are also shifting their own customers

– Introduces customers to competitors on the platform

– Lose access to valuable customer data

– Platforms don’t necessarily have restaurants’ best interest in mind

– Delivery provider is last customer touchpoint, and could have implications for quality of food delivered and overall experience

In February/March 2019, Taco Bell and Grubhub launched a co-branded marketing campaign, increasing awareness of delivery availability & the platform

– The campaign generated an incremental ~100-150bps to GRUB’s daily average orders in the quarter, which we estimate equates to ~$12-15MM for Taco Bell sales in the quarter

“Diners that place their first order with Taco Bell during the free delivery period are returning to Grubhub at the same or better rates as a typical diner even after we ended the free delivery campaign. Some come back and order Taco Bell again, but the majority are trying other restaurants on the platform as well.” – Matthew Maloney, GRUB Founder, CEO & Director, April 2019

Third-Party Delivery Platforms

60

Source: comScore, Credit Suisse estimates

Third-Party Platforms Can Be Complementary

Restaurants can enter customer consideration sets and increase awareness of delivery availability with platform presence

Based on commentary from restaurant companies, presence across multiple platforms is also complementary

Third-Party Delivery Platforms

Burger Restaurants & Delivery Platforms Overlap

Pizza Restaurants & Delivery Platforms Overlap

There is relatively limited overlap between users of the largest delivery platforms and the largest pizza chains, suggesting

opportunity for pizza chains to benefit from incrementality on platforms

*Read starting from left column. Example: 21% of Uber Eats users engage with Domino’s digitally, 16% of Uber

Eats users use Pizza Hut and 10% of Uber Eats users also use Papa John’s.

There is relatively limited overlap between users of the largest delivery platforms & the

largest burger chains, suggesting opportunity for burger chains to benefit from

incrementality on platforms

McDonald's Burger King Wendy's Sonic Jack in the Box

Uber Eats 20% 6% 7% 5% 1%

Grubhub 18% 6% 4% 3% 1%

DoorDash 18% 6% 6% 4% 2%

Postmates 21% 6% 7% 3% 2%

Domino's Pizza Hut Papa John's

Uber Eats 21% 16% 10%

Grubhub 17% 12% 8%

DoorDash 17% 12% 9%

Postmates 21% 14% 9%

*Read starting from left column. Example: 20% of Uber Eats users engage with McDonald’s digitally, 6% of

DoorDash users use Wendy’s digitally.

61

Source: McDonald’s (delivery order in NYC February 2019), Starbucks (delivery order in NYC March 2019), Credit Suisse

Quality Control in Delivery

Certain cuisines may not travel well, which could impact the experience for the customer

Transport of food by third party could have food safety implications

Many restaurant companies appear to be exploring different packaging for delivery to maintain the order’s integrity and enhance the quality of food delivered (i.e. separate packaging for hot/cold items)

Quality

Starbucks Delivery Packaging – March 2019 McDonald’s Delivery Packaging – February 2019

McDonald’s uses separate drink packaging to prevent spillage & adhesive to protect the order’s integrity

Starbucks also uses an adhesive to maintain the order’s integrity

62

Source: Chipotle presentation, Credit Suisse

Delivery Channel Increases Operational Complexity

Addition of new ordering channels increases restaurant complexity

– Lack of POS integration creates inefficiencies

Many restaurants require multiple tablets to key in orders if lacking POS integration

– Could result in slower service times for in-store customers

Requires changes in both back & front of house layouts to address potentially increased congestion and capacity requirements

Restaurants adding designated pickup areas for digital/delivery orders, modifying back of house and front of house layouts and considering digital/delivery channels in future prototypes

Operations

Chipotle Digitized Second Make-Lines Chipotle Pickup Shelves for Digital Orders

Chipotle is rolling out digital pick-up shelves and digitized second production lines to optimize its increasing digital sales mix

63

Competing for Delivery Drivers, Not Just Sales Working with multiple platforms – Many delivery drivers are agnostic to the third-party delivery

company they are working for and often work with multiple platforms

– This could have implications on the experience if delivery drivers work with multiple platforms at the same time to maximize delivery orders

Incentive alignment – Delivery drivers work as contractors for third-party platforms and have access to a variety of third-party platforms, so incentives & ownership mentality might suffer

– Delivery drivers working for platforms are focused on maximizing delivery orders and could lead to poor service (i.e. might wait in trade area to collect multiple delivery orders vs delivering one at a time for best quality)

Selecting partners – Third-party platforms’ networks of delivery drivers should be a key consideration in partnerships since there may not be sufficient capacity for delivery drivers even if demand exists

Who faces the greatest risk? Pizza chains with delivery infrastructures face the greatest risk in the competition for delivery drivers, and platform presence might be the only way to offset potential sales losses if the restaurants’ delivery driver network cannot handle the delivery capacity

– Pizza Hut – partnering with Grubhub, with presence on the platform and Pizza Hut delivery network completing the last mile

– Papa John’s – partnering with DoorDash, with the orders coming through the platform and DoorDash also completing the delivery

– Domino’s – has dismissed the idea of a national partnership with third party platforms (though some franchisees have presence for order aggregation)

Source: Company data, Credit Suisse

Delivery Drivers

64

Exposure to Delivery


Domino’s (DPZ)

• Best-in-class delivery infrastructure with high-level execution supportive of

delivery share gains long-term

Chipotle (CMG)

• Only large restaurant company to integrate delivery in its app; food travels well;

second production lines to execute digital orders optimizes operations

Shake Shack (SHAK)

• Prudent approach to delivery to optimize operations and quality of food delivered;

based on industry contacts, Shake Shack generates significant traction on platforms where available

McDonald’s (MCD)

• Delivery still in early stages, with opportunities for multiple partnerships and

marketing support as upside

65

Digital


Delivery

66

Digital Supports Incremental Sales Volumes Adding Convenience Not Seen Since The Drive-Thru


AUV*

Traditional

QSR

Drive-Thru

~50-70%

Sales Mix

Mobile Order

Drive-Thru

~20%

Sales Mix

Drive-thru orders tend to generate higher avg tickets relative to in-store orders (multiple people in car)

Digital channels support an additional layer of sales & orders generally 1.5-2x higher than an in-store order (multiple people on order; suggestive sell; more time to browse)


*Average unit volume

67

Technology Can Unlock Capacity Every 6 seconds saved at drive-thru = 1% in sales per former McDonald’s CEOs Jack Greenberg & Don Thompson


Deploying technology

to increase efficiency

of operations

Shift customers from

the drive-thru to

digital channels

Generate digital sales

at underutilized

dayparts

Digital menu boards, system integration, customer recognition

Add second production lines to execute digital orders

Digital orders allow for better planning; delivery transactions tend to come in after 4PM & weekends

68

Technology Comes At A Cost Corporate Level


Technology is a perpetual cost restaurants must incur to maintain their digital ecosystems

All companies across all restaurant segments are increasing investments in digital and the majority are partnering with third-party aggregators for delivery

Select companies are also making big investments in outside firms as they seek to gain a competitive advantage against peers (accelerate digital innovation, access to talent, etc.)

February 2018: $200MM in Grubhub July 2018: Acquires license for CardFree to accelerate digital development December 2018: Acquires QuikOrder for $77MM February 2019: $25MM digital investment, including $15MM for Accenture partnership March 2019: $100MM investment in Venture Fund that invests in food & retail startups March 2019: $300MM to acquire Dynamic Yield startup & $5MM investment in Plexure

69

Technology Comes At A Cost Restaurant Level


Infrastructure, Equipment & Software – Back of house/front of house technology and equipment, maintenance fees, support, etc. (annual & one time fees)

Technology/Digital Transaction Fees – Franchisees generally pay fees on every digital order

Credit Card Processing Fees – Digital orders generally transacted with credit/debit cards

Mobile offers and loyalty programs – Many restaurant companies are offering mobile-specific deals to encourage utilization and loyalty programs, with both discounts at the cost of the restaurants

Delivery Fees – Incremental costs: 1) commission costs for third-party delivery (commissions average ~15-30% of average ticket); 2) proprietary delivery infrastructure

70

Source: Euromonitor, Olo, PitchBook, Credit Suisse estimates

Digital Sales Utilization Continues to Expand

Digital represents ~7% of overall US restaurant sales currently, and we expect it to increase to ~25% of sales longer-term (including delivery)

Growth of online ordering platforms and third-party delivery providers and increasing digital investments from restaurants gives us confidence in ongoing digital growth

Restaurant Delivery & Ordering Platform Deals Digital as % of Sales

2% 2%4%

6%7%

25%

0%

5%

10%

15%

20%

25%

30%

2014 2015 2016 2017 2018 Long-

Term

Dig

ital as

% o

f S

ale

s

0

10

20

30

40

50

60

20

08

20

09

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Emergence of food-related apps/platforms signals greater adoption

As restaurants recognize the benefits of digital and continued consumer shift towards online channels, we expect digital utilization to continue to grow

Complementary apps to the restaurant industry, such as Uber Eats and Open Table, make up ~20% of the top 25 most downloaded food & drink apps, supporting channel & overall food market growth

0

200

400

600

800

1,000

1,200

1,400

Uber

Eats

McD

onald

's

DoorD

ash

Sta

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Chic

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Dom

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mate

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ay

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Inst

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ohn's

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Bell

Chip

otle

Litt

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Am

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# D

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in 2

018 (

MM

)

Restaurant App Complementary App Competitor App

Improvement in Food & Drink Category Ranking 2018 vs 2017 Food & Drink Category Top 25 Apps by Downloads in 2018

-10

-5

0

5

10

15

20

25

Uber

Eats

McD

onald

's

DoorD

ash

Sta

rbuck

s

Chic

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rt

OpenTable

Papa J

ohn's

Taco

Bell

Chip

otle

Litt

le C

aesa

rs

Am

azo

n P

rim

e N

ow

Bla

zin' R

ew

ard

s

Impro

vem

ent

in R

ank 2

018 v

s 2017

72

Source: Euromonitor, Olo, Credit Suisse estimates

Enhancing Convenience to Reap the Benefits

Digital Order

$12.50

In-Store Order

$10.00

~1.25x

With ~50% of restaurant sales consumed off-premise, there is significant runway to grow digital transactions

Average checks are generally ~20-30% higher on digital transactions (i.e. more time to review the menu; suggestive sell)

In-store vs Digital Average Checks Off-Premise Sales

50%

3% 6%

24%

20%

Delivery excl.

Pizza

Delivery Drive-Thru Takeout Transactions

consumed off-

premise

73


“Digital IQ” Varies Across Segments & Brands

• Domino’s: digital represents

65%+ of sales, with potential to reach nearly 100%

• Pizza Hut: digital represents ~50% of sales (~55% of delivery and carryout only)

• Papa John’s: digital represents 60%+ of sales, including ~2/3 through mobile

Pizza

• Starbucks: mobile order & pay

~15% of transactions; mobile payment ~35% of transactions & loyalty members represent ~41% of US company sales

• Dunkin’: mobile order & pay represents ~4% of transactions; loyalty members represent ~12% of sales

Coffee

• McDonald’s: mobile order & pay available nationwide

• Burger King: mobile order & pay available nationwide

• Wendy’s: rolling out mobile order & pay by end of 2019

• Jack in the Box: recently launched digital app

• Taco Bell: digital represents <10% of sales

• Subway: mobile represents ~10% of sales

• Chick-fil-A: digital represents ~15% of sales

• KFC: working on a digital app

• Popeyes: rolling out standardized POS system; recently rolled out digital app

Burgers/QSR Peers

• Chipotle: digital represents ~16% of sales

• Shake Shack: continues to invest in digital and drive higher digital sales mix

Fast Casual

74


Loyalty/Rewards Could Unlock Digital Utilization

A “loyalty/rewards program” was the number one factor respondents identified to increase mobile order and pay intent, highlighting an opportunity to unlock digital utilization

Loyalty/rewards programs growing in importance – from our surveys conducted in March 2019 to July 2018, more consumers indicated a loyalty/rewards program would influence them to use mobile order & pay more often (55% of consumers in March 2019 vs 43% in July 2018)

Potential Mobile Order & Pay Demand Drivers – Loyalty/Rewards Potential Mobile Order & Pay Demand Drivers


13%

23%

29%

29%

37%

40%

45%

55%

Nothing

LTOs available only via mobile ordering

Separate section in restaurant for pick up

Favorite restaurant starts to offer MOP

Able to save past orders

Curbside pickup option

Special mobile only discounts

Loyalty/rewards program

% Respondents

25%

23%

29%

31%

33%

38%

38%

43%

13%

23%

29%

29%

37%

40%

45%

55%

Nothing








% Respondents March 2019 July 2018

8%

31%

31%

31%

36%

46%

50%

61%

Nothing








% Respondents

What would get you to use mobile order & pay

MORE often? (Age 18-29)

75


Loyalty/Rewards Program Even More Important to Younger Digital Users Younger consumers appear more receptive to loyalty/rewards to drive mobile order & pay intent

– ~60% of consumers age 18-29 indicated a “loyalty/rewards program” would incentivize them to order mobile order & pay MORE often vs 43% on average – the greatest difference among all factors considered

– We view a loyalty/rewards program as a tool to unlock digital utilization, especially among younger consumers Potential Mobile Order & Pay Demand Drivers – Age 18-29 vs Average Potential Mobile Order & Pay Demand Drivers – Age 18-29

-5%

2%

1%

8%

-4%

9%

6%

6%

Nothing








% Respondents

What would get you to use mobile order & pay

MORE often? (Age 18-29 vs Average)


76

Source: Domino’s website, Starbucks app, Company data, Credit Suisse estimates

What Makes a Successful Loyalty Program? Data, Data and More Data Customer View: We believe the most successful loyalty programs are simple, easy to understand

and are frictionless at sign up

Restaurant View: A loyalty program is a tool to capture customer data to use for personalization and segmentation to drive increased spending – but must be used as part of an omni-channel strategy

Types of Loyalty Programs

Frequency-based – reward customers based on transactions (example: Domino’s)

Spend-based – reward customers based on dollars spent (examples: Starbucks, Dunkin’, Chipotle, Pizza Hut, Papa John’s)

Surprise & Delight – reward customers spontaneously (example: Panera)

Starbucks Domino’s

Spend Based Rewards Program Frequency-based Rewards Program

77

Company Highlight Domino’s


Domino’s competitive advantage is driven by how the company captures and leverages customer data to inform strategic decisions (suggested sell, personalized marketing, new unit development, etc.) – Digital makes up ~65% of Domino’s orders, relatively in-line with pizza peers

The Piece of the Pie loyalty program has been a meaningful contributor to SSS (20MM+ members) – The Points for Pies campaign (reward loyalty points for any pizza) shows the company’s innovative

approach to increase digital utilization, loyalty program growth and capture competitive information

Mobile:

50%+

Mobile:

~75%

Mobile:

65-70%

~65%

~50%+

60%+


Digital Sales Mix

The 3 largest pizza chains all have digital utilization

rates of 50%+, highlighting the way a company

leverages customer data is the competitive

advantage – not digital utilization alone

Domino’s uses suggestive sell at multiple points during the order

process, which has generated healthy avg check growth

Innovation around the loyalty program

highlights an opportunity to grow the program and capture more info

78

Company Highlight Starbucks


Best-in-class digital ecosystem with evolving capabilities, suggestive sell, digital relationships with non-reward members and strong personalized marketing (15% mobile order & pay; 35% mobile; 41% loyalty program)

– Ability to leverage customer data to make strategic decisions & influence behavior is and will remain the company’s competitive advantage

Starbucks has ~17MM members in the Starbucks Rewards program representing ~40%+ of US company sales & nearly all of SSS growth

The Starbucks Rewards program comprises

~17MM members with growth of 15%+ over the last five years

Starbucks is expanding digital relationships outside of Starbucks Rewards, with the goal to convert to

members over time; Loyalty members exhibit higher frequency and spend relative to non-members

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

4

6

8

10

12

14

16

18

1Q

14

2Q

14

3Q

14

4Q

14

1Q

15

2Q

15

3Q

15

4Q

15

1Q

16

2Q

16

3Q

16

4Q

16

1Q

17

2Q

17

3Q

17

4Q

17

1Q

18

2Q

18

3Q

18

4Q

18

1Q

19

2Q

19

MS

R M

em

ber

YO

Y G

row

th %

MS

R M

em

bers

(M

M)

MSR Members (MM) YOY %

~11MM ~13MM ~14MM ~16MM

~13MM

Dec 2015 Dec 2016 Dec 2017 Dec 2018

My Starbucks

Rewards Members

New Digital

Relationships

Digital

Opportunity

79

Company Highlight McDonald’s


Transforming Today’s Drive-Thru

Recent acquisition of Dynamic Yield suggests greater focus on digital innovation through increased personalization and use of decision logic technology

Near-term, McDonald’s is rolling out digital menu boards across the US system with the ability to suggest offers by time of day, weather & trending menu items

Long-term, machine learning will allow McDonald’s to increase personalization and tailor suggestions real-time based on in-restaurant traffic

– Technology will work across the digital ecosystem, including self-order kiosks, global mobile app and outdoor digital menu boards

– Opportunities for enhanced drive-thru experiences such as the recognition of customer license plates to suggest previous orders and other items, which could reduce service times, increase accuracy and improve convenience

Habitual Breakfast Positive For Digital Use

With a ~25% breakfast sales mix, McDonald’s is well positioned for digital utilization given breakfast is a more habitual occasion; the & current loyalty platform is for McCafé beverages

80

Company Highlight Chipotle

Source: Chipotle presentation, Company data, Credit Suisse estimates

Chipotle has doubled its digital utilization in just two years, with mobile order & pay and delivery now representing ~15% of sales (total out of restaurant sales incl. catering ~16%)

Operations are well suited for an omni-channel strategy, with secondary production lines executing out of restaurant sales (digitized second make-lines), “smarter pickup times” technology for visibility into order processing and in-store pickup shelves for digital orders

– Digital orders are more margin-accretive than in-store orders

Chipotle is the only large restaurant chain with delivery integrated in the app, supporting better economics and best leveraging aggregator partnerships for incremental sales through platform presence

6%

8%

10%

12%

14%

16%

18%

1Q

17

2Q

17

3Q

17

4Q

17

1Q

18

2Q

18

3Q

18

4Q

18

1Q

19

20

16

20

17

20

18

Dig

ital as

% o

f S

ale

s

Note: Represents “out of restaurant” sales which includes ~1% from catering.

Digitized secondary production

lines fulfill out of restaurant orders (primarily digital sales), unlocking capacity and limiting operational disruptions

In-store pickup shelves for out-of-store orders enhance the digital ordering experience and reduce friction

81

Company Highlight Shake Shack

Source: Shake Shack (delivery in NYC April 2019), Shake Shack presentation, Company data, Credit Suisse

Digital/delivery more meaningful contribution to sales

– Opportunity to fulfill demand for new customers & incremental occasions (i.e. customers who might otherwise not want to wait on line)

Long-term and prudent approach to delivery, as the company is testing different partners, investing in packaging, integrating POS systems, etc.

– Near-term, this strategy fails to leverage the brand’s strength with partners and company incurs higher costs (national partnerships offer more favorable delivery commissions, particularly with greater exclusivity)

Shake Shack is investing in delivery packaging to protect the integrity and quality of the order

Shake Shack is testing kiosks in select locations, which could also help offset labor costs

82


Credit Suisse Digital Framework

Mobile Order

& PayDelivery

In-restaurant

technological

investments

Delivery

Integrated in

App

Focus on

collecting

customer

data

Suggestive

Sell

Personalized

Marketing

Table Stakes Competitive AdvantageLong-Term Digital Strategy

Relative ranking based on

digital strategy within respective segment

83

M&A

84


Active Restaurant Deal Space

Restaurants deal space has been active over the last couple of years:

– Well-funded firms have recognized the synergies owning multiple brands and a larger base of restaurants

– Access to cheap capital

– Greater consolidation among franchisees

– Increase in shareholder activism

– Potentially a safe-haven for long-term capital with restaurants largely insulated from seismic changes in retail

85

Source: Company data, Media reports, Credit Suisse estimates

Select M&A Restaurant Deals Date Acquirer Target Deal Size ($MM) LTM EV/EBITDA

QSR/Fast Casual

2018 Durational Capital / The Jordan Company Bojangles' $715 9.9x

2018 Roark Capital/Inspire Brands Sonic Drive-In $2,300 15.7x

2018 CAVA Group Zoe's Kitchen $300 16.4x

2018 The Coca-Cola Company Costa $5,100 16.4x

2018 Butterfly Equity Modern Market

2018 Spice Private Equity Bravo Brio $100 3.8x

2017 Apollo Global Management, LLC Qdoba $305.0 5.9x

2017 JAB Panera $7,500 18.3x

2017 QSR Popeyes $1,800 20.8x

2016 JAB Krispy Kreme $1,340 18.3x

2014 Burger King Worldwide Inc./QSR Tim Hortons $11,900 14.6x

2014 JAB Einstein Noah Restaurant Group Inc $465 9.9x

2013 Roark Capital CKE Restaurants, Inc. $1,640 - $1,750

2012 JAB Caribou Coffee Company $311 11.5x

2012 Starbucks Teavana $620 17.3x

2012 JAB Peets Coffee & Tea, Inc. $949 21.0x

2011 Roark Capital/Inspire Brands Arby's Restaurants - Sub of Wendy's $430 9.0x

2010 3G Capital Burger King Holdings, Inc. $4,000 9.0x

2010 Mill Road Capital Rubio's Restaurant $83 6.3x

2010 Apollo Global Management CKE Restaurants, Inc. $1,005 6.0x

Casual Dining

2018 TriArtisan Capital Partners and Paulson & Co. P.F. Chang's Inc. $700

2018 Del Frisco's Barteca $362 17.6x

2018 Rhône Capital Fogo de Chão $560 10.2x

2018 Roark Capital/Arby's Restaurant Group Buffalo Wild Wings $2,900 10.3x

2017 NRD Capital Ruby Tuesday $335 7.9x

2017 Darden Cheddar's $780 10.4x

2017 Golden Gate Capital Bob Evans Farms $610 15.4x

2014 Sentinel Capital Partners TGI Fridays $800

2014 Golden Gate Private Equity Red Lobster/Darden $2,100 9.0x

2014 Apollo Global Management CEC Entertainment $1,300 7.7x

2012 Darden Yard House $585 14.2x

2012 Centerbridge Partners PF Chang's $1,124 8.6x

2011 Golden Gate Capital California Pizza Kitchen (CPK) $470 6.6x

86

Potential M&A Target Dunkin’ Brands (DNKN) DNKN has been discussed as a potential acquisition target for several years given its attractive

business model and growth opportunities

Potential Scenarios include:

JAB Holding – most frequently cited potential acquirer given its growing portfolio of coffee and bakery businesses and media reports on previous discussions between the two parties

– DNKN could be a good fit for JAB’s global coffee portfolio, but we believe DNKN’s CPG business could be a major hurdle for the deal (relationship with J.M. Smucker and profit sharing agreement with franchisees)

Roark Capital/Inspire Brands – seeking to grow its portfolio of restaurant brands and DNKN could be complementary with limited competitive overlap to existing brands

Private Equity Consortium – conglomerate of PE firms could partner in deal; similar to 2006 DNKN acquisition by Bain Capital/Carlyle Group/Thomas H. Lee Partners

3G/Restaurant Brands International – 100% franchised business model and global presence could fit well in RBI portfolio; significant competitive overlap with Tim Hortons

Coca-Cola – potential for company to enter coffee market given recent acquisition of Costa, but has strong relationship with McDonald’s

PepsiCo – could consider bid into coffee market, but has strong partnership with Starbucks

Nestlé – company involved in coffee market, but has strong partnership with Starbucks

87

Potential M&A Target Papa John’s (PZZA)

PZZA has been discussed as a potential acquisition target for several years, which was amplified following reports PZZA was seeking a buyer given challenges following negative publicity and resulting sales declines

– At a market cap of ~$1.5BN, deal would likely be attainable for a large number of buyers


Restaurant Brands International – complementary fit (pizza segment, heavily franchised, global presence); RBI could leverage PZZA’s digital/delivery infrastructure and has experience with integrating brands and operating commissaries/distribution centers; PZZA could benefit from economies of scale and international network

Yum! Brands – Papa John’s has significant overlap with Pizza Hut, so not an obvious complement to YUM’s portfolio; PZZA’s franchised mix is below YUM’s target and PZZA operates distribution centers

Wendy’s – press reports stated Wendy’s was in preliminary discussions with Papa John’s regarding a merger, but talks cooled

Roark Capital/Inspire Brands - seeking to grow its portfolio of restaurant brands & PZZA could be complementary with limited competitive overlap to existing brands; relatively small market cap aligns with size of current portfolio

John Schnatter – founder and former CEO owns ~18% of PZZA; previous reports indicated Schnatter was seeking to partner with PE firms as a takeover (has since reduced his stake)

Private Equity – Given PZZA’s relatively small market cap, makes deal attainable for a number of well capitalized buyers

88

Potential M&A Target Jack in the Box (JACK)

JACK was seeking a range of strategic and financing alternatives, including a sale of the company

– At a market cap of ~$2BN and with ~$1BN of debt, JACK is relatively small and likely attainable for a number of potential buyers


Yum! Brands – JACK could be complementary as a burger concept with limited competitive overlap in the existing portfolio and ~95% franchised mix; JACK could benefit from YUM’s economies of scale and development expertise

Restaurant Brands International – Jack in the Box faces significant overlap with Burger King, so not an obvious complement to RBI’s portfolio; ~95% franchised, but geographically concentrated and lacks international presence

Roark Capital/Inspire Brands – seeking to grow its portfolio of restaurant brands; Sonic and Jack in the Box have competitive overlap, but could generate synergies from competing brands and there are differences between the two geographically concentrated burger concepts

Apollo – purchased Qdoba in a deal closed March 2018; working relationship through transition and possible JACK could tap Apollo as part of its process in seeking strategic and financing alternatives

Private Equity – given JACK’s relatively small market cap, makes a deal attainable for a number of well capitalized buyers

89

Potential M&A Acquirer Restaurant Brands International (QSR)

QSR has history of M&A and has indicated it will be opportunistic with M&A

– At ~5x levered currently and the company delevers ~0.5x per year naturally, QSR likely has room to lever up (has gone up to ~7x in the past)

– We believe QSR seeks brands with a long history and significant runway for LT global growth

Potential Targets include:

Papa John’s – complementary fit (pizza segment, heavily franchised, global presence); QSR could leverage PZZA’s digital/delivery infrastructure and has experience with integrating brands and operating commissaries/distribution centers; PZZA could benefit from economies of scale and international network

Domino’s – press reports have cited Domino’s as a potential target of QSR, as DPZ’s international master franchisees and industry-leading digital/delivery capabilities could be complementary to QSR; but DPZ has high leverage, trades at a rich valuation and no obvious G&A opportunities

Little Caesars – third largest pizza chain in the US with ~$4BN in system sales and ~4,350 units in the US and ~1,000+ locations internationally

Dunkin’ –DNKN’s 100% franchised business model and global presence could fit well in RBI portfolio; significant competitive overlap with Tim Hortons

Wingstop – WING is ~98% franchised and at a ~$2BN market cap, likely attainable; WING’s chicken-based menu overlaps with Popeyes, so may not be as complementary

Taco Bell – QSR could view Taco Bell as attractive, which would be complementary to QSR’s existing portfolio

90

Unit Growth

25%

26%

27%

28%

29%

30%

31%

32%

33%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Top 5

00 a

s %

of

Indust

ry U

nits

Top 5

00 C

hain

s U

nit

Gro

wth

Top 500 Chains Unit Growth Top 500 as % of Industry Units

91

Source: Technomic, Credit Suisse estimates

US restaurant growth moderating, with large chains gaining share

Restaurant industry growth has averaged ~0.5% over the last 15 years, with limited service restaurants (QSRs and fast casual) outpacing full service restaurants

Large chains are gaining share, with the largest 500 restaurant chains exhibiting average growth of ~2% over the last 15 years representing ~33% of industry units

Unit growth has decelerated, with 2018’s 0.7% unit growth among the largest 500 chains the lowest in eight years

Top 500 Restaurants Unit Growth Restaurant Industry Unit Growth

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Rest

aura

nt

Indust

ry U

nit

Gro

wth

Total Restaurants Limited Service Restaurants Full Service Restaurants

92


US unit growth decelerating across all major segments

Slowing expansion among the top 500 restaurant chains highlights importance of driving growth within existing base

– Unit growth contributed ~20% to sales growth in 2018, the lowest in the history of our data set

Among the top 500 chains, all segments are demonstrating decelerating unit growth, with 2018 unit growth below the 5-yr average

Top 500 Restaurants Unit Growth by Segment Top 500 Restaurants Sales Growth (Unit Growth + SSS & Other)

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18S

ale

s G

row

th -

Top 5

00 R

est

aura

nts

Unit Growth SSS & Other

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

Burgers Pizza Coffee Chicken Mexican

Unti

Gro

wth

-Top 5

00 R

est

aura

nts

5-yr Avg Unit Growth 2018 Unit Growth

93


Mixed Unit Growth Dynamics Across Cuisine Segments

Segment leaders are largely gaining share as they outpace unit growth relative to other large chains in the segment

– Domino’s, Starbucks, Chick-fil-A & Taco Bell demonstrated higher unit growth relative to other large chains

But the 5 largest chains are not necessarily gaining share collectively

– Pizza Hut and KFC have offset pizza and chicken segment growth, respectively, with net closures

2018 Unit Growth – Top 5 Chains & Top 500 Chains in Segment 2018 Unit Growth – Segment Leader & Top 500 Chains in Segment

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%


2018 U

nit

Gro

wth

Top 5 Chains in Segment Top 500 Chains in Segment

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

McDonald's Domino's Starbucks Chick-fil-A Taco Bell


2018 U

nit

Gro

wth

Segment Sales Leader Top 500 Chains in Segment

94


Assessing Segment Dynamics – Room For Growth vs Market Share Battle

Burgers are the largest and most penetrated category, with ~$85BN of sales

– Large chains (35 concepts) comprise 95%+ of segment sales (top 5 ~80% of sales)

Pizza’s ~$43BN segment is highly fragmented, with the five largest chains making up <50% of segment sales, highlighting room for market share gains among the large chains

Coffee, Chicken and Mexican Restaurant segments are relatively small and attractive categories, reflecting mid- to high-single-digit growth

5-yr Sales CAGR by Segment Market Share by Segment

$66BN

$19BN$30BN

$18BN $21BN $18BN

$82BN

$26BN

$31BN

$24BN$27BN

$20BN

$85BN

$43BN

$33BN $31BN $29BN$24BN

Burgers Pizza Coffee Sandwich Chicken Mexican

Small Chains &

Independents

Top 500 Chains

Top 5 Chains

2.7%

4.3%

7.5%

2.0%

8.0%

6.4%

2.6%

4.1%

7.9%

1.8%

8.4%

6.3%

Burgers Pizza Coffee Sandwich Chicken Mexican

Total Segment Large Chains in Segment

95


Unit Growth Highest Among Less Penetrated Segments (Coffee, Mexican and Chicken)

The burger segment has ~49K units, with ~90% units concentrated with the larger chains

– Burger segment is already very penetrated, with unit growth likely more difficult than other segments

The pizza segment is one of the largest, with relatively low unit growth – expansion is largely a market share battle

– Pizza segment is also the most fragmented, with opportunities for chains to grow at the expense of small chains & independents

Coffee, Mexican Restaurants and Chicken segments are the smallest by units and growing the fastest

5-yr Unit CAGR by Segment Units by Segment

33.6K

22.3K32.9K

25.5K

11.1K 10.5K

39.2K

30.4K

44.4K

26.5K

13.4K 15.3K

64.0K 62.0K

48.7K

38.5K

25.4K

19.2K

Sandwich Pizza Burgers Coffee Mexican Chicken

Small Chains &

Independents

Top 500 Chains

Top 5 Chains

0.4% 0.5%0.7%

3.9%

2.4%

3.0%

0.4%

1.2%0.8%

4.9%

3.6%3.3%

Sandwich Pizza Burgers Coffee Mexican Chicken

Total Segment Large Chains in Segment

96

Source: Technomic, Thinknum, Credit Suisse estimates

Burger Segment Sales Share

Burger Segment Unit Overlap

The burger segment is the most concentrated

segment in the restaurant industry, with the top 5 mature burger players generating 78% of segment sales and the largest chains (35 brands) making up 97% of segment sales

Given significant concentration, notable

geographic overlap leading to an already saturated market, and limited unit growth among the mature names in recent years, we expect burger segment unit growth to remain approx. flat, with a focus on market share gains Note: Read starting from left column. Within a 3 mile radius, 77% of

McDonald’s store base competes with Burger King. For comparison,

95% of Burger King’s store base competes with McDonald’s.

Burger Segment Most Concentrated

78%

71%

90%

79%

72%

64%

59%

65%

45%

97%

92%

92%

90%

84%

77%

75%

69%

60%

0% 20% 40% 60% 80% 100%

Burgers

Chicken

Coffee

Bakery Café

Mexican

Sandwich

Frozen Desserts

Asian/Noodle

Pizza

Sales Composition by Segment

Top 5 Chains Other Large Chains Small Chains & Independents

% Exposure to Select Burger Chains (3 miles)

McDonald's Burger King Wendy's Sonic Jack in the Box

McDonald's 69% 77% 72% 39% 24%

Burger King 95% 55% 76% 41% 22%

Wendy's 97% 84% 50% 44% 19%

Sonic 89% 70% 67% 39% 28%

Jack in the Box 98% 87% 76% 52% 75%

97% of Wendy’s store base competes with McDonald’s within a 3 mile radius

97


Burger Segment Growth

Fast Casual Burgers vs QSR Burgers Unit Growth

Fast casual burgers generated outsized sales and unit growth relative to the overall burger segment in 2018

Fast Casual Burgers represent just 7% of units highlighting limited competitive impact, though do contribute a notable 65% to burger segment unit growth

Fast Casual Burgers Growing, But Still Limited Threat

12.2%

5.6%

2.4%

0.6%

2.7%

0.9%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

Sales Growth Unit Growth

Fast Casual Burger Chains Top 500 Burger Chains Total Burger Segment

Fast casual burger

sales & unit growth

are outpacing the

overall segment

7%

65%

93%

35%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% Units % Unit Growth Contribution

Fast Casual Burgers QSR Burgers

98

Source: Technomic, Thinknum, Credit Suisse estimates

Pizza Segment Sales Share

Pizza Segment Unit Overlap

Pizza Segment Most Fragmented

The pizza segment is the most fragmented segment across the industry, with <50% of sales generated by the largest five pizza chains

Overlap among the larger chains vary, with smaller independents likely representing a greater impact on pizza than other segments

78%

71%

90%

79%

72%

64%

59%

65%

45%

97%

92%

92%

90%

84%

77%

75%

69%

60%

0% 20% 40% 60% 80% 100%

Burgers

Chicken

Coffee

Bakery Café

Mexican

Sandwich

Frozen Desserts

Asian/Noodle

Pizza

Sales Composition by Segment

Top 5 Chains Other Large Chains Small Chains & Independents


Domino's 35% 72% 61%

Pizza Hut 64% 42% 48%

Papa John's 90% 80% 28%

% Exposure to Select Pizza Chains (3 miles)

Note: Read starting from left column. Within a 3 mile radius, 72% of

Domino’s store base competes with Pizza Hut. For comparison, 64% of Pizza Hut’s store base competes with Domino’s.

90% of Papa John’s store base competes with Domino’s within a 3 mile radius

99


Delivery Not New In Pizza Segment

Delivery represented ~27% of QSR pizza segment sales in 2018, down from ~37% in 2002

Despite the emergence of complementary technologies that help smaller chains and independents compete in the digital & delivery space, we expect intra-segment trends to remain largely stable

– Economics of delivery will remain challenging and we expect larger scale players that have well established infrastructures will continue to gain share

– Top 3 competitors represent 56% of the US QSR pizza delivery segment, up from 46% in 2006

US QSR Pizza Delivery Segment Market Share US QSR Pizza Segment Channel Sales Composition

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

% Q

SR

Pizza

Segm

ent

Sale

s

Dine-In

Carry Out

Delivery

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

% Q

SR

Pizza

Deliv

ery

Share

Top 3 as % of Delivery Local & Independents

95%

77% 74%65% 61%

55% 55% 53% 52% 52% 51%

0%10%20%30%40%50%60%70%80%90%

100%

Jack

in t

he B

ox

Dunkin

'

Shake S

hack

Chip

otle

Sta

rbuck

s

RB

I

Papa J

ohn's

Wendy'

s

Dom

ino's

McD

onald

's

Yum

! B

rands

% o

f U

S U

nits

Top Market Top 3 Markets Top 5 Markets Top 10 Markets

63% 63% 62%60%

51%

43%40%

35%

13%

1% 0%0%

10%

20%

30%

40%

50%

60%

70%

McD

onald

's

Dom

ino's

Yum

! B

rands

RB

I

Sta

rbuck

s

Dunkin

' B

rands

Papa J

ohn's

Shake S

hack

Wendy'

s

Chip

otle

Jack

in t

he B

ox

Inte

rnatio

nal as

% o

f U

nits

100

Source: Company data, Franchise Disclosure Documents, Credit Suisse estimates

Concentration in Select States and Lack of International Presence Could Weigh on Growth Potential

Restaurants with greater geographic concentration face higher expansion risks in new markets given lower brand awareness, new market inefficiencies & increased exposure to challenges in these markets

Jack in the Box, Dunkin’ and Shake Shack have the highest US concentration risk, with >70% of their US portfolios concentrated in ten states (vs 63% average across our coverage)

Jack in the Box, Chipotle and Wendy’s have limited international exposure, with <15% of units outside of the US

International as % of Total Units US Unit Exposure

Note: (1) RBI (Restaurant Brands International) includes Burger King, Tim Hortons and

Popeyes; (2) Yum! Brands includes KFC, Taco Bell and Pizza Hut

101


International Supports Global Development Opportunity

Companies with an existing international presence are likely better positioned to execute against unit growth targets, with diversified unit growth reducing risk in specific markets

We have greater confidence in companies with master franchise partnerships, supporting increased visibility into the unit growth pipeline with well-capitalized franchisees

– Scale is important internationally as companies look to gain brand awareness and establish supply chains to enhance the economics

0%

10%

20%

30%

40%

50%

60%

70%

-

5,000

10,000

15,000

20,000

25,000

30,000

35,000

YU

M

MC

D

QS

R

SB

UX

DP

Z

DN

KN

PZ

ZA

WE

N

SH

AK

CM

G

JA

CK

% Inte

rnatio

nal

# Inte

rnatio

nal U

nits

# International Units % International

International is

meaningful part of growth algorithm

102

Source: Company data, Consensus Metrix, FactSet, Credit Suisse estimates

Consensus Expectations Imply Accelerating Unit Growth Among Public Chains Consensus expectations imply global unit growth acceleration of 4%+ over the next four years, an

acceleration from 3.7% over the last four years

– Estimates also imply acceleration each year over the next four years

Unit growth supports the sector’s growth profile and premium valuation

– Restaurants with higher unit growth outlooks often receive premium valuations

Restaurant Valuations by Unit Growth Consensus Unit Growth Expectations – Public Restaurant Chains

3.5%

3.7%3.8% 3.8%

3.9%

4.1% 4.2%

4.3%

3.0%

3.2%

3.4%

3.6%

3.8%

4.0%

4.2%

4.4%

4.6%

20

15

20

16

20

17

20

18

20

19E

20

20E

20

21E

20

22E

% U

nit

Gro

wth

10.5x

15.0x

18.0x

0.0x

2.0x

4.0x

6.0x

8.0x

10.0x

12.0x

14.0x

16.0x

18.0x

20.0x

0-2% Unit Growth 2-6% Unit Growth 6%+ Unit Growth

NTM

EV

/EB

ITD

A

Unit Growth (FY19-FY21)

103


Some Long-Term Unit Growth Targets Could Be Aggressive

Most companies have set long-term unit growth targets implying growth in-line or accelerating from recent history

Companies facing the highest execution risk are those that require acceleration from recent history and/or plan to largely expand into new markets

Consensus Estimates

5-yr Unit CAGR FY19E FY20E FY21E FY22E Long-Term Unit Growth Targets

McDonald's 1.3% 1.9% 2.1% 2.4% 2.0%

Restaurant Brands 4.9% 5.1% 5.7% 5.4% 5.9% 40K units over 8-10 years (implies 4.5-5.5% 8-10 yr CAGR)

Yum! Brands 3.1% 4.1% 4.1% 4.0% 4.1% ~4% per year

Wendy's 0.5% 1.5% 1.9% 2.3% 3.2% 1.5% in 2019 & 1.5-2.5% in 2020

Jack in the Box -0.1% 0.6% 1.0% 1.2% 1.4% Low-single digit unit growth

Domino's 7.9% 7.2% 6.9% 6.2% 6.3% 6-8% per year; 25K units by 2025 (implies 6.7% 7-yr CAGR)

Domestic 3.3% 4.5% 4.8% 4.1% 4.3% ~8,000 by 2025 (implies 4.5% 7-yr CAGR)

International 11.2% 8.8% 8.2% 7.4% 7.3% ~17,000 by 2025 (implies 7.8% 7-yr CAGR)

Papa John's 3.7% 2.7% 3.4% 2.4% 3.1%

Starbucks 8.2% 7.1% 6.9% 6.6% 6.4% 6-7% per year

Dunkin' Brands 2.9% 1.3% 1.5% 1.6% 2.0%

Dunkin' US 4.2% 2.2% 2.3% 2.4% 2.6% 200-250 units per year (implies 2-2.5% growth)

Chipotle 9.3% 5.7% 6.0% 6.0% 5.9% 5,000 unit potential

Shake Shack 39.1% 26.9% 23.9% 17.7% 17.4%

Domestic Company 42.6% 30.6% 25.3% 19.7% 17.3% 200+ units by 2020 (implies 27% 2-yr CAGR); 450 unit potential

Licensed 34.6% 21.4% 21.6% 15.3% 17.5% 120+ units by 2020 (implies 19.5% 2-yr CAGR)

JACK target implies meaningful

acceleration from

approx. flat growth over last decade

Consensus expectations for WEN imply notable acceleration from recent

history

Consensus estimates are at high end of

DNKN target, though recent step

down and growth targeted in new markets could be risk

Diversified global growth and expectations for global growth largely in-line with recent

history seems achievable (QSR, YUM, DPZ, SBUX)

104


We Prefer Companies with Diversified Growth Strategies – National, International & Formats

National Presence

– Shows brand acceptance across different regions, ability to earn sufficient returns across markets and ability to compete with local and regional brands

International Presence

– Shows ability to adapt menus and cost structures across different regions; increases future growth algorithm; mitigates impact of idiosyncratic challenges in specific markets; often asset-light growth strategy (US companies will often work with well-capitalized partners to grow internationally)

Diversified Real Estate Formats

– Increases unit potential, with ability to earn sufficient returns by adapting formats

– Examples: drive-thru lanes if insufficient room for parking; decrease unit size if lower volume unit

105


Exposure to Unit Growth

• Potentially underappreciated unit

growth at QSR from Tim Hortons and Popeyes supported by unique master franchise JV network

• Domestic and international

runway for SHAK

• Potential for accelerating unit

growth for CMG and increased domestic unit potential with new prototypes

• Robust global development at DPZ

with well-capitalized franchisees

• Global unit growth at YUM

supported by development agreements and increased focus on expansion

• Cautious on JACK US unit growth, with low-single-digit target implying acceleration from flat growth over the last decade

• Cautious on DNKN US following a step down from recent history, increased capital requirements for remodels and unit growth targeted in newer markets

• Cautious on WEN international growth as the company has largely failed to execute against unit targets over the last several years and limited international penetration

106

Emerging Themes

107

Source: Nielsen, Credit Suisse estimates

Plant-Based Protein Unlock Incremental Customers and Occasions

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

22.0%

Feb-1

4

May-

14

Aug-1

4

Nov-

14

Feb-1

5

May-

15

Aug-1

5

Nov-

15

Feb-1

6

May-

16

Aug-1

6

Nov-

16

Feb-1

7

May-

17

Aug-1

7

Nov-

17

Feb-1

8

May-

18

Aug-1

8

Nov-

18

Feb-1

9

May-

19

% o

f M

eat

Alte

rnativ

es

Channel

Plant-based protein is gaining traction with increasing presence in foodservice – opportunity to attract incremental customers & occasions

Emerging companies Beyond Burger and Impossible Foods offer products that mimic meat and largely targeted towards meat eaters

– Within retail channels (Nielsen), “All Other Manufacturers” (majority includes Beyond Burger and Impossible Foods) now represents nearly 20% of the category market share

Burger King is in the process of rolling out the Impossible Whopper nationwide, with early test results suggesting ~20% sales lifts (conservative illustration shows ~4.5% sales lift)

Impossible Whopper – Illustrative Example of Sales Lift All Other Manufacturers as % of Retail Meat Alternative Channel

Beyond Burger & Impossible

Foods make up majority% of “All Other Manufacturers” in Nielsen Meat Alternative Channel

Impossible Whopper Impact Per Store

Burge King US AUV ($000s) $1,400

# Daily Impossible Whoppers Sold 40

Price/Burger $6

Daily Impossible Whopper Sales $240

Annualized Impossible Whopper Sales ($000s) $86.4

% Incremental 75%

Incremental Sales ($000s) $64.8

% Sales Lift 4.6%

Impossible Whopper as % of Sales 4.4%

108

Source: FAA, DOT, WSJ, Uber, Credit Suisse estimates

Drone Delivery Testing Near-Term, But Challenges Exist

Most work on drone delivery is targeted to rural/non-urban areas and in countries outside of the US with less restrictive legal barriers

Significant legal and regulatory challenges to overcome before drone food delivery is possible, including, but not limited to:

– Drone must be in line of sight of the pilot at all times

– Pilot can only operate one drone at a time

– Drone cannot be operated over a non-participating person or moving vehicle

– Drones cannot be operated after dark

– Drones cannot be operated in select airspace

– Complex and potentially contradictory federal, state and local laws

Uber Air – Uber has commented that the company is planning to run limited tests of food delivery by drones, with hope to be commercially operational in multiple markets by 2021

– Plans to deploy autonomous drones in 2019 and begin testing urban drone deliveries for Uber Eats

109

Source: Central Market York, Credit Suisse estimates

Virtual Kitchens

Virtual Kitchens (also known as ghost or dark kitchens) are used to execute orders exclusively for delivery and pickup

Benefits: minimal upfront investment, lower operational costs, faster time to market, benefits from shared services, opportunities to test new markets without significant risk

New concept – restaurants without a physical presence could open a virtual kitchen to test markets or limit risk given much lower initial costs

New markets – existing concepts could use virtual kitchens to test demand in a market before opening a high cost freestanding store

Overflow – restaurants can use virtual kitchens to handle overflow of digital or delivery orders, alleviating challenges from changes in operations and increasing capacity

Third-party delivery companies can use data to determine demand for certain cuisines and in select markets, and partner with existing restaurants or feature pop-up shops without a need to make significant upfront investments

110

Source: Ford, General Motors, WSJ, Activ, Credit Suisse estimates

Autonomous Vehicles Could Be Here Quicker Than We Think

US Auto companies are partnering with third-party delivery partners and select restaurant concepts to test food delivery through autonomous vehicles

– Ford partnering with Postmates, Walmart and Domino’s

Targeted commercial launch in 2021

– General Motors and DoorDash piloting food and grocery delivery

– Toyota and Pizza Hut partnering to test autonomous vehicle concept

Toyota plans to start testing the vehicle as early as 2020

Aptiv and Lyft partnering with recent launch of 30 autonomous vehicles in Las Vegas (Sept 2018)

Waymo (Google) launched a commercial robotaxi service in Phoenix (Dec 2018)

Uber is testing self-driving vehicles

Apple is working on building an autonomous driving system, potentially in partnership with Tesla (recently laid off employees related to its self-driving car program initiative)

111

Recent transactions highlight the changing retail landscape and move to broaden omnichannel capabilities as traditional brick & mortar companies fear the risk from Amazon

– Recent examples include: Kroger/Home Chef, Costco/Blue Apron partnership, Albertsons/Plated, Amazon/Whole Foods, Walmart/Jet

We expect consolidation could continue as traditional brick & mortar grocery companies seek to expand digital reach and improve logistics, while meal kit companies look to reduce customer acquisition costs

But in-store meal kits eliminate the convenience of at-home delivery, could result in significant waste if limited sell-through, could be cannibalistic to the grocery stores and alters the meal kit provider’s previous subscription based revenue stream

Recent Deals Suggest Increased Focus On Alternative Channels, But Should Be Limited Impact


Timeline of Select Meal Kit Deals/Partnerships

May 2018: Kroger announces deal to

acquire Home Chef

September 2017: Albertsons announces

deal to acquire Plated

June 2017: Amazon announces deal to

acquire Whole Foods

August 2016: Walmart announces deal to

acquire Jet.com

April 2018: Blue Apron starts selling

meal kits in select Costco retail stores

112

Company Summaries

113


Chipotle Mexican Grill (CMG) Outperform, $870 TP Executive Summary Key Charts

• Credit Suisse View: CMG has returned to a narrative of

growth rather than recovery, with on-trend initiatives that well position the company to appeal to its target base and outperform peers. Contributions from traffic and average check growth should support mid-single-digit SSS longer-term and generate margin leverage to support an EPS

CAGR of 30%+ through 2022.

• Confidence in Top-Line Performance: CMG’s comprehensive sales plan and omni-channel strategy should generate mid-single-digit SSS. Our confidence in

ongoing momentum includes contributions from: 1) digital & delivery initiatives, with CMG well positioned with a younger consumer base, transportable food, and best-in-class

operations.; 2) new menu innovation; 3) improved social media and marketing strategy; and 4) customer data analytics. Improving new-unit productivity and the potential for alternative formats support mid-single-digit unit growth, with modest step-ups likely.

• Power of the Economic Model: CMG is the only publicly

traded restaurant company in quick serve/fast casual with a 100% company-owned model. A return to $2.4MM AUVs ($2MM currently) should generate restaurant-level margins

of ~24% by 2022 (18.7% in 2018) and new-unit returns of 70-80%.

Units & Unit Growth

Revenue & Revenue Growth

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

500

1,000

1,500

2,000

2,500

3,000

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

YO

Y G

row

th %

Units

Units YOY Growth %

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

$4,500

$5,000

$5,500

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

YO

Y G

row

th %

Reve

nue (

$M

M)

Revenue YOY Growth %

Current Price $726.85NTM EV/EBITDA 26.0xNTM P/E 53.0x52-wk Range $385.84-$740.59

Price Date: 6/21/2019

114


Chipotle Mexican Grill (CMG) Outperform, $870 TP Valuation & Risks Valuation History • Our $870 TP is based on:

— EV/EBITDA of 25x our NTM EBITDA in 12 months

— P/E of 46x our NTM EPS in 12 months

• Our EV/EBITDA multiple is largely in-line with CMG’s recent trading multiple

• Key risks: headline risk related to food safety incidents, increased competition, consumer spending deceleration and increased food and supply costs

3-yr Historical EV/EBITDA

3-yr Historical P/E

Credit Suisse Estimates vs Consensus 2018 1Q19 2Q19E 3Q19E 4Q19E 2019E 2020E 2021E

SSS 4.0% 9.9% 8.0% 7.5% 6.5% 8.0% 5.5% 5.5%

Consensus 4.0% 9.9% 8.2% 7.1% 5.5% 7.7% 5.3% 4.8%

Units 2,491 2,504 2,527 2,575 2,635 2,635 2,795 2,965

YOY % 3.4% 2.6% 2.4% 4.5% 5.8% 5.8% 6.1% 6.1%

Consensus 2,491 2,504 2,529 2,577 2,634 2,633 2,790 2,958

YOY % 3.4% 2.6% 2.5% 4.6% 5.7% 5.7% 6.0% 6.0%

Revenue ($MM) $4,865 $1,308 $1,400 $1,360 $1,368 $5,435 $6,053 $6,712

YOY % 8.7% 13.9% 10.5% 11.0% 11.7% 11.7% 11.4% 10.9%

Consensus ($MM) $4,865 $1,308 $1,406 $1,357 $1,352 $5,424 $6,038 $6,659

YOY % 8.7% 13.9% 11.0% 10.8% 10.4% 11.5% 11.3% 10.3%

Operating Margin 7.2% 9.0% 10.2% 8.9% 8.6% 9.2% 11.0% 12.4%

Consensus 7.2% 9.0% 10.1% 8.8% 7.6% 8.9% 10.4% 11.3%

EPS $8.88 $3.40 $3.80 $3.26 $3.15 $13.60 $17.89 $22.42

YOY % 34.6% 59.7% 32.2% 50.4% 83.1% 53.1% 31.5% 25.3%

Consensus $8.88 $3.40 $3.76 $3.16 $2.73 $13.05 $16.76 $20.46

YOY % 34.5% 59.6% 31.0% 46.3% 58.7% 47.0% 28.4% 22.1%

5.0x

10.0x

15.0x

20.0x

25.0x

30.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

EV

/EB

ITD

A


10.0x

20.0x

30.0x

40.0x

50.0x

60.0x

70.0x

80.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

P/E




115


Dunkin’ Brands Group (DNKN) Underperform, $70 TP Executive Summary Key Charts

• Credit Suisse View: DNKN is trading near peak valuation despite ongoing traffic and SSS challenges and lower

development targets. While we believe DNKN’s 100% franchised business model warrants a premium, DNKN’s multiple has moved in-line with heavily franchised peers despite higher peer multiples driven by business model transformations. We see downside risk to shares against

lower growth prospects and elevated valuation.

• Traffic A Show-Me Story: Traffic has been negative for 12 consecutive quarters (-2.7% in 2018) and a reversal in

trends seems unlikely near-term against competitive headwinds. Mixed brand positioning makes Dunkin’ more susceptible to competition from high- and low-end peers.

While initiatives around espresso, value, operations and digital are positives, we’re cautious on a sustainable

improvement in SSS given recent trends, competitive backdrop and execution concerns.

• Moderating Unit Growth: Following a 4.2% unit CAGR over the last five years, we expect growth of ~2.1% over

the next four, or ~200 units per year (LT guide 200-250 units). Given a primary focus on improving SSS, competitive headwinds, reduced growth in core markets, cost pressures

and increased capital needed for remodels, a more tempered unit growth strategy seems prudent.

Units by Segment

Operating Income by Segment

-

5,000

10,000

15,000

20,000

25,000

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Units

Dunkin' US Dunkin' International

Baskin-Robbins US Baskin-Robbins International

$0

$100

$200

$300

$400

$500

$600

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Opera

ting Inco

me (

$M

M)

Dunkin' US Dunkin' International

Baskin-Robbins US Baskin-Robbins International



116


Dunkin’ Brands Group (DNKN) Underperform, $70 TP Valuation & Risks Valuation History • Our $70 TP is based on:

— EV/EBITDA of 16x our NTM EBITDA in 12 months

— P/E of ~22x our NTM EPS in 12 months

• Our EV/EBITDA multiple is a ~0.5x turn premium to

DNKN’s 3-yr avg.

• Key risks include M&A, acceleration in traffic, SSS and unit growth, increased competition and debt/interest rates


3-yr Historical P/E

Credit Suisse Estimates vs Consensus

10.0x

11.0x

12.0x

13.0x

14.0x

15.0x

16.0x

17.0x

18.0x

19.0x

20.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

EV

/EB

ITD

A


16.0x

18.0x

20.0x

22.0x

24.0x

26.0x

28.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

P/E


2018 1Q19 2Q19E 3Q19E 4Q19E 2019E 2020E 2021E

Dunkin' US SSS 0.6% 2.4% 1.0% 1.0% 2.0% 1.6% 1.5% 1.5%

Consensus 0.6% 2.4% 1.3% 1.4% 1.9% 1.7% 1.6% 1.7%

Global Units 20,912 20,920 20,982 21,044 21,176 21,176 21,495 21,814

YOY % 1.9% 1.6% 1.4% 1.3% 1.3% 1.3% 1.5% 1.5%

Consensus 20,912 20,920 20,993 21,067 21,191 21,192 21,516 21,869

YOY % 1.9% 1.6% 1.5% 1.5% 1.3% 1.3% 1.5% 1.6%

System Sales Growth 4.4% 4.1% 2.9% 2.6% 3.7% 3.3% 3.2% 3.2%

Consensus 4.4% 4.1% 2.9% 2.9% 3.6% 3.3% 3.4% 3.7%

Revenue ($MM) $1,322 $319 $363 $361 $337 $1,379 $1,426 $1,472

YOY % 3.6% 5.9% 3.4% 3.0% 5.4% 4.4% 3.3% 3.3%

Consensus ($MM) $1,322 $319 $361 $358 $335 $1,373 $1,418 $1,468

YOY % 3.6% 5.9% 2.8% 2.4% 4.7% 3.9% 3.3% 3.6%


Consensus 32.9% 33.3% 34.6% 34.3% 33.1% 33.8% 34.2% 34.4%

EPS $2.90 $0.67 $0.82 $0.81 $0.68 $2.98 $3.16 $3.39

YOY % 40.2% 8.3% 6.4% -2.9% -0.4% 2.7% 6.3% 7.3%

Consensus $2.90 $0.67 $0.82 $0.81 $0.70 $3.00 $3.24 $3.51

YOY % 40.1% 8.1% 6.5% -2.4% 2.9% 3.4% 8.0% 8.3%



117


Domino’s Pizza (DPZ) Outperform, $320 TP Executive Summary Key Charts

• Credit Suisse View: DPZ is one of the best growth stories

in restaurants, with ~10% revenue growth (~4% SSS, ~7% unit growth), margin expansion and benefits from repurchases driving an EPS CAGR of ~15% over the next four years.

• SSS Outperformance: DPZ should maintain SSS momentum and share gains as one of the few companies with contribution from positive traffic, the only company with a frequency-based loyalty program, consistent value messaging, favorable franchisee relations (avg franchisee

~$975K EBITDA) and an industry-leading digital ecosystem supporting best-in-class execution.

• Third-Party Delivery as NT Pressure, But Not LT Issue: An increasing number of cross-branded campaigns with national QSR chains, competition for delivery drivers and aggressive promos represent incremental competitive pressure NT. LT, pizza’s stable 10-yr ~$10BN delivery market

share should largely hold, with pizza a cuisine that travels well and offers great value. Positioning as a delivery company could be a net positive for DPZ as delivery demand increases, while increased focus on carryout can drive incremental sales and help offset competitive pressures.

Revenue Composition

Unit Composition

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Reve

nue C

om

posi

tion

US Stores International Franchise Supply Chain

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Unit

Com

posi

tion

US Company US Franchise International Franchise



118


Domino’s Pizza (DPZ) Outperform, $320 TP Valuation & Risks Valuation History • Our $320 TP is based on:

— EV/EBITDA of ~20.5x our NTM EBITDA in 12 months


• Our EV/EBITDA multiple is in line with DPZ’s current multiple

• Key risks include increased competition, primarily from

third-party delivery, and reduced consumer spending if there is a deterioration in economic conditions


3-yr Historical P/E


12.0x

14.0x

16.0x

18.0x

20.0x

22.0x

24.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

EV

/EB

ITD

A


15.0x

20.0x

25.0x

30.0x

35.0x

40.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

P/E


2018 1Q19 2Q19E 3Q19E 4Q19E 2019E 2020E 2021E

Domestic SSS 6.6% 3.9% 5.4% 5.8% 6.4% 5.5% 5.0% 4.9%

Consensus 6.6% 3.9% 4.6% 4.9% 5.2% 4.7% 4.2% 4.2%

Global Units 15,914 16,114 16,306 16,568 17,100 17,100 18,328 19,556

YOY % 7.1% 7.7% 7.8% 7.9% 7.5% 7.5% 7.2% 6.7%

Consensus 15,914 16,114 16,305 16,548 17,055 17,061 18,244 19,378

YOY % 7.1% 7.7% 7.8% 7.8% 7.2% 7.2% 6.9% 6.2%

Revenue ($MM) $3,433 $836 $841 $844 $1,165 $3,686 $4,042 $4,386

YOY % 23.1% 6.4% 7.9% 7.3% 7.7% 7.4% 9.7% 8.5%

Consensus ($MM) $3,433 $836 $837 $850 $1,178 $3,701 $4,045 $4,423

YOY % 23.1% 6.4% 7.4% 8.1% 8.8% 7.8% 9.3% 9.3%


Consensus 16.7% 17.2% 16.7% 17.1% 17.4% 17.1% 17.5% 17.5%

EPS $8.42 $2.20 $2.08 $2.11 $3.07 $9.44 $11.10 $12.66

YOY % 42.4% 9.7% 12.6% 7.8% 17.2% 12.1% 17.6% 14.1%

Consensus $8.42 $2.20 $2.01 $2.12 $3.10 $9.42 $10.93 $12.45

YOY % 42.5% 10.0% 9.2% 8.7% 18.3% 11.9% 16.0% 13.9%



119


Jack in the Box (JACK) Underperform, $75 TP Executive Summary Key Charts

• Credit Suisse View: Despite JACK’s enhanced business model (~95% franchised, G&A management, leverage target ~5x), we see risks to LT targets which require acceleration in

top-line trends. With limited visibility into the drivers supporting a sustainable inflection in SSS and unit growth, and fewer levers to unlock value, JACK warrants a valuation discount relative to peers and recent history.

• Top-Line Acceleration Elusive: JACK has demonstrated challenged SSS averaging 0.2% over the last 10 quarters, including traffic of -3.5%, amidst a competitive environment

and company-specific execution. We do not see a clear strategy to reaccelerate traffic trends, with recent value initiatives nothing new and a short-term digital strategy. Unit growth has been flat for nearly a decade, and we are not convinced JACK can meaningfully accelerate given franchisee

tension, investment requirements & margin pressures. We model below-target system sales of ~2%, incl. SSS of 1.5% (3-yr avg 0.6%) & unit growth of 0.7% (3-yr avg -0.2%).

• Cautious on Achievability of Long-Term Targets: We are

cautious on the achievability of FY22 EBITDA (~$300MM) and FCF (~$175MM) targets, which imply SSS and unit growth acceleration to ~3.5-4% from ~1% over the last three years. Visibility into execution against G&A and capex targets is high.

Unit Composition

Revenue by Source

-

500

1,000

1,500

2,000

2,500

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

Units

Company-operated Franchise

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

Reve

nue (

$M

M)

Sales Franchise royalty revenue & fees Franchise rental income



120


Jack in the Box (JACK) Underperform, $75 TP Valuation & Risks Valuation History • Our $75 TP is based on:

— EV/EBITDA of ~11x our NTM EBITDA in 12 months


• Our EV/EBITDA multiple reflects a discount to JACK’s 3-yr avg and current multiple of ~12x

• Key risks include: M&A; acceleration in SSS


3-yr Historical P/E

Credit Suisse Estimates vs Consensus 2018 1Q19 2Q19 3Q19E 4Q19E 2019E 2020E 2021E

SSS 0.1% -0.1% 0.2% 1.5% 1.5% 0.7% 1.5% 1.5%

Consensus 0.1% -0.1% 0.2% 1.8% 1.5% 0.8% 1.7% 1.8%

Global Units 2,237 2,241 2,240 2,245 2,250 2,250 2,266 2,282

YOY % -0.6% -0.4% -0.2% 0.2% 0.6% 0.6% 0.7% 0.7%

Consensus 2,237 2,241 2,240 2,245 2,251 2,251 2,274 2,301

YOY % -0.6% -0.4% -0.2% 0.2% 0.6% 0.6% 1.0% 1.2%

Revenue ($MM) $870 $291 $216 $219 $220 $946 $964 $1,005

YOY % -20.7% -15.3% -12.1% 16.7% 23.2% 8.8% 1.9% 4.3%

Consensus ($MM) $870 $291 $216 $221 $220 $947 $967 $1,002

YOY % -20.7% -1.2% 2.8% 17.4% 23.8% 8.9% 2.1% 3.6%


Consensus 30.4% 28.6% 28.4% 28.4% 26.9% 28.1% 28.3% 28.5%

EPS Excl. Gains $3.91 $1.35 $0.99 $0.97 $0.93 $4.26 $4.46 $5.03

YOY % 13.0% 9.9% 27.4% -3.0% 13.1% 9.0% 4.7% 12.8%

Consensus $3.79 $1.35 $0.99 $1.02 $0.91 $4.28 $4.78 $5.49

YOY % #VALUE! -6.2% 6.5% -41.7% 5.8% 12.9% 11.7% 14.9%

8.0x

9.0x

10.0x

11.0x

12.0x

13.0x

14.0x

15.0x

Jun-1

6

Aug-1

6

Oct

-16

Dec-

16

Feb-1

7

Apr-

17

Jun-1

7

Aug-1

7

Oct

-17

Dec-

17

Feb-1

8

Apr-

18

Jun-1

8

Aug-1

8

Oct

-18

Dec-

18

Feb-1

9

Apr-

19

Jun-1

9

EV

/EB

ITD

A


16.0x

17.0x

18.0x

19.0x

20.0x

21.0x

22.0x

23.0x

Jun-1

6

Aug-1

6

Oct

-16

Dec-

16

Feb-1

7

Apr-

17

Jun-1

7

Aug-1

7

Oct

-17

Dec-

17

Feb-1

8

Apr-

18

Jun-1

8

Aug-1

8

Oct

-18

Dec-

18

Feb-1

9

Apr-

19

Jun-1

9

P/E




121


McDonald’s (MCD) Outperform, $230 TP Executive Summary Key Charts

• Credit Suisse View: Recent asset and technology investments support a more modernized MCD, and we believe the company is effectively expanding its competitive

moat relative to peers. SSS represent the greatest source of upside to shares, with MCD’s slate of on-trend sales initiatives supporting outperformance. Healthy SSS, defensive characteristics & transition to ~95% franchised support the current premium valuation.

• US Sales Outperformance to Continue: Sales initiatives

are starting to gain traction, and should drive SSS of 4.5%

in 2019 and ~3% LT. We expect momentum to continue with contributions from: 1) delivery (new terms with Uber Eats); 2) digital (recent acq. of Dynamic Yield); 3) Experience of the Future (EOTF) as a net positive; 4) an improved value strategy with a shift to more localized

marketing; and 5) a return to breakfast share gains with local value & service time improvements.

• Digital Supports Future Gains: MCD’s recent tech investments suggest a long-term strategy to develop an

integrated digital infrastructure. With the acquisition of Dynamic Yield, MCD has unlocked access to innovative tech & talent, customer data, & incremental revenue channels over time.

Unit Composition

System Sales by Segment

-

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Units

US International Lead Markets

High Growth Markets Foundational Markets & Corporate

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Sys

tem

Sale

s ($

MM

)

US International Lead Markets

High Growth Markets Foundational Markets & Corporate



122


McDonald’s (MCD) Outperform, $230 TP Valuation & Risks Valuation History • Our $230 TP is based on:


— Implies a P/E of ~26x our NTM EPS in 12 months

• Our EV/EBITDA multiple is in line with MCD’s current multiple and a premium to its 3-yr avg of ~14.5x

• Key risks include increased competition, changes in consumer spending and FX volatility


3-yr Historical P/E


US SSS 2.5% 4.5% 4.5% 4.5% 4.5% 4.5% 3.5% 3.0%

Consensus 2.5% 4.5% 4.0% 4.1% 4.1% 4.2% 3.1% 2.8%

Global Units 37,855 37,971 38,136 38,301 38,576 38,576 39,376 40,296

YOY % 1.6% 1.8% 2.0% 2.0% 1.9% 1.9% 2.1% 2.3%

Consensus 37,855 37,971 38,129 38,300 38,563 38,565 39,368 40,341

YOY % 1.6% 1.8% 1.9% 2.0% 1.9% 1.9% 2.1% 2.5%

Revenue ($MM) $21,025 $4,956 $5,317 $5,458 $5,311 $21,042 $21,614 $22,186

YOY % -7.9% -3.6% -0.7% 1.6% 2.9% 0.1% 2.7% 2.6%

Consensus ($MM) $21,025 $4,956 $5,320 $6,868 $5,292 $21,022 $21,470 $22,095

YOY % -7.9% -3.6% -0.6% 27.9% 2.5% 0.0% 2.1% 2.9%


Consensus 43.1% 42.3% 44.1% 45.7% 43.1% 43.9% 45.3% 46.4%

EPS $7.90 $1.72 $2.06 $2.22 $2.03 $8.03 $8.74 $9.45

YOY % 18.9% -3.7% 3.5% 2.7% 3.3% 1.6% 8.8% 8.1%

Consensus $7.90 $1.72 $2.05 $2.21 $2.02 $7.99 $8.67 $9.37

YOY % 19.2% -3.9% 3.0% 2.3% 2.5% 1.1% 8.5% 8.1%

10.0x

11.0x

12.0x

13.0x

14.0x

15.0x

16.0x

17.0x

18.0x

19.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

EV

/EB

ITD

A


16.0x

18.0x

20.0x

22.0x

24.0x

26.0x

28.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

P/E




123


Papa John’s International (PZZA) Neutral, $45 TP Executive Summary Key Charts

• Credit Suisse View: PZZA is trading at a ~16x EV/EBITDA multiple without signs of a sustainable inflection in trends and high execution risk. PZZA recently announced intentions to invest $80MM through 2020 in the form of marketing and

franchisee royalty relief, suggesting the company is still facing consumer sentiment challenges and franchisee pressure is building. While we see risk to numbers and the multiple, short interest of ~30% of float (8 days to cover), activist involvement and takeout potential keep us Neutral.

• Catalysts Supporting Potential Upside: Starboard’s

investment, board changes, cultural initiatives, a new CMO

and the partnership with Shaquille O’Neal could gain traction faster than expected. Initiatives around marketing and value could be meaningful, with both lacking even prior to brand challenges. PZZA has also been cited as a potential acquisition target.

• Cautious on Execution: Consumer sentiment challenges

continue to weigh on sales trends and franchisee profitability. PZZA is investing $80MM to provide financial assistance to franchisees and increase marketing support through 2020.

We anticipate PZZA will use debt to fund the investment, further pressuring earnings. We’re cautious on the outlook given heightened competition, lack of effective value messaging and a challenging cost environment exacerbated by declining sales, with risk of elevated franchisee closures.

Unit Composition

System Sales

-

1,000

2,000

3,000

4,000

5,000

6,000

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Units

Company North America Franchise International Franchise

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

$4,500

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Sys

tem

Sale

s ($

MM

)

Domestic International



124


Papa John’s International (PZZA) Neutral, $45 TP Valuation & Risks Valuation History • Our $45 TP is based on:

— EV/EBITDA of ~13.2x our NTM EBITDA in 12 months


• Our EV/EBITDA multiple is a discount to PZZA’s 5-yr avg and current multiple given ongoing uncertainty regarding the

long-term outlook

• Key risks include: M&A, short squeeze, increased

competition, consumer sentiment challenges


5-yr Historical P/E


North America SSS -7.3% -6.9% -5.6% -1.5% -0.5% -3.6% 1.4% 2.0%

Consensus -7.3% -6.9% -5.8% -1.6% 0.9% -3.3% 2.2% 2.2%

Global Units 5,303 5,336 5,352 5,388 5,434 5,434 5,606 5,790

YOY % 2.0% 2.4% 2.0% 2.7% 2.5% 2.5% 3.2% 3.3%

Consensus 5,303 5,336 5,355 5,381 5,445 5,445 5,628 5,762

YOY % 2.0% 2.4% 2.1% 2.6% 2.7% 2.7% 3.4% 2.4%

Revenue ($MM) $1,611 $403 $392 $386 $401 $1,582 $1,609 $1,652

YOY % -9.6% -10.4% -4.0% 3.2% 5.6% -1.8% 1.7% 2.7%

Consensus ($MM) $1,573 $398 $392 $380 $398 $1,569 $1,621 $1,656

YOY % -11.8% -6.8% -3.9% 4.5% 6.4% -0.3% 3.3% 2.2%


Consensus 5.2% 5.4% 5.1% 4.1% 5.1% 4.9% 5.8% 4.4%

EPS $1.38 $0.31 $0.32 $0.16 $0.29 $1.08 $1.31 $1.55

YOY % -48.5% -41.9% -34.7% -17.5% 96.2% -21.7% 21.5% 18.1%

Consensus $1.34 $0.31 $0.29 $0.20 $0.36 $1.16 $1.69

YOY % -49.8% -38.0% -40.8% 0.0% 140.0% -13.4% 45.7% -100.0%

8.0x

10.0x

12.0x

14.0x

16.0x

18.0x

20.0x

Jun-14 Jun-15 Jun-16 Jun-17 Jun-18 Jun-19

EV

/EB

ITD

A


15.0x

20.0x

25.0x

30.0x

35.0x

40.0x

45.0x


P/E




125


Restaurant Brands International (QSR) Outperform, $78 TP Executive Summary Key Charts

• Credit Suisse View: RBI is well positioned to generate

global market share gains across its portfolio with contribution from SSS and unit growth. Increased confidence in accelerating SSS and sustainable global unit growth across the portfolio should support multiple expansion. We model EPS growth in the high-single-digits, with SSS

outperformance, TH unit growth acceleration & TH margin expansion as opportunities for upside.

• RBI Well Positioned In Home Markets: BK has plans to roll out the Impossible Whopper nationwide by the end of

2019, which could contribute at least ~460bps to US SSS (assumes 40 units sold per day per store). Digital enhancements and menu innovation support confidence in

momentum at Tim Hortons Canada (~50% customers on loyalty and Beyond sausage expected to rollout system-wide).

• Global Unit Growth Story Intact: We expect RBI to generate global unit growth of ~5.5% over the next four

years, an acceleration from ~5.2% over the past four years. International master franchise joint venture (MFJV) agreements offer confidence in the achievability of targets, largely driven by global strength at BK and whitespace potential for Popeyes in a growing chicken category. Better-

than-expected growth at TH could represent upside.

Units by Segment

EBITDA by Segment

4.4K 4.6K 4.7K 4.8K

15.0K 15.7K 16.8K 17.8K

2.9K3.1K

19.4K20.4K

24.4K25.7K

0.0K

5.0K

10.0K

15.0K

20.0K

25.0K

30.0K

2015 2016 2017 2018

Glo

bal U

nit

Count

Tim Hortons Burger King Popeyes

$906 $1,072 $1,136 $1,128

$760

$816 $903 $930

$107 $155

$0

$500

$1,000

$1,500

$2,000

$2,500

2015 2016 2017 2018

EB

ITD

A (

$M

M)

Tim Hortons Burger King Popeyes



126


Restaurant Brands International (QSR) Outperform, $78 TP Valuation & Risks Valuation History • Our $78 TP is based on:


— P/E of ~25.5x our NTM EPS in 12 months

• Our EV/EBITDA multiple reflects multiple expansion, with expectations for a return to a valuation premium relative to

heavily franchised peers

• Key risks: include increased competition, changes in

consumer spending and FX volatility


3-yr Historical P/E


12.0x

13.0x

14.0x

15.0x

16.0x

17.0x

18.0x

19.0x

20.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

EV

/EB

ITD

A


15.0x

17.0x

19.0x

21.0x

23.0x

25.0x

27.0x

29.0x

31.0x

33.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

P/E


2018 1Q19 2Q19E 3Q19E 4Q19E 2019E 2020E 2021E

BK Global SSS 2.0% 2.2% 2.5% 3.0% 3.0% 2.7% 2.5% 2.5% Consensus 2.0% 2.2% 2.3% 2.6% 2.4% 2.3% 2.2% 2.2%TH Global SSS 0.6% -0.6% 1.1% 1.6% 1.2% 0.9% 1.6% 1.8% Consensus 0.6% -0.6% 1.2% 1.4% 1.0% 0.8% 1.5% 1.7%PLK Global SSS 1.6% 0.6% 0.8% 1.8% 2.2% 1.4% 1.7% 1.8% Consensus 1.6% 0.6% 0.8% 1.7% 1.9% 1.3% 1.7% 1.9%

Global Units 25,744 25,809 26,079 26,419 27,094 27,094 28,614 30,194 YOY % 5.5% 5.1% 5.2% 5.4% 5.2% 5.2% 5.6% 5.5% Consensus 25,744 25,809 26,080 26,404 27,063 27,063 28,597 30,136 YOY % 5.5% 5.1% 5.2% 5.3% 5.1% 5.1% 5.7% 5.4%

Revenue ($MM) $5,358 $1,266 $1,390 $1,456 $1,467 $5,579 $5,882 $6,196 YOY % 17.1% 1.0% 3.4% 5.9% 5.9% 4.1% 5.4% 5.3% Consensus ($MM) $5,357 $1,266 $1,392 $1,451 $1,467 $5,578 $5,869 $6,149 YOY % 17.1% 1.0% 3.6% 5.5% 5.9% 4.1% 5.2% 4.8%

Operating Margin 37.5% 34.4% 37.7% 37.7% 37.7% 37.0% 38.0% 38.5% Consensus 37.5% 34.4% 37.7% 38.0% 38.6% 37.3% 38.3% 38.9%

EPS $2.63 $0.55 $0.68 $0.72 $0.75 $2.70 $2.99 $3.29 YOY % 25.2% -17.4% 3.3% 15.4% 9.9% 2.6% 11.0% 9.9% Consensus $2.63 $0.55 $0.67 $0.71 $0.74 $2.68 $2.97 $3.24 YOY % 25.2% -16.7% 1.5% 12.7% 8.8% 1.9% 10.8% 9.1%



127


Shake Shack (SHAK) Outperform, $77 TP Executive Summary Key Charts

• Credit Suisse View: Brand affinity and on-trend initiatives

support demand, while strong unit economics (returns ~50%) and demonstrated success across markets offer confidence in the whitespace potential. Sustained new unit productivity, timing of opens, SSS and unit growth represent upside potential. Growth in penetrated markets should help the

company leverage costs and increase efficiency over time.

• Growing Pains: Traffic and SSS likely remain volatile NT, but should stabilize as the growth rate decelerates, the comp base comprises a greater percentage of the system and

impact of indirect cannibalization (reduced exclusivity) dissipates. While SSS have limited impact on the model (1% SSS = $4.5MM revs), a return to more normalized SSS

should improve sentiment given limited visibility into the underlying portfolio with a range of volumes across markets, sophomore class unit declines (5% on average) and units entering the comp base in year 3.

• Margin Outlook Difficult, But Opportunities Exist: We expect restaurant margins to contract another 130-230bps in 2019, following 350bps of decline since 2015. While we model ~10-20bps of ongoing margin contraction from lower unit AUVs long term, we see opportunities for some margin

recovery through revised delivery terms, SSS leverage, higher price, favorable new unit mix and contribution from digital.

Unit Composition

System Sales Composition

-

50

100

150

200

250

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

Units

Domestic Company-Operated Domestic Licensed International Licensed

$0

$100

$200

$300

$400

$500

$600

$700

$800

2014 2015 2016 2017 2018

Sys

tem

Sale

s ($

MM

)

Domestic Company Domestic & International License


As of Price Date: 6/21/2019

128


Shake Shack (SHAK) Outperform, $77 TP Valuation & Risks Valuation History • Our $77 TP is based on:



• Our EV/EBITDA multiple is in-line with SHAK’s valuation multiple over the last few months, and a discount to

SHAK’s current multiple of ~28x

• Key risks include: changes in consumer spending, inflation;

new unit productivity


3-yr Historical P/E


SSS 1.0% 3.6% 3.0% 3.5% 0.5% 2.6% 1.9% 2.0%

Consensus 1.0% 3.6% 1.5% 2.4% 0.8% 2.1% 1.4% 1.6%

Global Units 208 218 229 242 266 266 332 396

YOY % 30.8% 29.8% 27.9% 28.7% 27.9% 27.9% 24.8% 19.3%

Consensus 208 218 230 243 264 264 327 385

YOY % 30.8% 29.8% 28.5% 29.3% 26.9% 26.9% 23.9% 17.7%

Revenue ($MM) $459 $133 $150 $154 $154 $591 $756 $899

YOY % 28.0% 33.8% 29.0% 28.5% 24.2% 28.6% 27.9% 18.9%

Consensus ($MM) $459 $133 $147 $152 $153 $585 $728 $865

YOY % 28.0% 33.8% 26.8% 27.0% 23.3% 27.4% 24.3% 18.8%


Consensus 7.7% 4.3% 7.4% 6.5% 0.9% 4.8% 4.9% 5.0%

EPS $0.71 $0.13 $0.26 $0.22 $0.05 $0.66 $0.90 $1.08

YOY % 25.8% -13.3% -11.3% 4.7% -15.2% -7.6% 36.2% 20.9%

Consensus $0.71 $0.13 $0.21 $0.19 $0.03 $0.57 $0.71 $0.87

YOY % 24.6% -18.8% -27.6% -9.5% -50.0% -19.7% 24.6% 22.5%

8.0x

13.0x

18.0x

23.0x

28.0x

33.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

EV

/EB

ITD

A


40.0x

50.0x

60.0x

70.0x

80.0x

90.0x

100.0x

110.0x

120.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

P/E



As of Price Date: 6/21/2019

129


Starbucks (SBUX) Outperform, $92 TP Executive Summary Key Charts

• Credit Suisse View: SBUX is one of the highest quality growth companies in restaurants, with ~8% rev growth

(guide: 7-9%), modest margin expansion and repurchases supporting our ~14.5% EPS growth 4-yr CAGR (guide: 10%+). Consistent 3-4% Americas SSS should support current valuation, with Americas sales leverage, improved performance in China, global margin expansion and strategic

optionality as drivers of upside.

• Americas SSS As Primary Focus: An evolving digital ecosystem, beverage innovation, improved food platform,

enhanced operations and pricing power support our 3-4% SSS estimate long term. SBUX’s loyalty program drives nearly all of its comp growth, and conversion of its non-rewards customers could be a powerful SSS unlock.

• EPS Growth Story Intact: Guidance for long-term growth of

10%+ appears achievable, with opportunity for a return to beat and raises with a lower bar and margins at multi-year lows (guide 17-18%; 5-yr avg. 19%). Greater sales leverage

in Americas (~65% operating profit), better-than-expected traction in China from recent initiatives (CAP ~20% operating profit) and strategic optionality represent the greatest sources of upside. SBUX’s 3-yr $25BN capital return (FY18-FY20), leverage and G&A savings targets improve EPS visibility with

more controllable factors.

Revenue by Segment

Units by Segment

$0

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

FY10 FY11 FY12 FY13 FY14 FY15 FY16 FY17 FY18

Reve

nue (

$M

M)

Americas EMEA CAP Channel Development Corporate & Other

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

FY10 FY11 FY12 FY13 FY14 FY15 FY16 FY17 FY18

Units

Americas EMEA CAP Corporate & Other



130


Starbucks (SBUX) Outperform, $92 TP Valuation & Risks Valuation History • Our $92 TP is based on:


— Implies an EV/EBITDA of ~18x our NTM EBITDA in 12 months

• Our P/E multiple is in-line with SBUX’s current trading

multiple, reflecting a premium to its 5-yr avg

• Key risks include: increased competition, changes in

consumer spending and inflation


5-yr Historical P/E


10.0x

11.0x

12.0x

13.0x

14.0x

15.0x

16.0x

17.0x

18.0x

19.0x


EV

/EB

ITD

A


16.0x

18.0x

20.0x

22.0x

24.0x

26.0x

28.0x

30.0x

32.0x

34.0x

36.0x


P/E


2018 1Q19 2Q19 3Q19E 4Q19E 2019E 2020E 2021E

Americas SSS 2.0% 4.0% 4.0% 4.0% 3.0% 3.7% 3.7% 3.5%

Consensus 2.0% 4.0% 4.0% 4.3% 2.8% 3.8% 3.0% 3.0%

Global Units 29,324 29,865 30,184 30,721 31,364 31,364 33,536 35,746

YOY % 7.3% 6.5% 7.0% 7.0% 7.0% 7.0% 6.9% 6.6%

Consensus 29,324 29,865 30,184 30,749 31,395 31,398 33,562 35,784

YOY % 7.3% 0 0 7.1% 7.1% 7.1% 6.9% 6.6%

Revenue ($MM) $24,719 $6,633 $6,306 $6,653 $6,691 $26,282 $28,496 $31,296

YOY % 10.4% 9.2% 4.5% 5.4% 6.1% 6.3% 8.4% 9.8%

Consensus ($MM) $24,719 $6,633 $6,306 $6,671 $6,636 $26,246 $28,233 $30,372

YOY % 10.4% 9.2% 4.5% 5.7% 5.3% 6.2% 7.6% 7.6%


Consensus 18.0% 17.4% 15.8% 18.0% 17.4% 17.2% 17.6% 18.0%

EPS $2.42 $0.75 $0.60 $0.73 $0.71 $2.79 $3.15 $3.70

YOY % 17.5% 14.7% 13.0% 17.8% 14.4% 15.0% 13.1% 17.3%

Consensus $2.42 $0.75 $0.60 $0.72 $0.71 $2.78 $3.09 $3.50

YOY % 17.5% 15.4% 13.2% 16.1% 14.5% 14.9% 11.2% 13.3%



131


The Wendy’s Company (WEN) Neutral, $20 TP Executive Summary Key Charts

• Credit Suisse View: Following WEN’s transformation over the last several years, its business model reflects an improved and more consistent FCF profile. But the story shifts to execution, and we are cautious on a meaningful acceleration in SSS and unit growth from recent levels. With shares

trading near peak and limited visibility into a meaningful inflection in top-line trends, we rate shares Neutral.

• Solid Outlook, but Heavy Competition: WEN’s historical focus on traffic-driving initiatives and prudent approach to

pricing has supported positive and consistent SSS growth

averaging ~2% over the last five years. A balanced high-low menu approach, digital, delivery and remodels should

contribute to SSS of ~1.8% over the next few years, but heightened competition will likely pressure more meaningful share gains. Unit growth acceleration remains a show-me story, particularly in international markets. We model unit growth of 1.5% over the next four years.

• FCF Expectations at Low End of Guide: Execution against

sales initiatives and unit growth will be the primary drivers of normalized 4-5% FCF growth post 2020. Operating margins are now at peak levels, and it is difficult to identify

opportunities to drive that much higher following recent optimization efforts.

Revenue Composition

Unit Composition

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

2013 2014 2015 2016 2017 2018

Reve

nue (

$M

M)

Sales Franchise Royalty Revenue & FeesFranchise Rental Income Advertising Funds Revenue

-

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Units

Company North America Franchise International Franchise



132


The Wendy’s Company (WEN) Neutral, $20 TP Valuation & Risks Valuation History • Our $20 TP is based on:


• Our EV/EBITDA multiple is in-line with WEN’s 3-year

average

• Key risks include: increased competition, inflation and

interest rates


3-yr Historical P/E


North America SSS 0.9% 1.3% 1.1% 2.4% 2.1% 1.7% 1.7% 1.8%

Consensus 0.9% 1.3% 1.3% 2.3% 2.1% 1.7% 1.8% 1.8%

Global Units 6,711 6,710 6,721 6,742 6,788 6,788 6,892 7,006

YOY % 1.2% 1.2% 1.0% 1.1% 1.1% 1.1% 1.5% 1.7%

Consensus 6,711 6,710 6,738 6,764 6,813 6,812 6,943 7,106

YOY % 1.2% 1.2% 1.2% 1.4% 1.5% 1.5% 1.9% 2.3%

Revenue ($MM) $1,590 $409 $438 $430 $419 $1,696 $1,772 $1,800

YOY % 3.8% 7.4% 6.6% 7.4% 5.2% 6.6% 4.5% 1.6%

Consensus ($MM) $1,590 $409 $440 $430 $424 $1,702 $1,780 $1,824

YOY % 3.8% 7.4% 7.0% 7.4% 6.5% 7.1% 4.6% 2.5%


Consensus 18.0% 16.8% 18.3% 18.0% 17.7% 17.7% 18.9% 19.1%

EPS $0.59 $0.14 $0.18 $0.16 $0.15 $0.63 $0.76 $0.81

YOY % 49.6% 27.4% 27.1% -7.4% -7.5% 7.5% 20.2% 6.5%

Consensus $0.59 $0.14 $0.17 $0.16 $0.16 $0.63 $0.77 $0.85

YOY % 51.3% 27.3% 21.4% -5.9% 0.0% 6.8% 22.2% 10.4%

10.0x

11.0x

12.0x

13.0x

14.0x

15.0x

16.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

EV

/EB

ITD

A


17.0x

19.0x

21.0x

23.0x

25.0x

27.0x

29.0x

31.0x

33.0x

35.0x

Jun-1

6

Aug-

16

Oct

-16

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

Jun-1

9

P/E




133


Yum! Brands (YUM) Neutral, $106 TP Executive Summary Key Charts

• Credit Suisse View: YUM’s ~98% franchise business model, diversified global portfolio and low operating leverage support high visibility into ongoing low-teens earnings growth

(we model ~14% long term). YUM’s proven ability to execute against long-term targets and a more controllable earnings algorithm support a premium valuation. But at current valuation, YUM is trading above its historical avg and relative to heavily franchised peers; we see limited upside to shares.

• Unit growth to represent majority of top line: We expect YUM to generate system sales growth of ~6% over the next

few years, including ~4% unit growth and ~2.5% SSS. Development agreements tied to refranchising deals, accelerating growth in China, Taco Bell (TB) US franchisee appetite for growth and management development expertise support our expectations for achievability of targets.

• Contribution from delivery elusive: YUM’s partnership

with Grubhub (GRUB) unlocks an asset-light delivery network, favorable terms and access to data, but we do not view single platform presence alone as sustainable. We are

skeptical delivery will be meaningful for TB with a low average ticket and food might not hold. KFC could realize the most benefits (legacy real estate; conducive to travel); we have a mixed view on the opportunity for PH.

Unit Growth

System Sales Growth

3.6%

3.0%2.8%

3.2%

3.9%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

2014 2015 2016 2017 2018

Glo

bal N

et

Unit

Gro

wth

KFC Pizza Hut Taco Bell

2.7%

3.9%

5.4%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

2016 2017 2018

Sys

tem

Sale

s G

row

th

KFC Pizza Hut Taco Bell



134


Yum! Brands (YUM) Neutral, $106 TP Valuation & Risks Valuation History • Our $106 TP is based on:



• Our EV/EBITDA multiple reflects a premium to YUM’s 3-yr average, and a discount to its current multiple of ~20x

• Key risks include: increased competition, changes in macro environment and FX volatility

Post China Spin EV/EBITDA

Post China Spin P/E


KFC SSS 2.0% 5.0% 4.0% 2.5% 2.5% 3.4% 2.5% 2.5% Consensus 2.0% 5.0% 3.9% 2.6% 2.6% 3.5% 2.5% 2.5%Pizza Hut SSS 0.0% 0.0% 1.0% 0.5% 0.5% 0.5% 0.5% 1.0% Consensus 0.0% 0.0% 1.1% 1.1% 0.8% 0.8% 1.0% 1.3%Taco Bell SSS 4.0% 4.0% 4.0% 2.0% 1.5% 2.7% 2.8% 3.0% Consensus 4.0% 4.0% 3.7% 2.2% 2.2% 3.0% 2.7% 2.7%

Global Units 48,124 48,457 48,749 49,161 50,063 50,063 52,011 54,019 YOY % 6.7% 6.9% 7.0% 6.9% 4.0% 4.0% 3.9% 3.9% Consensus 48,124 48,457 48,764 49,198 50,100 50,099 52,148 54,253 YOY % 6.7% 6.9% 7.0% 7.0% 4.1% 4.1% 4.1% 4.0%

Revenue ($MM) $5,688 $1,254 $1,284 $1,334 $1,636 $5,508 $5,717 $6,034 YOY % -3.2% -8.5% -6.1% -4.1% 5.0% -3.2% 3.8% 5.5% Consensus ($MM) $5,688 $1,254 $1,279 $1,338 $1,639 $5,510 $5,761 $6,122 YOY % -3.2% -8.5% -6.5% -3.8% 5.2% -3.1% 4.6% 6.3%

Operating Margin 31.0% 34.2% 35.9% 36.9% 34.4% 35.3% 35.9% 36.3% Consensus 31.1% 34.2% 35.8% 36.9% 34.9% 35.4% 36.1% 36.3%

EPS $3.17 $0.82 $0.88 $0.96 $1.16 $3.82 $4.13 $4.63 YOY % 7.0% -8.0% 7.7% -7.6% 188.0% 20.5% 8.1% 12.1% Consensus $3.17 $0.82 $0.87 $0.96 $1.17 $3.81 $4.22 $4.74 YOY % 7.1% -8.9% 6.1% -7.7% 192.5% 20.2% 10.8% 12.3%

13.0x

14.0x

15.0x

16.0x

17.0x

18.0x

19.0x

20.0x

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

EV

/EB

ITD

A

NTM EV/EBITDA Avg Post China Spin

+1 Std Dev -1 Std Dev

20.0x

21.0x

22.0x

23.0x

24.0x

25.0x

26.0x

27.0x

Dec-

16

Feb-

17

Apr-

17

Jun-1

7

Aug-

17

Oct

-17

Dec-

17

Feb-

18

Apr-

18

Jun-1

8

Aug-

18

Oct

-18

Dec-

18

Feb-

19

Apr-

19

P/E

NTM P/E Avg Post China Spin

+1 Std Dev -1 Std Dev


135

Credit Suisse HOLT® Analysis

Market implied growth vs. historical CAGR (sorted by difference between market implied and history)

Source: HOLT. Research forecasts.

136

40%

14% 11% 9% 9%

4% 6%

(1%)

(11%) (9%) (9%)

10% 7% 6% 4% 5% 4% 6% 5%

2% 4% 6%

(30%)

(6%) (5%) (5%) (3%)

0% 0%

6%

13% 13% 15%

SHAK CMG SBUX DPZ QSR PZZA DNKN MCD JACK WEN YUM

Last 10 year CAGR Market implied Market implied vs. historical CAGR

OP OP OP OP OP N UP N N OP UP

This analysis is based on the HOLT DCF framework and uses our Research forecasts as a starting point, keeping margins constant through 2030 and solving for the long term sales CAGR required to justify current valuations

After the explicit forecast (2030 for all companies and 2035 for SHAK and CMG), HOLT calculates the terminal value by fading returns on capital and growth towards cost of capital and GDP growth respectively. HOLT standard fade rate is 10%; for this analysis, we have adjusted the fade rate to 5% across our coverage, to account for the sector’s longer sustainability

HOLT’s discount rate is based on a market derived discount rate and specific company adjustments for size and leverage. For this analysis, we are using the US Country discount rate of 3.8% (inflation adjusted) across our coverage

Methodology

HOLT market implied expectations analysis: Long-term sales growth implied by current valuations

137

Restaurants’ returns on capital have been on a steady upward trend over the past few years and recently reached historical highs, consensus is forecasting further upside from here

Return on capital – CFROI® (%)

Restaurants coverage aggregate – historical performance

Source: HOLT.

Weighted average performance of our coverage: QSR, DPZ, CMG, MCD, SHAK, SBUX, WEN, PZZA, DNKN, JACK, YUM.

Margins (%)

Turns (Sales / Invested capital, x)

Drivers of returns on capital

Returns on capital and growth drive valuation multiples across our coverage, SHAK stands out because of its high growth, while DPZ stands out for its best in class returns on capital and above median growth

138

Source: HOLT, IBES estimates.

(1) FY1- FY3 sales CAGR based on consensus estimates.

Forecast returns on capital: 2020E CFROI(2)

Fore

cast F

Y1

-FY

3 s

ale

s C

AG

R

Bubble size and label represent 2020E EV/EBITDA

Ab

ove

me

dia

n g

row

th

Be

low

me

dia

n g

row

th

Above median profitability Below median profitability

GR

OW

TH

PROFITABILITY

median FY2 CFROI: 13.6%

(2) 2020E CFROI based on consensus EPS estimates and HOLT.

YUM: 19.7x

PZZA: 18.3x

DNKN: 18.1x

WEN: 14.4x

JACK: 12.1x

QSR: 17.1x

SBUX: 16.2x

MCD: 16.4x

DPZ: 19.7x

SHAK: 26.3x

CMG: 23.5x

0%

5%

10%

15%

20%

25%

0% 5% 10% 15% 20% 25% 30% 35% 40% 45%

Neutral Outperform Underperform

Quadrant median

FY2 EV/EBITDA :

18.2x

Quadrant median

FY2 EV/EBITDA :

14.5x

median sales growth: 4.8%

Most restaurants have increased returns on capital significantly over the past 10 years, driven by margin improvement, that has offset declining asset efficiency

139 Source: HOLT. Research forecasts. SHAK’s data starts from the year 2012 while DNKN’s data starts from 2009.

10 year change in returns on capital (CFROI)

10 year change in EBITDAR margins

10 year change in asset efficiency

13%

23%

8% 11% 7% 8% 7%

11%

29%

8% 13%

30% 38%

7% 13%

4%

16% 8% 6%

30%

9%

31%

16% 15%

(1%)

1%

(3%)

8% 1%

(5%)

0% 1%

17%

QSR DPZ CMG MCD SHAK SBUX WEN PZZA DNKN JACK YUM

2008

2018

2018 vs.2008 change

26%

17% 21%

38%

20% 19% 14% 12%

58%

20% 23%

46%

22%

18%

54%

21%

27% 31%

9%

61% 51% 47%

20%

5%

(3%)

16%

1% 8%

17%

(3%)

3%

30% 24%


2008

2018

2018 vs. 2008

0.8x

1.6x

0.7x 0.4x 0.6x

0.8x 0.7x

1.6x

0.6x 0.6x 0.8x 0.7x

2.0x

0.8x 0.3x

0.5x 0.8x 0.3x

1.2x 0.6x

0.2x 0.7x

(0.1x)

0.4x 0.1x

(0.1x) (0.1x) (0.1x) (0.4x) (0.4x)

(0.0x)

(0.4x)

(0.0x)


2008

2018

2018 vs. 2008

Returns on capital and growth vs. valuation multiples

Our Restaurant coverage’s combination of returns on capital and growth are above the median of all US sectors, sharing the top right quadrant only with Tech

140

Source: HOLT, IBES estimates. Note- IBES EV for PZZA was not available, hence EV / FY1 EBITDA from HOLT is considered.

(1) FY1- FY2 sales growth based on consensus estimates.

Forecast returns on capital: 2020E CFROI(2)

Fore

cast F

Y2

-FY

3 s

ale

s g

row

th

Bubble size and label represent 2020E EV/EBITDA

Ab

ove

me

dia

n g

row

th

Be

low

me

dia

n g

row

th

Above median profitability Below median profitability

GR

OW

TH

PROFITABILITY

(2) FY2 CFROI based on consensus EPS estimates and HOLT.

Restaurants: 18.1x

Consumer Staples: 11.3x

Information Technology: 14.1x

Consumer Discretionary: 8.8x

Communication Services: 8.9x

Health Care: 13.5x

Energy: 5.1x

Industrials: 9.2x

Materials: 7.5x

3%

4%

5%

6%

7%

8%

9%

0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20%

Quadrant median

FY2 EV/EBITDA :

16.0x

Quadrant median

FY2 EV/EBITDA :

7.6x

median 2020E CFROI: 11.1%

median sales growth: 4.4%

Companies Mentioned (Price as of 21-Jun-2019)

Chipotle Mexican Grill, Inc. (CMG.N, $726.85) Domino’s Pizza Inc. (DPZ.N, $280.33) Dunkin’ Brands Group, Inc. (DNKN.OQ, $79.54) Jack in the Box Inc. (JACK.OQ, $85.08) McDonald’s Corporation (MCD.N, $204.26) Papa John’s International, Inc. (PZZA.OQ, $44.37) Restaurant Brands International Inc (QSR.N, $69.99) Shake Shack (SHAK.N, $66.75)

Starbucks Corporation (SBUX.OQ, $83.82) The Wendy’s Company (WEN.OQ, $19.37) Yum! Brands, Inc. (YUM.N, $110.27)

Disclosure Appendix

Analyst Certification

I, Lauren Silberman, certify that (1) the views expressed in this report accurately reflect my personal views about all of the subject companies and securities and (2) no part of my compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this report.

As of December 10, 2012 Analysts’ stock rating are defined as follows:

Outperform (O) : The stock’s total return is expected to outperform the relevant benchmark* over the next 12 months.

Neutral (N) : The stock’s total return is expected to be in line with the relevant benchmark* over the next 12 months.

Underperform (U) : The stock’s total return is expected to underperform the relevant benchmark* over the next 12 months.

*Relevant benchmark by region: As of 10th December 2012, Japanese ratings are based on a stock’s total return relative to the analyst's coverage universe which consists of all companies covered by the analyst within the relevant sector, with Outperforms representing the most attractive, Neutrals the less attractive, and Underperforms the least attractive investment opportunities. As of 2nd October 2012, U.S. and Canadian as well as European ra tings are based on a stock’s total return relative to the analyst's coverage universe which consists of all companies covered by the analyst within the relevant sector, with Outperforms representing the most attractive, Neutrals the less attractive, and Underperforms the least attractive investment opportunities. Fo r Latin American and Asia stocks (excluding Japan and Australia), ratings are based on a stock’s total return relative to the average total return of the relevant country or regional benchmark (India - S&P BSE Sensex Index); prior to 2nd October 2012 U.S. and Canadian ratings were based on (1) a stock’s absolute total return potential to its current share price and (2) the relat ive attractiveness of a stock’s total return potential within an analyst’s coverage universe. For Australian and New Zealand stoc ks, the expected total return (ETR) calculation includes 12-month rolling dividend yield. An Outperform rating is assigned where an ETR is greater than or equal to 7.5%; Underperform wh ere an ETR less than or equal to 5%. A Neutral may be assigned where the ETR is between -5% and 15%. The overlapping rating range allows analysts to assign a rating that puts ETR in the context of associated risks. Prior to 18 May 2015, ETR ranges for Outperform and Underperform ratings did not overlap with Neutral thresholds between 15% and 7.5%, which was in operation from 7 July 2011.

Restricted (R) : In certain circumstances, Credit Suisse policy and/or applicable law and regulations preclude certain types of communications, including an investment recommendation, during the course of Credit Suisse's engagement in an investment banking transaction and in certain other circumstances.

Not Rated (NR) : Credit Suisse Equity Research does not have an investment rating or view on the stock or any other securities related to the company at this time.

Not Covered (NC) : Credit Suisse Equity Research does not provide ongoing coverage of the company or offer an investment rating or investment view on the equity security of the company or related products.

Volatility Indicator [V] : A stock is defined as volatile if the stock price has moved up or down by 20% or more in a month in at least 8 of the past 24 months or the analyst expects significant volatility going forward.

Analysts’ sector weightings are distinct from analysts’ stock ratings and are based on the analyst’s expectations for the fundamentals and/or valuation of the sector* relative to the group’s historic fundamentals and/or valuation:

Overweight : The analyst’s expectation for the sector’s fundamentals and/or valuation is favorable over the next 12 months.

Market Weight : The analyst’s expectation for the sector’s fundamentals and/or valuation is neutral over the next 12 months.

Underweight : The analyst’s expectation for the sector’s fundamentals and/or valuation is cautious over the next 12 months.

*An analyst’s coverage sector consists of all companies covered by the analyst within the relevant sector. An analyst may cover multiple sectors.

Credit Suisse's distribution of stock ratings (and banking clients) is:

Global Ratings Distribution

Rating Versus universe (%) Of which banking clients (%)

Outperform/Buy* 46% (32% banking clients)

Neutral/Hold* 39% (28% banking clients)

Underperform/Sell* 13% (22% banking clients)

Restricted 2%

*For purposes of the NYSE and FINRA ratings distribution disclosure requirements, our stock ratings of Outperform, Neutral, a nd Underperform most closely correspond to Buy, Hold, and Sell, respectively; however, the meanings are not the same, as our stock ratings are determined on a relative basis. (Please refer to de finitions above.) An investor's decision to buy or sell a security should be based on investment objectives, current holdings, and other individual factors.

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See the Companies Mentioned section for full company names

Credit Suisse currently has, or had within the past 12 months, the following as investment banking client(s): YUM.N, QSR.N

Credit Suisse provided investment banking services to the subject company (YUM.N, QSR.N) within the past 12 months.

Within the last 12 months, Credit Suisse has received compensation for non-investment banking services or products from the following issuer(s): MCD.N

Within the past 12 months, Credit Suisse has received compensation for investment banking services from the following issuer(s): YUM.N, QSR.N

Credit Suisse expects to receive or intends to seek investment banking related compensation from the subject company (YUM.N, WEN.OQ, QSR.N, DPZ.N, DNKN.OQ) within the next 3 months.

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Credit Suisse or a member of the Credit Suisse Group is a market maker or liquidity provider in the securities of the following subject issuer(s): CMG.N, DPZ.N, DNKN.OQ, JACK.OQ, MCD.N, PZZA.OQ, QSR.N, SHAK.N, SBUX.OQ, WEN.OQ, YUM.N

A member of the Credit Suisse Group is party to an agreement with, or may have provided services set out in sections A and B of Annex I of Directive 2014/65/EU of the European Parliament and Council ("MiFID Services") to, the subject issuer (YUM.N, QSR.N) within the past 12 months.

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This research report is authored by:

Credit Suisse Securities (USA) LLC .............................................................................................................................................. Lauren Silberman

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