Download pdf - Morgan Stanley Delivery report

MORGAN STANLEY & CO. LLC

John Glass

Brian Nowak, CFA

Christopher E Carril

Jonathan Lanterman, CFA

In-Line

Attractive

Restaurants

North America

IndustryView

Internet

North America

IndustryView

Restaurants and U.S. InternetRestaurants and U.S. InternetJune 14, 2016

N. America Insight: Food Delivery: WhatIf All Food Could Be Delivered as Easilyas Pizza?

For ~50 years pizza has dominated food delivery, but new online

delivery models are poised to expand selection. We lay out 4

potential scenarios for the future of food delivery and who wins in

each. For GRUB, we see an overlooked need to invest in delivery, and

are 9% below 2017 consensus EBITDA.

Pizza: the harbinger of what's to come? While food delivery has been

around for generations, its availability has historically been limited to urban,

densely populated areas… or to pizza. Indeed, pizza has benefited from and

driven the online food delivery industry, with one-third of pizza now delivered

online, and pizza making up an estimated 60% of the total online food

delivery market. Online delivery has changed the pizza market as well,

causing a consolidation of market share within the top three brands –

Domino's, Papa John's, and Pizza Hut – which gained an incremental 600bps

of share at the expense of smaller players. This demonstrates the power of

combining easier brand access through online ordering and the

stickiness of a first mover advantage.

Consumers say they want more than pizza delivery, but can't always

get it: Only about a third of the population orders delivery food that's not

pizza, according to our recent AlphaWise survey of 5k US adults, but

consumers do like take-out food – nearly 60% have ordered food to go from a

restaurant in the last six months and demand for take-out is consistent

across urban, suburban, and rural markets. We conclude from this that

there is a significant unmet demand as new delivery models (both restaurant

and third party) evolve to serve those consumers. Importantly, our survey

work suggests restaurant food delivery is highly incremental, with two

thirds of occasions replacing a meal eaten at home.

Delivery beyond pizza: Online food delivery is still in its nascency as, by our

math, only 5% (or $10B) of the ~$210B core addressable restaurant

spend is done through online delivery, and more than half of that is

pizza. This is 1/2 the penetration of e-commerce and 1/8th of online travel. In

this note we analyze the future of the online food delivery market, which, in

our view, is in the early days of a significant shift in the access to

delivery food as various mobile Internet-enabled businesses begin to scale

and offer variety, speed, and convenience to the consumer. These include order

aggregators such as Grub Hub (GRUB), private courier models such as

Postmates and DoorDash, and restaurants themselves, from the legacy pizza

players to recent entrants into self-delivery, such as Panera.

How can investors play this now? We see the restaurant chains as the

most likely winners, with favorable outcomes in three of our four

Exhibit 1:Exhibit 1: Four possible scenarios: chain restaurants could

win--or least not lose--in three of the four, while online

aggregators/couriers could win in two of the four

- Chains adopt 3rd party aggregator model - Chains endorse 3rd party aggregators,but maintain control over customers

- Aggregator models flourish andare able to take control over customers

- Online Delivery penetration grows

- Negative for chain restaurants; risk losing - Expands restaurant demand; good forcontrol of pricing, consumer; advantages branded chains, w/ possible exceptionindependents of pizza which risk losing delivery share

- Chain restaurants work with aggregators - Chain restaurants are able to build ownin very limited capacity in-house delivery business similar to

pizza market- Aggregator availability fails to scaleand drive incremental demand - Aggregator availability fails to scale and

drive incremental demand- Online Delivery penetration stays low

- Online Penetration grows- Neutral for restaurants; nothing gained,but little invested - Advantages those best positioned for

self-delivery (PNRA, WING, possibly

coffee players)

- Online Delivery penetration grows rapidly

- Aggregator models flourishes

Frenemy Rising Tide Lifts All Boats

Status Quo Chains Win+-

+

-

Chains

On

lin

e A

gg

reg

ato

rs

Sou rce: Morgan Stan ley Research

Morgan Stanley does and seeks to do business withcompanies covered in Morgan Stanley Research. As a result,investors should be aware that the firm may have a conflictof interest that could affect the objectivity of MorganStanley Research. Investors should consider MorganStanley Research as only a single factor in making theirinvestment decision.

For analyst certification and other important disclosures,For analyst certification and other important disclosures,refer to the Disclosure Section, located at the end of thisrefer to the Disclosure Section, located at the end of thisreport.report.

| June 14, 2016Restaurants and U.S. Internet

1

mailto:[email protected]




http://www.morganstanley.com/researchdisclosures

https://ny.matrix.ms.com/eqr/article/webapp/b809acb0-9596-11e5-8b22-cf8c4c2791ce?ch=rpint

https://ny.matrix.ms.com/eqr/article/webapp/cb673b84-e7c5-11e5-abc7-399e2298bd03?ch=rpint

https://ny.matrix.ms.com/eqr/article/webapp/dd44a316-df21-11e5-9d84-73de8f7e380b?ch=rpint

https://ny.matrix.ms.com/eqr/article/webapp/4ff73b1c-e134-11e5-a1de-a44efef26ea0?ch=rpint

https://ny.matrix.ms.com/eqr/article/webapp/fef6b390-dc7a-11e5-9403-7d321b10ff78?ch=rpint

https://ny.matrix.ms.com/eqr/article/webapp/fef6b390-dc7a-11e5-9403-7d321b10ff78?ch=rpint

scenarios. While Dominos (DPZ) will likely continue to win in online pizza, our

survey shows the next most ordered categories are sandwiches and Italian,

while coffee is lower on the list. This supports our OW and above-consensus

view on Panera (PNRA), an early mover in self-delivery, and increases our

conviction on smaller cap Wingstop (WING), where consumers are clamoring

for delivery and we think management will soon accede. Its also a positive for

Darden (DRI)'s Olive Garden brand, which has a burgeoning delivery business.

Consumers also ask for delivery from Buffalo Wing Wings (BWLD),

Cheesecake Factory (CAKE), and Chipotle (CMG). Findings imply that delivery

for Starbucks (SBUX) and Dunkin Brands (DNKN) may be less impactful than

investors hope near term, as demand is lower, though delivery for those

names is not core to current investment debates. Demand for traditional fast

food (MCD, WEN, et al.) is also relatively low.

From the aggregators' perspective, while GrubHub is in the lead among

the third party aggregators, our AlphaWise survey data, the scenario analysis

above, and competition from other aggregators for chain business all speak to

the importance of continuing to grow restaurant selection. On one hand, GRUB

could change its fee structure and start charging consumers in order to entice

the brands – but, for now, we view that as unlikely. Rather, we see GrubHub

needing to continue to invest in delivery to drive selection, which, while

potentially positive for the long term, will pressure near-term profitability. As

such, we are increasing our GRUB delivery cash burn assumptions in '17/'18.

This change drives our adjusted EBITDA estimates 9%/19% below consensus.

We remain EW and have reduced our DCF-based PT to $26 from $30 (see

GrubHub: The Cost of WinningGrubHub: The Cost of Winning). Postmates and DoorDash have an

advantage with chains given their consumer-fee based model, but the

sustainability of growth will come down to consumers' willingness to pay

(which for now our AlphaWise data support). The larger aggregators (Amazon

and Uber) are still materially trailing in selection, but must be watched given

their brand loyalty – imagine if Amazon had material restaurant selection that

offered free delivery to all Prime members – and theoretical ability to price

aggressively.


2

http://eqr-methode-mps-editorial.ms.com/eqr/article/webapp/b3ff77ba-2c01-11e6-b804-6e2be5dc4d99?forceUpdate

Cra

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here th

ere has b

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ay

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regato

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UB

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layers to recen

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NR

A.

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gly w

idesp

read u

se of d

elivery as a po

sitive for restau

rants as it exp

and

s the

market fo

r restauran

t foo

d, an

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party d

elivery firms are b

oth

taking

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st of th

e start up

risks and

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ital. In m

ost scen

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e shift to

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ill be ad

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s to ch

ain restau

rants

over in

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ore seam

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use tech

no

log

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fast and

efficient d

elivery – and

have th

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g clo

ut to

drive co

nsu

mers to

their b

rand

s' web

sites or ap

ps.

To b

etter un

derstan

d h

ow

likely con

sum

ers are to u

se these d

elivery services, if they are in

fact increm

ental, an

d

wh

at catego

ries are mo

st likely to b

e ord

ered o

nlin

e, we co

mm

ission

ed an

Alp

haW

ise survey o

f 5,0

00

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erican

adu

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% w

ho

have d

ined

ou

t recently, an

d 4

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wh

om

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od

.

Wh

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id

In A

pril 2

01

6, in

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rgan

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ley Alp

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ise, we co

nd

ucted

an o

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e survey o

f over

5,0

00

US

con

sum

ers, inclu

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g n

early 80

% o

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ents w

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and

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. The m

argin

of erro

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con

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regard

to d

elivery in g

eneral, as w

ell

as abo

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eir specific exp

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references w

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restauran

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ibit 2

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:O

nlin

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etitive land

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the U

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| Jun

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3

Bear in mind, however, that with the exception of GrubHub, most of these new enterprises have been in

business less than five years. As with any emerging sales channel, consumers may not have enough experience

with online order and delivery to fully appreciate if the service offered would be of use. If you were to have

surveyed consumers in the mid-1990s on whether they'd prefer to do most of their shopping at a website called

Amazon.com, most would have said they'd just as soon go to the store to pick it up. And yet with a combination

of vast selection and speedy, low-cost delivery, e-commerce now garners 10% of all retail sales. And online

travel agencies (OTAs) have captured 40% share of that segment offering that same kind of convenience. And

now, with just under 2% online penetration, online food delivery faces a similar opportunity in the near-$500B

restaurant sector.

What's changed with online food delivery. While the notion of food delivery has been around for decades,

online food delivery is just emerging. Some early models – notably GRUB – act as demand aggregators,

servicing as a central site or application for aggregating restaurant demand, and as a tool for exploration by the

consumer. GRUB charges the restaurant a ~15% referral fee for that service, and until recently has left the actual

delivery to the restaurants themselves.

Another class of businesses has emerged more recently. In this case, courier models, such as Postmates and

DoorDash, utilize a network of mobile device- empowered independent contractors to pick up and deliver food.

They need volume to keep these independent workers busy, and as such are migrating more to doing business

with chain restaurants, which have greater advertising clout and brand awareness. A third type of delivery

model is emerging from large tech players in adjacent markets looking to leverage existing networks or

business – such as Uber and Amazon.

When pizza met the internet. One of the best ways to prove the power of online-empowered delivery is to

look at pizza. While the pizza delivery category is over 50 years old, online has rapidly become one-third of

the category sales, and the top three players – Dominos, Papa John's and Pizza Hut – have 50% or more of

sales coming from online. The online migration had three notable outcomes: 1) online ordering at the top

chains went from 0% to over 50% in less than a decade; 2) market share has – and continues – to rapidly

consolidate, with the top three brands gaining an incremental 600bps of share at the expense of smaller chains

and independents; and 3) over $7B of incremental shareholder value was created in the top two publicly traded

companies alone. This happened despite the fact that the underlying category actually shrank by over 10% in

the last decade. This demonstrates the power of combining easier brand access through online

ordering and the stickiness of a first mover advantage.

Exhibit 3:Exhibit 3: Pizza's early lead on line has meant that it dominates digital ordering today

0

500

1,000

1,500

2,000

2,500

Est. Sales of Digital Delivery Order Platforms

Sou rce: Compan y data , Morgan Stan ley Research


4

Consumers say they want more than delivery, but can't always get it. Only about one-third of the

population orders delivery food that is not pizza, according to our survey, and the order frequency is lower than

pizza. But consumers like takeout food – in fact nearly 60% of US consumers have ordered food to-go from a

restaurant in the last six months… And demand for takeout is consistent across urban, suburban and rural

markets. That's at least a hint that there could be more demand if delivery service is available. The delivered

food is a smaller subset, skewing heavily urban, and younger, such as in suburban markets where delivery runs

Exhibit 4:Exhibit 4: Major pizza chains have taken an incremental 600 bp of share since launching digital ordering, all

while the category has remained flat

52% 58%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2007 2015

US QSR Pizza Delivery Share

Major Pizza Chains Small Chains/Independents

Major

Chains:


Exhibit 5:Exhibit 5: Growth in the online business has led to significant relative outperformance for the two delivery

pure plays and created over $7B in incremental shareholder value over the past five years

-100%

0%

100%

200%

300%

400%

500%

600%

Relative Stock Performance: QSR Pizza vs S&P 500

DPZ PZZA S&P 500

Sou rce: Th omson O n e


5

16 percentage points lower than takeout (46% vs 62%). That spread is even wider in rural markets. That's a

significant opportunity for new online order and delivery businesses to meet that unsatisfied

demand.

The key impediments to greater use of delivery is price and availability. Consumers are clear that the key

impediments to greater delivery usage is: 1) cost, 2) availability, and 3) delivery time. We think online delivery

solves at least two of these, and possibly a third. Greater availability through networks that service multiple

brands should solve both the availability issue as well as the economics of running a delivery network through

better capacity utilization. Delivery times – and certainty through feedback loops – should benefit speed (the

ability to track your order for example, akin to the way you track your Uber ride).

Exhibit 6:Exhibit 6: While two thirds of all consumers order delivery food, it's higher in urban markets where access is

easiest. Suburban and rural markets – where most chains currently reside – have the most upside for online

delivery.

59%

44%

57%

50%

62%

46%

58%

29%

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

Ordered food for take-out

Ordered food for delivery

Ordering and Eating Out Past 6 Months: by Area

Total

Urban

Suburban

Rural

Sou rce: Alph aW ise


6

But price is the biggest impediment, and currently pricing for courier models is high, in our view. And while

Millennials seem to be willing to spend now on convenience, broader usage may require lower fees, perhaps,

for example, through a Prime model similar to what Amazon has effectively used to encourage frequency by

charging one-time up-front delivery fee. In this regard, we think it is important to monitor 1) Amazon's ability to

scale its overall restaurant selection and 2) Postmates' emerging Plus Unlimited offering unlimited free

deliveries for $9.99 per month.

As another alternative, chain restaurants may over time need to underwrite a portion of that delivery cost, and

as that occurs, some restaurants may choose to investigate establishing their own delivery networks. We also

see room in restaurant margins to share in some of the delivery costs if it proves incremental. We explore this

more fully in a subsequent section.

There is one additional element that impedes delivery for some categories: food condition. Besides the normal

care required to delivery food in good condition, not all foods deliver equally as well. Pizza has been successful

because cheese is a good insulator and the product can withstand a 20-minute delivery journey. The same goes

for Asian, Italian, and sandwiches. Other categories don't fare as well. Coffee for example has some

impediments, as do burgers and fries, which tend to get soggy quickly. But we think consumers intuitively know

this when ordering, and this is reflected in the responses to our survey in lower delivery demand in these

categories. Moreover, packaging technology – not a topic many of us spend much time thinking about –

continues to evolve, perhaps making delivery in some of these more challenging categories more viable in the

near future.

Delivery demand is largely incremental for restaurants. Finally, consumers say that over two thirds of

delivery demand is incremental – insofar as it replaces a meal eaten at home vs. at a restaurant. This is

important, as margins on off-premise food – takeout or otherwise – are lower than dine-in due to lower drinks

and dessert attachment (both high margin products) and higher packaging costs. But if the sale is largely

incremental, then it benefits fixed cost leverage.

Exhibit 7:Exhibit 7: What keeps consumers from ordering delivery?

37%

23%

18%

17%

17%

14%

7%

6%

5%

Expensive

Prefer to order for take-out

Delivery ordering service not available

Delivery time is too long

Not convenient

Choices of cuisine are limited

Poor food condition (temperature, appearance)

Poor food quality

Poor customer service

Reasons for Not Ordering Food for Delivery in Past 6

Months



7

The size of the delivery prize is large. At nearly $500B, the restaurant industry is one of the largest in all of

retail. Of that, we estimate about $210B is restaurant food eaten off premise. We estimate that the current

delivery market is $30B, and $11B of that is online. But excluding pizza, online delivery is ~$4B, or just 2% of

the total addressable market. This is low compared to eCommerce, where an estimated 10% of retail sales

are online and online travel, which has achieved 40% penetration. Said another way, despite online delivery

being around for 15+ years (Seamless started in 1999), online food delivery has 1/5th the penetration of e-

commerce and ~1/20th(!) the penetration of online travel. See the following section, Sizing the Total

Addressable Market for Delivery for greater detail.

How big could online delivery be? As more fully described in later sections, we believe the total addressable

food delivery market is $210 B. Currently, the delivery market is $30B and the next closest market of non-QSR

take-out food is another $30B. Our survey work suggests that there is clearly some unmet demand for delivery

and many pick up themselves instead. But couldn’t this be even bigger? The next $150B is off premise fast food

- while two thirds of this or $100B goes through the drive thru, there's $50B that does not. Ultimately though

we think the entire $210B of off premise food is up for grabs. What gives us confidence? Current to-go

and delivery figures are based on existing infrastructure and lifestyles, but as we've seen with retail, travel and

transportation, technology can and does change those patterns when access is easier and cheaper. Changes in

shopping patterns may mean fewer car trips, and shift a portion of drive thru business to delivery. Social media

may change the number of occasions we choose to eat out vs eat in. Ultimately delivery may end up expanding

restaurant demand, not just shift share within it.

Exhibit 8:Exhibit 8: AlphaWise Survey Results: Food Delivery Replaces … (% of Respondents)

2%

30%

34%

34%

38%

68%

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

Other

Meal picked up by yourself without ordering aheadof time

Meal ordered as a take-out

Prepared meal from a grocery, convenience orsimilar store

Meal eaten at a restaurant

Meal eaten at home



8

How online delivery plays out: four scenarios. As with any emerging new channel, the path forward is not

clear, but at least can be captured in four potential scenarios. We outline four of the most possible scenarios,

described more fully below:

Exhibit 9:Exhibit 9: We estimate the current size of food delivery to be ~$30B (~6% of the $490B restaurant industry)

but with an immediately adjacent incremental $30B of non fast food off-premise opportunity.

Delivery Market Opportunity

Total Restaurant

Industry: ~$490B

Current

Delivery

Market:

~$30B

Delivery

Opportunity

Total Restaurant Off-

Premise Sales (incl.

Drive-Thru): ~$210B

Plus Non-QSR

Off-Premise:

~$60B

Sou rce: Morgan Stan ley Research , Tech n omic, Compan y Data

Exhibit 10:Exhibit 10: US Total Addressable Market:

Restaurant Delivery vs. eCommerce vs. Travel

$3,253

$690

$210

0

500

1,000

1,500

2,000

2,500

3,000

3,500

eCommerce Travel Restaurant Delivery

To

tal U

S A

dd

ressab

le M

ark

et ($

Bs)

Source: Company data, Alphawise, PhocusWright, US Census

Bureau, ComScore, Forrester, Euromonitor, Morgan Stanley

Research

Exhibit 11:Exhibit 11: Online Penetration - Restaurant

Delivery vs. eCommerce vs. Travel

10%

41%

5%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

eCommerce Travel Restaurant Delivery

On

lin

e P

en

etr

ati

on

Source: Company data, Alphawise, PhocusWright, US Census

Bureau, ComScore, Forrester, Euromonitor, Morgan Stanley

Research


9

— Win-Win: a rising tide lifts all delivery boats: In the best case scenario--one of the two most likely in our

view-- both chain restaurants and 3rd party online providers win. Chain restaurants, believing that online

ordering expands their market, work with the existing third party providers with lower risk and less capital

committed. As an added benefit, restaurants will not need to take on all the start up risk and costs. In addition,

many branded restaurants believe these services provide a buffer between their consumer and the brand. Early

on, delivery is fraught with execution risk, and many branded restaurants we believe would rather have the

consumer blame a third party for the mis-execution than the brand itself. Online order platforms benefit from

the increased volume and existing online order flow. Already, consumers are pre-programmed to contact the

restaurants directly to order, and (per our survey) 85% of all delivery orders are made with the restaurants

directly. Migrating more orders to online from the phone saves time and money for restaurants. Courier models

could benefit by inserting themselves into this already existing paradigm.

At a high level GRUB would benefit from the continued shift online, but it would also face incremental

competition from chains moving toward other online delivery models – like Postmates, Amazon, Uber – delivery

unless it chooses to offer a consumer pay model or reduce its fees to chains.

Why this scenario is likely: There is clear demonstrated demand for delivery food, based on our survey, and

the impediments that have been barriers to greater usage (pricing, availability, variety) are being addressed. If

delivery expands the addressable market for restaurants, they will be incented to participate. While certain high

volume brands (such as Panera, perhaps some other limited service brands) may choose to build their own

delivery networks, many more likely will rely on thrid party delivery, providing enough volume for one or more

of these networks to build a scaled model. In this scenario, the market for online food expands, moving to first

Exhibit 12:Exhibit 12: Four possible scenarios - chain restaurants could win - or least not lose - in three of the four,

while on line aggregators/couriers could win in two of the four

- Chains adopt 3rd party aggregator model - Chains endorse 3rd party aggregators,but maintain control over customers

- Aggregator models flourish andare able to take control over customers

- Online Delivery penetration grows

- Negative for chain restaurants; risk losing - Expands restaurant demand; good forcontrol of pricing, consumer; advantages branded chains, w/ possible exceptionindependents of pizza which risk losing delivery share

- Chain restaurants work with aggregators - Chain restaurants are able to build ownin very limited capacity in-house delivery business similar to

pizza market- Aggregator availability fails to scaleand drive incremental demand - Aggregator availability fails to scale and

drive incremental demand- Online Delivery penetration stays low

- Online Penetration grows- Neutral for restaurants; nothing gained,but little invested - Advantages those best positioned for

self-delivery (PNRA, WING, possibly

coffee players)

- Online Delivery penetration grows rapidly

- Aggregator models flourishes

Frenemy Rising Tide Lifts All Boats

Status Quo Chains Win+-

+

-

Chains

On

lin

e A

gg

reg

ato

rs



10

consolidate the existing $30B food delivery market, and perhaps expands into the adjacent $30B of takeout food

by making it easier and faster to order online rather than having to go and pick up food.

— Chains win: In this scenario, chains quickly learn from online providers, but prefer to capture more of the

delivery economics themselves by building their own delivery networks. Delivery is not an easy business to

execute, and has risk and therefore we think this scenario is less likely than the first. Most chains we think will

take a wait and see approach. Over time, a limited number of restaurant brands with consistent delivery demand

and high store densities could try to do it themselves. Already PNRA has announced plans to build its own

networks. A few others, notably SBUX, perhaps DNKN and some quick service brands may try, too. Brands with

lower frequency or less density – such as CAKE or Olive Garden (DRI) – may still be better served using third

party. The chart below depicts how we think about brands' density and frequency of use as it relates to which

ones may try delivery on their own. This scenario, in which the highest velocity and most popular brands do self

delivery, will be a negative for the third party delivery companies.

Why this is less likely - Though a handful of chains may venture into self-delivery as Panera has recently

indicated, the challenges and risks with starting up delivery without experience are significant, and we think

branded chains will more likely partner with specialists and self delivery won't be widely enough spread to

undermine the efforts of the third party operators.

Exhibit 13:Exhibit 13: Restaurants currently control 85% of online ordering, through phone and orders placed through

their websites

50%

35%

15%

Food Delivery Share (Last 3 Months)

Phone the restaurant directly

Online directly through restaurant's

website or mobile app

Online through delivery service

website or mobile app



11

— Restaurants become "frenemies" with third party delivery: In this scenario, our other most likely

scenario, restaurants work with third party delivery, but lose control of their customers, somewhat analogous to

how OTAs have (in some cases) superseded hotel and airline direct bookings. Losing ownership of their

customers is a restaurant brand's worst fear, ceding pricing power and customer data. And yet in this scenario

restaurants become dependent on the incremental volume provided by online delivery, making walking away

difficult. That loss may also level the playing field for some independent and smaller chain restaurants, as the

larger brands lose some of their clout on these platforms. This is the one scenario we envision in which

restaurants lose.

Until now, part of reason for the low level of adoption, in our view, has been lack of sufficient delivery options

and restaurant availability. Our survey shows that 18% of people who don't order food online do so because the

service isn't available and 44% of people who stop using GRUB list lack of restaurant selection as one of the

main reasons (see Exhibit 15Exhibit 15). We believe that as aggregators like GRUB (which represents 50+% of the market)

add selection, the consumer value proposition will increase and this could create a virtuous network effect in

which increased supply stimulates demand, which stimulates more supply.

Exhibit 14:Exhibit 14: In our view, key factors likely to be considered by large chains deciding whether to build their

own delivery network include restaurant density and customer frequency

Applebee's

McDonald's

Burger King

Olive Garden

Wendy's

Chili's

Taco Bell

Panera Bread

KFC

Qdoba

Starbucks

Dunkin' Donuts

Chipotle

Sonic

Jack in the Box

0

10

20

30

40

50

60

Sto

res

Pe

r M

illi

on

Pe

op

le (

Ag

e 1

6+

)Frequency vs. Restaurant Density

Low High

Frequency

Sou rce: Alph aW ise, Compan y Data , Morgan Stan ley Research


12

— Status quo: The whole third party online experiment fails to gain traction, either because pricing is too high,

not enough restaurants join the networks, or because execution doesn't live up to its promise. In this scenario,

third party aggregators clearly lose, but chain restaurants don't take much risk or spend capital, learn from the

experience, and continue on with business as usual. We don't see going back to the status quo as a likely

outcome as consumers, having seen the benefits of delivery, likely will increasingly demand this service.

Our Base Case Assumes Online Food Delivery Grows at a 17% CAGR...Reaching 9% Penetration

As our base case, we expect the emerging food delivery business models to drive continued user adoption. After

all, the notion of increased selection driving user growth and increased purchase behavior isn't new as

Amazon (the leader in e-commerce) has driven the e-commerce shift with 1) competitive pricing and 2) an

ever-growing selection and products. Similarly, online travel agencies (like industry-leading Priceline) talk

about the importance of selection and the number of hotels available on the site...and how that drives higher

end user conversion.

Now, with both the rise of online delivery specialists, combined with a willingness for restaurants to embrace

this new channel, we believe we are poised to see significant market growth, all of which is largely incremental

for restaurants and which will likely further accelerate the growth of prepared food spending. In our base case,

we see online food delivery penetration growing to 9% by 2020 , reaching nearly $25 B...as the market grows at

a 17% '15-'20 CAGR (See Exhibit 16Exhibit 16).

Exhibit 15:Exhibit 15: Reasons people churn off GrubHub

44%

32%28%

18%15% 15% 15% 15% 13%

11%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%



13

Key stock implications for restaurants: Online delivery is a benefit to chain restaurants – or at least not

negative – in three out of our four scenarios. But not all restaurants will likely benefit equally. Best-positioned

restaurants will have food that fits the following characteristics: easy to transport and retains heat well (or is

consumed at room temperature). Ability to be shared has also been a contributing factor in many cases.

Historically these have worked well for pizza and Asian food, but sandwiches and Italian are also in high demand

for delivery. Coffee and traditional QSR, have been less in demand for delivery, at least to date.

We'd argue that our findings are positive for PNRA's efforts to enter delivery, with new evidence of consumer

demand that strengthens our above-consensus thesis. We also see this as positive for WING, which has high

consumer demand for delivery and an already high proportion of to go sales as well as CMG, which is testing

delivery. It also supports Olive Garden's (DRI) efforts to begin offering delivery. Other brands consumers say

they are most likely to order delivery from, if available, include, BWLD, CAKE and Carrabba's (BLMN).

On the flip side, our findings are marginally negative for SBUX and DNKN as coffee delivery is less in

demand currently, but that could change if consumers see it as a more viable option. It is also negative, or at

least not in as high demand, for traditional fast food operators such as MCD, WEN, and Burger King

(QSR). The burger and fry category also has the logistical challenge of not traveling well.

Finally, while we do not have direct consumer evidence of this, it is possible that the acceleration in share gains

by major pizza chains, and especially DPZ, has been in part due to increased ease of ordering. It is logical then to

at least contemplate the possibility that some of those gains get shifted to new online categories.

Exhibit 16:Exhibit 16: Restaurant delivery and pickup penetration - GRUB vs. Non-GRUB

0%1%

1%1%

1% 1% 2% 2% 2%

2%3%

3%

4%

5%

5%

6%

6%7%

3%

3%

4%

5%

6%

7%

7%

8%

9%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

2012 2013 2014 2015 2016 2017 2018 2019 2020

Penetr

ati

on

of T

AM

GRUB Delivery other than GRUB Total Online Delivery

Sou rce: Compan y data , Morgan Stan ley Research ; Note: Th e Pen etration rates above in clu de Restau ran t D irect Ch an n els w h ich in clu des th e more

matu re ch ain Pizza delivery ch an n els an d defin es th e TAM as Picku p an d Delivery Restau ran t Spen d

Exhibit 17:Exhibit 17: US online gross food sales by channel (figures in $Millions), 2010-2020E

Contrib

CAGR to Growth

2010 2015 2020E 10-15 15-20E 10-15 15-20E

GrubHub $444 $2,355 $4,901 40% 16% 26% 21%

Eat24 $14 $264 $1,164 80% 35% 3% 7%

Other Online Platforms $37 $1,382 $8,541 107% 44% 18% 58%

Restaurant Direct $2,612 $6,500 $8,296 20% 5% 53% 14%

Total US Online Delivery $3,107 $10,500 $22,902 28% 17% 100% 100%

Sou rce: Compan y data , Morgan Stan ley Research ;


14

Key risks for restaurants: First, tech delivery firms such as GRUB and more recent start ups DoorDash,

Postmates, and UberEats among others may seek to disintermediate restaurants by not only controlling delivery

but ultimately seeking to control the customer. Second, wider-spread use of delivery may change restaurant unit

growth plans longer term as existing dine-in units could become less productive. Alternative formats could

include delivery only outlets similar to what the pizza industry has built.

Key stock implications for eCommerce: GRUB has an early lead in the third party delivery market (see

Exhibit 19Exhibit 19) but is only likely to be successful over the long term in two of the four scenarios – Rising Tide and

Frenemy – laid out above in ExhibitExhibit1212. In addition, all of the four scenarios (as well as our AlphaWise survey

in Exhibit 15Exhibit 15 ) speak to the importance for GRUB to continue to increase its restaurants selection in

order to grow its business and compete. We see this requiring continued investment in delivery and (in

order to entice more chains) a potential business model pivot with lower long-term commission rates or a

consumer-based fees.

Exhibit 18:Exhibit 18: In our view, outside of the QSR pizza chains, PNRA and WING are among the most advantaged

chains from a delivery perspective

Consumer

Demand -

Brand/Category

Incremental

to Business

Early Mover

Advantage

Existing

Scaled Takeout

Business

Food Delivers

Well/Easily

Delivery Advantaged QSR Pizza (DPZ, PZZA) ü ü ü ü ü

PNRA ü ü ü ü ü

DRI ü ü ü ü

CAKE ü ü

WING ü ü

BWLD ü ü

CMG ü ü

Traditional Burger QSR (MCD,

WEN, JACK, SONC) ü

Coffee (SBUX, DNKN) ü

Delivery DisadvantagedBar & Grill/Steak CDR (BJRI,

EAT, TXRH)



15

We are not modeling any material change in GRUB's position toward a consumer fee, but in our base case we

are now assuming GRUB continues its delivery investment into 2017 and 2018. Because while GRUB's

44,000 restaurant (as of 1Q:16) share is larger than its peers, it is still small in the grand scheme of things, with

625,000 estimated total restaurants in the United States (350k of which are independent). We believe GRUB has

to make these investments if it hopes to continue to grow its top-line and this overall market. Why do chains

matter? Chains make up >50% of restaurant food sales in the US and likely an even higher portion of sales

outside of urban areas. Because of this, GRUB's ability to sign up chains will be key in adding restaurant supply.

To offer a compelling service to chains, online aggregators must offer not just demand but delivery capabilities.

While investing in delivery is the right decision for the long-term, in the near-term we see this investment

pressuring profitability...and we are therefore lowering our 2017 EBITDA by 6% and are now 9% below

consensus 2017 EBITDA (See Exhibit 21Exhibit 21 and Exhibit 22Exhibit 22).

Exhibit 19:Exhibit 19: Delivery Food TAM: GRUB vs. Non-GRUB (in millions)

24%

23%

19%

14%4%2%

2%

2%

1%

0%0% 9%

Digital Delivery Order Market Share

Domino's

GrubHub/Seamless

Pizza Hut

Papa John's

Jimmy John's

Eat24

Postmates

DoorDash

Caviar

UberEats

Delivery.com

Other Online Platforms

Sou rce: Compan y Data , Morgan Stan ley Research

Exhibit 20:Exhibit 20: Chains already have the advantage over independents with respect to delivery

Independent

44%Chain

56%

Share of Food Delivery Orders in Past 3

Months, by Restaurant Type

14% of consumers

ordered from

independent

restaurants only

21% of consumers

ordered from chain

restaurants only



16

Key risks for GRUB: Growing competition from emerging start-ups (like Postmates, Doordash ) or larger

players (like Amazon or Uber) could impact its ability to continue to grow its restaurant count and share of

stomach, even through higher delivery investment. The chains' ability to grow their own in-house delivery

businesses would also be incremental competition.

Exhibit 21:Exhibit 21: Current Estimates vs. Previous

Estimates - FY17 and FY18 Adj. EBITDA

in $ millions (ex-EPS)

GrubHub 2017

Current

MS Est.

Previous MS

est. %/bpVar

Revenue $567 $552 3%

Adj. EBITDA $147 $157 -6%

Margin (%) 26% 28% -240 bps

Adj. EPS $0.93 $0.98 -5%


GrubHub 2018

Current

MS Est.

Previous MS

est. %/bpVar

Revenue $649 $646 0%

Adj. EBITDA $162 $189 -14%

Margin (%) 25% 29% -420 bps

Adj. EPS $1.10 $1.41 -22%

Source: Morgan Stanley Research

Exhibit 22:Exhibit 22: FY17E and FY18E Adj. EBITDA -

Morgan Stanley vs. Consensus


GrubHub 2017 MS est. Consensus %/bpVar

Revenue $567 $573 -1%

Adj. EBITDA $147 $163 -9%

Margin (%) 26% 28% -240 bps

Adj. EPS $0.93 $1.00 -7%



Revenue $649 $671 -3%

Adj. EBITDA $162 $201 -19%

Margin (%) 25% 30% -496 bps

Adj. EPS $1.10 $1.22 -10%



17

Sizing the Total Addressable Market for DeliverySizing the Total Addressable Market for Delivery

Many investors ask what is the size of the restaurant delivery and takeout number in the US. While GRUB cites a

Euromonitor report sizing the market at $75B for takeout plus delivery for independent restaurants plus $170B

when including chains (for $245B in total), most have looked at those figures with a healthy dose of skepticism.

Other sources size the current delivery and takeout market at $70B. As such, we have done our own work on the

subject by combining our survey work with company-specific data about and knowledge of the restaurant

industry to come up with our own Total Addressable Market estimates.

We estimate the current size of the food delivery business – on and off line – to be ~$30B, or roughly

6% of the $490B restaurant industry. The ultimate total addressable market of all off-premise

restaurant food is $210B. Currently, we estimate the size of the online food delivery business to be

$11B, with over $6B of that in online pizza sales alone. That would put total online sales at 5% of the $210B

addressable market. Excluding pizza, which is largely self-delivered, online delivery platforms (which we

estimate to be $4B) have just 2% of the total off-premise restaurant food dollars, compared to 10-11% of retail

sales that are e-commerce and 40% for online travel.

While we believe delivery to be $30B today, and the ultimate addressable market to be $210B, we see the

immediate opportunity for delivery to be an incremental $30B of non-fast food sales that is currently take-out.

We see this as potentially low hanging fruit for online food delivery penetration. The last $150B opportunity

($210B in all off premise sales less the $60B in current delivery and non-QSR takeaway food) may not be

immediately accessible to online delivery – much of it is fast food consumed on the go, much of it through the

drive thru – it does suggest that there is a sizeable market opportunity for food delivery with very low online

penetration.

Below we run through the math behind how we arrived at this sizeable total addressable market – from the

current $30B market, to the $60B potential for non-fast food takeout to $210B for total off-premise food sales

to the even larger $490B total restaurant market.


18

State of the Food Delivery Business TodayState of the Food Delivery Business Today

Based on our survey results around the percentage of people who order delivery, pickup, and eat at restaurants,

combined with frequency rates and our knowledge of average dollar order values, total Restaurant TAM

estimates from Technomic, and our knowledge of company-specific sizes in the online ordering market, we have

come up with a total addressable market estimate for restaurant spend by vertical.

Our analysis finds that of the $490B spent in the US on restaurants, ~$30B is spent on delivery (~$10.5B is

currently done online), another ~$180B on pick-up or drive-thru, and $280B on dining-in. Note that within the

Exhibit 23:Exhibit 23: We estimate the current size of food delivery to be ~$30B (~6% of the $490B restaurant

industry) but with an immediately adjacent incremental $30B of non fast food off-premise opportunity.

Delivery Market Opportunity

Total Restaurant

Industry: ~$490B

Current

Delivery

Market:

~$30B

Delivery

Opportunity

Total Restaurant Off-

Premise Sales (incl.

Drive-Thru): ~$210B

Plus Non-QSR

Off-Premise:

~$60B

Sou rce: Morgan Stan ley Research , Tech n omic, Compan y Data ; Alph aW ise

Exhibit 24:Exhibit 24: Derived Restaurant TAM by Order Method: We estimate online delivery is $11B today, but more

than half of that is pizza

$280B

$180B

~$19B

~$11B

$0

$100

$200

$300

$400

$500

$600

$ B

illio

ns Online Delivery

Phone Delivery

Pickup

Restaurant

4%

39%

57%

$490B Total

2%

Share (%)

Sou rce: Alph aW ise, Morgan Stan ley Research , Tech n omic , Compan y data


19

~$30B of delivery spend, we estimate that over half is still done through the telephone – meaning online

delivery spend is only ~$11B per year. Said another way, we estimate that ~2% of current US restaurant

spend is through online delivery.

Note that in the above analysis we assume:

By type of cuisine, pizza, no surprise, dominates the delivery business, representing a third of the

total. This is followed by Asian, and, equally as large, sandwiches, then Italian, burger and down the line.

Currently coffee is the smallest for the delivery categories, but still represents $1B in delivered sales.

Breaking Down How People Are Ordering Online Now

Taking a closer look at delivery, we found from our survey work that online ordering platforms only make up

~15% of the delivery spend, while Direct orders at restaurants via dedicated restaurant apps or websites make

up ~22% of total delivery spend. And the remaining 63% is ordered over the phone.

124 million households in the US.

~$490B total Gross Food Sales Spend (per Technomic).

The top 8 online marketplaces and delivery platforms represent the vast majority of total

delivery revenues.

The approximate ratio of delivery dollars is 65/22/13 for phone/online restaurant

direct/online platform which is slightly adjusted from our survey results to adjust for higher

phone orders, consistent with commentary from pizza delivery chains and discussion with

delivery platforms.

~$30 average order value for restaurant dine in orders.

Exhibit 25:Exhibit 25: Food Delivery Dollars by Food Type (Figures in $B)

$9,615

$4,664

$3,966

$3,036

$2,904

$2,316

$2,284

$1,090 $565

Pizza

Asian

Sandwiches

Italian

Hamburger

Mexican

Salads

Coffee

Other

Sou rce: Alph aW ise, Morgan Stan ley Research


20

We would highlight three things:

1) Phone Orders. With >50% of orders still coming through phone, this suggests material growth potential

from digital ordering simply from share shift without any market expansion.

2) Online Restaurant Direct. We believe a significant portion of online restaurant direct delivery comes from

the top three pizza chains (Domino's, Pizza Hut, and Papa John's together represent >$6B), which have been at

the forefront of delivery. We estimate QSR Pizza chains deliver ~$10B of gross food sales in the US annually

(including phone orders).

3) Online Website/Platform. With $4B of gross food sales, online websites/platform gross food sales only

represent 13% of total delivery sales. Given that independent restaurants represent ~40% of restaurant spend in

the US, but only 30% of online ordering for delivery spend, this implies that chain restaurants are unsurprisingly

ahead of the curve in online delivery (likely led by Pizza).

Exhibit 26:Exhibit 26: Delivery Market by Order Type: Phone vs. Restaurant Direct vs. Online Websites/Platforms

~$19.5B

~$6.5B

~$4B

$0

$5

$10

$15

$20

$25

$30

$35

$ B

illio

ns

Phone Restaurant Direct Online website/platform

Sou rce: Compan y Data , Morgan Stan ley Research , Alph aW ise

Exhibit 27:Exhibit 27: GrubHub/Seamless and the top three QSR Pizza players have roughly 75% of the digital

order/delivery market share

0

500

1,000

1,500

2,000

2,500

Est. Sales of Digital Delivery Order Platforms



21

Restaurant Dollars by Channel

In our survey, which is a representative sample of the US, we asked people questions regarding usage and

frequency rates for food takeout, food delivery, and dining at restaurants. We found that eating out at

restaurants was the most common activity and also the most frequent.

Penetration and Frequency

44% ordering food delivery... In the past six months, 80% of people surveyed have been to a restaurant to

dine in. This compares with 59% who have ordered food for pickup and 44% who have ordered food for

delivery.

...and 11% ordering delivery multiple times per week. In the past six months, 25% of people surveyed dine

at restaurants multiple times per week. This compares with 17% for food pickup orders and 11% for delivery

orders.

Where can this go?

While current online delivery penetration is only 5% of the total addressable market today (defined as pickup

and delivery food spend), we believe online penetration will continue to rise and forecast 9% penetration by

2020.

Exhibit 28:Exhibit 28: Frequency of Ordering vs. Pickup vs. Dining Out in the past 6 months

20%29%

44%

24%

31%

36%

56%

41%

20%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Delivery Pickup Restaurant

% o

f R

esp

on

den

ts

Once or more per week Less than once per week Never



22

Where does GrubHub fit into all of this?

From our previous work, we have found that GrubHub is the largest player in this space at ~$2.4b in annualized

gross food sales, nearly 5x as large as nearest competitors Eat24 (owned by Yelp) and Postmates.

Despite its lead, one thing that has held GrubHub back is the lack of chain restaurants on the platform, which are

key to rounding out supply, especially in locations outside of New York. We note that with GrubHub's recent

investment in delivery, starting with two acquisitions in January 2015 and organic delivery efforts starting in

2Q15, ~8% of gross food sales on GRUB's system is delivered by them. Importantly, with its new delivery

capabilities, GrubHub has been able to sign up a few national chains such as California Pizza Kitchen, Panda

Express, Johnny Rockets, and Boston Market. However, further expansion of branded restaurants onto the GRUB

platform will depend on the economics offered. At its current 20%+ take, GRUB offers an inferior deal to the

consumer-paid fee models of DoorDash and Postmates. The additional service that GRUB provides – namely

brand discovery – is of less value to chain restaurants that believe their brands are powerful enough to attract

demand to their own websites/apps, and would prefer only to contract out the delivery function.

Exhibit 29:Exhibit 29: US Online Penetration 2006-2020E - Restaurant Delivery vs. eCommerce vs. Travel

5%9%10%14%

41%

50%

0%

10%

20%

30%

40%

50%

60%

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

On

lin

e M

ark

et

Pen

etr

ati

on

Restaurant Delivery eCommerce Travel

Sou rce: Compan y data , Alph aW ise, Ph ocu sW righ t, US Cen su s B u reau , ComScore, Fo rrester, Eu romon ito r, Morgan Stan ley Research

Exhibit 30:Exhibit 30: 2015 Delivery Food TAM: GRUB vs. Non-GRUB (in millions)

$2,355

$264

$183

$183$25

$88$20

$882 GrubHub/Seamless

Eat24

Postmates

DoorDash

UberEats

Caviar

Delivery.com

Others



23

App proliferation. Despite the rhetoric of "there's only a limited number of spots on your smartphone, who

would download several restaurant apps?", restaurant downloads are outperforming platforms. This suggests

that there may be a future where consumers download restaurant-specific apps to order food rather than online

order platforms such as GrubHub offering choice, especially as restaurants are able to do more with their app

than just offer a delivery ordering service such as push discounts, enable loyalty programs, enable an instore

payment method, and provide information on locations/nutrition, etc.

Mobile app download and usage behavior – and the ways restaurants and online marketplaces/delivery

platforms attempt to incentivize people to download and (more importantly) use their mobile apps – will also be

Exhibit 31:Exhibit 31: Restaurant Chains in the US by Unit Count

0

5,000

10,000

15,000

20,000

25,000

30,000

1 26 51 76 101 126

# o

f U

nit

s in

a G

iven

Bra

nd

Restaurant Rank by Unit Count

GRUB currently has 4 national chain restaurants on its platform,ranging from ~200 units to ~2,000 units. We believe chainrestaurants of this size represent the "sweet spot" that GRUB can goafter as larger national chains can likely create their own onlineordering and delivery system ecosystem. We estimate that there are~100 chains of this size in the US, meaning that GRUB currently onlyhas 4% penetration.

Sou rce: NPD Grou p , Tech n omic, Morgan Stan ley Research

Exhibit 32:Exhibit 32: Cumulative US App Download estimates (since Jan 2014): Restaurants (blue) vs. Online Platform

(gray)

10.39.7

5.4

4.23.8 3.7

1.9 1.7 1.5 1.40.7 0.5 0.5

0

2

4

6

8

10

12

Cu

mu

lati

ve

Do

wn

loa

ds

(in

Ms)

Sou rce: Sen sor Tow er


24

important as customers using mobile apps are stickier, don’t have to be reacquired through Google, and

(therefore) have a higher lifetime value. So far, Restaurants are winning the app download battle, as cumulative

Restaurant app downloads (since January 2014) are much higher than the online marketplaces/delivery

platforms (see Exhibit 32Exhibit 32 above). GrubHub and Eat24 have had particular success in the Online

Marketplace/Delivery Platform app downloads, while McDonald's and Starbucks standout among the

restaurants. We note that because many of the online players are newer to the market, app download metrics

may have a negative bias. For example Uber Eats was only launched as a standalone app in March 2016. The

Restaurants are meaningfully ahead here, as the 4th largest Restaurant (Dunkin' Donuts) is bigger than

GrubHub (the largest Online player).

Longer Term Tailwinds

Millennials: like online, willing to pay up. Younger people also show a higher willingness to pay delivery

fees and will also find larger fees more acceptable to get the food that they want (see Exhibit 76Exhibit 76 in later section).

Exhibit 33:Exhibit 33: % of People Surveyed that Indicated the Ability to Order Online (Blue) or Over the Phone (Yellow)

was "Very Important" or "Somewhat Important" by Age

79% 82%79%

71%65%

52%

76%

84% 86% 86%91%

94%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

18-24 25-34 35-44 45-54 55-64 65+

% O

f R

esp

on

den

ts t

hat

Ind

icate

d V

ery

Imp

ort

an

t o

r S

om

ew

hat

Imp

ort

an

t

Ability to Order Online Ability to Order over the Phone



25

Delivery - What Consumers WantDelivery - What Consumers Want

To get a sense of the scale of the opportunity for restaurants and online order aggregators, we asked survey

respondents what factors are most important to them with respect to delivery, as well as other questions around

types of cuisine demanded, and expectations on delivery times/prices. Here's what we found:

Accuracy and food condition/quality top list of factors important to consumers in food delivery.

Among the factors most important for food delivery to respondents, order accuracy ranked highest, with 81% of

respondents stating that order accuracy was 'very important.' Following order accuracy, responses based

around food quality (e.g. food delivered in good condition, food is well prepared, and overall food quality) were

the next three attributes which respondents cited were of the highest importance to them, with over 70% of

respondents selecting "very important" for each these attributes. Lower on the list of important factors included

responses regarding pricing, fees associated with delivery, as well as functionality around delivery. At the

bottom of the factors most important to consumers were the ability to order line (36% said "very important")

and the ability to track orders online (24%), though we suspect that with online ordering still in its early stages

of broader utilization (versus phone ordering, for example), the importance of these attributes may rise over

time.

Not surprisingly, weekday dinner is the most common occasion for delivery; lunch and breakfast

represent greatest incremental upside in existing delivery market. With respect to occasions for food

delivery, we asked respondents to select the day-parts during which they have utilized food delivery. Not

surprisingly, the majority of those who have had food delivered did so during dinner. Per our survey, among

those who had ordered food for delivery, 74% of respondents noted using food delivery for weekday dinner,

while 67% used food delivery for weekend dinner. There is a steep drop off for lunch, however, with 29% of

Exhibit 34:Exhibit 34: Order accuracy and food condition top consumers' wish list for delivery; online ordering, tracking

less important today

11%

11%

15%

18%

27%

16%

18%

18%

24%

32%

35%

40%

40%

38%

36%

39%

40%

38%

35%

81%

80%

79%

73%

64%

60%

54%

54%

54%

49%

47%

42%

36%

24%

0% 50% 100%

Orders are fulfilled accurately

Food delivered in good condition

Food is well prepared

High-quality food

Delivered in the promised timeframe

Price of food

Variety of menu items

Quick delivery time

Helpful customer service

Ability to call to order over the phone

Low / no delivery fee

No minimum charge for the order

Ability to order online

Ability to track progress online

Factors of Importance for Food Delivery

Not at all important Low importance Somewhat important Very important



26

respondents stating they have used food delivery for lunch during the weekdays, and 26% on the weekend. And

finally, just under 10% said they used delivery for breakfast on both weekdays and weekends.

Consumers have most often chosen traditional delivery options (e.g. pizza/Asian), sandwiches and

Italian are not far behind. Consumers crave more variety of restaurants when ordering online. When

asking our survey respondents about the type of cuisine recently ordered for delivery (last three months), not

surprisingly, pizza (88%) and Asian (43%) lead all responses. Following the top two, sandwiches (36%) and

Italian (28%) were next, which makes sense to us given that each of these two types of food travel relatively well.

In our view, the difference between the top two (pizza/Asian) and the next two (sandwiches/Italian) underscores

the opportunity for sandwich and Italian chains, which potentially bodes well for PNRA and DRI's Olive Garden

brand. Our findings may also imply that delivery for SBUX and DNKN may not be as impactful as investors

hope given coffee is further down the list (10%), though this could change as delivery availability for coffee

increases.

Among respondents who have used one or more of the online delivery platforms, though, the overwhelming

majority of respondents (>80%) prefer the greatest variety of restaurants to choose from, as opposed to a

curated list of restaurants. This is even more so the case for older respondents (age 45+), where only a low-to-

mid-teens percentage of respondents prefer a limited list of recommended restaurants. Preference given to

greater variety of choice, coupled with expanding availability over time of less traditional delivery cuisines, may

ultimately help drive higher frequency of less traditional delivery, such as coffee and salads.

Exhibit 35:Exhibit 35: Weekday dinner is the most common occasion for delivery; breakfast and lunch have upside

potential

9%

29%

74%

8%

26%

67%

0% 20% 40% 60% 80%

Weekdays - Breakfast

Weekdays - Lunch

Weekdays - Dinner

Weekend - Breakfast

Weekend - Lunch

Weekend - Dinner

Occasions for Food Delivery



27

Consumers expect food delivery in ~30 minutes – but are willing to pay more for faster service. We

asked respondents what they believed was an appropriate delivery time – as well as what are considered to be

fast and long times – and the average response for "appropriate" was just above 30 minutes. Our sense is that

Exhibit 36:Exhibit 36: Pizza, Asian currently dominate delivery, but that's also likely a function of availability.

Sandwiches and Italian have upside, and travel well

88%

43%

36%

28%

27%

21%

21%

10%

5%

Pizza

Asian (Chinese, Sushi, etc)

Sandwiches

Italian

Hamburgers

Mexican

Salads

Coffee

Other

Cuisine for Food Delivery

(Ordered in Last 3 Months)


Exhibit 37:Exhibit 37: Two thirds of consumers say more choice is key to delivery. Younger consumers have less need

for advice from order aggregators

64% 59% 64% 68%57%

70% 64%

18%19%

20%20%

14%

13%14%

17% 22% 16% 12%29%

17% 21%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Total 18-24 25-34 35-44 45-54 55-64 65+

Choice of Restaurants: by Age

Like greatest choice of restaurants, but recommendations from the online

service on best ones

Like limited choice of restaurants, which the online service says are the best ones

to order from

Like greatest choice of restaurants so I can make a decision on my own



28

the belief that ~30 minutes is an appropriate delivery time is linked to promotions that have long been

eliminated by major chains (e.g. Domino's) given liability concerns stemming from delivery driver accidents, but

is nonetheless the standard to which consumers have held restaurants. When asked what a fast delivery time

would be, the average response was ~20 minutes, and we found that more than half of respondents (53%)

would pay $5 or more in delivery fees (excluding tips, on a $30 order) for "fast" delivery (versus 44% who would

pay $5+ for delivery under normal circumstances).

Impact on GRUB. Previously we have written that GRUB's 45-minute average order time leaves little room for

improvement. With half the delivery time reserved for food prep, this only left 20-25 minutes of delivery time to

improve. Given our survey results, we find that increasing the speed of delivery by 5-10 minutes may actually be

of value to consumers, and given responses to delivery fees (~44% said they would pay $5 or more), potentially

represents an opportunity for competitors who are logistics companies trying to get into the restaurant business

vs. GRUB, a restaurant company trying to get into the logistics business.

Exhibit 38:Exhibit 38: Our survey respondents indicated on average that they believe an "appropriate" delivery time is

30 minutes, but we think speed will ultimately drive higher adoption

20.12

30.25

48.88

Consider to be a fast delivery

time

Consider to be an appropriate

delivery time

Consider to be a long delivery

time

Expectations for Food Delivery Time (Mins)



29

Cost remains the biggest barrier to delivery; beyond that, availability of delivery service remains the

biggest barrier to use. Among the reasons why consumers have chosen to not order delivery within the past

six months, cost was the main reason (37% of respondents), followed by two non-delivery barriers – preference

to cook at home (35%) or to eat at the restaurant (29%). Beyond those, lack of availability of delivery (18%), and

length of delivery time (17%), indicate areas of incremental upside for delivery platforms and restaurants as

infrastructure continues to be built out.

Exhibit 39:Exhibit 39: Most consumers are willing to pay $5 for "fast" delivery, based on a $30 order

16% 15%

14%9%

19%

15%

6%

7%

27%

25%

5%

6%

5%11%

7% 11%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Maximum prepared to spend on

delivery fees (excluding tips) for $30

delivery



delivery order guaranteed to be

delivered fast

Expectations for Food Delivery Fees

I refuse to pay delivery fees $1-$2 $3 $4 $5 $6 $7-$8 $9-$10



30

Exhibit 40:Exhibit 40: Expense, lack of availability are key reasons for not using delivery . Both of these barriers can be

fixed with better delivery scale.

37%

23%

18%

17%

17%

14%

7%

6%

5%

Expensive

Prefer to order for take-out

Delivery ordering service not available

Delivery time is too long

Not convenient

Choices of cuisine are limited

Poor food condition (temperature, appearance)

Poor food quality

Poor customer service

Reasons for Not Ordering Food for Delivery in Past 6

Months



31

For Restaurants, Delivery Represents Mostly Opportunities and a FewFor Restaurants, Delivery Represents Mostly Opportunities and a Few

ChallengesChallenges

Increasing online food ordering and delivery represents an opportunity to materially expand the total

addressable market for chain restaurants over time. While we assess the size of the delivery market

opportunity in the near-term at $60B, we think the ultimate opportunity could be as much as four times larger.

Because the majority of consumers who order delivery are using it as a replacement of a home meal, rather than

cannibalizing a dine-in occasion, we think delivery is highly accretive to sales.

The growth of online delivery also comes at an important time: while food away from home has been gaining

share from food at home for many years, recent work we've done with the Morgan Stanley Research economics

team (see North America Insight: Quantifying the Impact of Hispanic Growth on the Consumer WalletNorth America Insight: Quantifying the Impact of Hispanic Growth on the Consumer Wallet,

published on May 23, 2016) suggests that one of the outcomes of the rise in the growth of Hispanic households

is a shift back towards eating in. Delivery is one of the ways in which restaurants can continue to grow their

share in the face of this trend.

The rise in third party online delivery companies represents a windfall for restaurants, as these businesses invest

in infrastructure and customer acquisition to build frequency, and yet do not disintermediate the restaurants

themselves, unlike the rise of e-commerce and their effect on retailers. Many restaurants have enthusiastically

embraced (at least) pilot programs with these startups. Key considerations for restaurants in this area:

Exhibit 41:Exhibit 41: For the past 20+ years, food away from home has been taking share from food at home; while

demographic shifts may cause this trend to reverse, delivery is one of the ways in which restaurants can

continue to grow share

-$2,000

$0

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

Grocery Sales Less Restaurant Sales

Sou rce: Haver, US Cen su s B u reau

Build vs. use existing infrastructure: With the exception of the legacy pizza players, most chain

restaurants, we think, would prefer to let others invest in this area first, building consumer awareness

and better understanding the economic models. Over time, brands that have both store density and

high order frequency may be inclined to consider building their own delivery network.

Order aggregators vs. delivery-only partners: Chain restaurants believe (we think correctly) that

given their brand equity, they do not need the 'discovery' function that order aggregators (such as


32

https://ny.matrix.ms.com/eqr/article/webapp/35ac0c32-f139-11e5-ba5d-4210774b721e?ch=rpint

Delivery – additive to overall restaurant demand. A key question surrounding new restaurant delivery

programs is what kind of dining occasions they are likely to replace. Specifically, are delivered meals

incremental to restaurant sales or do they cannibalize existing business? The reason this matters is that take-

out/delivery sales tend to be less profitable, with less beverage and dessert attachment and higher packaging

costs. However, if the demand is incremental, and/or utilizes excess kitchen capacity at shoulder periods, it can

be materially additive.

To answer this question we asked consumers what kind of meal delivery tends to replace for them (respondents

were not limited to one choice so percentages add up to more than 100%). By far the most frequent response

was “meals eaten at home,” at 68%. All the other responses (“meal eaten in a restaurant," “prepared meal from a

grocery store,” “meal ordered as take out” and “meal picked up without ordering”) were clustered in the ~30-

35%-range, with none higher than 38%. This is a strong result showing that delivery is more likely to replace a

meal at home than dining out--meaning that delivery is accretive to restaurant sales.

GRUB) provide and are therefore less willing to share in the economics with these providers for that

service. Rather, chains would like to drive online sales through their own website or app and have the

last mile delivery done by a third party and paid for by the consumer.

Who pays for delivery: the consumer, the restaurant, or both? Mature models, such as pizza,

suggest that low delivery prices have created the largest end markets by making the product

accessible to the largest number of consumers. Aggregator models such as GRUB charge the

restaurants for the online order aggregator service, but that’s of lower value to branded chains.

Courier models like Postmates and DoorDash charge the consumer, but those rates are currently

high, and may be a barrier to broader usage. Ultimately, restaurants may need to split the cost of

delivery with the consumer, and as long as it is incremental, they have room in the margin structure

to support it.

Delivered product quality: Not all food travels well, and just because a restaurant can do delivery

does not mean it should, based on its assessment of how the food will arrive to the consumer thirty

minutes later.

Risk to brand reputation and willingness to pay: Anecdotally, restaurant chains have expressed

concerns that botched delivery is a significant liability to brand equity. Having third party delivery

removes some of the reputational risk from the brands (i.e. blame goes to the delivery company, not

the restaurant). What's more, many chains believe that if they run their own delivery network, their

ability to charge for delivery is lower than it is for a third party. Our research on actual delivery fees

charged by restaurant chains vs. third party online delivery services bear this out .


33

While delivery should be additive to chain restaurants as a whole, we do not expect it to show the

same level of incrementality for all brands. To dig deeper, for the users of each brand we looked at the

responses for delivery replacing a meal at a restaurant net of responses for replacing a meal at home. We

divided the responses into two baskets: restaurant occasions (“meal eaten at a restaurant,” “meal ordered as

takeout” and “meal picked up without ordering”) and non-restaurant occasions (“meal eaten at home” and

“prepared meal from a grocery store”). We then looked at the users of each brand and subtracted the frequency

they said delivery tended to replace non-restaurant occasions from the frequency it replaced restaurant

occasions. Thus a lower value indicates delivery sales to these customers are more accretive and a higher score

indicates a higher likelihood of cannibalization of restaurant occasions. Note that the question asked customers

of each brand about delivery generically, not about delivery from specific brands. Note also the scale is

somewhat arbitrary because there were more restaurant occasion choices given than non-restaurant choices,

but we think this still demonstrates the relative incrementality of delivery for chain brands.

Exhibit 42:Exhibit 42: AlphaWise Survey Results: Food Delivery Replaces … (% of Respondents)

2%

30%

34%

34%

38%

68%

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

Other

Meal picked up by yourself without ordering aheadof time

Meal ordered as a take-out

Prepared meal from a grocery, convenience orsimilar store

Meal eaten at a restaurant

Meal eaten at home



34

Customers of QSR names showed the highest likelihood that delivery would be accretive while CDR

showed the least. This is not surprising since CDR customers already tend to be heavier users of delivery (see

below) so it makes sense that there would be an increased likelihood that their customers would use delivery to

replace a restaurant meal. SONC, Pizza Hut (YUM), and MCD showed the highest incrementality and at the other

end of the spectrum customers of BJRI and Carrabba’s (BLMN) showed the least likelihood of accretive sales

from delivery. While there is a general pattern favoring accretion from delivery with QSR customers over CDR

customers, and Quick Casual in the middle, a notable outlier is Qdoba (JACK) which fared near the bottom on

this metric. Keep in mind that this analysis only shows the likelihood that an incremental delivery occasion will

be more or less accretive to the restaurant and not the demand for delivery at each brand, which we discuss

below.

Chain vs. independent restaurant delivery. Our survey shows that (based on orders in the past three

months) just above 55% of food delivery share comes from chain restaurants, with just under 45% coming from

independents. While we estimate that chains make up ~45% of the total supply base (based on unit count), we

think that there remains opportunity for chains to take additional share from independents as chain delivery

infrastructure and availability grows, given relative brand strength and recognition. Furthermore, we also found

that nearly 15% of consumers ordered delivery from independents only, presenting potential additional upside

for share gain from customers who are already not utilizing chain delivery offerings.

Exhibit 43:Exhibit 43: Delivery is more likely to cannibalize dine in sales at brands like BJs, Carrabba's and Cheesecake;

less cannibalistic at QSRs

0%

5%

10%

15%

20%

25%

30%

35%

Delivery Replacing Meal Purchased from A Restaurant

(Net)



35

Delivery – what brands work best. In our survey work, we asked the respondents who had eaten at specific

restaurants the likelihood with which they would order delivery, assuming availability. The top three restaurants,

based on the combined percentage of respondents who said they would be somewhat likely and those very

likely to use delivery, were Domino's (90%), Pizza Hut (88%) and Papa John's (86%). This is entirely

unsurprising, particularly considering that when asked about the type of cuisine recently ordered for delivery

(last three months), 88% of our survey respondents selected pizza. Furthermore, the top brands each have

developed and mature delivery businesses, so there may be some bias to those businesses which are already

engaged in delivery. The incremental opportunity, however, exists for the next chains on the list, which

do not currently have developed/fully rolled out delivery: Buffalo Wild Wings (79%), Wingstop (76%)

and Cheesecake Factory (73%).

Exhibit 44:Exhibit 44: Chains already have the advantage over independents with respect to delivery

Independent

44%Chain

56%

Share of Food Delivery Orders in Past 3

Months, by Restaurant Type

14% of consumers

ordered from

independent

restaurants only

21% of consumers

ordered from chain

restaurants only



36

Breaking the above down into the category level, we found that pizza chains were on average the types of chains

that current customers would use delivery (aggregating those responses that indicated "somewhat likely" or

"very likely" to order delivery, assuming availability; 88%). Chicken and wing chains came in second, with an

average of 72% of respondents claiming they would be somewhat likely or very likely to order delivery,

followed closely by sandwich and Italian (each also ~72%). At the opposite end of the spectrum were

hamburger (60%) and coffee (62%) chains, though we suspect this may be partly the result of current consumer

behaviors or expectations.

Exhibit 45:Exhibit 45: Outside of pizza and sandwich chains, the incremental delivery opportunity exists for the next

chains on the list, including Buffalo Wild Wings, Wingstop and Cheesecake Factory

0%

20%

40%

60%

80%

100%

Among Current Consumers, Those Somewhat &

Very Likely to Use Delivery (Assuming Available)



37

Willingness to pay. A second way to infer demand delivery among the customers of individual brands is to

look at their willingness to pay for the service. We looked at the percentage of customers for each brand willing

to pay at least $5 in delivery fees (ex-tips) for a $30 order. At the top end, BJRI and Carrabba’s customers were

the most willing to pay $5 for delivery at 40% and 37% respectively, while QSR customers were generally less

willing to pay. This analysis supports our finding above that BWLD, WING and CAKE customers would order

delivery from these brands if it were available. Each were in the top ten on this metric, with Wingstop in the top

3 at 32%. Also of note, PNRA, despite its higher-income customer base, had the second lowest willingness to

pay, with just 17% prepared to pay a $5 delivery on a $30 order.

Exhibit 46:Exhibit 46: Pizza and chicken/wings topped categories for delivery demand, while hamburger and coffee

ranked lowest, though we suspect this may be partly the result of current consumer behaviors or

expectations

88%

72% 72% 72% 71% 69% 69% 66% 62% 60%

0%

20%

40%

60%

80%

100%

Among Current Consumers, Those Somewhat and Very

Likely to Use Delivery (Assuming Availability)



38

Current consumption behavior by restaurant segment users. As part of our survey, we polled respondents

on the frequency of their current usage of delivery and takeout. We found that, on average, casual dining

consumers were heavier users of delivery (29% ordered 3+ times per week), versus fast casual consumers

(27%) and quick serve consumers (22%). (Note that these groups of consumers are not mutually exclusive.) This

is the same case for takeout, with casual dining consumers used takeout more often (31% took out 3+ times per

week), versus fast casual consumers (29%) and quick serve consumers (25%). This may bode well for casual

dining companies and brands as they roll out delivery options, given casual dining consumers have a higher

propensity to use delivery and takeout (for which delivery could be a substitute).

Build or use existing delivery networks? Restaurants must grapple with two inter-related questions: one, do

they have the frequency of use to justify building a delivery network, and two, can they afford it? We've

answered the frequency question previously. On the ability for restaurants to share some of their delivery

Exhibit 47:Exhibit 47: Most consumers are willing to pay up to $5 for "fast" delivery, based on a $30 order

16% 15%

14%9%

19%

15%

6%

7%

27%

25%

5%

6%

5%11%

7% 11%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%



delivery



delivery order guaranteed to be

delivered fast

Expectations for Food Delivery Fees

I refuse to pay delivery fees $1-$2 $3 $4 $5 $6 $7-$8 $9-$10


Exhibit 48:Exhibit 48: We found that, on average, casual

dining consumers were heavier users of delivery

(29% ordered 3+ times per week)...

27%

22%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Casual Dining Fast Casual Quick Serve

Delivery Usage Frequency

by Restaurant Segment Customers

3+/Wk 1-2/Wk <1/Wk

Source: AlphaWise

Exhibit 49:Exhibit 49: … And this is the same case for

takeout, with casual dining consumers used

takeout more often (31% took out 3+ times per

week)

29%

25%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Casual Dining Fast Casual Quick Serve

Takeout Usage Frequency

by Restaurant Segment Customers

3+/Wk 1-2/Wk <1/Wk

Source: AlphaWise


39

profits with a third party, our admittedly simplistic model below suggests they have ample room in the margin

structure – provided delivery is incremental.

A typical restaurant is largely a fixed cost model, with food costs (~30% of sales) being the only true variable

cost. Cash flow margins at the restaurant level run ~20% typically, +/- 300 bps depending on brand, category

and top line performance.

Incremental sales, however, have a high flow through. Assuming food costs remain 30% (likely slightly higher in

reality given extra packaging, less high margin items like drinks), and assuming that only half of labor is

required, an incremental sale can yield margins of 50-60%. That leaves room, in our view, for restaurants to pay

some of that out to delivery companies and still remain profitable. However, that delivery 'take' can be

significant, with GRUB charging for example 15-25% of sales, depending on if delivery services are being

provided or not. There's not much publicly available detail on the cost structure for restaurants offering delivery,

as its often held close. PNRA recently disclosed that it breaks even on delivery at $3,000/week, or ~6% of sales.

That would suggest that in early days, restaurants need to be confident that delivery sales will remain above

break-evens in order to protect margins, and may wish to experiment first with third-party to better understand

demand patterns.

In considering the economics of delivery, we have also examined delivery fees, which can either be a source of

revenue to delivery aggregators, or a means of defraying costs associated with delivery for restaurants

themselves. In looking at a mature delivery market in QSR pizza, we found that the average delivery fee

(excluding tip) charged by the largest QSR pizza chains was about $3, with slight differences across chains

and/or geographies. Compared to other services, we found that the all-in cost to the consumer for delivery

(delivery fee, driver tip [assumed 15%] and/or service charges) for the largest QSR pizza chains was roughly at

the median of services examined. In comparing various delivery services (we used a $30 order as the baseline to

determine percentage of additional delivery costs), DoorDash and Postmates ranked highest in terms of all-in

costs (>40% of the $30 order charge), while UberEats and Amazon were the lowest. Over time, we would expect

the average all-in delivery charge to trend to where major QSR pizza chains sit (~$3 plus driver tip), given that

Exhibit 50:Exhibit 50: Per our illustrative example below, an order/delivery aggregator can potentially cost a restaurant

between 10-20% of additional margin on incremental food orders

Typical Restaurant Cost & Profit Structure

Sales 100%

Expenses:

Food Costs 30%

Labor Costs 30%

Other Costs 20%

Restaurant Level Margin 20%

* Other costs include rent, insurance, utitilies, etc.

Estimated Incremental Order Profit

W/o Delivery

Aggregator

W/

Order/Delivery

Aggregator

Sales 100% 100%

Incremental Expenses:

Food Costs 30% 30%

Labor Costs 10-20% 10-20%

Order/Delivery Aggregator Commission 0% 10-20%

Restaurant Level Margin 50-60% 30-50%



40

market's maturity. Furthermore, as we noted earlier, there is a steep drop-off of willingness to pay delivery fees

greater than $5, per our survey work. Over time, though, we expect fees/service charges to remain relevant as

delivery availability grows.

Longer-term implications for restaurants include possible slowing of unit growth as dine-in assets are less

productive, or increased delivery-only formats. At scale, a larger delivery business in some cases could be done

out of a commissary, for example. Over time, brands or segments that are less compatible with delivery may

lose share. Wider-spread delivery could potentially negatively impact pizza (DPZ, PZZA) as delivered food share

is spread among more competitors. Key risks to restaurants from tech-enabled delivery firms (GRUB, DoorDash,

Postmates, et al.) includes loss of control of customer relationships, which we see as a key objective of these

Exhibit 51:Exhibit 51: Delivery fees by the top players in QSR pizza average ~$3, but vary across brand and across

regions.

$0.00

$0.50

$1.00

$1.50

$2.00

$2.50

$3.00

$3.50

$4.00

New Jersey Texas California

Example Delivery Fees for Top QSR Pizza Chains

Pizza Hut Domino's Papa John's Average


Exhibit 52:Exhibit 52: An alternative to an order/delivery commission for restaurants operators are fees paid by the

consumer to the order aggregator, restaurant, and/or driver.

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

DoorDash Postmates Top 3

QSR Pizza

GrubHub UberEats Amazon Dine-In at

Restaurant

Est. Delivery Fees & Tips Paid by the Consumer

(% of $30 Order, Incl. Service/Other Fees)



41

start ups.

Detail by BrandDetail by Brand

As mentioned in previous sections, in our survey we asked respondents to what degree of likelihood they would

order food for delivery from restaurants at which they currently eat. We also asked each brand's customers

about their frequency of usage of delivery (i.e. across all restaurants). The below details the intersection of those

customers of each brand which are somewhat or very likely to order delivery from that brand, with the heaviest

users of delivery (three+ times per week, across all restaurants) from each brand's customer base. In our view,

those restaurants that have highest intent along with heavy users of delivery are well positioned should they

develop a delivery system--below are the results by segment.

Quick Service Restaurants

Within QSR, it is no surprise that the three key QSR Pizza chains have the highest intent to order, given maturity

of the pizza delivery market, as well as delivery availability/chain footprint. Beyond QSR pizza, however, the

chain we found to have highest intent to order delivery with the heaviest users of delivery among its customer

base is Wingstop, which among its customers has the heaviest users of delivery (>40%) and highest intent to

utilize delivery if available (76% somewhat and very likely to use delivery).

Fast Casual Restaurants

Within the fast casual segment, aside from Jimmy John's, which already features a mature delivery platform,

Zaxby's and Qdoba ranked highest among the chains when considering intent to use delivery if available and

current heavy delivery users. On a relative basis, Chipotle also scored high on the intent to use delivery if

available question, though its current customer base is roughly average when comparing current delivery

utilization (across all restaurants).

Exhibit 53:Exhibit 53: Beyond QSR pizza, the chain we found to have highest intent to order delivery with the heaviest

users of delivery among its customer base is Wingstop

Domino'sPizza Hut

Papa John'sKFC

Taco Bell

Chick-Fil-A

Wendy's

Burger King

Dunkin'

Donuts

Subway

Sonic

Jack in

the Box

McDonald's

Wingstop

10%

15%

20%

25%

30%

35%

40%

45%

50% 60% 70% 80% 90% 100%Cu

rre

nt

De

live

ry U

tili

zati

on

:

% C

ust

om

ers

Ord

eri

ng

De

live

ry

(An

ywh

ere

) 3

x+/W

ee

k

Somewhat or Very Likely to Order Delivery (From Specific Restaurant

Above) if Available

Current Delivery Utilization vs. Intent

Among QSR Customer Bases



42

Casual Dining Restaurants

Among the casual dining restaurant chains, BJ's, Carrabba's, Cheesecake Factory, and Buffalo Wild Wings all

scored above the peer average when considering intent to use each brand's delivery, as well as current delivery

utilization across all restaurants, with BJ's and Carrabba's boasting the heaviest delivery users among their

respective customer bases. Like Wingstop, Buffalo Wild Wings scores well versus peers when considering intent

to use that brand's delivery if available, a positive sign for the wing/chicken category across both QSR and

casual dining.

Exhibit 54:Exhibit 54: Aside from Jimmy John's, which already has a mature delivery platform, Zaxby's and Qdoba

ranked highest among chains when considering intent to use delivery and current heavy delivery users

Jimmy John'sChipotle

Panera

Zaxby's

Five Guys

Noodles

Qdoba

Starbucks

15%

20%

25%

30%

35%

40%

60% 65% 70% 75% 80% 85%Cu

rre

nt

De

liv

ery

Uti

liza

tio

n:

% C

ust

om

ers

Ord

eri

ng

De

liv

ery

(An

ywh

ere

) 3

x+/W

ee

k


Above) if Available


Among Fast Casual Customer Bases


Exhibit 55:Exhibit 55: Among CDRs, BJ's, Carrabba's, Cheesecake Factory and Buffalo Wild Wings all scored above peer

average considering intent to use the brand's delivery and current delivery utilization

Buffalo Wild

Wings

Olive Garden

Cheesecake

Factory

Texas Roadhouse

Carrabba's

Applebee's

LongHorn

Chili's

BJ's

Outback

Red

Robin

15%

20%

25%

30%

35%

40%

45%

50%

60% 65% 70% 75% 80%Cu

rre

nt

De

liv

ery

Uti

liza

tio

n:

% C

ust

om

ers

Ord

eri

ng

De

liv

ery

(An

yw

he

re)

3x+

/We

ek


Above) if Available


Among CDR Customer Bases



43


44

We See GRUB as BestPositioned to Drive the Online DeliveryWe See GRUB as BestPositioned to Drive the Online Delivery

Marketplaces...Though Investment Is NeededMarketplaces...Though Investment Is Needed

Consumers Want Choice….

Selection matters in online food marketplaces...as our AlphaWise survey data show that selection (aka offering

more restaurants) is material to determining consumer choice (See Exhibit 56Exhibit 56). In all, 64% of consumers say

they prefer online platforms that offer the greatest choice...rather than a curated experience. This is

not surprising or dissimilar to other online marketplace models – online travel agencies, e-commerce

marketplaces like Amazon – that believe their breadth of offerings drives traffic, user growth, and ultimately

conversion.

...Which Is GRUB's Competitive Advantage

This is an important competitive advantage for GRUB given the company's 44,000 estimate restaurants are

~1.5x more than the nearest competitor (Eat24) and anywhere from 15x to 45x more than the other major

players (See Exhibit 57Exhibit 57). While it is relatively easy to add restaurant onto platforms – as relationships are not

exclusive and restaurants will generally add additional platforms if they think it will result in incremental

revenue – for now we see GRUB's supply advantage (and the lack of limited unique supply by other

competitors like UberEats and Amazon) holding back their ability to materially impacting GRUB's

forward growth. For more on this, please see Is GRUB About to Experience the Amazon Effect? Is GRUB About to Experience the Amazon Effect?

Exhibit 56:Exhibit 56: AlphaWise Results: Consumer Preferences - Greatest Choice vs. Limited Choice of Curated

Restaurants

64%

18%

17%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% o

f R

esp

on

den

ts

Like greatest choice ofrestaurants, butrecommendations fromthe online service onbest ones

Like limited choice ofrestaurants, which theonline service says arethe best ones to orderfrom

Like greatest choice ofrestaurants so I canmake a decision on myown



45

https://ny.matrix.ms.com/eqr/article/webapp/5dafa32e-226c-11e6-97e2-3b58b1111250?ch=rpint

So far GRUB's leading restaurant selection and large user base (See Exhibit 58Exhibit 58)have driven its leadership as we

estimate that GRUB currently makes up 23% of the total online food delivery market and 59% of the total

market excluding restaurant-specific delivery (See Exhibit 59Exhibit 59).

GRUB Has Leading Awareness...

AlphaWise data indicate GRUB has a material lead in brand awareness too, as 43% of people are aware of GRUB,

which is anywhere from 2x to 6x more than their competitive subset. (See Exhibit 60Exhibit 60).

Exhibit 57:Exhibit 57: Restaurant Supply by Delivery/Online Ordering Platform

44,000

30,000

? ?

~3,000 ~2,500 ~1,500 ~1,000

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

50,000

# o

f R

est

au

ran

ts o

n P

latf

orm

Sou rce: Compan y data ; Note Postmates an d DoorDash do n ot d isclose restau ran t f igu res

Exhibit 58:Exhibit 58: Comscore Multiplatform Unique

Visitors

6.9

2.6

0.9

0.3

0

1

2

3

4

5

6

7

8

Un

iqu

e V

isit

ors

(in

Ms)

Source: Comscore

Exhibit 59:Exhibit 59: Online Delivery TAM and Largest

Players

24%

23%

19%

14%4%2%

2%

2%

1%

0%0% 9%

Digital Delivery Order Market Share

Domino's

GrubHub/Seamless

Pizza Hut

Papa John's

Jimmy John's

Eat24

Postmates

DoorDash

Caviar

UberEats

Delivery.com

Other Online Platforms

Source: Company data, Morgan Stanley Research


46

...But Why Is GRUB's Awareness to Conversion Ratio Still so Low?

That said, in our view, the more notable figure here is the gap between the percent of consumers who are aware

of GRUB and the percent of consumers who have used GRUB. In all, only ~28% of people who have heard of

GRUB have ever used it...and 24% of them have used it in the past 6 months. GRUB's current uptake is

equal to the ~26% of people who order food online (excluding pizza) and below the 34% of people who order

food online overall (See ExhibitExhibit5959).

And while the "awareness to use gap" was modestly smaller in the Northeast (we believe due to GRUB's strong

position in New York – See Exhibit 62Exhibit 62) at a higher level, the fact that only 26%-32% of people who are

aware of GRUB have used it speaks to an opportunity and challenge for GRUB as it likely needs to

change/improve its offering to continue to drive its topline. After all, given its leading position, in some

ways, as GRUB grows, so too with the overall on-line food delivery market.

Exhibit 60:Exhibit 60: AlphaWise Results: Food Delivery Service Awareness and Usage

7%

7%

7%

8%

10%

12%

13%

20%

43%

2%

3%

2%

4%

5%

3%

4%

7%

12%

1%

2%

2%

4%

4%

2%

3%

6%

11%

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Seamless

OrderUp

Postmates

Caviar

Eat24

UberEats

DoorDash

Delivery.com

GrubHub

% of Respondents

Awareness

Ever Used

Used P6M

Sou rce: Alph aW ise; Note: In th e su rvey, w e made a d istin ction betw een th e Gru bHu b an d Seamless b ran ds

Exhibit 61:Exhibit 61: Online Penetration: Ecommerce vs. Travel vs. Restaurant Delivery

88%

44%

34%

26%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Ecommerce Travel Restaurant DeliveryRestaurant Deliveryex-Pizza

% o

f P

eo

ple

wh

o h

ave T

ran

sacte

d O

nlin

e



47

Once Again, Selection Matters

Despite GRUB's leading selection, ironically, the number/quality/type of restaurants seems to be (in part) the

issue holding back consumer adoption. Indeed, 44% of consumers listed "Limited Restaurant Selection" as one

of the reasons they churned off of GRUB (See Exhibit 63Exhibit 63) . "Limited Restaurant Selection" was the most frequent

answer, and ~1.4X more frequent than the next most common answer (Too Expensive).

While 32% of consumers who churned off GRUB did so because the service was too "expensive", we note that

this is not materially different than the 37% of people overall who indicated they stopped ordering food online

because it was too expensive. We believe this is largely driven by household income and the greater

affordability of eating at home, as 54% of the same group did not dine at a restaurant over the past 6 months. If

anything , we see this "expensive" food barrier acting as a hindrance to other food delivery models built around

consumer fees – like Caviar, DoorDash, and Postmates – more than GRUB. For more on these competitors,

please see "What about the Chain Gang" section below. With this as a background, we believe GRUB needs to

Exhibit 62:Exhibit 62: GrubHub Awareness and Usage Rates by US Region

40%

42%

45%

46%

11%

11%

13%

15%

9%

9%

11%

13%

0% 10% 20% 30% 40% 50%

SOUTH

WEST

MIDWEST

NORTHEAST

Heard Of Used Used in Past 6 months


Exhibit 63:Exhibit 63: AlphaWise Results: Reasons Listed for Churning off a Service, GrubHub

44%

32%28%

18%15% 15% 15% 15% 13%

11%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Sou rce: Alph aW ise;


48

continue to improve its restaurant selection to grow.

The Need to Continue to Invest in Delivery

In our view, GRUB will need to continue to invest in its in-house delivery if it hopes to increase and

geographically broaden its restaurant selection, addressable market, and overall business. After all,

while the company has 13,500+ total restaurants across New York, Chicago, Los Angeles, San Francisco, and

Philadelphia (in aggregate making up 30% of its total restaurant supply), it only has ~30k total restaurants

across the 1,000+ cities it serves across the rest of the entire United States (See Exhibit 64Exhibit 64).

Because, while we estimate GRUB is the largest online food delivery service (See Exhibit 66Exhibit 66), by our math, they

only make up 1% of their total addressable $210bn of consumer spend (See Exhibit 67Exhibit 67). Note that in the figure

below we estimate GRUB's total addressable market to be the $210bn of spend across delivery + takeout . That

said, even if we exclude chains (which will likely take time to garner) we believe GRUB is still addressing an

Exhibit 64:Exhibit 64: GrubHub Restaurant Concentration by City

7,700

2,188

1,697

1,008

917

30,490

New York

Chicago

Los Angeles

San Francisco

Philadelphia

Outside Top 5

Sou rce: Compan y data

Exhibit 65:Exhibit 65: GrubHub Restaurant Supply by City

0

500

1,000

1,500

2,000

2,500

NY

CC

hica

go LA SF

Phi

lade

lphi

aD

CM

iam

iB

osto

nD

enve

rS

an D

iego

Hou

ston

Bal

timor

eP

hoen

ixD

alla

sS

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an J

ose

Mes

a, A

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ustin

Atla

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Long

Bea

chS

acra

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toP

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ndLa

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an A

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Loui

sville

Min

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For

t Wor

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Spr

ings

Tul

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irgin

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each

Det

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Fre

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Om

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El P

aso

OK

CM

emph

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ichi

ta

Resta

ura

nt

Su

pp

ly

1,000 Restaurants

100 Restaurants

In the top 50 cities in the US by population, GrubHub has over 1,000 restaurants on itsplatform in 4 of them (NYC, Chicago, LA, and SF), and between 100 and 999 restaurantsin 20 cities. This means that of the top 50 cities in the US, GrubHub offers fewer than 100restaurants in 26 of them.

7,700+



49

$84bn addressable market...meaning even then they only make up ~3% of the market now .

Introducing Our New Delivery Model

While we have written about GRUB's delivery investment and economics previously in These Unicorns Won'tThese Unicorns Won't

Deliver, Deliver, we are now adding more precision to our delivery investment modeling.

GrubHub started its delivery investment in 2015 (essentially hiring delivery people throughout the top 50

markets) which creates near-term margin pressure as the company guarantees its delivery people an hourly

wage (which we believe is ~$15 including tips). Once the delivery business grows to be large enough (city by

city) GRUB no longer has to pay its delivery crew out of pocket (as they are paid based on the estimated 30%

delivery commission rates).

But...in the near-term we see GRUB continuing to invest in new delivery capacity, which will create an EBITDA

headwind. GRUB has guided to a $10m-20m cash delivery burn in 2016 (we are currently modeling $15m) but

has not commented on 2017. Updating our model, we now expect GRUB to hire more delivery people in 2017

(as it works to grow supply and demand across the top 50 US markets) which will create an estimated $5m

headwind in 2017 and a $1m headwind in 2018. (See Exhibit 68Exhibit 68) We think this is important because shown in

Exhibit 65Exhibit 65, supply in many top 50 cities in the US (by city population) is below 100 restaurants.

While we believe demand for delivery in the largest markets (New York, Chicago, San Francisco, etc.) is likely to

be cannibalistic for now (meaning it will not lead to faster topline growth), over time we believe GRUB's ability

to successfully execute on its delivery strategy outside of the top markets will be important in

determining the company's top-line growth trajectory. Over time, increased restaurant selection in the

Exhibit 66:Exhibit 66: 2015 Online Restaurant Delivery

Gross Food Sales Estimates by Company (figures

in $ Millions)

$2,355

$264

$183

$183$25

$88$20

$882 GrubHub/Seamless

Eat24

Postmates

DoorDash

UberEats

Caviar

Delivery.com

Others


Exhibit 67:Exhibit 67: GrubHub vs. Independent Restaurant

Takeout & Delivery TAM vs. Total Restaurant

Takeout & Delivery TAM (figures in billions)

$2.4B

$84B

$210B

$0

$50

$100

$150

$200

$250

GRUB Total Pickup & Delivery -IndependentRestaurants

Total Pickup & Delivery

With GrubHub reporting ~$2.4b in grossfood sales in 2015, we estimate that itonly has a 1% share of its totaladdressable market and a 3% share ofthe independent restaurant market.


Exhibit 68:Exhibit 68: GRUB Estimated Cash Burn from Delivery (figures in $ Millions)

10

15

5

1 10

0

2

4

6

8

10

12

14

16

2015A 2016E 2017E 2018E 2019E 2020E

Cash

Bu

rn f

rom

Delivery



50

https://ny.matrix.ms.com/eqr/article/webapp/ddf84e36-62c4-11e5-9cda-2aec5fb33735?ch=rpint

large markets may also lead to faster diner growth and faster growth in spend per diner. This is the bull case for

delivery, but we need to see evidence it is working before getting more positive. As such, we intend to

monitor restaurant supply across GRUB's network...and in particular in markets 10-50 very closely

going forward – – as we see increased supply likely being a leading indicator of demand to come.

Indeed, in our base case we see business outside the top seven cities driving 38% of GRUB's forward gross food

sales growth...vs. only 27% in 2015 (See Exhibit 69Exhibit 69). Please see the Appendix for a complete description of our

delivery model.

In all, our new model assumes GRUB grows to 1.8% of its addressable market ($210bn including chains) from

1.1% in 2015...and to 4.6% of the restaurant spend excluding chains by 2020 (Exhibit 70Exhibit 70).

Near-term Investments Could Pressure Profitability

While we agree with GRUB's decision to invest in delivery – given we believe they need to in order to continue

to grow – this pick-up in investment will likely pressure near-term profitability. In all, we are reducing our 2017

non-GAAP EBITDA by 6% and our 2018 EBITDA by 14% (See Exhibit 71Exhibit 71). We now find ourselves 9%/19% below

Consensus 2017/2018 EBITDA (See Exhibit 72Exhibit 72) and remain on the sidelines until we get a sense that GRUB can

deliver top and bottom-line revisions and/or we see evidence of the company's delivery investment leading to a

pick-up in restaurant supply in markets 10-50.

Exhibit 69:Exhibit 69: GrubHub Growth Contributors by Segment, 2014-2020E

Gross Food Sales (in $ Millions)

CAGR Contribution to Growth

2014 2015 2020 2014-2015 2015-2020 2014-2015 2015-2020

Corporate 206 231 294 12% 5% 4% 2%New York Consumer 927 1,161 1,832 25% 10% 41% 26%Top 6 Metro 296 451 1,307 53% 24% 27% 34%Rest of USA 359 511 1,468 42% 23% 27% 38%

Total GRUB 1,787 2,355 4,901 32% 16% 100% 100%

* All Segment Figures are Morgan Stanley estimates. GrubHub does not make segment disclosures


Exhibit 70:Exhibit 70: GRUB Penetration of Restaurant Takeout & Delivery TAM: Independent vs. Total Restaurants

2.2%

2.8%

3.3%

3.7%4.0%

4.3%4.6%

0.9%1.1%

1.3%1.5% 1.6% 1.7% 1.8%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

2014A 2015A 2016E 2017E 2018E 2019E 2020E

GR

UB

Pen

etr

ati

on

of

TA

M (

%)

Independent Takeout & Delivery Total Takeout & Delivery

Sou rce: Compan y data , Morgan Stan ley Research ; Note: w e defin e G ru b 's TAM as th e in depen den t restau ran t sh are (40%) o f th e $210b p icku p an d

delivery market


51

The need to invest in delivery lowers our long-term GRUB earnings power as we have lowered our DCF-based

price target to $26 from $30 (see GRUB: The Cost of WinningGRUB: The Cost of Winning). In all, our $26 PT implies paying 13x 2017

EBITDA for 22% revenue growth ( see Exhibit 73Exhibit 73).

What about the Chain Gang?

Despite GRUB's dominant position in the online restaurant delivery market (we estimate > 50% market share),

GRUB has not had much success with large chains to date. While CPK, Boston Market, and Express has signed

onto GRUB, this has only been a recent development as GRUB builds out its delivery capacity (See Exhibit 74Exhibit 74).

For GRUB's core online marketplace offering, independent restaurants are willing to pay 15% for not only online

ordering execution but to enable customer discovery. There is inherently less value in this service for a chain

restaurant. In addition, GRUB has maintained that any deal with a chain restaurant will have equal economics to

deals with independent restaurants. This is because resulting sales from chains, particularly in top 7

metropolitan areas where GRUB has a good supply of restaurants, is likely to be largely substitutional and not

incremental.

Exhibit 71:Exhibit 71: Morgan Stanley 2017E and 2018E Adj.

EBITDA estimates, Previous vs. Current


GrubHub 2017

Current

MS Est.

Previous MS

est. %/bpVar

Revenue $567 $552 3%

Adj. EBITDA $147 $157 -6%

Margin (%) 26% 28% -240 bps

Adj. EPS $0.93 $0.98 -5%


GrubHub 2018

Current

MS Est.

Previous MS

est. %/bpVar

Revenue $649 $646 0%

Adj. EBITDA $162 $189 -14%

Margin (%) 25% 29% -420 bps

Adj. EPS $1.10 $1.41 -22%


Exhibit 72:Exhibit 72: 2017E and 2018E Adj. EBITDA,

Morgan Stanley estimates vs. Consensus



Revenue $567 $573 -1%

Adj. EBITDA $147 $163 -9%

Margin (%) 26% 28% -240 bps

Adj. EPS $0.93 $1.00 -7%



Revenue $649 $671 -3%

Adj. EBITDA $162 $201 -19%

Margin (%) 25% 30% -496 bps

Adj. EPS $1.10 $1.22 -10%

Source: Thomson One, Morgan Stanley Research

Exhibit 73:Exhibit 73: GRUB EV/EBITDA multiple and long-term revenue growth vs. Internet Platform peers

PCLN

GRPN

JE

SSTKEXPE

ETSY

GRUB

GRUB at PT

0x

5x

10x

15x

20x

25x

0% 5% 10% 15% 20% 25% 30%

EV

/EB

ITD

A m

ult

iple

(2017E

)

3-Year Revenue CAGR (2015-2018E)

Sou rce: Th omson Reu ters, Compan y data , Morgan Stan ley Research


52

http://eqr-methode-mps-editorial.ms.com/eqr/article/webapp/b3ff77ba-2c01-11e6-b804-6e2be5dc4d99?forceUpdate

This lack of interest from chain restaurants to sign on with GRUB has created the opportunity for emerging

logistics players like Postmates and DoorDash, which have signed on various chain partners. These emerging

players have been able to build unique chain supply vs GRUB by 1) offering delivery, which we believe many

chain restaurants do not want to service in-house and 2) shifting the fee burden from the restaurant to the

consumer (See Exhibit 75Exhibit 75).

GrubHub has repeatedly stated that its goal is to make the fees to the consumer as low as possible. However,

while this may enable demand aggregation, this means that the burden of payment falls on the restaurants. In

GrubHub's case, restaurants pay a 15% commission for online ordering, and close to ~25% for an order that is

delivered by GRUB. Other online players, such as Postmates, have opted to place most of the delivery fee on

consumers. This has resulted in a few high-profile relationships including Chipotle and Starbucks as restaurants

are essentially paying nothing (no take rate) and investing nothing as well as these providers also handle

delivery.

Exhibit 74:Exhibit 74: Online Marketplaces and Chain Relationships: GrubHub vs. Postmates vs. DoorDash vs. UberEats

vs. Amazon


Exhibit 75:Exhibit 75: Delivery Fee Structure by Provider; Example for a $30 Meal

30%27.5%

22%

0% 0%

17%15%

25%

41%

46%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

UberEats Amazon GrubHub Postmates DoorDash

Take Rate from Restaurant Fee to Consumer (including Tip)

Sou rce: Compan y data , Morgan Stan ley Research ; Note: F igu res above assu me a 15% tip ; Postmates h as a p rogram w h ere th ey ch arge th e con su mer

less an d p resu mab ly ch arge th e merch an t a take rate; in th e example above, w e u se a typ ical Postmates tran saction , w h ich w e assu me h as n o

merch an t take rate


53

While these businesses continue scaling and our survey data show ~45% of people (and 50%+ of millennials)

are willing to pay $5+ for delivery (See Exhibit 76Exhibit 76) long-term we question whether people will continue to be

wiling to pay for food delivery. So while we are modeling for Postmates and DoorDash to continue to take

share, consumers' willingness to pay these incremental fees and/or Postmates/DoorDash's ability to lower their

consumer fees over time will be important to monitor.

Exhibit 76:Exhibit 76: AlphaWise Survey Results: Maximum Willing to Pay for Delivery Fees for a $30 Order

16%8% 7% 11%

17% 21%31%

39%

40% 38%40%

40%40%

35%

45%52% 55%

49%44% 40%

34%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Total 18-24 25-34 35-44 45-54 55-64 65+

% o

f R

es

po

nd

en

ts

Age

$5+

$1-4

I Refuse



54

AppendixAppendix

Other Survey FindingsOther Survey Findings

Exhibit 77:Exhibit 77: AlphaWise Results: % of Respondents that Answered Very Important for the Respective Attributes

of Food Delivery Services

81% 80% 79%73%

64%60%

54% 54% 54%49% 47%

42%

24%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


Exhibit 78:Exhibit 78: Consumers Indicating Very Satisfied with Option of Restaurants to Dine In vs. Ones that Deliver

28%

41%

36%

46%

27%

43%

18%

28%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Number of restaurants you canorder food for delivery from

Number of restaurants you caneat out

% o

f R

esp

on

den

ts t

hat

were

Very

Sati

sfi

ed

Total

Urban

Suburban

Rural

There is a satisfaction gap between diner options for restaurants to eat out at vs.

restaurants that offer delivery, particularly in the suburbs.



55

Exhibit 79:Exhibit 79: Percentage of Those Surveyed who have used Delivery, Take-Out, or Dined at a Restaurant in the

Past 6 months categorized by Rural, Suburban, and Urban Consumers

50%57%

76%

46%

62%

84%

29%

58%

78%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Delivery Take-out Restaurant

% o

f S

urv

eyees w

ho

have d

on

e t

he

follo

win

g a

cti

vit

y in

th

e p

ast

6m

on

hts

Rural Surburban Urban


Exhibit 80:Exhibit 80: Percentage of Those Surveyed who have used Delivery in the past 6 months categorized by Rural,

Suburban, and Urban Consumers, Pizza-only orders vs. other Delivery

42%

34%

19%

8%11%

10%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Urban Surburban Rural

% o

f S

urv

eyees w

ho

have o

rdere

d f

oo

dd

elivery

in

th

e p

ast

6 m

on

hts

Delivery Non-Pizza Delivery Pizza

Pizza order rates are relatively consistent in urban/ suburban/ ruralareas. However, delivery order rates of non-pizza is much moresuccessful in urban areas.



56


Past 6 months categorized by Income Levels

37%

47%

70%

47%

63%

81%

46%

66%

88%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


% o

f S

urv

eyees w

ho

have d

on

e t

he

follo

win

g a

cti

vit

y in

th

e p

ast

6 m

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hts

Under $25,000 $25,000 - $49,999 $50,000 - $74,999

$75,000 - $99,999 $100,000 - $199,999 $200,000 or more



Past 6 months categorized by Age

60%

68%

80%

22%

47%

85%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%


% o

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18-24 25-34 35-44 45-54 55-64 65+



57

GrubHub Delivery Model DetailGrubHub Delivery Model Detail

Key Assumptions in our GRUB Delivery Model Include:

- We see delivery growing from ~8% of company gross food sales today (including acquired companies) to

~10% in 2016 and 17% by 2020.

- We estimate cash burn from delivery (defined as incremental take rate and delivery fees over the marketplace

business less direct delivery costs paid) will be $15m in 2016 , $5m in 2017 and breakeven by 2020.

- Operations and Support as a percentage of gross food sales for the core marketplace business will remain at

3.5%. Additional Operations and Support expenses include delivery expenses.


Past 6 months categorized by Job Status

55%

62%

84%

54%

66%

81%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Delivery Take-out Restaurant% o

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Retired Part-time employed Other

Self-employed Temporary unemployed Full-time employed

Student



Past 6 months US Region

48%

63%

81%

47%

62%

81%

40%

58%

78%

39%

55%

80%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%


% o

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West South Midwest Northeast



58

Exhibit 85:Exhibit 85: Delivery Model Summary (2015 - 2025)

Morgan Stanley | GRUB

(USD Millions) Delivery Model 2015A 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E

Food Sales Mix (%)

% Pure Marketplace 96.3% 90.5% 87.4% 85.0% 83.4% 82.8% 82.1% 81.4% 80.9% 80.4% 80.0%% of Food Delivered 3.7% 9.5% 12.6% 15.0% 16.6% 17.2% 17.9% 18.6% 19.1% 19.6% 20.0%

% of Food delivered by Acquired Companies 3.0% 5.4% 4.6% 4.0% 3.6% 3.2% 2.9% 2.6% 2.4% 2.2% 2.0%% Food delivered by In-House Delivery 0.7% 4.1% 8.0% 11.0% 13.0% 14.0% 15.0% 16.0% 16.7% 17.4% 18.0%

Implied Food Sales

Pure Marketplace 2,268 2,630 2,988 3,316 3,661 4,058 4,466 4,897 5,332 5,758 6,231Food Delivered 86 277 431 586 728 843 973 1,120 1,257 1,403 1,559Food delivered by Acquisitions 70 157 157 157 157 157 157 157 157 157 157Food delivered by In-House Delivery 17 120 274 429 570 686 816 963 1,100 1,246 1,402

Total Gross Food Sales 2,355 2,907 3,419 3,902 4,388 4,901 5,439 6,016 6,589 7,161 7,791

Delivery Food Sales Annual Run Rate 86 277 431 586 728 843 973 1,120 1,257 1,403 1,559

Op and Support

Company Wide 107 155 187 226 266 303 343 388 431 473 519- Marketplace 80 96 114 131 148 166 185 205 225 245 267- Acquired Delivery Costs 15 25 26 26 26 26 26 26 26 26 26= In-House Delivery 12 33 47 69 92 111 132 157 180 202 226

In-House Delivery P&L

Revenue from Delivery Orders 5.1 35.9 82.1 128.8 171.1 205.8 244.8 288.8 330.1 373.8 420.7Less: Online Marketplace Revenue portion 2.5 17.7 40.1 61.2 79.8 95.3 112.5 131.5 149.5 168.2 188.3= Delivery Revenue 2.6 18.2 42.0 67.6 91.3 110.5 132.3 157.2 180.6 205.6 232.4- Delivery Costs 12.1 33.3 47.1 68.7 92.3 110.7 132.3 157.1 179.9 202.4 226.3= Profit/(Loss) of Delivery (9.5) (15.0) (5.2) (1.1) (1.0) (0.2) 0.0 0.2 0.7 3.2 6.0In-House Delivery Margin -188% -42% -6% -1% -1% 0% 0% 0% 0% 1% 1%Incremental Margins -18% 21% 9% 0% 2% 0% 0% 1% 6% 6%

Profitability per Order

Pure Marketplace $2.94 $3.00 $3.08 $3.03 $3.01 $3.04 $3.06 $3.07 $3.09 $3.11 $3.13Food delivered by Acquisitions $10.77 $9.84 $9.45 $9.45 $9.45 $9.45 $9.45 $9.45 $9.45 $9.45 $9.45Food delivered by In-House Delivery -$16.20 -$3.75 -$0.57 -$0.08 -$0.05 -$0.01 $0.00 $0.01 $0.02 $0.08 $0.14

Total Company $3.07 $3.25 $3.38 $3.33 $3.28 $3.29 $3.29 $3.28 $3.29 $3.30 $3.32

Margin by Delivery Method

Pure Marketplace 76% 76% 76% 75% 75% 75% 75% 74% 74% 74% 74%Food delivered by Acquisitions 32% 47% 45% 45% 45% 45% 45% 45% 45% 45% 45%Food delivered by In-House Delivery -369% -82% -12% -2% -1% 0% 0% 0% 0% 2% 3%

Total Company 70% 67% 67% 65% 64% 63% 62% 61% 61% 60% 60%

Delivery Capacity Utilization Analysis - Organic Only

Gross Food Sales (Organic) 16.8 119.8 273.5 429.2 570.5 686.1 815.9 962.6 1,100.4 1,246.0 1,402.4/Average Order Value ($AOV) $28.7 $29.9 $29.6 $30.0 $30.4 $30.8 $31.1 $31.5 $31.9 $32.2 $32.6= Number of Orders 0.587 4.009 9.236 14.298 18.763 22.292 26.192 30.546 34.525 38.660 43.035/ Orders per Hour 0.6 1.2 1.6 1.6 1.6 1.6 1.6 1.6 1.6 1.6 1.6= # Of Delivery Hours Needed 0.973 3.417 5.818 8.697 11.510 13.685 16.153 18.932 21.447 23.966 26.618

Delivery Costs 12.1 33.3 47.1 68.7 92.3 110.7 132.3 157.1 179.9 202.4 226.3+ Total Tips 2.5 18.0 41.0 64.4 85.6 102.9 122.4 144.4 165.1 186.9 210.4

Tip % 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15%

= Total Pay for Delivery Drivers 14.6 51.2 88.1 133.1 177.9 213.6 254.7 301.5 344.9 389.3 436.7/ Delivery Hours 0.973 3.417 5.818 8.697 11.510 13.685 16.153 18.932 21.447 23.966 26.618= Total Pay/Hour to Delivery Person $15.0 $15.0 $15.2 $15.3 $15.5 $15.6 $15.8 $15.9 $16.1 $16.2 $16.4



59

Price Target $26 Price Target Based On DCF With A 8.6% WACC And 2% Perpetual

Growth Rate. Cost Of Equity Is Based On 1.35 Beta, Risk Free Rate

Of 1.8% And Expected Market Return Of 5.1%.

Bull $44

18x Bull Case 2017E

EV/EBITDA of $196m

GRUB sustains five-year CAGRs of 22% and 23% for revenue and

Adj EBITDA, respectively. Driven by 1) Increased consumer

adoption from: 15% to 20% in New York, 6% to 17% in the Top 6

Metro areas, and 4% to 13% in remaining addressable markets. 2)

Stable organic takes 3) Stable AOVs, and order frequencies at the

individual cohort level 4) GRUB reaches adj. EBITDA margins of

30% by 2020E and 31% by 2025E.

Base $26

13x Base Case 2017E EBITDA

of $147m

GRUB sustains five-year CAGRs of 18% and 13% for revenue and




Declining take rates, AOVs, and order frequencies at the individual

cohort level 3) GRUB adj. EBITDA margins fall to 24% by 2020E

and remain there.

Investment ThesisInvestment Thesis

We believe GRUB is well-positioned for a broad-

based secular shift to online take-out/delivery that

will drive users by 5x and revenue at a 18% 5-year

CAGR.

Our bottom-up model and survey confirm

considerable room exists to increase adoption by

driving awareness, as penetration even in

established geographies like NY at ~15% remains

low. Contrary to concerns, consumer behavior in

third-tier markets is similar to big city patterns.

We forecast EBITDA to grow at a 13% 5-year

CAGR as increased delivery investment offsets

margin expansion from the core marketplace

business.

While the magnitude of bottom line beats may

diminish due to near-term investments, we expect

top-line momentum to place an upward bias on

longer-term estimates and price targets.

Despite increased funding in the food delivery

space recently, our work gives us conviction that

GrubHub is the clear leader in its vertical.

Key Value DriversKey Value Drivers

Market dominance that took over 10 years to

establish, a platform that benefits from network

effect, and increasing scale, serve as deep

competitive moats.

Increasing awareness and healthy order

frequencies at the cohort level should drive orders,

food sales and revenue.

Despite a highly scalable model, delivery

investment should push margins to near 25%.

Potential CatalystsPotential Catalysts

Forward results that showcase GRUB's ability to

continue delivering strong user growth and

sustained top-line momentum.

Evidence that investments in in-house delivery,

which expand GRUB's TAM, begin to pay off.

Risks to Achieving Price TargetRisks to Achieving Price Target

Competition, if AMZN, GOOG, or PCLN

aggressively enter space, and competition from

Yelp (Eat24) proves less benign than expected.

Small city users do not prove valuable.

In-house delivery costs are higher than expected.

Bear $13

8x Bear Case 2017E

EV/EBITDA of $101m

GRUB sustains a five-year CAGR of 12% and 2% for revenue and




Pressured take rates and stable AOVs at the individual cohort level

3) For order frequencies we assume stability in New York and the

top 6 metro areas, but a 300bps annual decline for our rest of USA

cohort. 4) GRUB margins reset in FY17 to 17% due to in-house

delivery investments and rise to 18% by 2025E. .

Risk Reward - GRUBRisk Reward - GRUB

$26.00 (-8%)

$28.25

$13.00 (-54%)

$44.00 (+56%)

0

5

10

15

20

25

30

35

40

45

50

Jun-14 Dec-14 Jun-15 Dec-15 Jun-16 Dec-16 Jun-17

$

WARNINGDONOTEDIT_RRS4RL~GRUB.N~Price Target (Jun-17) Historical Stock Performance Current Stock Price

Sou rce: Th omson O n e, Morgan Stan ley Research


60

FinancialsFinancials

GrubHub Financials

Exhibit 86:Exhibit 86: GrubHub Estimate Changes

Morgan Stanley | GRUB model 2016E

Estimate Changes 1Q16A 2Q16E 3Q16E 4Q16E4Q25E2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E

Total Revenue (New) 112 115 113 132 472 567 649 730 817 908 1,005 1,102 1,198 1,305% change Y/Y 27% 30% 32% 32% 30% 20% 14% 13% 12% 11% 11% 10% 9% 9%

Total Revenue (Old) 112 115 113 132 472 552 646 732 826 926 1,033 1,137 1,237 1,339% change Y/Y 27% 30% 32% 32% 30% 17% 17% 13% 13% 12% 12% 10% 9% 8%

Variance 0% 0% 0% 0% 0% 3% 0% 0% -1% -2% -3% -3% -3% -3%

Non-GAAP EBITDA (New) 32 30 27 37 127 147 162 175 195 215 235 258 283 314% change Y/Y 15% 6% 28% 37% 21% 16% 10% 8% 12% 10% 10% 10% 9% 11%

Non-GAAP EBITDA (Old) 32 30 28 37 127 157 189 221 257 295 338 382 426 471% change Y/Y 15% 6% 29% 38% 21% 23% 20% 17% 16% 15% 15% 13% 12% 11%

Variance 0% 0% -1% 0% 0% -6% -14% -21% -24% -27% -31% -32% -34% -33%

Non-GAAP EPS (New) $0.20 $0.19 $0.18 $0.23 $0.80 $0.93 $1.10 $1.24 $1.35 $1.45 $1.58 $1.69 $1.78 $1.96% change Y/Y 15% 12% 31% 19% 16% 15% 18% 13% 9% 8% 8% 7% 5% 10%

Non-GAAP EPS (Old) $0.20 $0.19 $0.18 $0.23 $0.81 $0.98 $1.41 $1.64 $1.86 $2.10 $2.39 $2.64 $2.87 $3.15% change Y/Y 15% 11% 32% 19% 16% 21% 45% 16% 14% 13% 13% 11% 9% 10%

Variance 0% 0% -1% 0% 0% -5% -22% -24% -27% -31% -34% -36% -38% -38%



61

Exhibit 87:Exhibit 87: GrubHub Revenue Drivers

Morgan Stanley | GRUB

(USD Millions) Operating Model 2015A 2016E 2017E 2018E 2019E 2020E

TotalAddressable Population 110 110 111 112 112 113x Penetration % 6% 8% 9% 10% 12% 13%= LTM Active Diners 6.8 8.3 9.9 11.4 12.9 14.5x Orders per LTM Active Diner 12.3x 11.7x 11.4x 11.1x 10.9x 10.8x= Total Orders 82.9 97.5 112.4 127.0 141.4 156.4x $ AOV $28.4 $29.8 $30.4 $30.7 $31.0 $31.3YoY % Growth 6% 5% 2% 1% 1% 1%

= Gross Food Sales 2,355 2,907 3,419 3,902 4,388 4,901x % Commission 15.4% 16.2% 16.6% 16.6% 16.6% 16.7%YoY Change (in bp) 116bp 85bp 37bp 3bp 2bp 2bp

= Revenue 362 472 567 649 730 817

Y/Y ChangePenetration % (BPS) 154 bps 140 bps 136 bps 132 bps 131 bps 131 bpsLTM Active Diners 34% 23% 19% 15% 13% 12%Orders per LTM Active Diner -7% -5% -3% -2% -2% -1%Total Orders 24% 18% 15% 13% 11% 11%$ AOV 6% 5% 2% 1% 1% 1%Gross Food Sales 32% 23% 18% 14% 12% 12%% Commission (BPS) - Y/Y 116 bps 85 bps 37 bps 03 bps 02 bps 02 bps

Revenue 43% 30% 20% 14% 13% 12%

Adj. EBITDA 33% 21% 16% 10% 8% 12%YoY % Growth 24% 17% 15% 13% 11% 11%

CorporateLTM Active Diners 0.1 0.1 0.1 0.1 0.1 0.1x Orders per LTM Active Diner 100.4x 101.0x 102.0x 103.0x 104.1x 105.1x= Total Orders 8.1 8.3 8.6 8.8 9.1 9.4x $ AOV $28.4 $29.8 $30.4 $30.7 $31.0 $31.3= Gross Food Sales 231 248 261 272 283 294x % Commission 14.2% 14.3% 14.5% 14.5% 14.5% 14.5%= Revenue 33 36 38 39 41 43

Y/Y ChangeLTM Active Diners 2% 2% 2% 2% 2% 2%Orders per LTM Active Diner 3% 1% 1% 1% 1% 1%Total Orders 6% 3% 3% 3% 3% 3%$ AOV 6% 5% 2% 1% 1% 1%Gross Food Sales 12% 8% 5% 4% 4% 4%% Commission (BPS) - Y/Y 08 bps 15 bps 15 bps 00 bps 00 bps 00 bpsRevenue 13% 9% 6% 4% 4% 4%

New York - ConsumerAddressable Population 13 13 13 13 13 13x Penetration % 14.7% 15.7% 16.5% 17.3% 17.9% 18.4%= LTM Active Diners 1.9 2.1 2.2 2.3 2.4 2.5x Orders per LTM Active Diner 21.2x 21.7x 22.3x 22.8x 23.2x 23.7xNet Additions 0.8 0.6 0.5 0.5 0.5 0.4

= Total Orders 40.9 44.8 48.7 52.3 55.5 58.4x $ AOV $28.4 $29.8 $30.4 $30.7 $31.0 $31.3= Gross Food Sales 1,161 1,336 1,481 1,607 1,722 1,832x % Commission 15.5% 15.8% 16.0% 16.0% 15.9% 15.9%= Revenue 180 211 237.0 256.3 273.7 290.4

Y/Y ChangePenetration % (BPS) 171 bps 93 bps 86 bps 74 bps 60 bps 53 bpsLTM Active Diners 14% 7% 6% 5% 4% 3%Orders per LTM Active Diner 4% 3% 2% 2% 2% 2%Total Orders 18% 10% 9% 7% 6% 5%$ AOV 6% 5% 2% 1% 1% 1%Gross Food Sales 25% 15% 11% 8% 7% 6%% Commission (BPS) - Y/Y 47 bps 30 bps 20 bps -05 bps -05 bps -05 bpsRevenue 29% 17% 12% 8% 7% 6%

Top 6 Metro - ConsumerAddressable Population 28 28 28 29 29 29x Penetration % 6.2% 8.4% 10.0% 11.5% 13.1% 14.6%= LTM Active Diners 1.8 2.4 2.8 3.3 3.8 4.2Net Additions 0.4 0.6 0.5 0.5 0.5 0.5

x Orders per LTM Active Diner 9.1x 9.0x 9.3x 9.5x 9.7x 9.9x= Total Orders 15.9 21.4 26.4 31.4 36.5 41.7x $ AOV $28.4 $29.9 $30.4 $30.7 $31.0 $31.3= Gross Food Sales 451 638 803 964 1,133 1,307x % Commission 16.3% 17.3% 17.7% 17.7% 17.7% 17.7%= Revenue 73 111 142.2 170.7 200.5 231.3

Y/Y ChangePenetration % (BPS) 157 bps 214 bps 162 bps 154 bps 155 bps 149 bpsLTM Active Diners 34% 35% 20% 16% 14% 12%Orders per LTM Active Diner 7% 0% 3% 2% 2% 2%Total Orders 44% 35% 24% 19% 16% 14%$ AOV 6% 5% 2% 1% 1% 1%Gross Food Sales 53% 41% 26% 20% 17% 15%% Commission (BPS) - Y/Y 292 bps 108 bps 36 bps 00 bps 00 bps 00 bpsRevenue 86% 51% 29% 20% 17% 15%

Rest of USA - ConsumerAddressable Population 69 69 69 70 70 70x Penetration % 4.4% 5.5% 6.9% 8.2% 9.6% 11.0%= LTM Active Diners 3.0 3.8 4.8 5.7 6.7 7.7Net Additions 1.0 0.8 1.0 1.0 1.0 1.0

x Orders per LTM Active Diner 6.0x 6.0x 6.0x 6.0x 6.0x 6.1x= Total Orders 18.0 23.0 28.7 34.5 40.3 46.8x $ AOV $28.4 $29.8 $30.4 $30.7 $31.0 $31.3= Gross Food Sales 511 685 874 1,059 1,251 1,468x % Commission 14.8% 16.7% 17.2% 17.2% 17.2% 17.2%= Revenue 76 114 150.3 182.1 215.2 252.5

Y/Y ChangePenetration % (BPS) 150 bps 119 bps 135 bps 134 bps 135 bps 138 bpsLTM Active Diners 53% 28% 25% 20% 17% 15%Orders per LTM Active Diner -12% 0% 0% 0% 0% 1%Total Orders 34% 28% 25% 20% 17% 16%$ AOV 6% 5% 2% 1% 1% 1%Gross Food Sales 42% 34% 28% 21% 18% 17%% Commission (BPS) - Y/Y 198 bps 188 bps 52 bps 00 bps 00 bps 00 bpsRevenue 64% 51% 31% 21% 18% 17%



62

Exhibit 88:Exhibit 88: GrubHub Annual Income Statement

Morgan Stanley | GRUB Model

(USD Millions) Proforma to 3Q13A 2015A 2016E 2017E 2018E 2019E 2020E 2015-2020E CAGRIncome Statement

Revenue 361.8 471.6 567.3 648.5 730.4 816.8 18%

- Sales & Marketing 91.2 121.3 149.2 165.4 183.3 201.8 17%

- Operations & Support 107.4 154.6 187.2 225.7 266.3 302.6 23%

- Tech and Content 32.8 41.9 48.8 55.1 61.0 67.0 15%

- General & Administrative 40.5 50.9 60.1 68.1 76.0 84.1 16%

- Depreciation & Amortization 28.0 33.0 39.7 45.4 51.1 53.1 14%

= Operating Income 61.9 69.8 82.3 88.8 92.7 108.2 12%

+ Other Income / (Expense), Net -- -- -- -- -- --

+ Other Non-Operating Gains / (Losses) -- -- -- -- -- --

= Pretax Income 61.9 69.8 82.3 88.8 92.7 108.2 12%

+ Income Tax Provision (23.9) (29.8) (28.8) (31.1) (32.4) (37.9) 10%

= Net Income (Loss) 38.1 40.0 53.5 57.8 60.2 70.4 13%

- Preferred Stock Tax Distributions -- -- -- -- -- --

= Net Income (Loss) Attributable to Common 38.1 40.0 53.5 57.8 60.2 70.4 13%

GAAP Basic EPS $0.45 $0.47 $0.62 $0.67 $0.69 $0.80 12%

GAAP Diluted EPS $0.44 $0.46 $0.61 $0.66 $0.68 $0.79 12%

Non-GAAP EPS $0.69 $0.80 $0.93 $1.10 $1.24 $1.35 14%

Basic Shares Outstanding 84.1 85.0 85.8 86.6 87.5 88.4 1%

Diluted Shares Outstanding 85.7 86.1 87.0 87.8 88.7 89.6 1%

Non-GAAP Operating Income (x-SBC) 76.9 93.7 107.8 116.7 123.4 141.7 13%

Adj. EBITDA (x-SBC) 105.0 126.8 147.5 162.1 174.5 194.8 13%

Non-GAAP Net Income 59.4 69.3 80.8 96.6 109.9 121.1 15%

as % of Revenue (GAAP)

Sales & Marketing 25% 26% 26% 26% 25% 25%

Operations & Support 30% 33% 33% 35% 36% 37%

Tech and Content 9% 9% 9% 9% 8% 8%

General & Administrative 11% 11% 11% 11% 10% 10%

Depreciation & Amortization 8% 7% 7% 7% 7% 7%

Operating Margin 17% 15% 15% 14% 13% 13%

EBITDA 25% 22% 22% 21% 20% 20%

as % of Revenue (Non-GAAP)

Non-GAAP Operating Margin 21% 20% 19% 18% 17% 17%

Adj. EBITDA 29% 27% 26% 25% 24% 24%

Incremental Adj. EBITDA Margin 24% 20% 22% 18% 15% 24%

Non-GAAP Net Income 16% 15% 14% 15% 15% 15%

Y/Y Change

Revenue 43% 30% 20% 14% 13% 12%

Sales & Marketing 38% 33% 23% 11% 11% 10%

Operations & Support 72% 44% 21% 21% 18% 14%

Tech and Content 30% 28% 16% 13% 11% 10%

General & Administrative 25% 26% 18% 13% 12% 11%

Depreciation & Amortization 24% 18% 20% 14% 13% 4%

Operating Income 38% 13% 18% 8% 4% 17%

Pretax Income 38% 13% 18% 8% 4% 17%

Income Tax Provision 15% 25% -3% 8% 4% 17%

Net Income (Loss) 57% 5% 34% 8% 4% 17%

Net Income (Loss) Attributable to Common 59% 5% 34% 8% 4% 17%

GAAP Basic EPS 36% 4% 32% 8% 3% 16%

GAAP Diluted EPS 50% 5% 32% 7% 3% 16%

Non-GAAP EPS 40% 16% 15% 18% 13% 9%



63

Exhibit 89:Exhibit 89: GrubHub Balance Sheet


(USD Millions) Proforma to 3Q13A 2015A 2016E 2017E 2018E 2019E 2020E

Balance Sheet

ASSETS

Cash & Cash Equivalents 169.3 209.6 333.5 453.0 581.4 721.8

Short term Investments 141.4 121.1 121.1 121.1 121.1 121.1

Accounts Receivable 42.1 55.4 66.7 76.2 85.9 96.0

Deferred Taxes, Current -- -- -- -- -- --

Prepaid Expenses 3.5 4.5 5.5 6.4 7.3 8.1

Other Current Assets -- -- -- -- -- --

Total Current Assets 356.3 390.7 526.8 656.8 795.7 947.1

Property & Equipment, Net of D&A 19.1 24.2 25.3 26.3 27.2 28.0

Goodwill 396.2 396.2 396.2 396.2 396.2 396.2

Intangible Assets, Net of Amortization 285.6 267.9 248.3 225.6 199.8 174.8

Other Assets, Non-Current 3.1 68.4 68.4 68.4 68.4 68.4

Total Assets 1,060.2 1,147.4 1,265.0 1,373.3 1,487.3 1,614.4

LIABILITIES & SHAREHOLDERS EQUITY

Restaurant Food Liability 64.3 84.8 113.5 129.7 146.1 163.4

Accounts Payable 8.2 11.2 13.5 16.3 19.2 21.9

Accrued Payroll 4.8 3.8 3.8 3.8 3.8 3.8

Taxes Payable 0.4 0.4 0.4 0.4 0.4 0.4

Restructuring Accrual -- -- -- -- -- --

Other Accruals 11.8 15.4 23.0 26.6 30.4 33.8

Total Current Liabilities 89.6 115.6 154.2 176.8 199.9 223.2

Deferred Taxes, Non-Current 87.6 84.3 84.3 84.3 84.3 84.3

Other Accruals, Non-Current 5.5 5.5 5.5 5.5 5.5 5.5

Total Liabilities 182.7 205.4 244.0 266.6 289.7 313.0

Stockholders' Equity:

Convertible Preferred Stock -- -- -- -- -- --

Common Stock 0.0 0.0 0.0 0.0 0.0 0.0

Treasury Shares (CS) -- -- -- -- -- --

Accumulated Other Comprehensive Income (Loss) (0.6) (0.8) (0.8) (0.8) (0.8) (0.8)

Additional Paid-in Capital 759.3 783.9 809.5 837.3 868.0 901.5

Retained Earnings (Deficit) 118.9 158.9 212.4 270.1 330.4 400.7

Total Stockholders' Equity 877.6 942.0 1,021.0 1,106.7 1,197.6 1,301.4

Total Liabilities and Stockholders' Equity 1,060.2 1,147.4 1,265.0 1,373.3 1,487.3 1,614.4



64

ValuationValuation

Exhibit 90:Exhibit 90: GrubHub Cash Flow Statement


(USD Millions) Proforma to 3Q13A 2015A 2016E 2017E 2018E 2019E 2020ECash Flow Statement

Operating Activities

Net Income (Loss) 38.1 40.0 53.5 57.8 60.2 70.4

Depreciation 5.1 8.5 11.3 13.0 14.6 16.3

Provision for Doubtful Accounts 0.9 0.4 -- -- -- --

Loss on Disposal of Fixed Assets -- -- -- -- -- --

Deferred Taxes (3.8) (3.3) -- -- -- --

Amortization of Intangibles 22.9 24.5 28.4 32.4 36.5 36.8

Amortization on Tenant Allowance (0.2) -- -- -- -- --

Stock-based Compensation 13.5 23.1 25.5 27.9 30.7 33.5

Deferred Rent and Others 0.7 0.0 -- -- -- --

Funds from Operations (FFO) 77.1 93.3 118.7 131.0 142.1 156.9

Changes in Working Capital (32.4) 9.5 26.3 12.2 12.5 12.3

Operating Cash Flow 44.8 102.8 145.0 143.3 154.6 169.3

Investing Activities

Capitalized Website & Development Costs (7.1) (8.0) (8.7) (9.8) (10.7) (11.7)

Purchases of Property & Equipment (4.2) (10.4) (12.4) (14.0) (15.5) (17.1)

Purchases/ (Proceeds) of investments (30.8) (0.3) -- -- -- --

Others (74.3) (44.8) -- -- -- --

Investing Cash Flow (116.4) (63.5) (21.1) (23.7) (26.3) (28.8)

Financing Activities

Proceeds from Issuances -- -- -- -- -- --

Proceeds from Exercise of Stock Options 11.9 1.0 -- -- -- --

Excess Tax Benefit Related to Stock-based Compensation27.8 10.6 -- -- -- --

Taxes Paid Related to Net Settlements of Stock-based Compensation Awards(0.3) (0.7) -- -- -- --

Repurchase of Common Stock -- (9.8) -- -- -- --

Preferred Stock Tax Distributions -- -- -- -- -- --

Others -- -- -- -- -- --

Financing Cash Flow 39.4 1.2 -- -- -- --

Effects of Exchange Rate Changes on Cash & Equivalents(0.3) (0.2) -- -- -- --

Net Increase (Decrease) in Cash & Equivalents (32.5) 40.3 123.9 119.5 128.3 140.4

+ Cash & Equivalents - BOP 201.8 169.3 209.6 333.5 453.0 581.4

+ Other -- -- -- -- -- --

= Cash & Equivalents - EOP 169.3 209.6 333.5 453.0 581.4 721.8



65

Exhibit 91:Exhibit 91: GrubHub DCF Valuation

Morgan Stanley | GRUB DCF 2015A 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E TY - 2026

Discounted cash flow analysisNet revenue 362 472 567 649 730 817 908 1,005 1,102 1,198 1,305 1,331

% change Y/Y 43% 30% 20% 14% 13% 12% 11% 11% 10% 9% 9% 2%

Adjusted EBITDA 105 127 147 162 175 195 215 235 258 283 314 320- Cash taxes (22) (24) (29) (31) (32) (38) (43) (47) (55) (65) (73)+ Changes in working capital (32) 10 26 12 13 12 13 14 14 14 15- Capex (11) (18) (21) (24) (26) (29) (31) (34) (37) (39) (42)- Stock-based compensation (13) (23) (26) (28) (31) (33) (36) (39) (42) (44) (47)= Unlevered free cash flow (UFCF) 26 70 98 92 98 107 117 129 139 148 167 170

% of revenue 7% 15% 17% 14% 13% 13% 13% 13% 13% 12% 13% 13%

EBITDA Margin 29% 27% 26% 25% 24% 24% 24% 23% 23% 24% 24% 24%UFCF / EBITDA 25% 55% 67% 57% 56% 55% 54% 55% 54% 52% 53% 53%

Morgan Stanley - GRUB DCF analysis Equity Value: WACC vs. Perpetual GrowthPV of FCF 750 $2,287 7.6% 8.1% 8.6% 9.1% 9.6%+ NPV of terminal value 1,206 1.5% 2,499 2,335 2,196 2,078 1,977= Enterprise value 1,956 2.0% 2,633 2,444 2,287 2,154 2,040- Debt -- 2.5% 2,794 2,573 2,392 2,241 2,113+ Cash 331= Equity value 2,287 Equity Value per Share: WACC vs. Perpetual Growth/ Fully Diluted Shares 86.6 ####### 7.6% 8.1% 8.6% 9.1% 9.6%= Equity value per share $26 1.5% 29 27 25 24 23Implied terminal EBITDA multiple 8.2x 2.0% 30 28 26 25 24

2.5% 32 30 28 26 24DCF Valuation AssumptionsValuation Date 1 Yr ForwardWACC 9%Perpetual Growth Rate 2%



66

Valuation Methodology and RisksValuation Methodology and Risks

For valuation methodology and risks associated with any price targets, ratings or recommendations referenced

in this research report, please contact the Client Support Team as follows: US/Canada +1 800 303-2495; Hong

Kong +852 2848-5999; Latin America +1 718 754-5444 (U.S.); London +44 (0)20-7425-8169; Singapore +65

6834-6860; Sydney +61 (0)2-9770-1505; Tokyo +81 (0)3-5424-4349. Alternatively you may contact your

investment representative or Morgan Stanley Research at 1585 Broadway, (Attention: Research Management),

New York, NY 10036 USA


67

More on AlphaWiseMore on AlphaWise

AlphaWise conducts proprietary evidence-based investment research. Click to read AlphaWise Market ResearchMarket Research

and Web Research Web Research whitepapers on evidence gathering. For further information, please contact

[email protected].

Other Recent Morgan Stanley Research Based on AlphaWise Evidence

EU Leisure Jamie Rollo June 7, 2016

"Cruise Chat": Mixed Performance Continues

Our monthly travel agent and webscraping survey shows strong demand for US-based cruises in

May, but weakness still in Europe, and weaker yields in Q2 relative to Q1.

NA Hardlines Simeon Gutman June 5, 2016

Survey Says: E-Commerce Making Bigger Dent in Home Furnishings; Now ~20% of the Market

Home Furnishings sales backdrop solid but sales diffusion and accelerating channel shift suggest

further challenges for the public retailers in the segment. Market share erosion for BBBY points to a

flat Q1 comp and a $0.02 EPS miss

AP Gaming Praveen Choudhary June 2, 2016

Asian Gaming: AlphaWise Survey – Gaming recovery much more tied to the economy than

consensus assumes

Our AlphaWise survey of 1,000 Chinese gamblers reveals that UnionPay, FX, and Shanghai Disney

are all near-term threats to Macau, offset by potential for Wynn Palace to spur renewed interest.

Downgrade MPEL to EW; upgrade Wynn Macau to EW.

EU Retail Edouard Aubin May 31, 2016

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In our April survey, we had seen Asda improving its pricing relative to Tesco (to 4.1%, from 2.2% in

March). Our sample basket shows a gap narrowing to only 2.0% in May (average is 3.7% since July

2011).

AP Macro Sheela Rathi May 30, 2016

Job Growth Pickup – A Precursor to Consumption Recovery

In March 2011, we launched the AlphaWise City Vibrancy Index (ACVI) to track the growth trends in

the consumption economy. The index growth has remained strong through the period, with

doubling of the index value indicating a robust growth trend in the consumption infrastructure.

NA Retail Kimberly Greenberger May 23, 2016

Bag Check Round 3: Premium Handbag Segment Continues to Take Share


68

http://link.articles.morganstanley.com/?b=Y2g9T3V0bG9vayUyMEJsYXN0bWFpbCZjdT02NUNGVyZpZD01MDQyMzY%3D&d=f%2Fhq3im9n0-3on2-g000-a3c8-d8d3855a5100%3Fstore%3D0%26d%3DUwBSZXNlYXJjaAA1MDQyMzY%253D%26user%3Dc6ksxki652apa-0%26__gda__%3D1498855257_b8505794424a5f7ee2e9f0446ae74a40&s=f%2Fhq3im9n0-3on2-g002-a3c8-d8d3855a5100%3Fstore%3D0%26d%3DUwBSZXNlYXJjaFNXRgA1MDQyMzY%253D%26user%3Dc6ksxki652apa-2%26__gda__%3D1498855257_8f121edff8e6367ebaafc7bf8ffdbab7

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of women purchasing a handbag over $100 continues to grow, especially among Millennials

EU Retail Nicholas Ashworth May 19, 2016

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Magnit is its own biggest competitor, and the biggest competitor to peers. But Dixy and X5 have

more federal competitor overlap. Competition is rising; overlap will increase (especially given X5's

strong logistics improvement). ROCE is unlikely to grow now for most. We lower PTs. X5 OW,

Magnit UW.

NA REITs Richard Hill May 16, 2016

Malls Aren't Dying (Just Some of Them)

We utilize proprietary big data in collaboration with Morgan Stanley's AlphaWise to analyze REIT

portfolios. While it's intuitive that more productive malls are located in more densely populated

areas with more affluent demographics, our analysis provides precise figures to measure the

magnitude of difference across portfolios.

Please note that all important disclosures including personal holdings disclosures and Morgan Stanley

disclosures appear on the Morgan Stanley public website at www.morganstanley.com/researchdisclosures.www.morganstanley.com/researchdisclosures.


69

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http://www.morganstanley.com/researchdisclosures

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to buy or sell a stock should depend on individual circumstances (such as the investor's existing holdings) and other considerations.

Global Stock Ratings Distribution(as of May 31, 2016)The Stock Ratings described below apply to Morgan Stanley's Fundamental Equity Research and do not apply to Debt Research produced by the Firm.For disclosure purposes only (in accordance with NASD and NYSE requirements), we include the category headings of Buy, Hold, and Sell alongside ourratings of Overweight, Equal-weight, Not-Rated and Underweight. Morgan Stanley does not assign ratings of Buy, Hold or Sell to the stocks we cover.Overweight, Equal-weight, Not-Rated and Underweight are not the equivalent of buy, hold, and sell but represent recommended relative weightings (seedefinitions below). To satisfy regulatory requirements, we correspond Overweight, our most positive stock rating, with a buy recommendation; we correspondEqual-weight and Not-Rated to hold and Underweight to sell recommendations, respectively.

COVERAGE UNIVERSE INVESTMENT BANKING CLIENTS (IBC)

STOCK RATING CATEGORY COUNT % OF TOTAL COUNT % OF TOTAL

IBC

% OF RATING

CATEGORY

Overweight/Buy 1177 35% 283 40% 24%

Equal-weight/Hold 1431 43% 337 47% 24%

Not-Rated/Hold 78 2% 7 1% 9%

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TOTAL 3,349 714

Data include common stock and ADRs currently assigned ratings. Investment Banking Clients are companies from whom Morgan Stanley receivedinvestment banking compensation in the last 12 months.

Analyst Stock RatingsOverweight (O). The stock's total return is expected to exceed the average total return of the analyst's industry (or industry team's) coverage universe, on arisk-adjusted basis, over the next 12-18 months.Equal-weight (E). The stock's total return is expected to be in line with the average total return of the analyst's industry (or industry team's) coverageuniverse, on a risk-adjusted basis, over the next 12-18 months.Not-Rated (NR). Currently the analyst does not have adequate conviction about the stock's total return relative to the average total return of the analyst'sindustry (or industry team's) coverage universe, on a risk-adjusted basis, over the next 12-18 months.Underweight (U). The stock's total return is expected to be below the average total return of the analyst's industry (or industry team's) coverage universe, ona risk-adjusted basis, over the next 12-18 months.Unless otherwise specified, the time frame for price targets included in Morgan Stanley Research is 12 to 18 months.

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circumstances and objectives of those who receive it. Morgan Stanley recommends that investors independently evaluate particular investments andstrategies, and encourages investors to seek the advice of a financial adviser. The appropriateness of an investment or strategy will depend on an investor'scircumstances and objectives. The securities, instruments, or strategies discussed in Morgan Stanley Research may not be suitable for all investors, andcertain investors may not be eligible to purchase or participate in some or all of them. Morgan Stanley Research is not an offer to buy or sell or thesolicitation of an offer to buy or sell any security/instrument or to participate in any particular trading strategy. The value of and income from yourinvestments may vary because of changes in interest rates, foreign exchange rates, default rates, prepayment rates, securities/instruments prices, marketindexes, operational or financial conditions of companies or other factors. 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INDUSTRY COVERAGE: Restaurants

COMPANY (TICKER) RATING (AS OF) PRICE* (06/13/2016)

John Glass

BJ's Restaurants, Inc. (BJRI.O) E (09/16/2015) $46.04Bloomin' Brands Inc (BLMN.O) E (11/05/2015) $18.79Brinker International Inc. (EAT.N) E (06/26/2013) $46.30Buffalo Wild Wings, Inc. (BWLD.O) E (08/12/2014) $144.28Chipotle Mexican Grill, Inc. (CMG.N) O (09/30/2013) $394.00Darden Restaurants Inc. (DRI.N) E (10/30/2014) $67.73Dominos Pizza Inc. (DPZ.N) E (03/27/2008) $124.79Dunkin Brands Group Inc (DNKN.O) E (09/06/2011) $45.19El Pollo Loco Holdings (LOCO.O) E (12/03/2014) $11.28Jack in the Box Inc. (JACK.O) O (04/08/2016) $83.59McDonald's Corporation (MCD.N) E (10/06/2014) $122.99Noodles & Co (NDLS.O) E (03/30/2014) $9.54Panera Bread Company (PNRA.O) O (03/08/2016) $211.92Red Robin Gourmet Burgers, Inc. (RRGB.O) E (01/09/2013) $53.52Restaurant Brands International, Inc. (QSR.N) E (04/08/2016) $42.13Shake Shack Inc (SHAK.N) U (07/07/2015) $33.46Sonic Corp. (SONC.O) E (06/19/2013) $28.16Starbucks Corp. (SBUX.O) O (03/07/2011) $55.04Texas Roadhouse, Inc. (TXRH.O) U (11/05/2015) $45.38The Cheesecake Factory, Inc. (CAKE.O) E (03/27/2008) $49.67The Wendy's Company (WEN.O) E (01/08/2015) $9.91Wingstop Inc (WING.O) O (07/07/2015) $26.96Yum! Brands, Inc. (YUM.N) E (01/09/2014) $82.57

Stock Ratings are subject to change. Please see latest research for each company.* Historical prices are not split adjusted.

INDUSTRY COVERAGE: Internet

COMPANY (TICKER) RATING (AS OF) PRICE* (06/13/2016)

Brian Nowak, CFA

Alphabet Inc. (GOOGL.O) O (08/11/2015) $731.88Amazon.com Inc (AMZN.O) O (04/24/2015) $715.24Care.com Inc (CRCM.N) E (02/03/2016) $8.55Criteo SA (CRTO.O) E (01/26/2016) $43.02eBay Inc (EBAY.O) U (04/19/2016) $23.89Etsy Inc (ETSY.O) E (05/11/2015) $9.57Expedia Inc. (EXPE.O) E (05/01/2015) $104.33Facebook Inc (FB.O) O (04/27/2016) $113.95Groupon, Inc. (GRPN.O) E (02/25/2015) $3.13GrubHub Inc. (GRUB.N) E (05/04/2016) $28.25LinkedIn Corp (LNKD.N) ++ $192.21Priceline Group Inc (PCLN.O) E (02/25/2015) $1,315.47RetailMeNot Inc (SALE.O) E (07/13/2015) $7.00Rubicon Project Inc (RUBI.N) E (01/26/2016) $13.85TrueCar Inc (TRUE.O) E (07/13/2015) $6.59Twitter Inc (TWTR.N) U (10/21/2015) $14.55Yahoo! Inc (YHOO.O) O (03/26/2015) $36.47Yelp Inc (YELP.N) E (07/29/2015) $26.64Zillow Group Inc (Z.O) O (07/13/2015) $32.40Zynga Inc (ZNGA.O) E (07/13/2015) $2.54

Stock Ratings are subject to change. Please see latest research for each company.* Historical prices are not split adjusted.

© 2016 Morgan Stanley


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