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June 2021
Sector Report
Internet
f
cus
Zomato: Delivering convenience
Pranav Kshatriya Nihal Mahesh Jham
+91 22 4040 7495 +91 22 6623 3352
Pranav.Kshatriya@edelweissfin.com Nihal.Jham@edelweissfin.com
Sandip Agarwal Pulkit Chawla
+91 22 6623 3474 Pulkit.Chawla@edelweissfin.com
Sandip.Agarwal@edelweissfin.com Edelweiss Securities Limited
Internet
Contents
Executive Summary ................................................................................................. 2
Ordering frequency- Key Driver of LTV .................................................................... 5
Quality of Network Effects .................................................................................... 12
Dissecting disintermediation ................................................................................. 15
Large addressable market ..................................................................................... 20
QSRs: Beneficiaries with a caveat .......................................................................... 24
Business Model ...................................................................................................... 30
Financial Outlook ................................................................................................... 34
Valuation ............................................................................................................... 41
Key Risks ................................................................................................................ 46
Global Peer Set ...................................................................................................... 47
Management Overview ......................................................................................... 62
Financials ............................................................................................................... 64
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Executive Summary
Zomato IPO is shaping up as a landmark: the first IPO of an India-based
large-scale consumer platform. In its essence, the upcoming IPO
shows investors’ hunger to pay top dollar, at rich valuations, for a fast-
growing food delivery business in a large addressable market. Indeed,
Zomato is well-entrenched and fast-growing, but also loss-making.
Our menu for this note includes sizing up emergence of food delivery
platforms globally (Meituan, Doordash, Deliveroo) and decoding
Zomato’s success recipe using our proprietary three-pronged
framework, comprising: i) quality of network effect; ii) consumer
lifetime value (LTV); and iii) total addressable market. (Link)
Food delivery platforms presuppose network effects, which drive
scale. But that’s much weaker than other global platforms due to local
clustering, which means food platforms seldom have pricing power—
thereby curtailing profitability. Global insights indicate consumers
love the sheer convenience of online food ordering, leading to higher
ordering frequency, which drives growth and – eventually – profits.
For restaurants, delivery platforms are a necessary evil: a lower-
margin channel that also cannibalises dine-in, but expands catchment
and drives incremental business. Restaurants/QSRs (McDonald’s,
Domino’s) are hence trying to disintermediate delivery platforms, but
it’s a tall order—to emulate convenience, variety and experience
offered by platforms. Meanwhile, we do view Swiggy as a worthy
competitor: smaller, backed by marquee investors and growing faster.
Zomato’s success rests squarely on its execution vis-a-vis Swiggy.
On balance, we have an optimistic growth outlook for food delivery
platforms in India and their unit economics. Zomato’s valuation has
high sensitivity to average order value (AOV), and we peg its valuation
at USD7–9bn (base case: USD8.1bn, 49% premium to its last funding
round). A notable dip in AOV due to single orders – instead of family
orders – and rising discounts due to increased competitive intensity
are the key risks to unit economics, and valuations.
A plateful of levers: A classical aggregator model
For a small fee, food delivery platforms offer consumers a variety of food choices,
ease and a consistent ordering experience. Restaurants gain from starkly larger
catchment and an on-demand delivery fleet. But, since food delivery platforms have
higher market power, they can tweak commissions for restaurants as well as delivery
partners, or even delivery charges levied on consumers, to drive profitability.
A platform’s stickiness also drives higher advertising revenue from restaurants. Food
delivery platforms also typically run loyalty programs that reduce delivery charges,
but ensure higher ordering frequency. Hence, we see food delivery platforms
operating on an asset-light model with high consumer loyalty, which gives them a
plateful of levers to drive unit economics.
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Main ingredient: Convenience drives ordering frequency, LTV
Food delivery platforms’ LTV is driven by: i) average order value (AOV); ii) take rates;
iii) delivery charges; iv) average ordering frequency; and v) churn rate. Of these, we
note that ordering frequency is the key driver of LTV; other parameters largely settle
at a steady state after initial improvements.
In this way, convenience of online ordering and an array of food options on tap are
the key drivers of increasing ordering frequency. In fact, AOV has remained broadly
flat in most geographies. Take rates tend to increase during initial years and then
plateau as platforms focus on on-boarding restaurants. Delivery charges decline as
order volumes rise, kicking in efficiencies. However, since these are point-to-point
orders, there are limits to efficiencies. Churn typically dips as customers tend to
gravitate towards one platform after tasting a few.
Mild flavour: Network effect modest…you get scale, not pricing power
Network effect in food delivery platforms is limited due to local clustering,
commoditised offerings and vulnerability to multi-homing. Network effect for food
delivery platforms are somewhat similar to ride-hailing and is lower than global
platforms in messaging, social media, etc. Typically one large player dominates even
in large markets, such as the US and China, but they have limited pricing power and
hence low profitability. Local clustering thus has had a fallout: even reasonably well
established players in a local market can lose market share as newer players with
more efficient offerings enter. Hence, operational excellence by driving down
delivery costs, among others, is critical to maintaining leadership and profitability.
Alternative recipe? Yes, but risk of disintermediation low
With restaurants’ revenue from food delivery platforms rising materially during the
pandemic, their profitability was hit due to high take rates. Hence, restaurants are
trying to orchestrate the direct food delivery platforms by collaborating with SaaS-
based ordering platforms and third-party delivery services. While overall consumer
experience is satisfactory, we believe most standalone restaurants do not have the
financial and marketing wherewithal to drive orders through their own platforms.
Many payment apps such as PhonePe, Paytm and GPay are aggregating direct
delivery platforms, restaurant discovery and ordering experience remain much
poorer than specialised food delivery platforms. On the whole, risks of
disintermediation are low for food delivery platforms, although a portion of high-
value ordering such as gourmet food and bulk orders may shift to direct delivery.
Stomach for more? Indian food delivery market can gulp lots more
Online food delivery platforms are at a nascent stage in India with an industry size
of meagre USD4.2bn (USD21bn for USA, USD90bn in China). It is, however, growing
rapidly in the country with food delivery reporting a staggering 147% CAGR over
FY18–20. However, with the pandemic nibbling away at the business, the industry
had to swallow a 41% decline. Even so, growth is phenomenal and driven by
increasing adoption of food delivery platforms, rising ordering frequency, and an
expanding proportion of restaurant food consumption versus home food.
We believe adoption of food delivery platforms in India will be a function of user
education, availability and ease of payment options, and reach of platforms. Since
India has only 45–55mn online food delivery users compared with 740mn mobile
data connections, online food delivery platforms has swathes of space for
penetration that can fuel its growth for a long time.
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Culinary comparison: QSRs are beneficiaries with a caveat
Zomato’s public filing has some interesting trends from the restaurant/QSR
perspective. We note the following. i) Jubilant FoodWorks’ recovery has been similar
to Zomato’s GOV, pointing to the strength of its delivery-based model. (QSR: The
Right Combo) ii) Active competition has not reduced as initially thought. iii)
Platforms are a long-term enabler for the sector. That said, it is a lower-margin
channel than dine-in. Incremental business drives profit but cannibalization impacts
negatively. We also compare JFL with Zomato —similarities aside, the two business
models are fundamentally different with Zomato’s being more scalable.
Tempting aroma: Consumers globally are loving food delivery
We note that evolution of online food delivery is different across players and
geographies, but with a few similarities. Many companies such as Uber, Grab and
Gojec got into food delivery because they already had riders that could deliver food.
Players such as Zomato went from restaurant listing to delivery, while a few like
Swiggy and DoorDash started as online food delivery platforms. Almost all delivery
platforms across the globe have seen a huge spurt in delivery volumes riding on
consumer convenience. However, we also note that most delivery platforms make
losses at operating level; even the most matured ones work at meagre operating
margins, e.g. Meituan at 4.2%.
Foodies can surprise: High growth driving up valuation
Zomato’s global peers trade at 2–12x 1-year forward price to sales. The multiple is
contingent on growth potential of a market and market share of the player. For
Zomato, we use a two-stage DCF model, which yields a value of INR581bn
(USD8.1bn). Our assumptions: 32% revenue CAGR over FY21–30, 10% FCF growth
for next eight-years and 10% for second-stage, and 4% terminal growth. The
valuation has high sensitivity to AOV; for instance, a 10% lower AOV will suppress
valuation by 22%. We believe Zomato’s valuation depends on its ability to sustain
and fortify its leadership in the Indian food delivery market.
For perspective, Swiggy is slightly smaller than Zomato, but has delivered stronger
growth; hence, for Zomato to sustain valuations, it must gear up.
Rigours of recipe: Key risks
As online food delivery, and the gig economy in general, is at an early stage of
development, the ecosystem is evolving and there are risks to watch out for: i)
unfavourable regulations curtailing pricing or increasing delivery costs etc; ii)
increase in competition, leading to weaker unit economics and higher costs, would
impact profitability; iii) deeper-than-anticipated fall in AOV; iv) delivery and other
cost escalations and inability of platform to pass them through; and v) despite low
odds of success for direct delivery, an unlikely success can potentially disrupt food
delivery platforms’ business models, including Zomato’s.
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LTV = f(ordering frequency)
Convenience of online ordering is driving ordering frequency, which is the most
important driver of LTV.
LTV = [Average order value (INR) X take rate (%) – Delivery charges (INR) –
Discounts (INR)] X Average ordering frequency/ Churn
Average order value (AOV) tends to remain steady under normal circumstances.
Zomato savoured an AOV surge during the pandemic as: i) more family ordering
took place than individual ordering; ii) premium dine-in restaurants joined the
food delivery platform bandwagon; and iii) consumers showed increasing
preference for hygienic restaurants, even though more expensive. To be sure,
some of these factors are temporary, and might reverse.
Delivery charges tend to dip as ordering volume rises, bringing in efficiencies.
However, as these orders are point-to-point orders, there are limits to which
efficiencies can be extracted.
In our last Internet report Decoding platform economy, we had laid out the
framework for evaluation of platform businesses on the basis of three parameters:
i) LTV of customers; ii) the quality of network effect; and iii) total addressable
market. We are using the same proprietary framework for evaluating Zomato.
Ordering frequency: Biggest driver of LTV Convenience of online ordering driving LTV
Consumer lifetime value is one of the crucial parameters in determining the
valuation of the company. Below equations shows the LTV of customers, which is a
function of the following terms: i) AOV; ii) take rates; iii) delivery charges; iv) average
ordering frequency; and v) churn rate.
LTV= {Average order value (INR) X take rate (%) – Delivery charges (INR) –
Discounts (INR)} X Average ordering frequency/ Churn
We note that LTV is largely a function of AOV and ordering frequency since other
parameters largely settle at a steady state after initial improvements. Globally, we
have seen improving average ordering frequency as the biggest driver of LTV while
churn dips as customers tend to gravitate towards one platform after trying a few of
them.
Average order value has largely remained flat in most geographies. Besides,
platforms have cut down on the discounts for attracting consumers and driving
repeat orders. Besides, these platforms have increased the take rate as restaurants
also see the benefit of higher asset turnover. Delivery charges are seen declining
with increasing ordering volume bringing in efficiencies. However, as these orders
are point-to-point, there are limits to which efficiencies can be extracted.
Average ordering frequency is rising across the globe
Across the globe, cohorts tend to indicate that popularity of food platforms
continues to be on the rise. This trend has been consistent across both developed
and emerging countries. Not only are the total number of users rising rapidly, the
frequency of ordering has been on an uptrend across the world. GrabFood, which
has seen a sharp increase in GMV per user cohorts across users. While average order
value grew substantially only in 2020, average ordering frequency has been the
major driver of GMV per user cohort.
Similarly, the cohort for Doordash shows that the marketplace GOV from each
customer cohort has gone up year after year. Also newer cohorts are spending
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higher. For instance, spend of 2018 cohort in Year 2 is higher than that of spend of
2016 cohort in year 4 and 2017 cohort in year 3.
GrabFood – GMV per user cohort DoorDash – Marketplace GOV cohort
Source: Company Source: Company
In China, Meituan’s ordering frequency almost tripled over the last five years.
Coupled with rapid growth in new users, this has been the primary driver of growth
for its gross merchandise value (GMV).
Meituan – Rising average transactions per user Meituan – Transaction cohort
30 28.1
27.4
25 23.8
20 18.8
15 12.9
10.4
10
5
FY15 FY16 FY17 FY18 FY19 FY20
Source: Company, Edelweiss Research Source: Company, Edelweiss Research
Average order value (AOV) trends are mixed
While GMV has increased across companies, not many of them have seen any
meaningful increase in their AOV. Rather, there is no clear trend in the AOV across
the board. DoorDash and Delivery Hero in developed markets have seen a drop in
their AOVs over the last few years. On the other hand, Meiutan has seen a 14.3%
AOV CAGR over the last five years, but the AOV spurt was in the initial two years
while the three-year CAGR is barely 3.7%.
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No clear trends in AOV across global companies (rebased to 100)
200
170
140
110
80
50
FY15 FY16 FY17 FY18 FY19 FY20
Meiutan Doordash Just Eat Takeaway Delivery Hero Grubhub
Source: Company, Edelweiss Research
Zomato AOV spurt led by family, premium ordering
Zomato’s AOV increased 32% in Q1FY21 to Zomato witnessed a 32% increase AOV post lockdown announcement as highly
INR378, from INR287 in Q4FY20 as lockdown mobile young professionals started working from home and they tended to order
resulted in larger ordering for family, and for the family, instead of ordering for an individual. Also, premium restaurants,
ordering from premium restaurants which were solely for dine-in patrons, were forced to list on food delivery platforms
in the wake of pandemic. Yet another reason that can be attributed to the increase
in order value is customer preference for premium restaurants, which tend to have
higher hygiene standards.
Spike in Zomato's AOV during pandemic
450
407
394
378
360
292 287
265 273
270
(INR)
180
90
0
Q1 FY20 Q2 FY20 Q3 FY20 Q4 FY20 Q1 FY21 Q2 FY21 Q3 FY21
Source: Company, Edelweiss Research
That said, we expect AOV to trend down once the economy starts opening up and
more individuals start ordering (as opposed to families). Furthermore, expansion
into newer cities is expected to exert pressure on the average order value. However,
we expect AOV to come down by only 6% in FY22 to INR360 (from INR381 in FY21)
and remains higher than the pre-pandemic level. We note that the low pre-
pandemic AOV was also supressed due to food delivery platforms promoting flat-
priced meals and affordable single-serve meals, which may not come back.
Moreover, we expect the pandemic to drive more users to more hygienic
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restaurants, which tends to be more expensive. Hence, we do expect AOV to reduce
to INR360 in FY22, but will remain higher than the pre-pandemic level of INR280.
Take rates tend to stabilise
We observe that take rates tend to increase initially and then settle at a steady state.
Food delivery platforms begin with lower take rates to incentivise restaurants in a
bid to on-board them. As they business starts picking up, they tend to increase take
rates to cover the cost of delivery, promotions, etc.
There can be a difference among take rates across platforms in a country. While
companies such as Deliveroo and Delivery Hero have the highest take rates in the
world (25–30%), the take rate for DoorDash and Uber Eats would be in the vicinity
of 11–14%. Meituan’s take rate (13–14%) is also among the lowest across countries.
We attribute the lower take rates in China to higher penetration, denser population
driving down costs, and higher competition.
Take rates – A global view
35
29
28
22.8
21
(%)
13.6 12.9
14 11.7
7
0
Deliveroo Zomato Meituan Uber Eats DoorDash
Source: Company, Edelweiss Research
While take rates have been rising over the last few years, we need to be cognizant
that this trend is unlikely to continue for long. There has been opposition from
restaurants and regulators alike, who feel the need to protect restaurants from
higher take rates charged by aggregators. In fact, several cities including New York,
San Francisco, Las Vegas, Washington, etc. had put a temporary cap on delivery
commission to protect interests of restaurants during the pandemic.
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Meituan – Monetization rate Uber Eats – Take rate
15% 14.0% 25%
13.5% 13.6% 22%
12.3% 20%
12% 20% 18%
9.0%
9% 15% 12.90%
9.70%
6% 10%
3% 5%
1.1%
0% 0%
FY15 FY16 FY17 FY18 FY19 FY20 2016 2017 2018 2019* 2020*
Source: Company, Edelweiss Research Source: Company, Edelweiss Research
*Uber started combining Uber Eats in Delivery segment and changed
the definition from 2019 onwards. Hence, prior years are not
comparable
Deliveroo – Take rate DoorDash – Take rate
32% 12%
11.7%
31% 12%
30% 30%
11.0%
29% 29% 29% 29% 11%
28%
28% 11% 10.3%
27% 10%
26% 10%
FY15 FY16 FY17 FY18 FY19 FY20 FY18 FY19 FY20
Source: Company, Edelweiss Research Source: Company, Edelweiss Research
Take rates of Indian companies: Already elevated
Take rates of Indian companies, including Indian companies such as Zomato and Swiggy currently charge a take rate of 22–
delivery charges, are 22–25%, while for 25%, which is on the higher side globally and among the highest in developing
global peers they range from 11–30% countries. Higher take rates can spur risk of disintermediation, as well as new
competitors entering the segment. Amazon is also eying this segment by offering
half of the current take rate. However, since Amazon does not have a different cost
structure, we believe these introductory take rates will be neither sustainable nor
scalable. This, at best, may keep industry profits low till competition wanes out.
Zomato follows a different commission structure based on the type of restaurant.
While non-chain restaurants pay a much higher commission, outlets part of a chain
pay lower. At present, the commission rates vary anywhere from 18–40% of the
order value. The amount depends on parameters such as order size and restaurant
type. Companies such as Jubilant FoodWorks (JFL), which lists on the platforms like
Zomato to receive orders but deliver through their own fleet, pay a 6–8%
commission.
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Estimated commission take rate
30
24-26
24
18
14-16
(%)
12
6-8
6
0
Only Listing/Self Delivery Large Chains Non Chain Restaurants
Source: Edelweiss Research
One of the key concerns of restaurants has been a potential further increase in take
rates by food platforms would eat into their margins. However, a comparison of
Zomato’s historical take rate trends, comparison with global peers and also
Amazon’s potential entry in this segment (pilot underway in Bangalore), we expect
steady take rates.
Delivery costs economises with scale
Companies have been focused on reducing delivery cost per order by taking several
initiatives. For instance, Zomato has seen a steady decline in its last-mile delivery
costs. The delivery cost comprises payment to delivery partners along with an
availability fee. Reduction has been achieved by a combination of higher throughput
and lowering of availability incentives.
Zomato – Delivery cost per order trending down
100
88 86
76
(INR)
65
64
52
52
45
40
FY18 FY19 FY20 9MFY21
Source: Company, Edelweiss Research
However, once companies undertake steps to optimize delivery costs per order,
these costs generally stagnate at a certain level. For instance, Meituan in China has
seen its delivery rider costs now stabilize within RMB4.5–5. Given these are point-
to-point deliveries, optimization and economies of scale can be improved only to a
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certain extent and idleness of a rider cannot be reduced beyond a degree. Due to
this, cost per order has started increasing for Meituan.
Meituan- Delivery cost per order
6
4.8 4.9
4.7
4.8 4.5
3.6 3.2
(RMB) 2.4
1.2
0.4
0
FY15 FY16 FY17 FY18 FY19 FY20
Source: Company, Edelweiss Research
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Quality of network effect is modest
The network effect in food delivery platforms is curtailed due to local clustering,
commoditised offerings and vulnerability to multi-homing.
Network effect for food delivery platforms is somewhat similar to ride hailing
and is lower than global platforms in messaging and social media.
Typically a large player dominates food delivery, even in large markets (US,
China), but nevertheless has limited pricing power and hence low profitability.
Restaurants are trying to disintermediate food delivery platforms by going direct,
but considering challenges of on-boarding customers on individual restaurant
platforms, they may succeed only in gourmet food or high-order value cases.
Network effect helps achieve scale, but pricing power is limited
Various factors determine the quality of network effect, such as: i) network
clustering (local or global clustering); ii) commoditized or differentiated supply; iii)
vulnerability to multi-homing; and iv) risk of disintermediation. Besides, the gradient
of customer acquisition cost (CAC) over time series is a good measure of the quality
of network effect. Exhibit 14 summarises network effects in case of food delivery
platforms.
Scorecard for quality of network effect for food delivery platforms
Parameter Score Remark
Food delivery platforms are local in nature as a limited
Network clustering Low
number of restaurants can cater to a cluster
Commoditized or
Medium Few exclusive cloud kitchen and restaurants tie-ups
differentiated supply
Vulnerability to multi- Multi-homing is possible but only a few platforms are there
Medium
homing and consumer can be locked into with loyalty program
Risk of
High Risk of disintermediation is real only in high-value items
disintermediation
Network effect strong enough to drive scale but not pricing
Overall Medium
power
Source: Edelweiss Research
Network clustering
In terms of network clustering, food delivery platforms are local in nature; these
platforms may boast a large number of restaurants but for a customer, only the
number of restaurants which can deliver to him matters. Hence, if in one locality a
platforms can onboard higher number of restaurants, and have sufficient delivery
fleet to match another platform, consumers in that area will want to migrate to that
platform basis the better choice. Hence higher number of restaurants at overall level
does not add value to the network if the size of the network in certain area is weak.
Localisation reduces the barrier to entry and hence there have been examples of
existing players losing market share to newer and more efficient players. Despite
DoorDash’s late entry in the US food delivery market, it captured a 55% market share
on the back of its efficiencies.
Food delivery platforms are local in nature
Initially, the US too had more localised monopolies, creating an oligopolistic
as limited number of restaurants can cater structure at a national level. Grubhub was a leader at the national level. However,
to a cluster DoorDash managed to scale up much faster than any other player during the
pandemic with better execution, which was largely around the number of
restaurants, delivery speed, etc. This resulted in a nearly 55% market share for
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DoorDash, whereas other players lost market share. We note that even in larger
markets, superior execution can rapidly drive market share. Hence in a market like
India, which has a long growth runway, better execution to drive growth is key to
value creation.
Food delivery market share in US
Source: Bloomberg Second Measure
Commoditized or differentiated supply
Food delivery platforms can differentiate via
Food delivery platforms tend to fall somewhere between commoditized and
exclusive ties-up with local popular differentiated supply. On the one hand, the supply is differentiated because there
restaurants, but it comes at a cost are many restaurants and type of foods to choose from. Some platforms even have
an exclusive partnership with popular restaurants. But, on the other hand, if all of
these food delivery platforms provide more or less the same menu—all restaurants
are available across platforms—the supply would get commoditized. The point
of differentiation therefore shifts to delivery cost, delivery speed, ease of use
and other features.
Vulnerability to multi-homing
Food delivery platforms are addressing Multi-homing measures the switching cost of a platform. It simply means how easy
multi-homing issues by introducing loyalty is it for users to switch between platforms that provide similar services. Food
programs delivery platforms may see multi-homing on both – consumer and delivery
personnel side. To reduce multi-homing, companies can opt for loyalty bonus or
membership offerings that promotes frequent ordering on one platform, or they can
enter into exclusive partnerships with popular restaurants. Some platforms also
introduce their own cloud kitchen, which not only increases choice, but also captures
a higher portion of value from the transaction.
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Swiggy Super and Zomato Pro – A comparative snapshot
Swiggy Super Zomato Pro
INR89 (Bit)/ INR169 (Bite)/ INR329
Price INR200/3 months
(Binge) per month
Bit' plan - Five free deliveries
per month.
'Bite' plan - Ten free Up to 30% extra off on food
deliveries per month and one deliveries
'Buy One Get One free' from up to 40% off on each dining
Features
restaurant partners experience
'Binge' plan - Unlimited free Faster delivery with top-rated
deliveries and unlimited 'Buy valets
One Get One free' offers from
partner restaurants
Cities 80 41
Partner
> 7,000 >25,000
Restaurants
Source: Company, Edelweiss Research
Risk of disintermediation – Low in most cases
Since impromptu and frequent ordering
Food delivery platforms, for a small fee, offer consumers choice, ease and consistent
drives the bulk of order value on food ordering experience, which has led to rapid adoption among consumers. However,
platforms, we believe the risk of for restaurants, food delivery platforms charge a significant commission for availing
disintermediation is low a higher catchment area and an on-demand delivery fleet. High take rate impacts
profitability of restaurants, especially for high-value orders. Hence, premium
restaurants are increasingly looking to connect directly with consumers for food
delivery. However, since impromptu and frequent ordering drives the bulk of order
value, we believe the risk of disintermediation remains low.
Weaker network effect has kept profitability under check
Due to local clustering of food delivery platforms, the risk of disruption by a new
player remains high. Hence, we note, largest players typically command a market
share of 50%-plus in most geographies, but they still operate at low margins. Despite
over a 65% market share in the Chinese market, Meituan’s operating profit margin
in food delivery is a meagre 4.3%. Most other companies have a negative operating
profit. That said, we expect profitability to improve as market matures and larger
players create efficiencies of scale, which act as an entry barrier for new players.
Operating margin of global companies are low
10
3.6
0
Meituan Just Eat Takeaway DoorDash Delivery Hero
-5.2
-10
(%)
-15.1
-20
-30
-40 -36.2
Source: Bloomberg, Edelweiss Research
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Dissecting disintermediation
Restaurants are keen on exploring solutions to reduce their dependence on food
delivery platforms considering high take rates that eat into their profitability.
SaaS-based ordering platforms such as Dotpe and Thrive are creating ordering
platforms for restaurants, along with integration of third-party logistics players
for order fulfilment.
While deploying these solutions is relatively easy, pushing consumers to adopt
direct ordering is the biggest challenge for restaurants.
We see large QSRs and chain restaurant with enough resources to drive direct
ordering; other restaurants will find it challenging to market their platforms.
Direct delivery – Crucial to restaurants’ profitability
Shift in restaurant business in favour of
Although food delivery platforms help restaurants drive volumes, they also create
delivery, from dine-in in the wake of the two challenges: i) food delivery platforms do not share customer data with
pandemic has eaten into their profitability restaurants; hence restaurants find it difficult to create patronage; and ii) food
delivery platforms charge a high fee, which significantly impacts profitability. High
fees is a significant challenge for premium restaurants. Many dine-in restaurants do
not offer home delivery due to high charges levied by delivery platforms. However,
the pandemic has significantly altered the revenue mix for restaurants with dine-in
revenue almost entirely going away.
In order to address the issue of consumer data and high commissions, some
restaurants are working with SaaS platforms such as DotPe and Thrive to create
seamless ordering systems. These ordering systems, if required, can also source
delivery fleet from third-party delivery partners such as Dunzo, WeFast and
Shadowfax. In order to drive usage of their own platforms, restaurants are
leveraging social media platforms, such as Instagram and Facebook for popularising
their services. Indian Hotels has also launched their own app “Qmin” offering food
delivery from their restaurants and kitchens, which have INR1,000 as the ordering
threshold.
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DotPe – Direct delivery
Source: Company
Discovery and variety – A key challenge for customers
On the consumer experience side, we note consumers are likely to go to the
restaurant portal to order only if they are aware of the direct ordering facility, are
sufficiently incentivised, and the experience is as good as ordering on a food delivery
platform. To incentivise, restaurants offer no delivery fee apart from other
discounts. Since the address and payment details are stored by SaaS platforms,
despite their web-based interface, user experience is reasonably smooth.
While direct-to-consumer has numerous advantages for restaurants, the main
challenge continues to be pertaining to discovery. These companies have also
realized this problem and have consequently tied up with popular payment
platforms such as GPay, PhonePe and Paytm. Using these apps, customers can
search for restaurants and order directly via these apps without the hassle of
searching them individually.
Although this adds discoverability, but the experience is not as sophisticated as on
food delivery platforms as there are no options to sort the restaurants according to
various parameters, there is no visibility on how much time restaurant will take for
delivery, rating of the restaurants, etc. Considering payment apps are not sufficiently
integrated with restaurants’ and third party logistics providers, we do not expect
discovery platforms to become as sophisticated as food delivery platforms, and thus
the experience offer is likely to be sub-par.
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Direct food ordering is available on platforms like Google Pay, Phonepe and Paytm
Source: Company
Consumer experience, outside discovery, is seamless
Technology integration for direct delivery works in such a way that SaaS platforms
can on-board restaurants in a matter of days by creating digital menus, integrating
the billing system and offering third-party delivery platforms on-the-go. For high-
ticket size, third-party delivery platform costs work out lower than those charged by
delivery platforms. Since SaaS platforms work this through an Application
Programing Interface (API), consumer get a fairly seamless experience with a
WhatsApp or SMS update on food dispatch with a link to track delivery personnel in
real time.
Direct delivery – Impact varies for players
We believe different segments of restaurants face their own set of challenges –
resource availability and dependence on food delivery platforms is different – due
to which their possibility and success in adoption of direct ordering will be different.
Hence, we are evaluating the opportunities and success possibilities for each
segment separately. We are broadly classifying restaurants into three categories: i)
large QSR chains and cloud kitchens; ii) large chain restaurants; and iii) standalone
restaurants and eateries.
Large QSR chains and cloud kitchens
Large and popular QSR chains such as McDonald’s, Domino’s and KFC as well as large
cloud kitchens such as Rebel Foods (which owns brands such as Faasos, Behrouz
Biryani and Oven Story), Poncho Hospitality (which owns Box8 and Mojo Pizza),
typically have their own apps for food delivery. These companies also possess
enough financial, marketing and logistics muscle to provide full-stack services.
Furthermore, they can drive discovery through digital marketing branding
campaigns. However, customers are unlikely to download many QSR or cloud
kitchen apps; hence food delivery platforms will continue to drive the bulk of
delivery business.
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We note that success of direct delivery has been mixed for different companies.
Domino’s has been particularly successful with ‘30 minutes delivery’ attracting
customers’ craving at breakneck speed. Other QSR chains and cloud kitchens are
relatively less successful due to their inability to match this speed and other factors.
However, with food aggregators gaining prominence, most of these companies have
been unable to match the ease of use provided by aggregators. User experience for
food aggregators has been far superior to those provided by these apps. We believe
that this section of restaurants will be able to get 20–30% food delivery on their own
platforms. The proportion of direct ordering will be a function of strength of the
brand and their execution capabilities.
McDonald’s, Domino’s and Faasos food delivery
Source: Companies
Popular chain restaurants
Popular chain restaurants are characterised by high patronage, repeat customers
and relatively high AOV. They typically rely on dine-in patrons for revenue, but the
pandemic changed this dynamic. Since the take rate for aggregators is high, these
restaurants have faced a major brunt, having to pay a significant amount to the likes
of Zomato and Swiggy. Discovery is not a major issue for these restaurants as they
are anyway well-known.
Consequently, these restaurants have been at the forefront of the direct delivery
campaign. While these restaurants do have a certain connect with customers, their
ability to drive these customers to direct delivery portal, by discounting, by
marketing will determine their success. We note that chain restaurants will have to
invest sufficient marketing resources to drive traffic to their own portal.
Some of SaaS based ordering platforms suggest high adoption by restaurants –DotPe
claiming 150k partner restaurants and Tribe suggests another 15k. However, we
believe that some of these on-boarding would be for features other than delivery
and only a handful of restaurants would promote their own delivery. In terms of
cost, Tribe indicated 3% of the GMV as platforms fees and third-part delivery may
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charge ~INR100 for delivery. Hence, assuming a 10% marketing cost and a 10%
discount, own platform breaks even at an order value of INR1,000. This is
significantly higher than Zomato, whose AOV would be lower than INR400. Hence,
we believe that only a handful restaurants would opt for standalone delivery
platforms and it would drive 15–20% of their delivery volumes.
Breakeven analysis: Own platform vis-a-vis Zomato/ Swiggy
(INR) Own Platform Zomato/ Swiggy
AOV 1000 1000
Platform Fees/ Commission 3% 30%
Platform Fees per order 30 300
Delivery Charges 70
Marketing Costs 100
Discount 100
Total Costs 300 300
Source: Edelweiss Research
Standalone restaurants
For small standalone restaurants, while implementing order management platform
is relatively easy, diverting orders to their own platforms will be challenging. We
believe that restaurateurs will find it challenging to attract consumers to their
platforms. Hence, we believe that this segment is unlikely to see any traction with
direct ordering. Consequently, they will continue to remain dependent on food
aggregators for both discovery and delivery.
We believe that most restaurants are not adequately equipped for driving the
marketing campaigns for online ordering platforms. From consumers’ side, while the
ordering experience is seamless, discovery will be a challenge. We believe that
consumers are likely to order from standalone platforms only in case they are aware
exactly what they are looking to order and are adequately informed about the
benefits thereof. Standalone restaurants will require significant marketing support,
which smaller restaurants will not be able to manage. Hence, we believe adoption
of the standalone platform will be limited to premium restaurants or larger chains
that can afford enough.
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Large addressable market
Food delivery platforms have made online food discovery and ordering
experience very convenient. This is fuelling growth of online food delivery
platforms across the globe.
Indian food delivery market at ~INR300bn (USD4.2bn) is only a fraction of the
INR4.2tn (USD67bn) out-of-home food eating out market. Restaurants in India
are highly fragmented with chain restaurants accounting for only 6.2% of the
value; standalone restaurants account for the rest of the pie.
Low penetration of online food delivery ordering in India offers a mouth-
watering opportunity.
Non-home cooked food or restaurant food is only ~10% of the overall USD670bn
food consumption market in India (54% in United States and 58% in China).
Changing consumer behaviour, reduced dependence on home-cooked food and
increasing disposable income are further expanding the addressable market.
Indian food delivery market: Long growth runway
Online food delivery platforms are at nascent stage in India with an industry size of
meagre USD4.2bn (USD21bn in US, USD90bn in China). It is, however, growing
rapidly. Food delivery grew at an eye-opening 147% CAGR over FY18–20. However,
with pandemic impacting the business, the industry had to swallow a 41% decline in
FY21. Even so, growth is phenomenal and driven by increasing adoption of food
delivery platforms, rising ordering frequency, and an expanding proportion of
restaurant food consumption versus home food.
Food Services defined as non-home cooked food or restaurant food currently
contributes only approximately 10% to the overall USD670bn food market. This is
starkly lower than global economies such as the United States and China with
respective figures of 54% and 58% (of the total food consumption).
According to RedSeer, the total addressable food services market opportunity of
USD65bn (INR4.6tn) would growing at 9% per annum to USD110bn (INR7.7tn) in
2025. It particularly notes highly under-penetrated restaurant food-eating
behaviour today. While Food Services in India is highly under-penetrated, it is likely
to grow steadily, eating into home-cooked food much like the trend in the past.
Growth will be driven by changing consumer behaviour, reduced dependence of
millennials on home-cooked food/kitchen set-up, increasing consumer disposable
income, and higher adoption among smaller cities.
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Indian markets nascent; comparative snapshot of India, US and China
Source: Zomato DRHP
India has only 45–55mn online food delivery We believe adoption of food delivery platforms will be a function of user education,
users compared with 740mn mobile availability and ease of payment options, and reach of platforms. Since India has only
broadband subscribers 45–55mn online food delivery users compared with 740mn mobile broadband
connections, penetration of online food delivery platforms has a long runway for
growth in the country.
Ease of usage driving adoption
Online food delivery apps have fundamentally altered the food ordering experience.
Restaurant food ordering, pre-food delivery apps era, was cumbersome: i)
restaurant discovery was challenging as consumers had to have the restaurant
contact number and should have been aware of the menu for ordering food, which
limited the choice; ii) restaurant food delivery was subject to in-house fleet and thus
limited to a much smaller geography; iii) payment option was mostly restricted to
cash; and iv) there was no way to track food delivery progress.
Online food delivery platforms have solved all of these problems. These platforms
aggregate multiple restaurant menus with all the relevant details, including pricing,
and reviews, making ordering a seamless experience. They also provide a delivery
fleet to restaurants, thereby significantly widening their catchment area. In most
cases, consumers get real-time updates on the progress of their order, such as
whether the food has left the restaurant and contact details of the delivery person.
And there is a customer friendly helpdesk to check in case something goes wrong.
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Zomato – Ease of usage
Source: Company
We believe higher food tech platform usage can increase India’s eating out
frequency, which is much lower than comparable global peers. Even a comparison
of Zomato’s GOV by cohorts points to increasing frequency or usage/eating out.
Currently Zomato completes close to 30–35mn deliveries every month. Swiggy,
which operates on a similar scale, also does roughly the same number of deliveries.
For perspective, Meiutan, the largest food delivery company in the world, makes
850mn deliveries in a single month (65% market share). The largest company in the
US fulfils close to 70mn orders a month (55% market share).
While we do expect the user base to grow significantly, it would be incorrect to
assume the orders at similar levels of these countries without taking into account
the difference in demographics of the aforesaid countries. India has a much larger
population and relatively low penetration, but it is unlikely to scale up to the levels
of other countries, considering India’s huge rural population. Nevertheless, we
expect Zomato’s total orders to grow strongly north of 30% for the next four–five
years to about 130mn orders a month.
Globally, the online food delivery industry has grown rapidly over the last few years.
The Chinese market has been at the forefront clocking a 40% CAGR over 2015–20 to
RMB664.4bn largely driven by increased penetration as more consumers moved
online en masse. Developed markets of Europe have also grown at a brisk pace over
the last few years. OC&C (Strategy Consultants) reckons a 19% CAGR for the online
home delivery segment from 2017–19.
The pandemic has also significantly catalysed online deliveries. In South Asia, GMV
of food delivery surged by 183% in FY20 to USD11.9bn. As highlighted earlier, this
rapid growth has been driven by increased penetration and higher number of
transactions per user.
In the past year, both Zomato and Swiggy have outgrown all major global companies
(except DoorDash) as more users have logged onto food aggregators. However, on
an absolute basis, the GMV of both Zomato and Swiggy remains well below these
global companies.
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Comparison of food delivery companies’ GOV and GOV growth
80 250
64 200
(USD bn)
48 150
(%)
32 100
16 50
0 0
JET
Meituan
Doordash
Delivery Hero
Grubhub
GrabFood
Zomato
GOV % Growth
Source: Company, Edelweiss Research
GMV for both Zomato and Swiggy has soared over the last few years. Zomato’s GMV
more than doubled from USD0.7bn to USD1.5bn over FY19 to FY20. Swiggy has also
seen equally strong performance over the last couple of years with order growth of
320% and 145% in FY19 and FY20, respectively.
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QSRs: Beneficiaries with a caveat
Zomato’s public filings throws up some interesting trends from the
restaurant/QSR perspective. We deduce: i) JFL’s recovery has been similar to
Zomato’s GOV, corroborating the strength of its delivery-based model. ii) Fall in
active competition is not as intense as believed initially. iii) Platforms are a long-
term enabler for the sector. iv) Take rates in the industry remain high, even in
context of a global comparison.
We also evaluate profitability of online channel versus dine-in —this remains a
lower-margin channel and incremental business drives profit, but cannibalization
impacts negatively.
While JFL and Zomato are fundamentally different business models, we compare
the two on certain key parameters.
JFL’s recovery has been in sync with Zomato; other have lagged
A comparison of Zomato’s GOV and sales of the three major Indian QSRs shows that
JFL managed to report recovery similar to Zomato on the back of its delivery
excellence. While recovery for burger QSRs has been higher than the industry, it has
lagged Zomato’s given the higher dine-in share.
Sales recovery comparison
125
100
75
50
25
0
Q3FY20 Q4FY20 Q1FY21 Q2FY21 Q3FY21
Zomato (GOV) JFL WDL BKI FS Industry
Source: Zomato DRHP, Company, Edelweiss Research
Note: For Zomato, considered its GOV, for JFL, WDL and BKI considered their reported sales.
Industry competition is nearly back to pre-covid levels
Our business is built around the core idea
In its report on the restaurant industry in August 2020 (Link), Zomato mentions that
that, over time, people in India are going out it expects ~40% of restaurants to shut down. While this was based on a survey by
to eat at restaurants more than they cook at the company (~15,000 restaurants), looking at the bounce back in restaurants on its
home.” platform points to majority of the network bouncing back.
Zomato DRHP
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Active food delivery restaurants
150000 1,43,089
1,32,769
120000
94,286
90000
(#)
60000
33,192
30000
0
FY18 FY19 FY20 9MFY21
Source: Zomato DRHP
Zomato’s customer evolution points to expanding eating frequency
Overall though, online partnerships have been a boon for restaurants as they have
helped increase overall top line by ~30% via a larger consumer base. With improved
kitchen utilisation, online partnerships have also enabled restaurants to improve
their bottom lines, considering the bulk of their costs are fixed (with only 25% of
restaurant costs being food related, i.e. variable).
75% of restaurants costs are non-food/ fixed Ordering online drives a sharp improvement
EBIT
Margin, 5
D&A, 5
Food, 25
Post-Online 70 20 10 30
Other
costs, 20
Pre-Online 70 20 10
Marketing,
5
Labour, 25
Rent, 15 0 50 100 150
Dine in Phone based Take away Online ordering
Source: Prosus, Edelweiss Research Source: Company, Edelweiss Research
Online aggregators also influence consumption behaviour and lead to a significant
increase in ordering.
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Evolution of customer using apps
Source: RedSeer Consulting
We believe higher food tech platform usage, can increase India’s eating out
frequency, which is much lower than comparable global peers. Even a comparison
of Zomato’s GOV by cohort shows increased frequency or usage/eating out.
GOV retention by cohort
Source: Zomato DRHP
Per capita spend on food services
Country CY15 CY20
USA 1,735 2,239
China 659 684
Saudi 665 769
Brazil 634 707
South 170 282
Indonesia 219 253
Turkey 124 181
India 94 122
Source: Burger Kind India DRHP, Edelweiss Research
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Take rates/commissions: Limited scope to increase
Zomato follows a varied commission structure based on restaurant’s presence.
While non-chain restaurants pay a much higher commission, outlets that are part of
a chain, shell out lower. At present, commission rates vary anywhere between 18–
40% of the order value. The amount depends on parameters such as the size of the
order and restaurant type. Companies such as JFL, which only use the app for
origination (and not delivery), only pay commission.
One of the key concerns in the industry has been the potential to further increase
take rates of food platforms, which will dent restaurants’ margins. However, a
comparison of Zomato’s historical take rate trends and its comparison with global
peers, not to mention Amazon’s potential entry in this segment (pilot on in
Bangalore), indicates the current levels are more or less the ceiling for take
rates/commissions.
Estimated commission rates
30
24-26
24
18
14-16
(%)
12
6-8
6
0
Only Listing/Self Delivery Large Chains Non Chain Restaurants
Source: Edelweiss Research
One of the key concerns in the industry has been the potential to further increase
take rates of food platforms, which will dent restaurants’ margins. The focus on
commission/take rates has increased recently, especially in the backdrop of higher
sales from these platforms, post covid.
As highlighted above, Zomato’s take rates are among the highest globally and imply
limited scope for further expansion. Also, while pick-up in the Direct Delivery model
remains a debate, it will definitely be an added factor in keeping any further addition
in take rates under check
Foodtech platforms: An incremental business driver, but still lower margin
FoodTech delivery players have been able to provide value to partner restaurants.
Even after factoring in platform commissions (~20%), the incremental business
drives up restaurant profitability. However, business generated from food tech
players is naturally lower margin. If any outlet is generating incremental business,
then food tech is a profitable channel, but substitution of the same customer online
dents margins (refer to Exhibit 34).
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