Most investors see Southeast Asia as a fragmented market comprised of different countries with their own nuances with the potential of scaling up somewhat complicated. However, Tier 1 cities are on par with developed markets underpinned by an emerging middle class and strong consumer growth, demonstrating homogeneous consumer behavior. The next tier of cities or the mass middle could be seen as developing market so essentially the divide is developed VS developing markets rather than on geographical lines. • What are the opportunities in SEA? • How investors are viewing the region? • How to capitalise on the burgeoning market? • What is the Indonesia investment potential? • Fragmented Vs homogeneous markets- is this the way to go?

1. SEA Venture :
Discovering the opportunity in a
fragmented market
Amit Anand
Yash Sankrityayan
Li-Anne Ooi
@jungleventures 1

2. Confidential & Proprietary Information
Focus
Consumer internet category leaders in
South East Asia or Globally disruptive
technology companies from Asia
Team
15 Investing & Operating professionals
with decades of experience
Investors
AUM of >$140m with top tier limited
partners and strategic investors
Jungle invests in and helps build Technology Category Leaders
in Southeast & South Asia
2@jungleventures

3. SEA is the fastest growing internet
market in the world!
@jungleventures 3

4. 2020 : 480m users
2015 : 256m users
Projected to reach half a billion internet users by 2020
Adding ~3.8mn new users online each month
▲
Source : Google-Temasek e-conomy SEA report
@jungleventures 4

5. SEA countries
Median age
(years)
Internet users as
% of population
(Jan’17)
Average time
spent on online
daily
Thailand 37.2 67% 8 hr 49m
Indonesia 29.9 51% 8 hr 44m
Malaysia 28.2 71% 8 hr 31m
Singapore 34.3 82% 6 hr 41m
Vietnam 30.1 53% 6 hr 53m
Philippines 23.4 58% 9hrs
Majority young internet population spending > 6 hours online,
daily
Source : Wearesocial – 2017 Digital in Asia : SouthEast Asia
@jungleventures 5

6. 540.87mil
11% of global
644.03mil
9% of global
339.13mil
9% of global
305.84mil
11% of global
+8%+39% +31%SEA
vs.
Global growth (%) +5%+10% +21%
Growing >50%
faster than
global average
SEA social media users make-up >10% of global total
Experiencing growth rates 50% higher than global average
Source : Wearesocial – 2017 Digital in Asia : SouthEast Asia
@jungleventures 6

7. Online economy projected to grow > 6x to ~US$200bn by 2025
Source : Google-Temasek e-conomy SEA report
@jungleventures 7

8. Highly fragmented market
Collection of dissimilar countries
Under developed venture ecosystem
Not big enough to support large exit/ IPO outcomes
However, despite headline numbers, general market perception
remains that SEA is…
@jungleventures 8

9. 1st acqui-hire in SEA $30M undisclosed
$250M
$1B
$130M $750M
M&A is accelerating
$90M
$100M $550M
More mega-rounds from foreign investors / corporates
$147M
undisclosed
SEA venture investments and M&A have been growing,
Also weathered the 2016 slowdown better
Source : Pitchbook, State of SEA Technology Startup Ecosystem 2016, Crunchbase, Map of the Money 4.0
$200M$100M> $30m
@jungleventures 9

10. Highly fragmented market
Collection of dissimilar countries
Under developed venture ecosystem
Not big enough to support large exit/ IPO outcomes
However, despite headline numbers, general market perception
remains that SEA is…
@jungleventures 10

11. Looking closely at the Top 10 metros
in SEA
@jungleventures 11

12. SEA Country ID TH MY SG VN PH
Population (mn) 262.0 68.2 30.9 5.7 94.9 103.0
Country nominal GDP
(USD mn)
861.9 395.2 296.3 292.7 193.6 292.5
Average GDP / capita
(USD)
3,290 5,792 9,570 51,000 2,039 2,840
Metro cities Jakarta Bangkok Kuala Lumpur Singapore Ho Chi Minh Manila
Population (mn) 32.2 15.6 6.1 5.7 8.2 12.9
% of total population 12% 23% 20% 100% 9% 13%
Nominal GDP (USD) 232.1 191.1 132.7 292.7 41.9 61.9
% to country GDP 27% 48% 45% 100% 22% 21%
GDP / capita (USD) 7,207 12,251 21,750 51,000 5,100 4,763
No of times average
GDP/capita
2.19x 2.11x 2.61x 1.0x 2.50x 1.6x
Respective SEA metro cities alone make up >20% of country
GDPs. GDP/capita are ~2x higher than country average (implying
discretionary spending power)
Source : Brookings Institution; Worldbank; Wearesocial – 2017 Digital in Asia : SouthEast Asia; Wikpedia; NESDB Thailand; National Statistical
Coordination Board Philippines; Statistics Office of Vietnam; DOSM
@jungleventures 12

13. Note: GDP per capita numbers are specifically for the city areas.
Source: Brookings Institution; Worldbank; Wearesocial – 2017 Digital in Asia : SouthEast Asia; Wikipedia; NESDB Thailand; National Statistical
Coordination Board Philippines; Statistics Office of Vietnam; DOSM
Metro area
Population
million
(2014 Est.)
GDP/capita 2014
Delhi 23 $3,580
Mumbai 22 $1,990
Kolkata 16 $1,116
Chennai 10 $1,870
Bangalore 8 $1,420
Hyderabad 6 $1,430
India Total 85 million $2,148 w/ave
Metro area
Population
million
(2014 Est.)
GDP/capita 2014
Manila 13 $4,763
Jakarta 32 $7,207
Bangkok 16 $12,251
Kuala Lumpur 6 $21,750
HCMC 8 $5,100
SEA Total 75 million $8,798 w/ave
Singapore 6 $51,000
SEA with SG 81 million $11,924 w/ave
Most consumer tech businesses are metro-city focused rather than serving whole country populations
(at least in the first 3-5 years of their evolution and growth)
GDP/capita is 5.2x higher across the top SE Asian cities and as a result immediately addressable market in $
terms in SEA is >~5x of India
$965B Total$182B Total
Top 6 Indian cities Top SEA cities
SEA metros have comparable population with >5x spending
power vs. India, relevant as these metros are immediate target
markets for most start-ups
@jungleventures 13

14. Online media and
Social networks
Aspirational
brands
Spending power
(as represented by GDP
per capita)
Ho Chi Minh
$5,100
Bangkok
$12,251
Jakarta
$7,207
Delhi
$3,580
Manila
$4,763
Digital product
and services
Customers in metros demonstrate homogenous consumer
behaviour
@jungleventures 14

15. Delivery and
fulfilment options
Payment networks Digital marketing
and advertising
Cloud/
Computing /
Platform
Infrastructure solutions are uniformly available today via
regional / global service providers
@jungleventures 15

16. Takeaway #1
Combined, Top 10 Metros of SEA is a ~100mn, homogenous market
with projected US$50+B potential for online consumption
@jungleventures 16

17. And early success of these startups is
evidence towards that..
@jungleventures 17
** Jungle Portfolio Company
****

18. Looking closely at Indonesia’s
middle market
@jungleventures 18

19. 65
46
28
65
57
48
44
47
51
42
55
68
23 36 49
7 12 173 5 7
0
50
100
150
200
250
300
2012 2016 2020
mil
Poor Aspirant Emerging Middle
Middle Upper middle Affluent
Elite
2012 : 74mil 2016 : 108mil 2020 : 141mil
Monthly Household Expenditure only
on basic expenses (food, utilities,
transport, communication, household
supplies); excludes discretionary spend
USD equivalent
Elite Above 562
Affluent 375 less than 562
Upper Middle 225 less than 375
Middle 150 less than 225
Emerging Middle 112 less than 150
Aspirant 75 less than 112
Poor Less than 75
“MAC”
Defined as basic
household
monthly
expenses >$150
Indonesian middle and affluent consumers (MAC) is currently
~100+mn, and projected to be >50% of population by 2020
@jungleventures 19
Source: BCG Population and Household Expenditure Report 2012

20. Substantial MAC population outside of Jakarta, and growing
much faster
(50+mn is outside Jakarta and doubling over this decade)
Source: BCG Population and Household Expenditure Report 2012
@jungleventures 20

21. Online shoppers as % of total
online population more than
doubled in just 2014-15 à
Implying ecommerce is growing
fast but still comprises ~30% of
online population
91%+ online users are active on
social networks and 50%+ use IM
apps à
Implying substantial time spent
and comfort with usage
Social network (90%+) and IM (50%+) usage is already high
amongst both urban and rural populations who are online
Source: Credit Suisse Indonesia Consumer Survey 2016
@jungleventures 21

22. Takeaway #2
Indonesia’s growing MAC is a large homogenous market with
significant online potential over the next decade
@jungleventures 22

23. And these startups with network based
business models are well positioned to
dominate that market potential..
@jungleventures 23
** Jungle Portfolio Company
** **

24. Network-based
Target large populations/ user bases and go
broad with what you can layer on as services
An ideal business at scale has user sets of 50m+
users spending 40$+ per year resulting in $2b+ in
revenues/ GMV but with thinner gross margins
(net take rate) of ~3-5%
Consumption-based
Target the metro cities initially, build brand and
go deeper with each customer’s spend
An ideal business at scale has presence in 5+ large
metros and with 0.5m+ shoppers in each metro
spending 100$+ per year on the platform sees net
revenues of $250m+ with high gross margins of
30%+
Investors and startups need to deeply evaluate what they are
building / funding, and accordingly, plan to go wider and/or
deeper in new markets
@jungleventures 24

25. Thank you
Amit Anand
Yash Sankrityayan
Li-Anne Ooi
@jungleventures 25

26. 26
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