juxt indian mobile, internet & mobile internet learnings & way forward-apr14_public

Mobile, Internet & Mobile

Internet in India

This document summarizes the learning & insights from Juxt’s studies, and their potential relevance for Internet Industry stakeholders

April 2014

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Let’s take a good look of India before digging deeper…

Public April 2014

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35 States & UTs

640 districts

7,935+ towns

640,867+ villages

1.2billion individuals

247million households

Map Visual: http://www.economist.com/content/indian-summary

Public April 2014 Source: Census 2011

http://www.economist.com/content/indian-summary

How many & who are the users?

4Public April 2014

Saturated mobile voice users base – a ready targetable base for differentiated services

210mn HHs with mobile users - Mobile is already in 83% of the HHs (90% U, 80% R)

49mn HHs with Internet* users - Internet is already in 20% of the HHs (50% U, 6% R)

589mn Mobile users - Mobile is already used by 50% of the Individuals (75% U, 39% R)

106mn Internet users - Internet is already used by 9% of the Individuals (23% U, 3% R)

34mn Mobile internet users

5Public April 2014 Source: Juxt Studies/Estimates 2013-14

Note: Internet user is someone accessing internet on PC/Laptop, Mobile/Tablet or Smart TV), excluding the ones using mobile operators’ content portal

On-device (mobile operators’ content portal) users base stand at 136mn

55% of these are overlap with regular internet users (large + small screen)

“Mobile operators’ content portal users” base is bigger than “regular Internet users” base


With data connectivity – users with active 2G/3G/4G connections is at 34.6mn However, the interesting trend is in “exclusive

mobile internet users” base Over last 2 years it has moved from 130K to

7mn+

Without data connectivity – exclusive on-device (operators’ content portal) users stand at 61.2mn – The ones unknowingly experiencing Internet first time, that to not through a large screen

Current mobile Internet usage in the country is just the tip of iceberg


You can double count to raise money, but then be prepared for the under performance and higher gestation period

Please understand that AUBUC ≠ A+B+C,

175mn ≠ 276mn active internet users in India


Number of PCs/Laptops at home & elsewhere is still a small number

Therefore, what matters is the PC users or mobile users or Internet users number not so much device numbers

9Public April 2014

Source: http://mait.com/uploads/file/MAIT-KPMG%20Report%20-%20Executive%20Summary.pdf

Town classes are more important than telecom circles in an unified licensing era

10Public April 2014

• 640K+ villages (69% of Indian Pop) • Of 821mn rural pop 6% using InternetRural

• 7531 towns (41% urban Indian pop)• Of 159mn people 8% using internet

Up to 1lakh+ population

• 404 towns (21% of urban Indian pop)• Of 80mn people 7% using internet

1 to 5lakh population

• 45 towns (8% of urban Indian pop)• Of 31mn people 9% using internet

5 to 10 lakh population

• 47 towns (30% of urban Indian pop)• Of 117mn people 29% using internet 10lakh+ population

Source: Juxt Studies/Estimates 2013-14

Intuitively, females account for 50% of population, consumption and 75% of consumption decisions

However, only about 36% of the mobile users are female (39% U, 33% R)

26% (27% U, 19% R) of Internet users are female

Females are yet to become the mobile or data users


Penetration is still limited to 19 to 35yrs. old urban population

Only about 45% of the Urban population in 19 to 24 years age and 56% of urban population in 25 to 35 years age are internet users

In all other age groups penetration is sub 20% in urban India and sub 10% in rural India. 12Public April 2014

Age GroupsUrban Pop

(mn)Urban Int.

Pent.Rural Pop

(mn)Rural Int.

Pent.Total Pop

(mn)All Int.

Pent.

Up to 18 yrs 128.5 6% 343.6 1% 472.1 2%

19-24 yrs 44.6 45% 87.7 7% 132.3 20%

25-35 yrs 75.0 56% 143.4 7% 218.4 24%

36-45 yrs 52.4 20% 100.6 2% 153.0 8%

46-55 yrs 35.9 10% 67.2 1% 103.1 4%

Above 55 yrs 39.1 4% 88.3 0.4% 127.4 2%

All India 375.5 23% 830.8 3% 1206.4 9%


Six major keys to unlock the potential

13Public April 2014

Average upload & download speed* users get is between 0.99mbps to 1.98mbps

Home users get the lowest upload & download speed (0.65mbps upload, 1.42mbps download)

Best speed is available to Office, Cyber-café & Data-card users in that order

1st Key - Speed

14Public April 2014

*Note: Based on 22.9K actual speed test API calls done by representative set of respondents across various place of access.

All Internet Users Office Cyber Cafe

Data card/dongle

Average upload speed in Mbps 0.99 1.90 0.85 0.80Average download speed in Mbps 1.98 3.74 1.60 1.64


Online ActivitiesAll Internet

UsersOnly

Home

Only Place of

WorkOnly Cyber-

café

Both Home & Place of

Work

Both Home &

Cyber-café

Both Place of Work & Cyber-café

All Three

Projected Base 10,69,00,967 3,75,37,461 2,02,73,631 1,13,96,242 1,78,24,921 44,75,730 38,49,883 62,80,179 Social networking 82% 79% 79% 82% 90% 87% 82% 94%Download music 63% 65% 54% 58% 73% 67% 61% 67%Watch videos 62% 58% 55% 58% 73% 78% 60% 83%Train Ticketing 46% 42% 46% 42% 57% 57% 58% 63%Download movies 30% 27% 25% 31% 40% 46% 24% 46%Share/upload pictures 29% 26% 24% 28% 36% 43% 29% 44%Online games 22% 20% 19% 24% 28% 30% 19% 36%Listen/stream music online 20% 17% 17% 21% 26% 25% 20% 33%

Share/upload videos 17% 12% 14% 20% 21% 25% 19% 30%Share/upload music 12% 9% 9% 15% 15% 19% 14% 22%

Heavy bandwidth requiring activities must be leading to bad experience or yet to take off


More than half of the Internet users who prefer their own vernacular language as preferred language of reading end up visiting English websites

Reasons Absence of local language computing environment in

the country Difficulty in exploration/lack of access/search engines

not suggesting/local language sites’ lack of funds to create awareness etc.

2nd Key - Local language content

16Public April 2014

Preferred Language

EnglishLocal

Language

Websites Visit Regularly

Local Language 29% 46%

English 71% 54%


87% of the current installed base of handsets are below Rs. 3,500 cost (84% U, 90% R)

For mass adoption, the sweet spot of device has to below Rs. 3,000

3rd Key - Device

17Public April 2014

Cost of Handset Owned All Mobile Users Urban RuralUp to Rs.800 3% 1% 5%Rs. 801 - Rs. 1200 24% 21% 27%Rs. 1201 - Rs. 1800 21% 18% 24%Rs. 1801 - Rs. 2500 24% 26% 21%Rs. 2501 - Rs. 3500 15% 17% 13%Rs. 3501 - Rs. 5000 10% 13% 7%Rs. 5001 - Rs. 7500 3% 4% 3%Rs. 7501 - Rs. 10000 2% 2% 2%Above Rs. 10000 4% 4% 4%Average cost of handset (In Rs.) 2921.22 3167.72 2695.40


Paraphrasing Jason Calcanis -- The migration from “lean back” to “lean front” to now “curl up” experience is inevitable.

4th Key –Shift from type to touch

18Public April 2014

Lean back – 99% passive with interaction limited to zombie-like remote control behavior

Lean forward to use a keyboard and look into the screen

Curl up computing is the future - the most important experience in media is no longer learning forward into your computer, or leaning back to consume video, it's curling up with a device

For reading 90% of mobile users prefer an Indian language to English However, 84% of these people operate their phones in

English

Lower operating comfort level will also dictate lower usage of the phone for various purposes including browsing (Very important given that mobile devices are spurring connectivity and data usage in this country in line with international trends)

Touch screen is the only hope in absence of a local language computing environment in the country

Touch screen with local language environment will create the killer combination


Two key questions: Historically, consumers never paid the actual

worth of Newspaper, Radio or TV, then why would they pay for Internet?

Would an average user ever pay significantly higher than the current “data ARPU”? (Rs. 60 to Rs. 80)

Possible answer is in “closing the attribution loop in online-to-offline commerce” to subsidize the cost of data access for a regular consumer

5th Key – Cost of data access

20Public April 2014 Source: Industry Reports

What “blind to its surrounding” mean: e.g., smart phone have no idea when one

arrive at a theater after purchasing a ticket through “bookmyshow” app or

When one ended up in a restaurant after searching it on a “zomato” app

But the essence is much deeper than the average marketer’s wet dream of pushing location based coupons (or promos) Can there be a system for providing “viewing

ability” to a smart phone, that helps in closing the attribution loop in online-to-offline commerce? (similar to iBeacon by Apple)

A smart device should not remain “blind to its surroundings”

21Public April 2014

6th Key - Identifying the segments, developing relevant offers and communicating differentiated services

Being in constant touch with the customers would be the most important key to success

22Public April 2014

Methodology

23Public April 2014

User-ship estimates based on a very large land survey of over 121,311 individuals spread across all mainland states & union territories of the country. Survey conducted in May–July 2013 among 24,225 households in 109 towns and 5,841 households in 196 villages – a total of over 30,066 households profiling 121,311 individuals in those households

Most ‘comprehensive’ profiling of Indian consumers users – in their demographics, socio-economic

A deeper profiling of the Indian consumers, their consumption lifestyle including details about their location, economic status, martial status, Mother tongue, etc

24October 2014

Juxt offline enumeration study - Overview

A large-scale land survey was conducted to profile and estimate the Indian internet users. The survey covered ‘towns’ and ‘villages’ of all population strata in all the mainland states and union territories in India (covering all the key, and 80 of the total 88 regions in India as classified by NSSO) – all 23 telecom circles were covered extensively

Though the selection of towns and villages was ‘purposive’, trying to get at least one town from each NSSO region and each town class within a state

The sampling within the towns was done on ‘2-stage random’ basis (firstly a random selection of polling booths, and then a random selection of households from the electoral list within each of these randomly selected polling booths); within villages sampling was done on ‘systematic random’ basis (selection of every nth house in the village)

25October 2014

Juxt offline enumeration study

The objective of the online sampling and survey was to reach out to the actual Internet users and collect the ‘in-depth’ information on their Internet access and usage behavior and preferences directly from them through a ‘self-administrable’ online questionnaire.

The online sampling this year was done using Juxt’s 50million strong ‘online access panel’, ‘GetCounted’ (www.getcounted.net) and its associate partner’s panels.

The details about their more recent internet usage behavior, like the ‘online activities’ they undertake, the websites they visit the most to undertake these activities, their online shopping status and behavior, etc. were captured by conducting an ‘online survey’ among the active GetCounted and associate partner panel members. A reportable sample of 36,464 internet users, including 6,166 Cybercafe users was collected among these active panel members.

The online questionnaire used in the ‘online survey’ was pre-tested and timed to take approximately 30-40 minutes for a respondent to complete depending on the speed of comprehension and answering of the questions. A new responsive UI was designed to minimize the level of ‘respondent fatigue’ to an extent that was practically possible.

The Online Sampling and Survey

26Confidential

http://www.getcounted.net/

Thank [email protected], +91-9717133445

27Public April 2014

mailto:[email protected]

juxt indian mobile, internet & mobile internet learnings & way forward-apr14_public

Data & Analytics