Blink Traffic: Stevia Angesty Ian Christopher Michael Feng Richard Kidarsa
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Transcript of Blink Traffic: Stevia Angesty Ian Christopher Michael Feng Richard Kidarsa
Blink Traffic: Stevia AngestyIan ChristopherMichael FengRichard Kidarsa
Stanford UniversityENGR 245: The Lean
LaunchpadWinter 2011
Final Project Report
Initial Product Idea
Shanghai Lahore
Bangkok Jakarta
Mobile application providing crowd-sourced real time traffic map in
developing countries
Meet the Team
Michael Feng
Background: Investment Banking and Private Equity in Asia
Expertise: Finance, Marketing
Role: Financials, Strategy
Stevia Angesty
Background: Engineering, Business
Expertise: Indonesian connections, logistics experience
Role: Liaising with customers and partners, market research
Ian Christopher
Background: Computer Science
Expertise: Programming
Role: Technical framework, server-side development
Richard Kidarsa
Background: Engineering
Expertise: Programming, Indonesian connections
Role: Client application development, website
Business Canvas 1
What we did (part 1)
• Interviewed market leader in traffic information services
• Interviewed 8 corporate customers in Indonesia
Inrix Interview
Market Leader in Traffic Data Services
Customer Segments:
Public Sector
Automotive
Media
Mobile
Pass/Fail
Customer Segment: CorporateInterviewed 8 potential business sector customers:
“We have our own proprietary traffic system”
“Traffic is driver’s responsibility. We will evaluate the fuel usage”
“We only give out limited number of corporate Blackberries to employees”
“Tardiness is tolerable. We use motorcycles if it is too late” cTc
Customer Segment: Corporate
Users
The Dispatchers:Sounds cool. It’d be more efficient than relying on drivers.
Customer Archetypes
Customer Segment: Corporate
Users Influencers and Recommenders
The Managers:We’d love to have the app if it works
Customer Archetypes
Customer Segment: Corporate
Users
Influencers and Recommenders
Economic Buyers, Decision Makers
The Procurement Dept:Our drivers know the the traffic better than you!
Customer Archetypes
Customer Segment: Corporate
Users
Influencers and Recommenders
Economic Buyers, Decision Makers
Archetypes
Saboteurs
The Drivers:Are you questioning our expertise?
International, local, large, and small companies
Pass/Fail
FAIL
Customer Segment: Corporate
High Acquisition
Cost
Huge Penetration
Barrier
Good Drivers +
Fuel Usage Tracking
Corporates are not our initial target market
Business Canvas 2
What we did (part 2)
• Interviewed market leader in consumer traffic applications (Waze)
• Interviewed 2 Indonesian web startups• Surveyed 98 Indonesian commuters
Waze Interview
• How did they grow?
• What markets are they focusing on?
• What are the key challenges?
• How do they make money?
100% crowdsourced traffic targeting
consumers
2009 (est) 2010 20110
500,0001,000,0001,500,0002,000,0002,500,000
Use
rs
Recently raised $25 million Series B
round
Social and gaming features
North America
Data costs, cultural differences
They don’t…yet
Jagoan Interview
User friendly interface while
looks savvyUser
Loyalty
* Indonesian Social App* Partnered with Retail
Companies
SLOWconnection
Disdus Interview
Troublesomepaymentmethod
* Indonesian Groupon* Potential partnership
for advertising
Hard to monetize before
critical mass
B2C Customer Feedback
98web and phone
surveys in Indonesia
2½h
spent in car per day
1h spent in heavy traffic (<6mph)
per day
$8
on gasoline per day
B2C Customer Feedback
20% of reduction in heavy traffic would save a person1:
50hsaved per year
$42gasoline costs per
year2 $1/month
Blink Subscription:
1. Assumes 5 working days per week and 50 workweeks per year2. Assumes gasoline usage is 30% of normal usage during heavy traffic
B2C Customer Feedback
120web and phone
surveys in Indonesia
46%CARPOOL
52%USE DRIVERS
Plenty of time to use mobile devices while commuting
1. Motivated by 3-person HOV lanes
2. Alternative: pay “carpool jockeys” $2.50 per trip
B2C Customer feedback1
Blackberry leads usage but iPhone/iPads important
Blackberry iPhone iPad other smartphones None0%5%
10%15%20%25%30%35%40%45% 40%
28%
4%8%
20%
What mobile device do you use in the car?
Conclusion:Focus on Blackberry first and iPhone/Pad second
1. Data obtained from web and phone surveys of 120 potential customers
1. Data obtained from web and phone surveys of 120 potential customers
B2C Customer feedback1
What do you do with your smartphones in the car?
Never Rarely Sometimes Often Always >= Sometimes
Work 39 17 33 6 17 50%Gather traffic information 66 28 17 6 0 20%Read news 39 22 22 28 0 46%Browse internet 28 17 11 33 28 62%Socialize with friends 11 6 28 28 44 86%Play games 33 17 39 11 17 58%
How often would you use these features of our application?
Never Rarely Sometimes Often Always >= Sometimes
Report incidents 22 28 22 33 17 60%Join a chat 33 28 44 17 0 50%Play mini-games 44 28 28 22 0 41%Ask and respond to questions 39 39 28 17 0 37%Find your friends and followers 22 39 22 28 6 48%Earn points for driving more 33 39 22 22 11 44%
Community and game mechanics are critical to driving usage and virality
Business Canvas 3
What we did (part 3)
• Assessed market size• Tested demand creation via website
How Big is the Market?1. Located outside the U.S., Western Europe, and Australia2. Mobile penetration rate * population >= 4 million3. Population density >= 2500 per sq km4. GDP growth rate >= 5%
South Asia: Mumbai, Delhi, Kolkata
Africa: Cairo, Lagos
SE Asia: Jakarta, Surabaya, Bangkok, Singapore, Kuala Lumpur, Manila
North Asia ex-China: Taipei, Hong Kong, Seoul
China: Beijing, Shanghai, Shenzhen
Mediterranean: Istanbul
South America: Rio de Janeiro, Sao Paulo, Bella Horizonte, Lima, Santiago. Buenos Aires
Latin America: Mexico City
Total cities: 24Total mobile users: 203.7 million
Market Growth Plan
Market 1 2 3 4
Cumulative number of cities
1 6 15 25
Cumulative mobile users (millions)
10.4 36.9 109.6 203.7
Detailed income statement and assumptions in Appendix
Success Depends on Virality > ChurnRatio of early stage virality rate to churn rate = 2.00x
Success Depends on Virality > ChurnRatio of early stage virality rate to churn rate = 1.50x
Success Depends on Virality > ChurnRatio of early stage virality rate to churn rate = 1.0x
Demand creation via website
“Not a landing page”No Indonesian version
1 32
Doesn’t show the product
Demand creation via website - results
1 2 30
20406080
22
68 74Clicks
1 2 30.00%0.50%1.00%1.50%2.00%
0.59%
1.25%1.56%
CTR
1 2 30
0.5
1
1.5 1.34
0.54 0.62
CPC
1 2 30.00%
2.00%
4.00%
0.00%
2.94%4.05%
Conversions per click
People need to use the product for us to maximize learning
Business Canvas 4
What we did (part 4)
• Developed server backbone integrated with OSM and Hadoop
• Built a working Blackberry application• Iterated based on user feedback• Talked to potential partners
Server Backbone with OSM and Hadoop
Front End
Client
OSM DATA BLINK DATA
MAP MANAGER
AGGREGATION
USER/EVENT MANAGER
TRAFFIC DATA
Blackberry application testing
• Iterate through different versions
Ver1
Ver2
Ver3
First release issuesDevice cannot
connect to internet
Different provider setting
for Indonesia
Downloading problems
Fix website,Provide
instructions
People don’t want to leave
feedback
Pop up windowto force people
to give feedback
Second release issues
Bad GPSsignal
Use data-assisted GPS
Users dislike Pop-ups
Show instructions and
pop-up once
Users have old Blackberry OS Support older OS
Second release feedback result
User wants to see their friends Want traffic data So far 50
downloads
Third release
Feedback on 3rd release:
User can locate others on map
20 downloads since release 3
days ago
Battery life
Adjust server ping rate
Privacy
Implement privacy toggle
Implemented chatting
5 new users introduced via
sharing
Key Partners
AGM
Large companies are hard to negotiate. Blink will focus more on partnering with other Startups
Final Business Canvas
• MVP has to include virality, not just traffic• Legal-ese is difficult to handle. It took us a long time to understand this• Users need to test the product in order to maximize learning• We need to assume that users are technically illiterate• Simplicity is everything from the user’s perspective• Users who like our idea are not the same as early adopters / promoters• Need to balance tech planning and implementation• Difficult learning curve to master technologies like EC2 and Apache• Blackberry is not developer-friendly and it spreads to the server• Getting user feedback is a lot harder than we originally thought• Difficult to approach customers large and small the second time around• From mindsets to trends to technical literacy, the tech landscape is different in parts of the world.• We cannot spend too much time thinking off / writing an elegant solution, but you also cannot
write garbage• Code organization really starts to become more and more important as you LOC grows. By 5,000
LOC it will be crucial to have a well organized code base.• User mindsets and technological environment differ tremendously from market to market
Epilogue: What we learned• MVP has to include virality, not just traffic• Legal-ese is difficult to handle. It took us a long time to understand this• Users need to test the product in order to maximize learning• We need to assume that users are technically illiterate• Simplicity is everything from the user’s perspective• Users who like our idea are not the same as early adopters / promoters• Need to balance tech planning and implementation• Difficult learning curve to master technologies like EC2 and Apache• Blackberry is not developer-friendly and it spreads to the server• Getting user feedback is a lot harder than we originally thought• Difficult to approach customers large and small the second time around• From mindsets to trends to technical literacy, the tech landscape is different in parts of the world.• We cannot spend too much time thinking off / writing an elegant solution, but you also cannot
write garbage• Code organization really starts to become more and more important as you LOC grows. By 5,000
LOC it will be crucial to have a well organized code base.• User mindsets and technological environment differ tremendously from market to market
Epilogue:• Is this a viable business?
– Potential to solve a hair-on-fire problem for a huge and growing market– Small capital investment needed to validate business model– High ROI
• Will we pursue it after the class?
– YES!
“You gotta be in front of the wave to catch it”
Business Canvas Change Progress
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Business Canvas Change Progress
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Business Canvas Change Progress
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Business Canvas Change Progress
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Business Canvas Change Progress
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Business Canvas Change Progress
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Business Canvas Change Progress
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Business Canvas Change Progress
FINAL
THANK YOU!
Appendix: Key Assumptions
Growth stages Early Mid Late Plateau
Market penetration rate 0.0% 3.0% 10.0% 15.0%
Churn rate 50% 50% 20% 10%
Virality coefficient 0.75 0.60 0.20 0.10
Promotion % increase 10% 3% 2% Population growth
Employees per city 5 10 20 30
Rent per city 1,000 2,000 5,000 10,000
CostsMonthly salary per employee $1000Setup costs per city $100,000 Technology costs per 1000 users $20 Fixed promotion costs per city $10,000 Annual promotion costs per active user $1 Tax rate 25%
RevenuesAd revenues start when users per city exceed 10,000 Views per month per active user 67.75Advertising eCPM 1.00
Premium revenues start when users per city exceed 200,000 Premium percentage of regular users 17%Premium pevenue per user per month 1.00
Appendix: MarketsRank
(Global Density)
City / Urban area Country Population
Land area Density GDP GDP Mobile phones Market
(in sqKm) (per sqKm) per capita growth rate per capita size
1 Mumbai India 14,350,000 484 29,650 3,400 8.30% 63.22% 9,072,0702 Kolkata India 12,700,000 531 23,900 3,400 8.30% 63.22% 8,028,9404 Lagos Nigeria 13,400,000 738 18,150 2,400 6.80% 50.30% 6,740,2005 Shenzhen China 8,000,000 466 17,150 7,400 10.10% 62.80% 5,024,000
6 Seoul/Incheon South Korea 17,500,000 1,049 16,700 30,200 6.10% 97.20% 17,010,000
7 Taipei Taiwan 5,700,000 376 15,200 35,100 8.30% 100.00% 5,700,00010 Shanghai China 10,000,000 746 13,400 7,400 10.10% 62.80% 6,280,00011 Lima Peru 7,000,000 596 11,750 9,200 7.80% 95.50% 6,685,00012 Beijing China 8,614,000 748 11,500 7,400 10.10% 62.80% 5,409,59213 Delhi India 14,300,000 1,295 11,050 3,400 8.30% 63.22% 9,040,46015 Manila Philippines 14,750,000 1,399 10,550 3,500 6.70% 73.60% 10,856,00017 Jakarta Indonesia 14,250,000 1,360 10,500 4,300 6.00% 73.10% 10,416,75021 Cairo Egypt 12,200,000 1295 9,400 6,200 5.30% 76.80% 9,369,60025 Sao Paulo Brazil 17,700,000 1968 9,000 10,900 7.50% 100.00% 17,700,00027 Mexico City Mexico 17,400,000 2072 8,400 13,800 5.00% 79.80% 13,885,20028 Santiago Chile 5,425,000 648 8,400 15,500 5.30% 100.00% 5,425,00029 Singapore Singapore 4,000,000 479 8,350 62,200 14.60% 100.00% 4,000,00032 Istanbul Turkey 9,000,000 1166 7,700 12,300 7.30% 92.20% 8,298,00035 Rio de Janeiro Brazil 10,800,000 1580 6,850 10,900 7.50% 100.00% 10,800,00037 Hong Kong Hong Kong 7,100,000 1100 6,455 45,600 5.70% 100.00% 7,100,00038 Bangkok Thailand 6,500,000 1010 6,450 8,700 7.60% 81.00% 5,265,00047 Buenos Aires Argentina 11,200,000 2266 4,950 15,000 7.80% 100.00% 11,200,00052 Belo Horizonte Brazil 4,000,000 868 4,600 10,900 7.50% 100.00% 4,000,00090 Kuala Lumpur Malaysia 4,400,000 1606 2,750 14,700 7.10% 100.00% 4,400,000
Total mobile users: 203.7 million
Appendix: Base Case Income StatementYear 0 1 2 3 4 5 6 7 8 9 10
Active users 200 7,329 268,559 1,535,297
2,980,314 6,056,792 13,783,296 21,013,877 33,175,710 36,705,798 39,698,300
% of market 0.0% 0.1% 1.9% 3.2% 2.0% 4.0% 5.1% 7.7% 12.1% 13.3% 14.2%
Premium users - - 45,655 252,455
503,865 927,475
2,332,870
3,572,359 5,639,871 6,239,986 6,748,711
Basic users 200 7,329 222,904 1,282,842
2,476,449 5,129,317 11,450,427 17,441,518 27,535,839 30,465,812 32,949,589
Revenues
Advertising - 64,502 614,266
1,445,797 3,180,516
6,551,758 12,404,549 18,487,439 23,697,673 25,988,931
Premium - 45,655 1,846,731
3,819,142 9,198,477 19,113,580 36,267,426 55,890,537 71,641,922 78,568,768
Total Revenues - 110,157 2,460,997 5,264,939 12,378,993 25,665,338 48,671,976 74,377,976 95,339,594 104,557,698
Costs
Market Entry Costs 100,000 - 500,000
900,000 -
1,000,000
-
-
-
-
Employee Salaries 60,971 62,800 399,824
756,995 1,809,328
3,008,931
4,821,172 6,152,098 8,395,482 9,511,708
Technology 550 20,152 220,947
503,758 1,127,276
2,320,268
4,388,843 6,575,357 8,428,461 9,243,384
Rent 12,000 12,000 75,000
148,000 348,000
582,000
959,000 1,210,000 1,760,000 2,085,000
Promotion 121,697 182,198 1,435,261
2,879,322 6,240,609 11,424,743 20,684,296 29,383,836 37,824,415 41,264,727
Total Costs 295,218 277,150 2,631,032
5,188,075 9,525,213 18,335,942 30,853,311 43,321,292 56,408,358 62,104,819
Operating cashflow (295,218) (166,993) (170,034) 76,865 2,853,780
7,329,396 17,818,665 31,056,685 38,931,236 42,452,880
Taxes paid - 5,626 290,449
514,985 1,176,461
2,465,737
4,946,514 7,764,171 9,732,809 10,613,220
Net income (295,218) (172,619) (460,483) (438,120) 1,677,319 4,863,659 12,872,151 23,292,514 29,198,427 31,839,660
Retained earnings (295,218) (467,836) (928,320) (1,366,440) 310,880 5,174,539 18,046,689 41,339,203 70,537,630 102,377,290
Appendix: Blink Customer Archetypes
Commuters in large developing market cities:
- Working professionals with cars
- Working professionals using public transport
- Students
- Stay-at-home partners (Tai-Tai’s)