第1页
INTERNET TRENDS 2014 – CODE CONFERENCE
Mary Meeker May 28, 2014 kpcb.com/InternetTrends
第2页
Outline
1) Key Internet Trends 2) Status Update – Tech Stocks / Education / Healthcare 3) Re-Imagining Continues 4) Screen + Video Growth = Still Early Innings 5) China’s Epic Share Gains 6) Public Company Trends 7) One More Thing(s)... 8) Ran Outta Time Thoughts / Appendix
第3页
KEY INTERNET TRENDS
第4页
High-Level User / Usage Trends*
• Internet Users <10% Y/Y growth & slowing...fastest growth in more difficult to monetize developing markets like India / Indonesia / Nigeria
• Smartphone Subscribers +20% strong growth though slowing...fastest growth in underpenetrated markets like China / India / Brazil / Indonesia
• Tablets +52% early stage rapid unit growth
• Mobile Data Traffic +81% accelerating growth...video = strong driver
*Details on Internet Users & Smartphone Subscribers in Appendix. Source: Tablet growth per Morgan Stanley Research, 5/14. Mobile traffic per Cisco Visual Networking Index, 5/14.
第5页
Mobile Usage Growth = Very Strong
第6页
Global Smartphone Quarterly Units Shipped (MM)
Global Smartphone Users as % of Mobile Phone Users
Smartphone Users = Still Lots of Upside... @ 30% of 5.2B Mobile Phone User Base
Global Smartphone Quarterly Unit Shipments & Smartphone Users as % of Mobile Phone Users, 2009 – 2013
400 40%
300 291 30%
266 244 233
200 170 159 172
134 102 104 113
100 83
35 42 43 54 55 64
20% 10%
0 0%
Smartphone Units Shipped
Smartphone Users as % of Mobile Phone Users
Source: Smartphone shipments per Morgan Stanley Research. User base per KPCB estimates based on Morgan Stanley Research and ITU data. Smartphone users & mobile phone users represent unique individuals owning mobile devices, as noted on slide 8; Mobile Subscribers based on number of connections & may therefore overstate number of mobile users.
第7页
Tablet Units = Growing Faster Than PCs Ever Did... +52%, 2013
Global PC (Desktop / Notebook) and Tablet Shipments by Quarter Q1:95 – Q4:13
Global Units Shipped (MMs)
0 Q1:95 Q1:97 Q1:99 Q1:01 Q1:03 Q1:05 Q1:07 Q1:09 Q1:11 Q1:13
Desktop PCs
Notebook PCs
Tablets
Source: Morgan Stanley Research. Note: Notebook PCs include Netbooks.
第8页
Tablet Users = Loads of Growth Ahead... @ 56% of Laptops / 28% of Smartphones / 8% of TVs
Global Users of TVs vs. Mobile Phones vs. Smartphones vs. PCs vs. Tablets, 2013
Population Penetration
TV
5.5B
78%
Mobile Phone
5.2B
73%
Smartphone
1.6B
22%
Laptop PC
789MM
11%
Desktop PC
743MM
10%
Tablet 0
439MM 1,000
2,000
3,000
4,000
Global Users (MMs)
5,000
6,000
6%
Source: KPCB estimates based on Morgan Stanley Research and ITU data. TV Users is estimate for users with TVs in household, given 1.4B households with TVs in world.
第9页
Mobile Usage = Continues to Rise Rapidly... @ 25% of Total Web Usage vs. 14% Y/Y
Mobile Usage as % of Web Usage, by Region, 5/14
50%
% of Page Views Coming From Mobile Devices
40%
37%
38%
30% 20% 10%
19% 11%
17% 6%
23% 16% 8%
18%
25%
17%
12%
14%
0%
North South Europe Asia
Africa
America America
May-13
May-14
Oceania
Global
Source: StatCounter, 5/14.
第10页
Global Smartphone Operating Systems ‘Made in USA’... 97% Share from 5% Eight Years Ago
Global Smartphone Operating System Market Share (by Units Shipped), 2005 vs. 2010 vs. 2013
100%
Market Share of Smartphone OS
80% 60% 40% 20%
Other OS iOS Android Windows Phone BlackBerry OS Linux Nokia Symbian
0% 2005
Source: 2005 & 2010 data per Gartner, 2013 data per IDC.
第11页
Each New Computing Cycle = 10x > Installed Base than Previous Cycle
Source: Morgan Stanley Mobile Internet Report (12/09)
第12页
Advertising / Monetization = Mobile Especially Compelling
第13页
Internet Advertising = Remains Strong... +16%...Mobile +47% to 11% of Total
Global Internet Advertising, 2008 – 2013
$125
$116
25%
$100
$100 $86
$76
$75 $62
$64
20% 15%
$50 10%
Global Internet Advertising ($B) Y/Y Growth
$25 5%
$0 2008
Desktop Advertising
Source: PWC Global Entertainment & Media Outlook, 2013.
Mobile Advertising
0%
Y/Y Growth
第14页
ARPU Upside for Facebook + Twitter... Google ARPU = 6x Facebook...Facebook = 2x Twitter
Annualized Ad ARPU ($) & Mobile % of MAU
Annualized Ad ARPU ($) Q1:12 Q2:12 Q3:12 Q4:12 Q1:13 Q2:13 Q3:13 Q4:13 Q1:14
Google ($) Y/Y Growth
$37 $37 $38 $43 $42 $41 $41 $46 $45 9% 6% 6% 14% 14% 11% 10% 8% 8%
Facebook ($) Y/Y Growth Mobile % of MAU
$4.00 $4.28 $4.43 $5.15 $4.60 $5.65 $6.14 $7.76 $7.24 1% (2%) 7% 12% 15% 32% 39% 51% 57%
54% 57% 60% 64% 68% 71% 74% 77% 79%
Twitter ($) Y/Y Growth Mobile % of MAU
$1.29 $1.50 $1.64 $2.15 $1.97 $2.22 $2.65 $3.65 $3.55 90% 134% 108% 93% 52% 48% 61% 69% 80% -- -- -- -- -- 75% 76% 76% 78%
Source: SEC Filings & Comscore. ARPU = Average Revenue per User, defined as annualized revenue per Monthly Active User (MAU). Google ARPU is calculated using Google’s gross revenue & Comscore unique visitors.
第15页
Remain Optimistic About Mobile Ad Spend Growth... Print Remains Way Over-Indexed
% of Time Spent in Media vs. % of Advertising Spending, USA 2013
% of Total Media Consumption Time or Advertising Spending
50% 40% 30% 20% 10%
0%
19%
5% Print
Time Spent
Ad Spend
45% 38%
Internet Ad Mobile Ad
= $43B = $7.1B
25% 22%
20%
~$30B+
Opportunity in USA
12% 10%
Radio
TV
Internet
4% Mobile
Source: Advertising spend based on IAB data for full year 2013. Print includes newspaper and magazine. $30B+ opportunity calculated assuming Internet and
Mobile ad spend share equal their respective time spent share. Time spent share data based on eMarketer 7/13 (adjusted to exclude outdoors / classified media 15
spend). Arrows denote Y/Y shift in percent share.
第16页
Mobile App Revenue = Still Trumps Mobile Ad Revenue... @ 68% of Mobile Monetization
Global Mobile App + Advertising Revenue, 2008 – 2013
Mobile Ad + Apps Spending ($B)
$40 Mobile Apps Mobile Advertising
$30
$20
$10
$2 $0
$3 2009
$6 2010
$14 2011
$24 2012
$38 2013
Source: Global Mobile App revenue per Strategy Analytics; comprises virtual goods, in-app advertising, subscription, & download revenue. Global Mobile Advertising revenue per PWC; comprises browser, search & classified advertising revenue.
第17页
Cyber Threats Intensifying...
第18页
Cybersecurity Trends – Kevin Mandia (Mandiant / FireEye)
1) # of Active Threat Groups Rising Rapidly = 300 (+4x since 2011) per Mandiant tracking
2) Increased Nation-State Activities* 3) Vulnerable Systems Placed on Internet Compromised in
<15 Minutes** 4) +95% of Networks Compromised in Some Way 5) As Mobile Platforms Grow, Directed Attacks Will Rise
Source: *FireEye Operation Saffron Rose, **Honeynet Project.
第19页
STATUS UPDATE –
TECH STOCKS / EDUCATION / HEALTHCARE
第20页
Technology Company Valuation Excess? Some? Yes...
But, Let’s Look @ Patterns...
第21页
2013 Technology IPOs = $ Volume 73% Below 1999 Peak Level... NASDAQ 18% Below March 2000 Peak
Number of IPOs per Year
Global Technology IPO Issuance, 1990 – 2014YTD
March 10, 2000 = Technology Market Peak, NASDAQ @ 5,049
310 300
May 22, 2014 = NASDAQ @ 4,154
221 87% Below
193 200
134 126
93 76 44 51
86 20 16 19 50 38 39 65 6 15 48 44 43 41 25
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
$40
$31 $31
$30
73% Below
$21
$20 $18
$9 $10 $1 $2 $4 $5 $3
$7 $6
$10 $12 $12
$11
$7 $7
$8
$2 $2
$4 $1
$8 $5
$0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012* 2013 2014
United States
North America
Asia
Europe
South America
NASDAQ
*Facebook = 75% of 2012 IPO $ value. Source: Morgan Stanley Equity Capital Markets, 2014YTD as of 5/21/14, data per Dealogic, Bloomberg, & Capital IQ.
Annual Technology IPO Volume ($B)
第22页
2013 Venture Financings = $ Volume 77% Below 2000 Peak Level
USA Technology Venture Capital Financing, 1989 – 2013
# of USA Technology Companies Receiving Venture Financing
Aggregate Venture Financing for US Technology Companies ($B)
6,000 4,500 3,000 1,500
5,476
50% Below
3,668
2,354 1,782 1,462 765 636 589 679 586 655 985
3,182 2,141 1,898 2,036 2,095 2,349 2,505 2,587 1,918 2,230 2,571 2,637 2,746
0 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Funding per Financing ($MM)
$3
$3
$2
$5
$4
$4
$5
$5
$6
$8 $14 $18 $11 $8
$8
$9
$8
$9
$8
$9
$7
$7 $10 $8
$9
$125 $100
$75 $50 $25
$0
$101
77% Below
$50 $19 $2 $2 $1 $3 $2 $3 $5 $8 $11
$35 $18 $15 $18 $17 $22 $20 $24 $13 $17 $25 $20 $24
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Source: Thomson ONE. Funding per Financing ($MM) calculated as total venture financing per year divided by number of deals.
第23页
Tech Companies @ 19% of S&P500 Value = Well Below 35% March, 2000 Peak Level
Technology Company Market Value as % of S&P500, 1991 – 2014YTD
40%
March 10, 2000 = NASDAQ Peak, Tech as % of S&P @ 35%
30%
20%
10%
0% 1991
Source: Morgan Stanley, Bloomberg, CapIQ, 2014YTD as of 5/21/14.
第24页
Education = May Be @ Inflection Point
第25页
Education Realities = Facts – USA...
Education is Important – Getting education right is crucial for future success
Education is Expensive • Secondary School Costs – USA ranks 4th globally in expenditure per
student among 34 OECD countries* • Higher Education Costs – 71% of 4-year college grads = $30K average
student loan debt. All in, this $1T+ exceeds credit card & auto loan debt
Education Results Often Subpar • Public Schools – Rank 27th globally in math / 20th in science / 17th in reading • College Job Prep – 1/3 of four-year college graduates feel their education
did not prepare them well for employment
*USA ranks behind Luxembourg / Switzerland / Norway. Source: OECD Programme for International Student Assessment, 2011 & 2012. The Institute for College Access & Success, 2014. Consumer Financial Protection Bureau. ‘Voice of the Graduate,’ McKinsey / Chegg.
第26页
...Education Realities = Reasons for Optimism...
• People Care About Education – 8 in 10 Americans say education issue is extremely / very important to them
• Personalized Education Ramping – People learn in different ways and Internet offers many options – on own terms and at low cost – to many, with real-time feedback
• Distribution Expanding & Education Start Up Costs Declining – Direct to consumer / teacher allows education products to receive rapid mass adoption...productization / distribution costs falling
Source: GfK Public Affairs & Corporate Communications, 2012
第27页
...Education Realities = Green Shoots Data
• Graduation Rates Rising – 81% of high school freshman graduated in 2012, up from 74% five years ago
• Language Learning Easier / Fun – 25MM+ people (+14x Y/Y) use Duolingo app to learn new language
• Communication Easier – 12MM+ teachers / students / parents (+15x Y/Y) use Remind101 to send 500MM+ messages
• Behavior Feedback Easier – 35MM+ teachers / students / parents using ClassDojo to help improve student behavior through real-time feedback
• Online Courses Can Help Learning Process (for Teachers + Students) • 430MM+ views (+69% Y/Y) on Khan Academy YouTube channel, 10MM MAUs • 65MM+ courses (+59% Y/Y) from iTunes U Open University downloaded • 7MM+ students (+ >2x Y/Y) enrolled in Coursera courses
Source: National Center for Education Statistics, 2014. Company data.
第28页
Online Education = It’s a Global Thing
Duolingo (25MM Users)
Traffic Distribution, 4/14
5% 11%
29%
25%
30%
North America Latin America Africa / Oceana
Source: Duolingo, Coursera.
Europe Asia
Coursera (7MM Users)
Student Distribution, 3/14
6%
25%
35%
11%
23%
North America Latin America Africa / Oceana
Europe Asia
第29页
Healthcare = May Be @ Inflection Point
第30页
Healthcare Realities = Facts – USA...
• Costs Up to 17% of GDP – @ $2.8T in 2012, +2x as percent of GDP in 35 years
• Waste = 27% of Spend – $765B of healthcare spend estimated from excess costs: $210B = unnecessary services; $190B = excess administrative; $55B = missed prevention opportunities; $310B = inefficient delivery of care / fraud / inflated prices (2009)
• Employers Carry Big Burden – $620B spend by employers for 150MM Americans (2014E)...costs up 28% vs. 5 years ago...67% CFOs indicate healthcare costs = leading economic concern
• Individual Costs Rising – >25% of family income likely to go to healthcare spending in 2015E vs. 18% in 2005...top 5% healthcare consumers (most with multiple chronic illnesses) spent 50% of healthcare dollars (2009)...>50% of personal bankruptcies driven by healthcare costs
• Chronic Conditions = +75% of Spend – Most costly = cancer / diabetes / heart disease / hypertension / stroke...1 in 2 Americans has at least 1 chronic condition, 1 in 4 has 2+...32% of Americans obese in 2008, up from 15% in 1990
• Behavior = Root Cause of Many Health Problems – Health risk behaviors cause chronic diseases. 52% of adults did not meet recommendations of physical activity (2011)...50% of those with chronic conditions not complaint with taking medicine to manage disease = $100B on avoidable hospitalizations (2010)
Source: Beth Seidenberg, KPCB General Partner; Lynne Chou, KPCB Partner. Sources: Healthcare costs per Center for Medicaid and Medicare Services (CMS). Healthcare waste data per Institute of Medicine. Employers’ healthcare costs per CMS, Kaiser Family Foundation, BAML CFO Outlook Report, Towers Watson. Individual healthcare costs per ChartPack, Leerink & Kaiser. Chronic conditions data per CMS, The New England Journal of Medicine. Behavior data per Centers for Disease Control & New England Journal of Medicine.
第31页
...Healthcare Realities = Reasons for Optimism...
• Digital Technology Enables Change – Healthcare system has relied on antiquated systems
• Government Enabled Change Pushes Technology • HITECH Act – $35B administered by Office of the National Coordinator for Electronic Health Records (EHR) + health information technology in 2013...penalties exist for non-compliance • Affordable Care Act – Coverage expansion in works
• Consumerization of Healthcare – Majority (52%) of consumers want to access tools / websites rankings for quality / satisfaction / patients reviews of doctors + hospitals
Source: Beth Seidenberg, KPCB General Partner; Lynne Chou, KPCB Partner. Sources: ACA data per CBO office. HITECH Act data per HIMSS Report Frost and Sullivan & HealthIT. Consumerization of healthcare data from Deloitte, 2012.
第32页
...Healthcare Realities = Green Shoots Data
• Digitization of Healthcare Happening
• Providers Using Fully Functioning EHR – 84% of Hospitals / Academic / Institutional practices...51% (& rising) of office-based practices
• Consumers Happy to Communicate via Email – 62% for healthcare concerns • Digital Health Venture Investments Rising – +39% Y/Y to $1.9B (2013, USA)
• Quality Over Quantity Incentives Being Implemented
• Payers Incentivized to Engage Patients / Improve Care / Outcomes / Reduce Costs • Providers Shifting to Value-Based from Fee-for-Service Payments • Employers Lowering Costs by Offering Services to Improve Engagement / Choices /
Care – 46% of employers will enact participatory / outcomes based incentives (like weight loss / cholesterol levels)... By 2015, 60% will offer price transparency tools from health plans
• Patient Engagement Rising & Yielding Results
• Redbrick Health – employer engagement platform = 4:1 ROI savings per participant • Teladoc – employer focused telemedicine platform = $798 savings per consultation vs.
office visit & ER over 30 days • Mango Health – adherence app = 84% Statin adherence vs. 52% market average • WellDoc – chronic disease platform = diabetes app prescription with reimbursement
Source: Beth Seidenberg, KPCB General Partner; Lynne Chou, KPCB Partner. Sources: Digitization data per Black Book, Deloitte, & Rock Health. Incentives data per Leerink. Employers lowering costs data per Towers Watson. Company data.
第33页
RE-IMAGINING CONTINUES
第34页
Re-Imagining Messaging / Communications
第35页
A Tweet – David Sacks (Yammer CEO / Founder)
第36页
Global OTT (Over-the-Top) Messaging Services = >1B Users in <5 Years...
Global Messaging Ecosystem – Select Players, 2013
WhatsApp (USA), 4+ Years
MAUs = 400MM, +100% Y/Y Messages / Day = 50B, +178% Y/Y
Tencent WeChat (China), 3+ Years
MAUs = 355MM, +125% Y/Y
Line (Japan), 2+ Years
MAUs = 280MM Messages / Day = 10B Revenue = $388MM, +5x Y/Y (Q4:13)
KakaoTalk (Korea), 3+ Years
Messages / Day = 5.2B, +24% Y/Y Revenue = $203MM, +4xY/Y
Snapchat (USA), 2+ Years Messages / Day = 1.2B
Viber (Israel), 3+ Years MAUs = 100MM
Source: Publicly disclosed company data for 2013. Note: Snapchat messages / day comprises number of snaps sent per day and number of stories viewed per day.
第37页
Evolution of Messaging New Social Graphs... Edges = Potentially More Value than Nodes...
High
Broadcasting Fewer Messages to Large Audiences
Nodes = # of
Contacts
Frequent Interactions with Smaller Group of
Close Contacts
Low Edge Weights = Frequency of
Communication
Source: Anjney Midha, KPCB Associate; Jared Morgenstern, KPCB Entrepreneur Partner.
High
第38页
Evolution of Communications Image + Video Sharing Rising Rapidly
‘Visual Web’ Social Networks: Unique Visitors Trend, USA, 3/11 – 2/14
USA Unique Visitors (MM)
Desktop Only
Multi-Platform
0 3/11
8/11
Tumblr
1/12 6/12 11/12 4/13 9/13 2/14
Pinterest
Instagram
Vine
Snapchat
Source: Comscore, State of Digital Advertising Q1 2014, 4/14.
第39页
Re-Imagining Apps
第40页
Evolution of Apps Internet Unbundling...
First, multi-purpose web apps... ...then, multi-purpose mobile apps...
Cindy Cheng
...now, single-purpose = ‘there’s an app for that...’
Source: Megan Quinn, KPCB Partner.
第41页
Evolution of Apps Internet Unbundling = Rise Of Invisible App
...now some apps are disappearing altogether...
Foursquare Swarm Runkeeper Breeze
Dark Sky
WUT
We’re entering the age of apps as service layers.
These are apps you have on your phone but only open when you know they explicitly have something to say to you.
They aren’t for ‘idle browsing,’ they’re purpose-built & informed by contextual signals like hardware sensors,
location, history of use & predictive computation.
– Matthew Panzarino, TechCrunch, 5/15/14
Source: Matthew Panzarino, Techcrunch.
第42页
Re-Imagining Distribution Channels
& Content
第43页
Social Distribution Leaders = Facebook / Pinterest / Twitter...
• Social Media Traffic Referral Leaders = Facebook / Pinterest / Twitter with estimated 21%, 7%, 1% of global referrals, per Shareaholic, 3/14.
• Social Distribution Happens Quickly = Average article reaches half total social referrals in 6.5 hours on Twitter, 9 hours on Facebook, per SimpleReach, 5/14.
Source: Shareaholic, 3/14. SimpleReach, 5/14. Note: Traffic referral % is percentage of total traffic referrals across Shareholic network.
第44页
Social News Content Leaders = BuzzFeed / Huffington Post / ABC News...
Top Facebook News Publishers, 4/14
# of Interactions (MM)
BuzzFeed Huffington Post
ABC News Fox News
NBC IJReview The Guardian New York Times The Blaze Daily Mail
12 8 Facebook Shares
Facebook Likes 8 Facebook Comments 8
7 10 20 30 40
Source: NewsWhip - Spike, 4/14.
Top Twitter News Publishers, 4/14
# of Shares (MM)
BBC New York Times
Mashable ABC News
CNN Time The Guardian Forbes BuzzFeed Fox News
2 2 2 1 1 1 1 1 1 12
3 3
第45页
Re-Imagining Content + Content Delivery = BuzzFeed... Lists / Quizzes / Explainers / Breaking / Video / Mobile
BuzzFeed
130MM+ Unique Visitors +3x Y/Y (5/14) >50% Mobile, >75% Social, >50% age 18-34
15 Things You Didn’t Know Your iPhone Could Do
17MM+ views
What State Do You Actually Belong In?
40MM+ views
Why I Bought A House In Detroit For $500
1.5MM+ views
Photoshopping Real Women Into Cover Models
13MM+ video views
Source: Buzzfeed, 5/14.
第46页
Re-Imagining Day-to-Day Activities
第47页
Re-Imagining How People Meet
~70K Bars / Nightclubs, USA
Tinder
800MM Swipes per day, +21x Y/Y 11MM Matches per day, +21x Y/Y
Source: IBIS World, 5/14. Company data.
第48页
Re-Imagining Local Services / Reputation = Leverage + Efficiency
6MM Guest Stays 550K Listings, +83% Y/Y
11x Ratio Guest Stays / Listings
231MM Buyers, +44% Y/Y 8MM Sellers
29x Ratio $31K / Year Avg to Alibaba’s China
Retail Marketplace Sellers
39MM Meal Orders, +74% Y/Y 29K Restaurants, +3X Y/Y
1,367x Ratio $35K / Year Avg to Restaurants
All data for 2013. Sources: Company data, SEC filings. Airbnb Listings is total number at year-end. In 2013, Alibaba’s China retail marketplaces comprised of Taobao, Tmall, and Juhuasuan, which generated Gross Merchandise Volume of $248B from 8MM active sellers. GrubHub’s average annual $ to restaurants calculated using 2013 Gross Food Sales totaling $1B+ across 29K restaurants on platform.
第49页
Re-Imagining Grocery Shopping
>47% of Online Transactions Use ‘Free-Shipping,’ vs. 35% Five Years Ago... Same-Day Local Delivery = Next Big Thing... Instacart
Amazon Fresh
Source: Comscore. Images: Indiana Public Media, Film North Florida; Kearny Hub, Wall Street Journal.
第50页
Re-Imagining Media (Music) Consumption = Streaming +32%, Digital Track Sales -6%
USA Music Consumption, 2013
120 118B
2013 Units
Y/Y Growth
80 32%
60% 40%
USA Music Units Consumed (B) Y/Y Growth
40 20%
0 Music Streams
1.3B
-6%
Digital Track Sales (First Y/Y Decline)
172MM
0%
-13% Physical Music Sales
-20%
Source: Nielsen & Billboard 2013 US Music Report, 1/14. Note that absolute consumption comparisons are apples-and-oranges as tracks / physical sales are likely played multiple times but data is illustrative as growth rate is key indicator.
第51页
Re-Imagining Money
第52页
Re-Imagining Money
第53页
Number of Bitcoin Wallets (MM)
Fact that ~5MM Bitcoin Wallets (+8x Y/Y) Exist Proves Extraordinary Interest in Cryptocurrencies
Number of Bitcoin Wallets by Wallet Provider, 4/14
5 Android Bitcoin Wallet
4 Coinbase Multibit
3 Blockchain
11/11
3/12
7/12 11/12 3/13
7/13
11/13
3/14
Source: CoinDesk. Largest wallet providers (Blockchain / MultiBit / Coinbase / Bitcoin Wallet) at ~4.9MM wallets account for majority of Bitcoin wallets created. 53
第54页
Re-Imagining an
Industry Vertical
第55页
Internet Trifecta = Critical Mass of Content + Community + Commerce...
1) Content =
Provided by Consumers + Pros
2) Community =
Context & Connectivity Created by & for Users
3) Commerce =
Products Tagged & Ingested for Seamless Purchase
第56页
...Internet Trifecta = Critical Mass of Content + Community + Commerce...
Houzz – Content (Photos) / Community (Professionals + Consumers) / Commerce (Products), 4/12 – 4/14
23MM
5.5MM
3.2MM 2.5MM
400K 120K
400K
70K
4/12 7/12 10/12 1/13 4/13 7/13 10/13 1/14 4/14
Consumers
Content (Photos)
Commerce (Products)
Active Professionals
Source: Houzz, Consumer defined as unique monthly users, Active Professional defined as active users of Houzz with a business profile.
第57页
...Houzz = Ecosystem for Home Renovation & Design
Content
Community
Commerce
Inspiration Photos
~3MM (+230% Y/Y) World’s largest photo
database
Editorial Guides / Articles
10K (+143%) ‘Wikipedia’ of home
design
Services – Professionals
400K (+198%) Portfolios & reviews
Discussions
800K (+225%) Pro & homeowner support / advice
Products
2.5MM (+590%) Discover & purchase
Source: Houzz, 4/14.
第58页
Biggest Re-Imagination of All =
People Enabled With Mobile Devices + Sensors
Uploading Troves of Findable & Sharable Data
第59页
More Data + More Transparency = More Patterns & More Complexity
Transparency Instant sharing / communication of many things has
potential to make world better / safer place but potential impact to personal privacy will remain on-going challenge...
Patterns Mining rising volume of data has potential to yield patterns that help solve basic / previously unsolvable problems but create new challenges related to individual rights...
第60页
Big Data Trends
1) Uploadable / Findable / Sharable / Real-Time Data Rising Rapidly 2) Sensor Use Rising Rapidly 3) Processing Costs Falling Rapidly...While The Cloud Rises 4) Beautiful New User Interfaces – Aided by Data-Generating
Consumers – Helping Make Data Usable / Useful... 5) Data Mining / Analytics Tools Improving & Helping Find Patterns 6) Early Emergence of Data / Pattern-Driven Problem Solving
第61页
Uploadable / Sharable / Findable Real-Time Data Rising Rapidly
第62页
Photos Alone = 1.8B+ Uploaded & Shared Per Day...
Growth Remains Robust as New Real-Time Platforms Emerge
Daily Number of Photos Uploaded & Shared on Select Platforms, 2005 – 2014YTD
1,800
# of Photos Uploaded & Shared per Day (MM)
1,500 1,200
900 600
Flickr Snapchat Instagram Facebook WhatsApp (2013, 2014 only)
0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014YTD
Source: KPCB estimates based on publicly disclosed company data, 2014 YTD data per latest as of 5/14.
第63页
Uploadable / Sharable / Findable – Mojo Update
Pinterest
• 750MM+ cumulative Boards (4/14) • 30B+ cumulative Pins • +50% Pin growth vs. 10/13
IMGUR
• 130MM MAUs (3/14) • 3B page views per month • 1.5MM images uploaded &
1.3B images viewed per day
Fitbit
• 47B 2.4T steps (2011 2013)... Distance = Earth to Saturn
MyFitnessPal
• 65MM registered users (+50% Y/Y, 5/14)
• 100MM+ pounds lost by users since inception
Eventbrite
• $1B gross ticket sales in 2013 (+60% Y/Y)
• 58MM tickets sold (+61% Y/Y) • 1MM events in 187 countries
Github
• 13MM repositories in 2013 (+100% Y/Y)
• 10K users added per weekday
Source: Company data.
第64页
Uploadable / Sharable / Not Findable* – Mojo Update
WhatsApp
• 50B messages sent per day (2/14)
• 700MM photos per day (4/14) • 100MM videos per day
Snapchat
• 700MM+ snaps shared per day (4/14)
• 500MM stories viewed per day
Tinder
• 800MM swipes per day (+21x Y/Y, 5/14)
• 11MM matches per day (+21x Y/Y)
*Note: “Not findable” = uploaded content not searchable / publicly available Source: Company data.
第65页
‘Digital Universe’ Information Growth = Robust... +50%, 2013
2/3rd's of Digital Universe Content = Consumed / Created by Consumers ...Video Watching, Social Media Usage, Image Sharing...
15 13ZB
(+40% Y/Y) 12
9 >4ZB
(+50% Y/Y) 6
Zetabytes (ZB)
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Note: 1 petabyte = 1MM gigabytes, 1 zetabyte = 1MM petabytes. Source: IDC Digital Universe, data as of 5/14.
第66页
Sensor Use Rising Rapidly
第67页
Sensors = Big / Broad Business, Rapid Growth, Rising Proliferation IN Devices...
iPhone (2007) 3 Sensors
Apple
iPhone 5s (2013) 5 Sensors
• Accelerometer / proximity / ambient light
• 3-axis gyro / fingerprint / accelerometer / proximity / ambient light
Galaxy S (2010) 3 Sensors
Samsung
Galaxy S5 (2014) 10 Sensors
• Accelerometer / proximity / compass
• Gyro / fingerprint / barometer / hall (recognizes whether cover is open/closed) / RGB ambient light / gesture / heart rate / accelerometer / proximity / compass
Note: Sensor count for illustrative purposes only – Apple & Samsung sensor count methodology may differ. Source: Publicly available data from Apple & Samsung, and third party reviews.
第68页
...Sensors = Big / Broad Business (+32% Y/Y to 8B) Rising Proliferation OF Devices
Global MEMS Unit Shipments by Consumer Electronics Device, 2006 – 2013
Global MEMS Unit Shipments (MM)
10,000 8,000 6,000 4,000
Other Gaming Cameras Wearables Laptops Headsets Media Tablets Mobile Phones
2,000 0
727 523 2006
802 525 2007
1,202
788 2008
1,726
1,190 2009
2,765
1,914 2010
4,174
2,919 2011
6,039
4,362 2012
7,961
6,060
Source: IHS Consumer & Mobile MEMS Market Tracker, April 2014. MEMS = microelectromechanical systems. Includes sensors + actuators (a type of motor that is responsible for moving or controlling a mechanism or system, such as an autofocus system in a camera).
第69页
Processing Costs Falling Rapidly... While The Cloud + Accessibility Rise
第70页
Compute Costs Declining = 33% Annually, 1990-2013...
Decreasing cost / performance curve enables computational power @ core of digital infrastructure...
$1,000.00 $527
Global Compute Cost Trends
$100.00
$ per 1 MM transistors
$10.00
$1.00
$0.10
$0.05 $0.01
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
Note: Y-axis on graph is logarithmic scale. Source: John Hagel, Deloitte, 5/14.
第71页
...Storage Costs Declining = 38% Annually, 1992-2013...
Decreasing cost / performance of digital storage enables creation of more / richer digital information...
$1,000.00
$569
Global Storage Cost Trends
$100.00
$ per Gigabyte
$10.00
$1.00
$0.10
$0.02
$0.01 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
Note: Y-axis on graph is logarithmic scale. Source: John Hagel, Deloitte, 5/14.
第72页
...Bandwidth Costs Declining = 27% Annually, 1999-2013...
Declining cost / performance of bandwidth enables faster collection & transfer of data to facilitate richer connections / interactions...
$10,000
Global Bandwidth Cost Trends
$1,245 $1,000
$ per 1,000 Mbps
$100 $10
$16
$1 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Note: Y-axis on graph is logarithmic scale. Source: John Hagel, Deloitte, 5/14.
第73页
...Smartphone Costs Declining = 5% Annually, 2008-2013
Smartphone prices continue to decline, increasing availability to masses...
Average Global Smartphone Pricing Trends
$450
$430
$400
$350
$300
Source: IDC, 5/14.
$335
第74页
...While The Cloud Rises
Amazon Web Services (AWS) Leading Cloud Charge...
2,000
Objects Stored in Amazon S3* (B)
Number of Amazon S3 Objects (B)
1,500 1,000
0 Q4 Q4 Q4 Q4 Q4 Q4 Q1 Q3 Q2 2006 2007 2008 2009 2010 2011 2012 2012 2013
*Note: S3 is AWS’ storage product and used as proxy for AWS scale / growth . Source: Company data.
第75页
Beautiful New User Interfaces – Aided by Data-Generating Consumers –
Helping Make Data Usable / Useful...
第76页
...Challenging Non-Cloud Business Models
Startups – Often Helped by Crowdsourcing – Often Don’t Have Same Challenges with Error-Prone Legacy Data
New Companies – With New Data from New Device Types –
Doing Old Things in New Ways & Growing Super Fast
第77页
Re-Imagining User Interfaces – Finding a Local Business
Yellow Pages
Yelp
Image: wordwatch.com.
第78页
Re-Imagining User Interfaces – Finding a Place to Stay
Booking Hotel Room
Airbnb
Image: iTunes.
第79页
Re-Imagining User Interfaces – Organized Logistics / People Moving
Hailing Cab
Uber
Images: Flickr - KayVee, CultofMac.
32 min
第80页
Re-Imagining User Interfaces – Managing Traffic With Crowdsourcing
Driving in Traffic
Waze
Images: THEMETAQ, streettrafficapp.
第81页
Re-Imagining User Interfaces – Finding Music
Satellite Radio
Spotify
Images: Spotify.
第82页
Re-Imagining User Interfaces – Finding Video With Voice
TV Remote Control
Amazon Fire TV
Images: idownloadblog, diytrade.com.
第83页
R.I.P. Bad User Interfaces
Source: John Maeda, KPCB Design Partner, 5/14.
第84页
Data Mining / Analytics Tools Improving & Helping Find Patterns
第85页
34% (& Rising) of Data in ‘Digital Universe’ = Useful but Only 7% Tagged...1% Analyzed
Significant Portion (34%) of IDC Digital Universe Data = Useful –
Derived from embedded systems / data processing / social media / photos / sounds...
Small Portion (7%) Data = Tagged –
Fastest growing segment of valuable data comes from Internet of Things (IoT) – billions of sensors / intelligence systems capturing / sending data, increasingly in realtime...
Immaterial Portion (1%) Data = Analyzed –
Newer tech companies are making it easier to understand / make use of increasing amount of data...
Source: IDC, 5/14.
第86页
Data Mining / Analytics Tools that Mine / Organize Data = Playing Catch Up to Demand & Growing Fast
Jawbone
Health Wearable
Dropcam
Home Monitoring
• 100MM nights of sleep logged = 27K years • ~100B video frames processed per
• 50B activity data points crunched per week hour
• 1MM personalized insights per week
• +300% Y/Y revenue growth, 2013
Netflix
Media Personalization / Discovery
• Terabytes of user data analyzed to generate personalized media recommendations
• 44MM subscribers (+25% Y/Y, 2013)
AppDynamics
App Performance Monitoring
• 500B Web / mobile transactions instrumented / tracked
• 1.4MM hours saved waiting on apps • 1,200 enterprise customers
SnapLogic
Cloud Integration / Data Transmission
• 500MM+ machine / device scans integrated per day
• 160+ data / cloud connectors on SnapStore
• +128% Y/Y subscription revenue, 2013
Ayasdi
Automated Insight Discovery
• Auto extracts business insights from datasets with 1MM+ features
• 120K hours saved of manual data analysis in 2013
• +451% Y/Y bookings growth, 2013
Source: Company data.
第87页
Early Emergence of Data / Pattern-Driven
Problem Solving
第88页
Big Data = Being Used to Solve Big Problems
Google Voice Search
Voice Recognition
• Uses neural nets to reduce speech recognition errors by 25%
• Used by 1/6 of Google’s U.S. mobile users
Nest
Energy
• 2B+ Kilowatt hours (kWh) of energy saved since 2011*
• Reduces heating / cooling costs up to 20%...an estimated annual savings of $173 per thermostat
Zephyr Health
Healthcare & Life Sciences
• Hundreds of millions healthcare data points ingested / organized (+192% Q/Q, Q3:13)
• 3,500+ independent life sciences sources used daily (+159% Q/Q & accelerating), spanning all major disease areas
• +111% Y/Y contracted revenue growth, 2013
OpenGov
Government Financials
• Compiles data of 37K US governments • Real-time queries across millions of
rows of transactions • Adding new paying government
customer every 4 days (& accelerating)
Automatic
Connected Car
• Collects / analyzes hundreds of millions of data points daily
• Provides personalized feedback to drivers, saving up to 30% in fuel costs
• Discovered driving over 70 MPH saves <5% time, but wastes $550 gas / year
Wealthfront
Investment Management
• +4.6% return vs. average mutual fund** • 200K risk questionnaires completed • 650K free trades, saving clients $5MM+ • 10K+ clients • $800MM+ AUM, +700% since 1/13
*Based on Nest comparison of actual schedules and set points to a hypothetical (holding constant temperature). **Includes fees + underperformance; client savings of $5MM+ assumes $8 per trade retail. Source: Company data.
第89页
Cost / Time to Sequence Genome Down to $1,000 / 24 Hours – Treasure Trove of Patterns Will Rise Rapidly
Accurate diagnosis is foundation for choosing right treatments for patients & clinical lab tests provide critical information health care providers use in ~70% of decisions*
Genetic & genomic testing can be at heart of a new paradigm of [precision] medicine that is evidence-based & rooted in quantitative science**
*UK Department of Health. ** American Clinical Laboratory Association / BattelleTechnology Partnership Practice. Image: Illumina. Note: Genome sequencing data per Eric Schaldt. $1,000 cost is price of sequencing a genome at 30x coverage in the Mount Sinai Genome Core, 5/14.
第90页
Biggest Re-Imagination of All =
People Enabled With Mobile Devices + Sensors
Uploading Troves of Findable & Sharable Data =
Still Early & Evolving Rapidly
第91页
SCREEN + VIDEO GROWTH = STILL EARLY INNINGS
第92页
Future of TV – Reed Hastings (Netflix CEO / Founder)
1) Screens Proliferating 2) [Traditional] Remote Controls Disappearing 3) Apps Replacing Channels 4) Internet TV Replacing Linear TV
Source: Netflix Long Term View.
第93页
Screens Proliferating
第94页
Screens Today = You Screen...I Screen...We All Screen
Image: Telegraph.
第95页
Mobile (Smartphone + Tablet) Shipments =
4-5x Unit Volume of TV & PC...Just 10 Years Since Inception
1,500 1,200
Global TV vs. PC (Desktop + Notebook) vs. Mobile (Smartphone + Tablet) Shipments, 1999 – 2013
TV PC (Desktop + Notebook) Mobile (Smartphone + Tablet) Smartphones Tablets
Global Units Shipped (MMs)
0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Sources: TV unit shipments per NPD DisplaySearch (2004-2013 data) and Philips (1999-2003 data). PC (laptop + desktop) and smartphone + tablet unit shipments per Morgan Stanley Research.
第96页
Smartphones = Most Viewed / Used Medium in Many Countries, 2014
Daily Distribution of Screen Minutes Across Countries (Mins)
Indonesia Phillipines
China Brazil Vietnam
USA Nigeria Colombia Thailand
Saudi South Africa
Czech Russia Argentina
UK Kenya Australia Spain Turkey Mexico
India Poland South Korea Germany Canada Slovakia Hungary Japan France
Italy
Screen Minutes 0
132 99 89 113 69
147 131 114 78 102 115 111 98 104
148 132 125 124 111 93 96 98 127 129 104 95 98 125 134 89
117 143 161
146 160
103 80 123 96 99 126 122 158 114
97 65
102 97 109 103 95 132 94 77 97 106 112 68 83 85
181 110
174 115
170 59
149 66
168 69
151 43
193 39
165 35
167 95
189 43
127 63
119 70
98 66
166 30
111 55
174 33
132 37
122 53
132 163
39 32
TV
162 31 90 61
Laptop + PC
144 137
14 36
Smartphone
124 98
51 52
Tablet
90 48
135 15
79 30
109 34
100 200 300 400 500
Source: Milward Brown AdReaction, 2014. Note: Survey asked respondents “Roughly how long did you spend yesterday...watching television (not online) / using the internet on a laptop or PC / on a smartphone or tablet?” Survey respondents were age 16-44 across 30 countries who owned or had access to a TV and a smartphone and/or tablet. The population of the 30 countries surveyed in the study collectively represent ~70% of the world population.
第97页
Mobile Owners (84%) Use Devices While Watching TV... ~2x Higher Over 2 Years
What Connected Device Owners are Doing While Watching TV, USA
Surfing the Web
Shopping
Checking Sports Scores
Looking Up Info on Actors, Plot, Athletes, etc.
Emailing / Texting Friends About Program Reading Discussion About TV Program on
Social Media Sites Buying A Product / Service Being Advertised
Voting or Sending Comments to a Live Program Watching Certain TV Program Because of Something Read on Social Media 0%
49%
24%
27% 29% 29%
29% 23% 12% 18% 7% 14% 9% 12% 10% 17%
44% 41%
66%
20%
40%
60%
80%
Smartphone Tablet
Source: Nielsen Connected Devices Report, Q3:13. Note: Data gathered from USA general population sample 13+ years old with 9,448 respondents who own a Tablet, e-Reader, Smartphone, or Streaming Capable Device. Study conducted in 9/13.
第98页
Media Engagement Rises With Screen Usage =
2x Higher for 4 Screen Users vs. Solo TV During Olympics
Average Minutes per Day Following the Olympics, by Device, 2012 Olympics Fans
Minutes Spent per Day Following Olympics
600 TV
500 PC (Desktop + Notebook) Phone
Tablet 400
40 51 55
59 300 50
200 367
259 268 300 100
0 TV Only
TV + PC
TV + PC + Phone TV + PC + Phone + Tablet
Source: ComScore Single Source Multi-Platform Study, London Olympics Lab for NBC, 7/12. Note: Data based on total day time spent. N = 720 panelists that use multiple devices and are Olympic fans.
第99页
More Screens = Consumers Get More Content in Less Time?
5 Hours of TV Screen Media
5 Hours of Multiple Screen Media
=
4 Hours of Content + 1 Hour of Commercials
vs.
Smartphone (35%) + TV (27%) + PC (26%) + Tablet (12%)
=
>5 Hours of Content?
Sources: Millward Brown AdReaction, 2014. Nielsen TV Advertising Audiences Report, 5/14. Note: Average global daily screen media time = 417 minutes, of which 147 are on smartphones, 113 on TV, 108 on PC (desktop + notebook), 50 on Tablets. In 2013, an average of 14 minutes of commercials were shown for each hour of Network TV Programming.
第100页
[Traditional] Remote Controls Disappearing
第101页
Re-Imagining Remote Controls = The ‘Now’ = A New IP-Enabled Search Engine
Then...
...Now
Images: eBay, YouTube.
第102页
As Smartphones Eclipsed Feature Phones...
Smart TV Adapters + Smart TVs = Game Changers for
Internet-Enablement of Screens (Big & Small)
第103页
Smart TV Adapters = Tens of Millions of Users Google Chromecast + Amazon Fire TV Raise Bar
New
Company / Product Amazon Fire TV
Google Chromecast Roku
Apple TV
Nintendo Wii Nintendo Wii U
Old
Sony PlayStation 3 Sony PlayStation 4
Microsoft Xbox 360 Microsoft Xbox One
Source: Company data.
Launch Date 4/14 7/13 5/08 1/07
12/06 11/06 11/05
第104页
Smart TV Shipments = Rising % of TVs Shipped... 39% = 2013...Still <10% Installed Base
Smart TV Units Shipped, Installed Base, & Shipment Mix 2008 – 2013, Global
250 40%
Global Smart TV Units Shipment or Installed Base (MM)
Smart TVs Shipped as % of TV Shipments (%)
200 32%
150 24%
7 0
14 2009
27 2010
50 2011
72 2012
87 16% 8%
0%
Smart TV Units Shipped Smart TV Units Installed Base % of Global TV Units Shipped
Source: Generator Research, 2014. Note: Smart TVs defined as internet-enabled television sets and exclude connected devices or adapters that stream content to television sets, such as game consoles or hybrid set-top boxes.
第105页
Apps Replacing Channels
第106页
Linear TV Channels Increasingly = On-Demand Apps
ESPN
BBC
• 34MM (52%) ESPN digital users access ESPN just on smartphones / tablets = 48% of time spent on ESPN digital properties, 4/14
• 234MM requests for TV programs on iPlayer in 2/14, +21% Y/Y
• 46% of requests from mobile / tablet vs. 35% Y/Y
HBO
• 1,000+ hours of video content
Sources: ESPN, BBC, HBO.
第107页
Internet = Evolved from Directory to Search / Apps... TV = Evolving from Directory to Apps / Search
TV Guide
YouTube - Search Bar Comcast - X1 Guide
Images: YouTube, Comcast, mag+
第108页
There’s a Bevy of New Channels on Premier Distribution Network
YouTube...
Of Which 40% (& Rising) # of Users Are Mobile
第109页
YouTube Channels = Huge Reach + Growth
Channel
Subscribers Y/Y Growth
(MM)
(%)
Music 85 166%
Gaming
165%
Sports
164%
News 35 213%
Popular
133%
Spotlight
342%
Movies
195%
TV Shows
106%
Education
--
Source: YouTube. Note: Y/Y growth rates as of 5/14.
Music News Movies
Gaming
Sports
Popular
Spotlight
TV Shows
Education
第110页
Consumers Love Video – Long-Form & More / More
Short-Form
第111页
Every New Medium New Stars...YouTube Top Videos = 6 - 26MM Subs...Top 10 Video Average Duration = ~7 Minutes
Video Game Commentator PewDiePie
26MM+ subscribers, +230% Y/Y
Comedy Duo Smosh
17MM+ subscribers, +81% Y/Y
Spanish Comedian HolaSoyGerman
17MM+ subscribers, +157% Y/Y
Comedian nigahiga 12MM+ subscribers, +50% Y/Y
Make-Up Artist Michelle Phan 6MM+ subscribers,
+70% Y/Y
Style and Beauty Blogger Bethany Mota
6MM+ subscribers, +180% Y/Y
Source: YouTube, 5/14. Note: Y/Y growth rates as of 5/14. Select Top YouTube channels that primarily feature a new artist. Excludes channels that aggregate videos around specific topics.
第112页
Consumers Loving Best Ads = The Art of Short-Form
#1 = Nike Football @ 49MM+ Views
#2 = Dove: Patches @ 20MM+ Views
#3 = Evian Spider Man @ 16MM+ Views
#4 = Castrol Footkhana @ 14MM+ Views
#5 = “Unsung Hero” (Thai Life) @ 12MM+ Views
. Source: YouTube
第113页
Ads the Digital Way... Google TrueView = Game-Changer
YouTube’s TrueView Ads = ‘Cost-per View’ Video Marketing
AdWords Dynamically Places Video Ad Content on Google / YouTube Users Can Skip
• Ads = Great Content – Transformation potential from commercials users want to skip to short-form content users choose to watch
• Advertisers Win – Better results as only pay for users who are engaged & watch video...improves direct click-through options with consumers
• Data – As YouTube collects data on how users engage with ads, it continues to improve the user experience and advertiser ROI
Evian Baby & Me = Most Watched YouTube Ad Of 2013 = 87MM+ views
Source: YouTube.
第114页
Fans Trump Audiences – Alex Carloss (YouTube)
An audience tunes in when they're told to, a fanbase chooses when and what to watch...
...An audience changes the channel when their show is over...
...A fanbase shares, comments, curates, creates...
第115页
Consumers Voting for Social Video / TV
第116页
New Genre(s) of Video = ‘Spectator Gaming’* – Players Players / Active Spectators
Twitch 45MM MAUs (12/13) vs. 8MM Three Years Ago (7/11)
12B Minutes Watched / Month, +2x Y/Y 900K Broadcasters / Month, +3x Y/Y
Twitch = Top Live Video Streaming Site by Volume, USA, 4/14
Rank
Site Volume (%)
1 Twitch 44%
2 WWE
18%
3 Ustream 11%
4 MLB.com
7%
5 ESPN
6%
Source: Company data. Qwilt, 4/14. *ReadWrite
第117页
Social TV = Can Provide Advertiser Lift
第118页
TV + Twitter = Boosts Ad Impact
Impact of TV Ads on Viewers – TV with Twitter vs. TV without Twitter
60% 45% 30% 15%
0%
Ad Recall 53%
40%
TV Only TV x Twitter Viewers Viewers
Brand Favorability (% Lift)
Purchase Intent (% Lift)
18% 7%
TV Only Viewers vs. No Recent
TV
TV x Twitter Viewers
(Tweeters) vs. No Recent TV
30% 16%
TV Only
TV x Twitter
Viewers vs. No Viewers
Recent TV (Tweeters) vs.
No Recent TV
Source: Twitter x TV Study, Millward Brown Digital, 12/13. Note: TV x Twitter users defined as people who used Twitter while watching TV. N = 7,500+ respondents who were part of a study to assess impact of TV ads among people who watched TV with and without Twitter.
第119页
Consumers Voting for Personalization
第120页
Netflix = Personalization...
A Father of Two
A Female Millennial
Images: Screenshot of Netflix homepages of two subscribers.
第121页
Younger Consumers Voting for On-Demand Video
第122页
Millennials = 34% of TV Time Online, ~3x > Non-Millennials
Distribution of Total TV Time Millennials vs. Non-Millennials, USA
100%
80% 60% 40% 20%
0%
59%
17% 12% 12% Non-Millennials
41%
15% 10% 34% Millennials
Live TV DVR Viewing On-Demand Online
Source: Verizon Digital Media Study, 3/14. Note: Study encompassed quantitative survey of 1,000 USA consumers (800 millennials age 16-34 and 200 non-millennials age 35-64). Data collected on 11/13.
第123页
Internet TV Replacing Linear TV –
Early Stages of TV Golden Age With Epic
Content Creation / Consumption / Curation / Distribution
第124页
Consumers Increasingly Expect to Watch TV Content... On Own Terms
Device Share of TV Content, USA, 1/14
Circa 1950
Circa 2014
TV Set (Live) = 100% of viewing
57%
23%
10% 6%
4%
TV Set (Live) DVR / VOD / DVD Connected TV Computer Mobile Device
Source: Horowitz Associates, State of Cable and Digital Media Report, 4/14. Note: Study based on 1,200 interviews in 1/14 among heads of households (18+) who watch any kind of TV. Live TV defined as watching linear programming that is not time-shifted from original programming time intended. TV Content defined as any type of video content. Computer includes desktop + notebook. Mobile includes smartphone + tablet.
第125页
Mobile = More & More Video Consumption... 22% (+2x Y/Y) of Online Video Time Spent
Mobile Share of Online Video Plays and Time, 8/11 – 12/13, Global
25%
Mobile Share of Online Video (%)
20%
15%
10%
5%
0% 08/11 11/11 02/12 05/12 08/12 11/12 02/13 05/13 08/13 11/13
Mobile Share of Online Video Plays (%)
Mobile Share of Online Video Time (%)
Source: Ooyala Global Video Index. Data based on anonymized viewing habits of nearly 200MM unique viewers in over 130 countries and data from Ooyala’s video publishers, which include hundred of broadcasters and operators.
第126页
Future of TV – Reed Hastings (Netflix CEO / Founder)
1) Screens Proliferating 2) [Traditional] Remote Controls Disappearing 3) Apps Replacing Channels 4) Internet TV Replacing Linear TV
Source: Netflix Long Term View.
第127页
CHINA’S EPIC SHARE GAINS
第128页
Global GDP = China Rise Continues
% of Global GDP
40%
33%
30%
27% 20% 16%
10%
2%
0%
Percent of Global GDP, 1820 – 2013, USA vs. Europe vs. China vs. India vs. Latin America
19% 16% 16%
9% 2% 6%
USA Europe China India Latin America
Source: Angus Maddison, University of Groningen, OECD, data post 1980 based on IMF data (GDP adjusted for purchasing power parity).
第129页
China Mobile Internet Users (MM) % of Total China Internet Users
500MM (80%) of China Internet Users = Mobile... More Critical Mass than Any Place in World
China Mobile Internet Users as % of Total Internet Users, 2007 – 2013
600 100% China Mobile Internet Users (MM)
% of Total China Internet Users 500
80%
400 60%
40% 200
20% 100
0 2007
0%
Source: CNNIC.
第130页
1/13 – 9 of Top 10 Global Internet Properties ‘Made in USA’... 79% of Their Users Outside America
Top 10 Internet Properties by Global Monthly Unique Visitors, 1/13
Google Microsoft Facebook
Yahoo! Wikipedia Amazon.com Ask.com Glam Media
Apple Tencent
Source: comScore, 1/13.
USA Users International Users
400 600 800 1,000 Monthly Unique Visitors (MMs)
1,200
1,400
第131页
3/14 – 6 of Top 10 Global Internet Properties ‘Made in USA’... >86% of Their Users Outside America...China Rising Fast
Top 10 Internet Properties by Global Monthly Unique Visitors, 3/14
Google Microsoft Facebook
Yahoo! Wikipedia
Alibaba Baidu
Tencent Sohu
Amazon.com 0
Source: comScore, 3/14.
USA Users International Users
400 600 800 1,000 Monthly Unique Visitors (MMs)
1,200
1,400
第132页
China = Mobile Commerce Innovation Leader
Source: Liang Wu, Hillhouse Capital*
*Disclaimer – The information provided in the following slides is for informational and illustrative purposes only. No representation or warranty, express or implied, is given and no responsibility or liability is accepted by any person with respect to the accuracy, reliability, correctness or completeness of this Information or its contents or any oral or written communication in connection with it. A business relationship, arrangement, or contract by or among any of the businesses described herein may not exist at all and should not be implied or assumed from the information provided. The information provided herein by Hillhouse Capital does not constitute an offer to sell or a solicitation of an offer to buy, and may not be relied upon in connection with the purchase or sale of, any security or interest offered, sponsored, or managed by Hillhouse Capital or its affiliates.
第133页
Tencent WeChat = 400MM Mobile Active Chat Users... Increasingly Using Payments + Commerce
WeChat ‘My Bank Card’ Page
Manage money / invest in money market funds via WeChat Payment
Find restaurants / daily group buy deals - powered by Dianping pay via WeChat Payment
Source: Tencent, Liang Wu (Hillhouse Captial).
Order taxi - powered by Didi pay via WeChat Payment
New Year Lucky Money – fun / social game to incentivize
users to link bank cards to WeChat Payment... 5MM users used on
Chinese New Year Eve, 2014
第134页
Tencent WeChat Services = Virtual Assistant
WeChat Service Accounts = Interactive Accounts with Communication / CRM / Ordering Capability
Personal Banker Shopping Assistant
Private Chef
China Merchant Bank allows Mogujie / Meilishuo (fashion
Hahajing (a chain deli
customers to check & repay discovery & shopping sites) give
restaurant) allows
balances and ask live
customers tailored suggestions customers to order & deliver
questions via WeChat
via WeChat
food via WeChat
Grocery Getter
Xiaonongnv (a grocery delivery startup) prepares fresh groceries
& delivers to your address via WeChat
Source: Liang Wu (Hillhouse Captial).
第135页
Didi Taxi – 100MM+ Users = 5MM+ Daily Rides, +15x in 77 Days... Driven by WeChat Payment Integration & Subsidy*
Daily Taxi Trips Booked (000) Registered Users (MM)
6,000 5,000 4,000 3,000 2,000 1,000
Didi Taxi, Daily Taxi Trips Booked, 1/10/2014 – 3/27/2014
Daily Taxi Trips Booked (000) Registered Users (MM)
3MM
2MM
5MM
350K Jan-10
Feb-9
Feb-24
Mar-27
120 100 80 60 40 20 0
Note: * Subsidy ranges from $1-3 per ride. Estimated total subsidy during this period was ~$233MM. Source: Didi, Liang Wu (Hillhouse Captial).
第136页
Alipay Yu’E Bao – Mobile Money Market Fund Launch... Drove $89B AUM* in 10 Months
• Simple, fun-to-use mobile product • Built on top of Alipay – the most
popular online payment platform in China with 160MM+ accounts. • Technology enables same-day settlement.
• $0 $89B asset under management in 10 months
• Top 3 global money market fund by assets under management (AUM)
$100
Alipay Yu’E Bao Assets Under Management, 5/13 to C1:14
$89B
$80
Asset Under Management ($B)
$60
$40
$20
$1B $0
Launch (5/29/13)
$9B 3Q13
*Note: AUM is asset under management, Fidelity and Vanguard manage more assets than Alipay’s Yu’E Bao. Source: Alipay, Liang Wu (Hillhouse Capital).
$31B 4Q13
1Q14
第137页
PUBLIC COMPANY TRENDS
第138页
Global Internet Public Market Leaders = Apple / Google / Facebook / Amazon / Tencent...
Rank Company
1 Apple 2 Google 3 Facebook 4 Amazon 5 Tencent 6 eBay 7 Priceline 8 Baidu 9 Yahoo! 10 Salesforce.com 11 JD.com 12 Yahoo! Japan 13 Netflix 14 Naver 15 LinkedIn 16 Twitter 17 Rakuten 18 Liberty Interactive 19 TripAdvisor 20 Qihoo 360
Total
Region
USA USA USA USA China USA USA China USA USA China Japan USA Korea USA USA Japan USA USA China
2014 Market Value ($B)
$529 377 157 144 132 66 63 59 35 33 29 25 24 23 19 18 16 14 13 11
$1,787
2013 Revenue ($MM)
$173,992 59,825 7,872 74,452 9,983 16,047 6,793 5,276 4,680 4,071 11,454 3,641 4,375 2,190 1,529 665 4,932 11,252 945 671
$404,644
Source: CapIQ. 2014 market value data as of 5/23/2014. Note: Colors denote current market value relative to Y/Y market value. Green = higher. Red = lower. Purple = newly public.
第139页
...Global Internet Leaders = Intense M&A + Investment Activity
Company / Volume, 2012Market Cap ($B) 2014YTD ($B)
Select Transactions, 2012-2014YTD
Google $377B
$6B (M&A)
DeepMind
$400MM
(1/14)
$3B* (Investments)
Cloudera
$160MM*
(3/14)
Nest
$3B
(1/14)
DocuSign
$100MM*
(3/14)
Waze
$1B
(6/13)
Uber
$258MM
(8/13)
Facebook $157B
$24B (M&A)
Oculus
$2B
(3/14)
WhatsApp
$19B+
(2/14)
Instagram
$1B
(4/12)
Tencent $132B
$7B* (Investments)
JD.com
$3B
(3/14)
CJ Games
$500MM
(3/14)
Activision $429MM Blizzard (7/13)
Alibaba TBD
$5B (M&A)
ChinaVision
$800MM
(3/14)
$5B* (Investments)
Youku Tudou
$1B
(4/14)
AutoNavi
$1B+
(2/14)
Weibo
$1B
(4/13)
Source: Morgan Stanley IBD & public filings. CapIQ, 2014 market value data as of 5/23/2014. Note: Includes investments that corporations and their subsidiaries/affiliates have made in companies. Google’s Docusign investment represents the latest round; however, the Company had been a previous investor. *Some data may include entire funding round, of which a portion may be attributable to investors other than the Company listed here.
第140页
ONE MORE THING(S)...
第141页
From One Extreme To the Other...
第142页
Live Streaming = Oculus Rift-Enabled Drones?
Image: Mashable.
第143页
Re-Imagining Global Access to Internet?
Source: Hola.
第144页
Thanks...
KPCB Partners Especially Alex Tran / Cindy Cheng / Alex Kurland who helped take spurts of ideas and turn them into something we hope is presentable / understandable... Participants in Evolution of Internet Connectivity From creators to consumers who keep us on our toes 24x7...
Walt & Kara For continuing to do what you do so well...
第145页
RAN OUTTA TIME THOUGHTS / APPENDIX
第146页
IMMIGRATION UPDATE
REPORT: http://www.kpcb.com/file/kpcb-immigration-in-america-the-shortage-of-high-skilled-workers
第147页
World Trade as % of GDP
Global Economies / People = Increasingly Connected / Co-Dependent
World Trade as % of World GDP, 1960 - 2013
30%
25%
20%
15%
10%
5%
0% 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Source: Trade data per World Trade Organization (WTO), GDP data per United Nations (UN).
Note: World trade calculated as the sum of all countries’ imports (or exports). The biggest trading partners of USA includes EU nations, Canada, China, Mexico, 147
Japan and South Korea.
第148页
60% of Top 25 Tech Companies Founded by 1st and 2nd Generation Americans = 1.2MM Employees, 2013
Founders / Co-Founders of Top 25 USA Public Tech Companies, Ranked by Market Capitalization
Rank Company
Mkt Cap ($MM)
LTM Rev ($MM)
1 Apple 2 Google 3 Microsoft 4 IBM 5 Oracle 6 Facebook 7 Amazon.com 8 Qualcomm 9 Intel 10 Cisco 11 eBay 12 Hewlett-Packard 13 Priceline 14 EMC 15 Texas Instruments 16 VMware 17 Automatic Data Processing 18 Yahoo! 19 salesforce.com 20 Adobe Systems 21 Cognizant Technology 22 Micron 23 Netflix 24 Intuit 25 Sandisk Total Founded by 1st or 2nd Gen Immigrants
$529,000 376,536 331,408 188,205 187,942 157,448 143,683 134,827 130,867 125,608 65,927 63,903 62,767 54,458 49,920 41,549 38,014 35,258 32,783 32,004 29,583 29,253 24,120 22,595 21,325
$2,053,676
$176,035 62,294 83,347 98,827 37,902 8,916 78,123 25,712 52,892 47,202 16,561
111,820 7,133
23,314 12,303
5,376 11,958
4,673 4,405 4,047 9,245 13,310 4,621 4,426 6,341 $577,580
Employees
1st or 2nd Gen Immigrant Founder / Co-Founder
80,300
Steve Jobs
47,756
Sergey Brin
99,000
--
431,212
Herman Hollerith
120,000
Larry Ellison / Bob Miner
6,337
Eduardo Saverin
117,300
Jeff Bezos
31,000
Andrew Viterbi
107,600
-- *
75,049
--
33,500
Pierre Omidyar
317,500
William Hewlett
9,500
Jay Walker
63,900
Roger Marino
32,209
Cecil Green / J. Erik Jonsson
14,300
Edouard Bugnion
60,000
Henry Taub
12,200
Jerry Yang
13,300
--
11,847
--
171,400 Francisco D'souza / Kumar Mahadeva
30,900
--
2,327
--
8,000
--
5,459
Eli Harari
1,226,873
Generation
2nd-Gen, Syria 1st-Gen, Russia
-2nd-Gen, Germany 2nd-Gen, Russia / 2nd-Gen, Iran
1st-Gen, Brazil 2nd-Gen, Cuba 1st-Gen, Italy
--1st-Gen, France --2nd-Gen, Italy 1st-Gen, UK / 2nd-Gen, Sweden 1st-Gen, Switzerland 2nd-Gen, Poland 1st-Gen, Taiwan --1st-Gen, India** / 1st-Gen, Sri Lanka
--1st-Gen, Israel
Source: CapIQ, Factset as of 5/14. “The ‘New American’ Fortune 500”, a report by the Partnership for a New American Economy; “American Made, The Impact
of Immigrant Founders & Professionals on U.S. Corporations.”
*Note: while Andy Grove (from Hungary) is not a co-founder of Intel, he joined as COO on the day it was incorporated. **Francisco D’souza is a person of Indian
origin born in Kenya.
第149页
USA Sending More Qualified Foreign Students Home Post Graduation – 3.5x Rise in Student & Employment Visa Issuance Gap Over Decade
Number of Visas Issued (000s)
Number of Student Visas (F1) vs. Employment (H-1B) Visas Issued per Year, 1992 – 2013
F1 Student Visa Issued 500 H-1B Employment Visa Issued
300 ~380K Difference
~100K Difference
85K H-1B Visas
Subject to
Cap
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Source: U.S. Department of State, 5/14.
第150页
USA, INC. UPDATE
REPORT: http://www.kpcb.com/usainc/USA_Inc.pdf VIDEO: http://www.kpcb.com/insights/2011-usa-inc-video
第151页
USA Inc. Income Statement, F2013 – Revenue (Taxes) +13%...Expenses -2%...-24% Net Margin
Revenue ($B) Y/Y Growth
Individual Income Taxes* % of Revenue
Social Insurance Taxes % of Revenue
Corporate Income Taxes* % of Revenue
Other % of Revenue
Expense ($B) Y/Y Growth
Entitlement / Mandatory % of Expense
Non-Defense Discretionary % of Expense
"One-Time" Items % of Expense
Defense % of Expense
Net Interest on Public Debt % of Expense
Surplus / Deficit ($B) Net Margin (%)
USA Inc. Profit & Loss Statement, F1998 / F2003 / F2008 / F2013
F1998
F2003
F2008
F2013
Comments
$1,722 9%
$1,783 -4%
$2,524 -2%
$2,775 13%
On average, revenue grew 3% Y/Y over the past 15 years
$829 48%
$572 33%
$189 11%
$133 8%
$794 45%
$713 40%
$132 7%
$144 8%
$1,146 45%
$900 36%
$304 12%
$174 7%
$1,316 47%
$948 34%
$274 10%
$237 9%
Largest driver of revenue
Payroll tax on Social Security & Medicare
Fluctuates significantly with economic conditions Includes estate & gift taxes / duties & fees; relatively stable
$1,652 3%
$2,160 7%
$2,983 9%
$3,455 -2%
On average, expense grew 5% Y/Y over the past 15 years
$870 53%
$1,168 54%
$1,582 53%
$2,049 59%
Significant increase owing to aging population and rising healthcare costs
$273 17%
$434 20%
$518 17%
$551 16%
Includes education / law enforcement / transportation / general government
--$268 16%
$241 15%
--$405 19%
$153 7%
$14 0%
$616 21%
$253 8%
--$633 18%
$221 6%
Includes discretionary spending on TARP, GSEs, and economic stimulus Significant increase owing to on-going War on Terror
Decreased owing to historic low interest rates
$69 4%
-$377 -21%
-$459 -18%
-$680 -24%
USA Inc. median net margin between 1998 & 2013 = -16%
Source: White House Office of Management and Budget. Note: USA federal fiscal year ends in September; *individual & corporate income taxes include capital gains taxes. Non-defense discretionary includes federal spending on education, infrastructure, law enforcement, judiciary functions.
第152页
Where Your Tax Dollars Go –
Entitlements as % of Government Spending = 63% vs. 59% Y/Y
% of USA Federal Government Spending, 2013
Entitlement Spending = 63%
9% 14% 16%
24%
18% 12% 6%
0%
Medicaid Defense
Medicare Other
Income Security Social Security Interest
20%
40%
60%
80%
Source: White House OMB. Note: Income security includes unemployment; food, nutrition and housing assistance; federal retirement. Other expenses include transportation, education, justice, and other general government functions.
100%
第153页
...KEY INTERNET TRENDS
第154页
Global Internet Users (B) Y/Y Growth
Internet User Growth = +9% in 2013 vs. +11% in 2012 = Solid, But Slowing
Global Internet Users, 1996 – 2013 (B)
3.0 120%
2.6 2.5 2.4 100%
2.2
2.0 1.9 1.7
1.5 1.5 1.4
1.1
1.0
0.9 1.0 0.8
0.7
0.5
0.4 0.5 0.1 0.1 0.2 0.3
0.0
80% 60% 40% 20% 0%
Internet Users
Internet User Growth
Source: United Nations / International Telecommunications Union, US Census Bureau, Euromonitor International.
第155页
Established ‘Big’ Internet Markets (China / USA / Japan / Brazil / Russia) = +7% Growth in 2013 vs. 8% Y/Y = Slowing, Past / Near 50% Penetration
Countries with Internet Penetration >45%, 2013
Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
2013 Internet 2013 Internet
Country
Users (MMs) User Growth
China
618 10%
USA
263 2
Japan
101 0
Brazil
100 12
Russia
76 9
Germany 68 1
United Kingdom
France
55 5
Iran 45 16
South Korea
Turkey
36 6
Italy
36 2
Spain
34 7
Canada
30 5
Poland
25 0
Top 15
1,583
6%
World
2,609
9%
2012 Internet User Growth
10% 2 1
12 14
1 3 4 19 0 9 6 3 4 4 7% 11%
Population
T otal
Penetration Population (MMs)
46%
1,350
83 316
79 127
50 201
53 143
84 81
87 63
83 66
56 80
84 49
45 81
58 61
72 47
87 35
65 38
58%
2,739
37%
7,098
Source: United Nations / International Telecommunications Union, US Census Bureau.
China Internet user data from CNNIC (12/2013). Iran Internet user data from KPCB estimates per data from Islamic Republic News Agency, citing data released 155
by the National Internet Development Center.
第156页
‘Big’ Internet Markets (India / Indonesia / Nigeria / Mexico / Philippines) = +20% Growth in 2013 = Strong, Material Penetration Upside
Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Country India Indonesia Nigeria Mexico Philippines Egypt Vietnam South Africa Pakistan T hailand Ukraine Kenya Venezuela Peru Uzbekistan Top 15 World
Countries with Internet Penetration ≤45%
2013 Internet 2013 Internet
Users (MMs) User Growth
154 27%
71 13
57 19
46 11
38 27
38 13
37 14
20 20
19 12
18 12
15 17
14 17
13 11
11 7
10 22
560 18%
2,609
9%
2012 Internet User Growth
36% 15 21 14 18 29 16 41 14
6 22 105
9 5 52 24% 11%
Population
T otal
Penetration Population (MMs)
13%
1,221
28 251
33 173
38 119
36 106
44 85
39 92
41 49
10 193
27 67
34 45
32 44
44 28
38 30
37 29
22%
2,532
37%
7,098
Source: United Nations / International Telecommunications Union, US Census Bureau. Indonesia Internet user data from APJII (1/2014).
第157页
Established ‘Big’ Smartphone Markets (USA / Japan / UK / Germany / Korea) = +17% Growth in 2013 = Slowing, Well Past 50% Penetration
Rank Country 1 USA 2 Japan 3 UK 4 Germany 5 Korea 6 France 7 Saudi Arabia 8 Poland 9 Australia 10 Canada 11 Malaysia 12 Netherlands 13 Taiwan 14 Sweden 15 UAE Top 15 World
Markets with >45% Penetration
2013 Smartphone 2013 Smartphone
Subs (MMs)
Sub Growth
188 21%
99 5
43 18
40 34
38 18
33 29
30 20
22 29
19 20
18 21
16 23
12 18
11 23
9 10
9 20
588 19%
1,786
28%
Population
T otal
2014E Smartphone
Penetration Population (MMs) Sub Growth
59%
12%
78 127
68 63
49 81
79 49
50 66
110 27
57 38
85 22
53 35
54 30
69 17
49 23
94 10
160 5
65%
13%
25%
7,098
24%
Source: Informa. Note: Japan data per Gartner, Morgan Stanley Research, and KPCB estimates.
第158页
Developing ‘Big’ Smartphone Markets (China / India / Brazil / Indonesia / Russia) = +32% Growth in 2013 = Strong, Material Penetration Upside Remains
Rank Country 1 China 2 India 3 Brazil 4 Indonesia 5 Russia 6 Mexico 7 Egypt 8 Italy 9 Spain 10 Philippines 11 Nigeria 12 South Africa 13 Thailand 14 Turkey 15 Argentina Top 15 World
Markets with ≤45% Penetration
2013 Smartphone 2013 Smartphone
Subs (MMs)
Sub Growth
422 26%
117 55
72 38
48 42
46 30
22 49
21 41
21 33
21 20
20 43
20 43
20 32
18 27
18 32
17 40
905 33%
1,786
28%
Population
T otal
2014E Smartphone
Penetration Population (MMs) Sub Growth
31%
1,350
19%
10 1,221
36 201
19 251
33 143
19 119
25 85
34 61
44 47
19 106
12 173
41 49
27 67
22 81
41 43
23%
3,996
28%
25%
7,098
24%
Source: Informa.
第159页
Mobile Traffic as % of Global Internet Traffic = Growing >1.5x per Year & Likely to Maintain Trajectory or Accelerate
% of Internet Traffic
Global Mobile Traffic as % of Total Internet Traffic, 12/08 – 5/14 (with Trendline Projection to 5/15E)
35% 30%
25% in 5/14
Trendline
25%
20%
15%
10% 0.9% in 5/09
5%
2.4% in 5/10
6% in 5/11
10% in 5/12
15% in 5/13
0% 12/08
12/09
12/10
12/11
12/12
12/13
12/14 E
Source: StatCounter Global Stats, 5/14. Note that PC-based Internet data bolstered by streaming.
第160页
...PUBLIC COMPANY TRENDS
第161页
Financial Philosophy – Michael Marks (Stanford GSB)
1) Three Ways to Get Capital into Company – Sell stock, borrow money, earn it. Earn it is best!
2) Balance Sheets Matter – Without a balance sheet, it's hard to understand where a company stands.
3) Great Companies Grow Revenue, Make Profits and Invest for Future – Companies that do just 2 of 3 are signing up for being just ‘OK,’ not ‘great.’
4) Companies Learn to Make Money or Not – Companies that make money generally continue to do so, companies that don't make money generally continue that also. It becomes core to ‘culture.’
第162页
Tech Companies = Top 1 or 2 Sector by Market Cap in S&P500 for Nearly 2 Decades
20 Years Ago: Dec 1994 – S&P500 = $3.2T
Sector
Weight Largest Companies
CONS. STAPLES
14%
COCA-COLA ALTRIA
CONS. DISC.
13%
MOTORS LIQUIDATION FORD
INDUSTRIALS 13%
GENERAL ELECTRIC 3M
FINANCIALS 11%
AIG FANNIE MAE
TECHNOLOGY 11%
IBM MICROSOFT
HEALTHCARE
10%
MERCK JOHNSON & JOHNSON
ENERGY
9%
EXXON MOBIL
TELECOM
8%
SOUTHWESTERN BELL GTE
MATERIALS 7%
DUPONT DOW CHEMICAL
UTILITIES
4%
SOUTHERN COMPANY DUKE ENERGY
Peak of NASDAQ: Mar 2000 – S&P500 = $11.7T
Sector
Weight Largest Companies
TECHNOLOGY 35%
MICROSOFT CISCO
FINANCIALS
13%
CITIGROUP AIG
CONS. DISC.
10%
TIME WARNER HOME DEPOT
HEALTHCARE 10%
MERCK PFIZER
INDUSTRIALS
8%
GENERAL ELECTRIC TYCO
TELECOM
7%
SOUTHWESTERN BELL AT&T
CONS. STAPLES 7%
WAL-MART COCA-COLA
ENERGY
5%
EXXON MOBIL CHEVRON
MATERIALS
2%
DUPONT ALCOA
UTILITIES
2%
DUKE ENERGY AES
Today: May 2014 – S&P500 = $17.4T
Sector
Weight Largest Companies
TECHNOLOGY 19%
APPLE GOOGLE
FINANCIALS 16%
WELLS FARGO JPMORGAN CHASE
HEALTHCARE
13%
JOHNSON & JOHNSON PFIZER
CONS. DISC. 12%
AMAZON.COM WALT DISNEY
INDUSTRIALS
11%
GENERAL ELECTRIC UNITED TECHNOLOGIES
CONS. STAPLES
11%
WAL-MART PROCTOR & GAMBLE
ENERGY
10%
EXXON MOBIL CHEVRON
MATERIALS 3%
DUPONT MONSANTO
UTILITIES
3%
DUKE ENERGY NEXTERA ENERGY
TELECOM
2%
VERIZON AT&T
Source: CapIQ, updated as of 5/21/14.
第163页
Disclosure
This presentation has been compiled for informational purposes only and should not be construed as a solicitation or an offer to buy or sell securities in any entity.
The presentation relies on data and insights from a wide range of sources, including public and private companies, market research firms and government agencies. We cite specific sources where data are public; the presentation is also informed by non-public information and insights.
We publish the Internet Trends report on an annual basis, but on occasion will highlight new insights. We will post any updates, revisions, or clarifications on the KPCB website.
KPCB is a venture capital firm that owns significant equity positions in certain of the companies referenced in this presentation, including those at www.kpcb.com/companies.
第164页
INTERNET TRENDS 2014
kpcb.com/InternetTrends