Internet Trends Report 2018

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Internet Trends Report 2018

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Post Date: 18/07/2018, 03:14
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1. Internet Trends 2018 Mary Meeker May 30 @ Code 2018 kleinerperkins.com/InternetTrends 2. 2 Thanks Kleiner Perkins Partners Ansel Parikh & Michael Brogan helped steer ideas and did a lot of heavy lifting. Other contributors include: Daegwon Chae, Mood Rowghani, Eric Feng (E-Commerce) & Noah Knauf (Healthcare). In addition, Bing Gordon, Ted Schlein, Ilya Fushman, Mamoon Hamid, Juliet deBaubigny, John Doerr, Bucky Moore, Josh Coyne, Lucas Swisher, Everett Randle & Amanda Duckworth were more than on call with help. Hillhouse Capital Liang Wu & colleagues’ contribution of the China section provides an overview of the world’s largest market of Internet users. Participants in Evolution of Internet Connectivity From creators to consumers who keep us on our toes 24x7 + the people who directly help us prepare the Report. And, Kara & team, thanks for continuing to do what you do so well. 3. 3 Context We use data to tell stories of business-related Trends we focus on. We hope others take the ideas, build on them & make them better. At 3.6B, the number of Internet users has surpassed half the world’s population. When markets reach mainstream, new growth gets harder to find - evinced by 0% new smartphone unit shipment growth in 2017. Internet usage growth is solid while many believe it’s higher than it should be. Reality is the dynamics of global innovation & competition are driving product improvements, which, in turn, are driving usage & monetization. Many usability improvements are based on data - collected during the taps / clicks / movements of mobile device users. This creates a privacy paradox... Internet Companies continue to make low-priced services better, in part, from user data. Internet Users continue to increase time spent on Internet services based on perceived value. Regulators want to ensure user data is not used ‘improperly.’ Scrutiny is rising on all sides - users / businesses / regulators. Technology-driven Trends are changing so rapidly that it’s rare when one side fully understands the other...setting the stage for reactions that can have unintended consequences. And, not all countries & actors look at the issues through the same lens. We focus on Trends around data + personalization; high relative levels of tech company R&D + Capex Spending; E-Commerce innovation + revenue acceleration; ways in which the Internet is helping consumers contain expenses + drive income (via on-demand work) + find learning opportunities. We review the consumerization of enterprise software and, lastly, we focus on China’s rising intensity & leadership in Internet-related markets. 4. 44 Internet Trends 2018 1) Users 5-9 2) Usage 10-12 3) Innovation + Competition + Scrutiny 13-43 4) E-Commerce 44-94 5) Advertising 95-99 6) Consumer Spending 100-140 7) Work 141-175 8) Data Gathering + Optimization 176-229 9) Economic Growth Drivers 230-237 10) China (Provided by Hillhouse Capital) 237-261 11) Enterprise Software 262-277 12) USA Inc. + Immigration 278-291 5. 5 Internet DEVICES + USERS = GROWTH CONTINUES TO SLOW 6. 6 Global New Smartphone Unit Shipments = No Growth @ 0% vs. +2% Y/Y Source: Katy Huberty @ Morgan Stanley (3/18), IDC. New Smartphone Unit Shipments vs. Y/Y Growth 0% 30% 60% 90% 0 0.5B 1.0B 1.5B 2009 2010 2011 2012 2013 2014 2015 2016 2017 Y/YGrowth NewSmartphoneShipments,Global Android iOS Other Y/Y Growth 7. 7 Source: United Nations / International Telecommunications Union, USA Census Bureau. Internet user data is as of mid-year. Internet user data: Pew Research (USA), China Internet Network Information Center (China), Islamic Republic News Agency / InternetWorldStats / KP estimates (Iran), KP estimates based on IAMAI data (India), & APJII (Indonesia). Note: Historical data (particularly in Sub-Saharan Africa) revised by ITU in 2017 to better account for dual-SIM subscriptions (i.e. two Internet subscriptions per single smartphone user). Global Internet Users = Slowing Growth @ +7% vs. +12% Y/Y 0% 4% 8% 12% 16% 0 1B 2B 3B 4B 2009 2010 2011 2012 2013 2014 2015 2016 2017 Y/YGrowth InternetUsers,Global Global Internet Users Y/Y Growth Internet Users vs. Y/Y Growth 8. 8 Global Internet Users = 3.6B @ >50% of Population (2018) 24% 49% 0% 20% 40% 60% 2009 2010 2011 2012 2013 2014 2015 2016 2017 InternetPenetration,Global Internet Penetration Source: CIA World Factbook, United Nations / International Telecommunications Union, USA Census Bureau. Internet user data is as of mid-year. Internet user data: Pew Research (USA), China Internet Network Information Center (China), Islamic Republic News Agency / InternetWorldStats / KP estimates (Iran), KP estimates based on IAMAI data (India), & APJII (Indonesia). Note: Historical data (particularly in Sub-Saharan Africa) revised by ITU in 2017 to better account for dual-SIM subscriptions (i.e. two Internet subscriptions per single smartphone user). 9. 9 Internet Users… Growth Harder to Find After Hitting 50% Market Penetration 10. 10 Internet USAGE = GROWTH REMAINS SOLID 11. 11 Digital Media Usage @ +4% Growth... 5.9 Hours per Day (Not Deduped) Source: eMarketer 9/14 (2008-2010), eMarketer 4/15 (2011-2013), eMarketer 4/17 (2014-2016), eMarketer 10/17 (2017). Note: Other connected devices include OTT and game consoles. Mobile includes smartphone and tablet. Usage includes both home and work for consumers 18+. Non deduped defined as time spent with each medium individually, regardless of multitasking. Daily Hours Spent with Digital Media per Adult User 0.2 0.3 0.4 0.3 0.3 0.3 0.3 0.4 0.4 0.6 2.2 2.3 2.4 2.6 2.5 2.3 2.2 2.2 2.2 2.1 0.3 0.3 0.4 0.8 1.6 2.3 2.6 2.8 3.1 3.3 2.7 3.0 3.2 3.7 4.3 4.9 5.1 5.4 5.6 5.9 0 1 2 3 4 5 6 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 HoursSpentperDay,USA Other Connected Devices Desktop / Laptop Mobile 12. 12 Internet Usage… How Much = Too Much? Depends How Time is Spent 13. 13 INNOVATION + COMPETITION = DRIVING PRODUCT IMPROVEMENTS / USEFULNESS / USAGE + SCRUTINY 14. 14 Devices Access Simplicity Payments Local Messaging Video Voice Personalization Innovation + Competition = Driving Product Improvements / Usefulness / Usage 15. 15 Devices = Better / Faster / Cheaper Source: Apple, Google, Katy Huberty @ Morgan Stanley, IDC. *ASP Based on Morgan Stanley’s new smartphone shipment breakdown by taking the midpoint of each $50 price band & assuming a $1,250 ASP for smartphones over $1,000. Note: Deloitte estimates that 120MM used smartphones were traded in 2016 and 80MM in 2015 which may further reduce smartphone costs to consumers as the ratio of used to new devices rises. Apple 2016 = iPhone 7 Plus, 2017 = iPhone X. Google 2016 = Pixel, 2017 = Pixel 2. Apple iPhone 2016 2017 ‘Portrait’ Photos Water Resistant Face Tracking Full Device Display Wireless Charging 2016 2017 Google Assistant ‘AI-Assisted’ Photo Editing ‘Lens’ Smart Image Recognition Always-On Display Google Android $0 $100 $200 $300 $400 $500 2007 2009 2011 2013 2015 2017 NewSmartphoneShipmentASP,Global* New Smartphone Shipments – ASP 16. 16 Access = WiFi Adoption Rising WiFi Networks Source: WiGLE.net as of 5/29/18. Note: WiGLE.net is a submission-based catalog of wireless networks that has collected >6B data points since launch in 2001. Submissions are not paired with actual people, rather name / password identities which people use to associate their data. 0 100MM 200MM 300MM 400MM 500MM 2001 2003 2005 2007 2009 2011 2013 2015 2017 WiFiNetworks,Global 17. 17 Simplicity = Easy-to-Use Products Becoming Pervasive Media Spotify Source: Telegram (5/18), Square (5/18), Spotify (5/18). Messaging Telegram Commerce Square Cash 18. 18 Payments = Digital Reach Expanding… 1% 2% 3% 4% 4% 7% 7% 8% 9% 15% 40% Other Wearables / Contactless Smart Home Device QR Codes Other In-App Payments Mobile Messenger Apps P2P Transfer Other Mobile Payments Buy Buttons Other Online In-Store 0% 10% 20% 30% 40% 50% % of Global Responses (9/17) Transactions by Payment Channel Thinking of your past 10 everyday transactions, how many were made in each of the following ways? Source: Visa Innovations in a Cashless World 2017. Note: Full question was ‘Please think about the payments you make for everyday transactions (excluding rent, mortgage, or other larger, infrequent payments). Thinking of your past 10 everyday transactions, how many were made in each of the following ways?’, GfK Research conducted the survey with n = 9,200 across 16 countries (USA, Canada, UK, France, Poland, Germany, Mexico, Brazil, Argentina, Australia, China, India, Japan, South Korea, Russia, UAE), between 7/27/17 – 9/5/17. All respondents do not work in Financial Services, Marketing, Marketing Research, Advertising, or Public Relations, own and currently use a smartphone, have a savings or checking account; own/use a computer or tablet, and own a credit or debit card. 60% = Digital In-Store 19. 19 …Payments = Friction Declining... Source: China Internet Network Information Center (CNNIC). Note: User defined as active user of mobile- passed payment technology for everyday transactions, as well as more complex transactions, such as bill paying in the relevant period. Includes all forms of transactions on mobile (e.g., QR codes, P2P, etc.) 0 200MM 400MM 600MM 2012 2013 2014 2015 2016 2017 MobilePaymentUsers,China China Mobile Payment Users 20. 20 …Payments = Digital Currencies Emerging Source: Coinbase. Note: Registered users defined as users that have an account on Coinbase. Coinbase Users 1x 2x 3x 4x January March May July September November CoinbaseRegisteredUsers,Global(Indexedto1/17) 2017 21. 21 Local = Offline Connections Driven by Online Network Effects 0 50K 100K 150K 200K 2011 2012 2013 2014 2015 2016 2017 2018 ActiveNeighborhoods,USA Source: Nextdoor (5/18). Note: There are ~130MM households in USA. Nextdoor estimates that there are ~650 households per average neighborhood (~200K USA neighborhoods). Nextdoor Active Neighborhoods 22. 22 Messaging = Extensibility Expanding 0 0.5B 1.0B 1.5B 2011 2012 2013 2014 2015 2016 2017 WhatsApp Facebook Messenger WeChat Instagram Twitter Messenger MAUs QQ WeChat Messaging Tencent (2000 ? 2018) Source: Facebook, WhatsApp, Tencent, Instagram, Twitter, Morgan Stanley Research. Note: 2013 data for Instagram & Facebook Messenger are approximated from statements made in early 2014. Twitter users excludes SMS fast followers. MAUs (Monthly Active Users) are defined as users who log into a messenger on the web or through an application. 23. 23 Video = Mobile Adoption Climbing... Source: Zenith Online Video Forecasts 2017 (7/17). Note: Based on a study across 63 countries. The historical figures are taken from the most reliable third-party sources in each market including Nielsen and comScore. The forecasts are provided by local experts, based on the historical Trends, comparisons with the adoption of previous technologies, and their judgement. 0 10 20 30 40 2012 2013 2014 2015 2016 2017 2018E DailyMobileVideoViewingMinutes,Global Mobile Video Usage 24. 24 …Video = New Content Types Emerging Source: Twitch (3/18). Note: Tyler “Ninja” Blevins Twitch stream has 7MM+ followers (#1 ranked) as of 5/29/18 based on Social Blade data. 0 6MM 12MM 18MM 2012 2013 2014 2015 2016 2017 AverageDailyStreamingHours,Global Twitch Streaming HoursFortnite Battle Royale Most Watched Game on Twitch 25. 25 95% 95% 70% 80% 90% 100% 2013 2014 2015 2016 2017 WordAccuracyRate Google Threshold for Human Accuracy Voice = Technology Lift Off… Google Machine Learning Word Accuracy Source: Google (5/17). Note: Data as of 5/17/17 & refers to recognition accuracy for English language. Word error rate is evaluated using real world search data which is extremely diverse & more error prone than typical human dialogue. 26. 26 …Voice = Product Lift Off Source: Consumer Intelligence Research Partners LLC (Echo install base, 2/18), Various media outlets including Geekwire, TechCrunch, and Wired (Echo skills, 3/18) Amazon Echo Installed Base 0 10MM 20MM 30MM 40MM Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 InstalledBase,USA 0 10K 20K 30K 2015 2016 2017 2018 NumberofSkills Amazon Echo Skills 2015 2016 2017 27. 27 Devices Access Simplicity Payments Local Messaging Video Voice Personalization Innovation + Competition = Driving Product Improvements / Usefulness / Usage 28. 28 Personalization = Data Improves Engagement + Experiences… Drives Growth + Scrutiny 29. 29 Personal + Collective Data = Provide Better Experiences for Consumers… Source: Facebook (5/18), Pinterest (5/18), Spotify (5/18), Netflix (5/18). Note: Facebook Q1:18 MAU (4/18), Pinterest MAU (9/17), Spotify Q1:18 MAU (5/18), Netflix Q1:18 global streaming memberships (4/18). Music VideoNewsfeed Discovery 170MM Spotifys 125MM Netflixes 2.2B Facebooks 200MM Pinterests 30. 30 ...Personal + Collective Data = Provide Better Experiences for Consumers 100MM+ Snap Map MAUs 17MM** Nextdoor Recommendations 20% UberPOOL Share of All Rides, Where Available* 100MM+ Waze Drivers Real-Time Social Stories Often Real-Time Local News Real-Time Transportation Real-Time Navigation Source: Facebook (5/18), Waze (2/18), Snap (5/18), Nextdoor (5/18) *Active Markets = Atlanta, Austin, Boston, Chicago, Denver, Las Vegas, Los Angeles, Miami, Nashville, New Jersey, New York City, Philadelphia, Portland, San Diego, San Francisco, Seattle, Washington D.C., Toronto, Rio de Janeiro, Sao Paulo, Bogota, Guadalajara, Mexico City, Monterrey, Lima, Paris, London, Ahmedabad, Bangalore, Chandigarh, Chennai, New Delhi, Guwahati, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Pune, & Sydney. **Refers to cumulative recommendations as of 11/17. 31. 31 Internet Companies Making Low-Priced Services Better, in Part, from User Data Internet Users Increasing Time on Internet Services Based on Perceived Value Regulators Want to Ensure User Data is Not Used ‘Improperly’ Privacy Paradox 32. 32 Rising User Engagement = Drives Monetization + Investment in Product Improvements... Facebook Annualized Revenue per Daily User $16 $34 $0 $10 $20 $30 $40 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Source: Facebook (4/18). Note: Facebook Daily Active Users (DAU) defined as a registered Facebook user who logged in and visited Facebook on desktop or mobile device, or took action to share content or activity with his or her Facebook friends or connections via a third-party website that is integrated with Facebook, on a given day. ARPDAU calculated by dividing annualized total revenue by average DAU in the quarter. 2015 2016 2017 2018 AnnualizedAverageRevenue perDailyActiveUser(ARPDAU),Global 33. 33 ...Rising Monetization + Data Collection = Drives Regulatory Scrutiny Source: European Union (5/18), European Commission (6/17, 10/17, 12/16), Bundeskartellmt (German Competition Authority (12/17). German Federal Ministry of Justice and Consumer Protection (10/17). Competition Commission fines Google €2.42 billion for abusing dominance as search engine by giving illegal advantage to its own comparison shopping service. - European Commission, 6/17 Commission approves acquisition of LinkedIn by Microsoft, subject to conditions. - European Commission, 12/16 Commission finds Luxembourg gave illegal tax benefits to Amazon worth around €250 million. - European Commission, 10/17 Taxes Data / Privacy The Germany Network Enforcement Act will require for-profit social networks with >2MM registered users in Germany to remove unlawful content within 24 hours of receiving a complaint. - German Federal Ministry of Justice & Consumer Protection, 10/17 Safety / Content The European Data Protection Regulation will be applicable as of May 25th, 2018 in all member states to harmonize data privacy laws across Europe. - European Union, 5/18 Facebook’s collection & use of data from third-party sources is abusive. - German Federal Cartel Office, 12/17 34. 34 Internet Companies = Key to Understand Unintended Consequences of Products... Source: Facebook (4/18). We’re an idealistic & optimistic company. For the first decade, we really focused on all the good that connecting people brings. But it’s clear now that we [Facebook] didn’t do enough. We didn’t focus enough on preventing abuse & thinking through how people could use these tools to do harm as well. - Mark Zuckerberg, Facebook CEO, 4/18 35. 35 …Regulators = Key to Understand Unintended Consequences of Regulation Source: Bloomberg (5/18). This month, the European Union will embark on an expansive effort to give people more control over their data online... As it comes into force, Europe should be mindful of unintended consequences & open to change when things go wrong. - Bloomberg Opinion Editorial, 5/8/18 36. 36 It’s Crucial To Manage For Unintended Consequences… But It’s Irresponsible to Stop Innovation + Progress 37. 37 USA Internet Leaders = Aggressive + Forward-Thinking Investors for Years 38. 38 Global USA-Listed Technology IPO Issuance & Global Technology Venture Capital Financing Investment (Public + Private) Into Technology Companies = High for Two Decades TechnologyIPO&PrivateFinancing,Global Source: Morgan Stanley Equity Capital Markets, *2018YTD figure as of 5/25/18, Thomson ONE. All global USA-listed technology IPOs over $30MM, data per Dealogic, Bloomberg, & Capital IQ. 2012: Facebook ($16B IPO) = 75% of 2012 IPO $ value. 2014: Alibaba ($25B IPO) = 69% of 2014 IPO $ value. 2017: Snap ($4B IPO) = 34% of 2017 $ value. NASDAQComposite 0 2,000 4,000 6,000 8,000 $0 $50B $100B $150B $200B 1990 1995 2000 2005 2010 2015 Technology Private Financing Technology IPO NASDAQ 2018YTD* 39. 39 Technology Companies = 25% & Rising % of Market Cap, USA USA Information Technology % of MSCI Market Capitalization Source: FactSet, Katy Huberty @ Morgan Stanley. MSCI, Formerly Morgan Stanley Capital International = American provider of equity, fixed income, hedge fund stock market indexes, and equity portfolio analysis tools. Data refers to MSCI’s index of USA publicly traded companies. 0% 10% 20% 30% 40% 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 33% March, 2000 25% April, 2018 IT%ofMSCIMarketCapitalization,USA 40. 40 Technology Companies = 6 of Top 15 R&D + Capex Spenders, USA USA Public Company Research & Development Spend + Capital Expenditures (2017) Source: SEC Edgar, Katy Huberty @ Morgan Stanley. Note: All figures are calendar year 2017. Amazon R&D = Tech & Content spend. General Motors does not include purchases of leased vehicles. AT&T capex does not include interest during construction, just purchases of property, plant, & equipment. Verizon capitalizes R&D expense (i.e. Reported as capex). General Electric R&D = GE funded, not government or customer. Bold indicates tech companies. $0 $10B $20B $30B $40B Merck General Electric Johnson & Johnson Chevron Facebook Ford General Motors Exxon Mobil Verizon AT&T Microsoft Apple Intel Google / Alphabet Amazon 2017 R&D + Capex Capex R&D Amazon Google / Alphabet Intel Microsoft Apple +45% Y/Y +23% +11% +5% +6% -4% +1% -4% +5% +5% +40% -26% +12% +2% +3% Facebook 41. 41 Technology Companies = Largest + Fastest Growing R&D + Capex Spenders, USA Research & Development Spend + Capital Expenditures – Select USA GICS Sectors $0 $100B $200B $300B 2007 2009 2011 2013 2015 2017 R&D+Capex,USA Technology Healthcare Energy Materials Industrials Discretionary Staples Utilities Telecom Technology +9% CAGR +18% Y/Y Healthcare* +4% CAGR +8% Y/Y Discretionary 0% CAGR -22% Y/Y Source: ClariFi, Katy Huberty @ Morgan Stanley. GICS = Global Industry Classification Standard, an industry taxonomy developed in 1999 by MSCI and Standard & Poor's (S&P) for use by the global financial community. CAGR = Compounded annual growth rate from 2007-2017. Note: Amazon, Netflix and Expedia removed from Discretionary Sector & added to Technology. Discretionary includes companies that sell goods & services that are considered non-essential by consumers such as Starbucks (restaurants) & Nike (apparel). See appendix for detailed GICs definition. ClariFi does not have R&D or Capex data from Financial Services. *Healthcare Includes pharmaceutical companies. 42. 42 Technology Companies = Rising R&D + Capex as % of Revenue…18% vs. 13% (2007) USA Technology Company Research & Development Spend + Capital Expenditures vs. % of Revenue 13% 18% 0% 5% 10% 15% 20% $0 $200B $400B $600B $800B 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 %ofRevenue R&D+Capex,USA R&D + Capex % of Revenue Source: ClariFi, Katy Huberty @ Morgan Stanley. GICS = Global Industry Classification Standard, an industry taxonomy developed in 1999 by MSCI and Standard & Poor's (S&P) for use by the global financial community. Note: Amazon, Netflix and Expedia removed from Discretionary Sector & added to Technology. Discretionary includes companies that sell goods & services that are considered non-essential by consumers such as Starbucks (restaurants) & Nike (apparel). See appendix for detailed GICs definition. 43. 43 USA Tech Companies… Aggressive Competition + Spending on R&D + Capex = Driving Innovation + Growth 44. 44 E-COMMERCE = TRANSFORMATION ACCELERATING 45. 45 E-Commerce = Acceleration Continues @ +16% vs. +14% Y/Y, USA E-Commerce Sales + Y/Y Growth Source: St. Louis Federal Reserve FRED database. Note: Historic data (Pre-2016) adjusted / back-casted in 2017 by USA Census Bureau to better align with Annual Retail Trade + Monthly Retail Trade Survey data. 0% 4% 8% 12% 16% 20% $0 $100B $200B $300B $400B $500B 2010 2011 2012 2013 2014 2015 2016 2017 E-Commerce Sales Y/Y Growth E-CommerceSales,USA Y/YGrowth 46. 46 E-Commerce vs. Physical Retail = Share Gains Continue @ 13% of Retail E-Commerce as % of Retail Sales 0% 4% 8% 12% 16% 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 E-CommerceShare,USA Source: USA Census Bureau, St. Louis Federal Reserve FRED database. Note: 13% = Annualized share. Penetration calculated by dividing E-Commerce sales by “Core” Retail Sales (excluding food services, motor vehicles / auto parts, gas stations & fuel). All figures are seasonally adjusted. 47. 47 Amazon = E-Commerce Share Gains Continue @ 28% vs. 20% in 2013 E-Commerce Gross Merchandise Value (GMV) – Amazon vs. Other Source: St. Louis Federal Reserve FRED database, Brian Nowak @ Morgan Stanley (5/18). Morgan Stanley Amazon USA GMV estimates exclude in-store GMV and assume 90% of North American GMV is USA. Market share calculated using FRED E-Commerce sales data. 0% 20% 40% 60% 80% 100% $0 $100B $200B $300B $400B $500B ShareofE-Commerce,USA GMV 2017 2013 2013 2017 Other Amazon $52B GMV = 20% Share $129B GMV = 28% Share 48. 48 E-Commerce = Evolving + Scaling 49. 49 E-Commerce = Mobile / Interactive / Personalized / In-Feed + Inbox / Front-Doored Source: Instacart (5/18) Find Local Store Explore Custom Savings View + Share Recommendations Pay Seamlessly Update Instacart 50. 50 E-Commerce = A Look @ Tools + Numbers… Payment Online Store Online Payment Fraud Prevention Purchase Financing Customer Support Finding Customers Delivering Product 51. 51 Offline Merchants = Set Up Payment System… 0 1MM 2MM 3MM 2013 2014 2015 2016 2017 $0 $30B $60B $90B GPV Active Sellers Estimated Active Sellers & Gross Payment Volume (GPV) Source: Square (5/18). Note: Active Sellers have accepted five or more payments using Square in the last 12 months. In 11/15 Square disclosed it had 2MM users and in 3/16 disclosed it was adding 100K sellers per quarter – assuming seller Trends remained constant, Square had approximately 2.8MM active sellers at the end of 2017. (~2.8MM = 2017E) Square Points of Sale (POS) Software Services Payroll Loans Invoices Analytics EstimatedActiveSellers,Global GPV,Global 52. 52 ...Build Online Store… 0 300K 600K 900K 2013 2014 2015 2016 2017E $0 $10B $20B $30B GMV Merchants ActiveMerchants,Global GMV,Global Active Merchants & Gross Merchandise Volume (GMV) Shopify Online Stores Source: Shopify, Brian Essex @ Morgan Stanley. Note: Active Merchants refers to merchants with an active Shopify subscription at the end of the relevant period. 2017 Active merchants and GMV are estimates based on periodic disclosures. (609K = 2017E) 53. 53 …Integrate Online Payment System… Stripe Payment API Implementation Source: Stripe (5/18). <form action="your-server-side-code" method="POST"> <script src="https://checkout.stripe.com/checkout.js" class="stripe-button" data-key="pk_test_6pRNASCoBOKtIshFeQd4XMUh" data-amount="999" data-name="Stripe.com" data-description= "Example charge" data-image= "https://stripe.com/img/documentation/checkout/marketplace.png" data-locale="auto" data-zip-code="true"> </script> </form> 54. 54 ...Integrate Fraud Prevention… 0 4K 8K 12K 2015 2016 2017 Merchants ActiveMerchants,Global Signifyd Fraud Prevention Source: Signifyd (5/18). Note: Merchants refers to retailers using Signifyd services to monitor for fraud @ period end. (10K = 2017) IncreaseRevenue FastDecisions(milliseconds) Shift Liability 55. 55 …Integrate Purchase Financing… Affirm Financing Source: Affirm (5/18). 1,200+ = Merchants $350 56. 56 Intercom Real-Time Support …Integrate Customer Support… Customer Conversations Source: Intercom (5/18). Note: Conversations started include messages initiated by business & customers. (500MM = 2018) 0 100MM 200MM 300MM 400MM 500MM 2013 2014 2015 2016 2017 2018 ConversationsStarted,Global 57. 57 …Find Customers… Source: Criteo (5/18). Note: Clients defined as active clients @ relevant period end. (18K = 2017) 0 5K 10K 15K 20K 2013 2014 2015 2016 2017 Marketing Clients Clients,Global Criteo Customer Targeting 58. 58 …Deliver Products to Customers Parcel Volume UPS + FedEx + USPS* 0 2B 4B 6B 8B 10B 12B 2012 2013 2014 2015 2016 2017 Volume,USA* USPS UPS FedEx Product Delivery Source: UPS, FedEx, USPS, Caviar. *Combines USPS's domestic shipping & package services volumes, FedEx's domestic package volumes, and UPS's domestic package volumes. All figures are calendar year end except FedEx which includes LTM figures ending November 30 due to offset fiscal year. 59. 59 …E-Commerce = A Look @ Tools + Numbers Payment Online Store Online Payment Fraud Prevention Purchase Financing Customer Support Finding Customers Delivering Product 60. 60 Building / Deploying Online Stores = Trend Evinced by Shopify Storefront Exchange Source: Shopify (5/18) Shopify Storefront Exchange (Launched 6/17) Loopies.com 61. 61 Online Product Finding Evolution = Search Leads… Discovery Emerging Getting More... Data Driven / Personalized / Competitive 62. 62 Product Finding = Often Starts @ Search (Amazon + Google...) 49% 36% 15% Where Do You Begin Your Product Search? Source: Survata (9/17). Note: n = 2,000 USA customers. Amazon Search Engine Other 63. 63 Product Finding (Amazon) = Started @ Search...Fulfilled by Amazon Product Search Source: The Internet Archive, Amazon. 1-Click Purchasing Prime Fulfillment Sponsored Product Listings Voice Search + Fulfillment 64. 64 Product Finding (Google) = Started @ Search...Fulfilled by Others Organic Search Paid Search Google Shopping Product Listing Ads Shopping Actions Source: The Internet Archive, Google. 65. 65 Online Product Finding Evolution = Search Leads… Discovery Emerging Getting More... Data Driven / Personalized / Competitive 66. 66 Product Finding (Facebook / Instagram) = Started @ Personalized Discovery in Feed Source: Facebook (5/18), Instagram (5/18). Facebook Instagram 67. 67 Online Product Finding Evolution = Search Leads… Discovery Emerging Getting More... Data Driven / Personalized / Competitive 68. 68 Google = Ad Platform to a Commerce Platform... Amazon = Commerce Platform to an Ad Platform Source: Advia (Google 2000 image), TechCrunch (2/17), Amazon (5/18). AdWords Sponsored Products1-Click Checkout Google Amazon Google Home Ordering 1997…2000 2018 69. 69 E-Commerce-Related Advertising Revenue = Rising @ Google + Amazon + Facebook Amazon $4B +42% Y/Y = Ad Revenue Google 3x = Engagement Increase For Top Mobile Product Listing Ad* Facebook >80MM +23% Y/Y = SMBs with Pages Source: Google (7/17), Brian Nowak @ Morgan Stanley (Amazon Ad revenue estimate, 5/18), Facebook (4/18). *Google disclosed that the leftmost listing in a mobile product listing ad experiences 3x engagement. 70. 70 Social Media = Enabling More Efficient Product Discovery / Commerce 71. 71 Social Media = Driving Product Discovery + Purchases Source: Curalate Consumer Survey 2017 (8/17). Note: n = 1,000 USA consumers ages 18-65. Left chart question: ‘In the last 3 months, have you discovered any retail products that you were interested in buying on any of the following social media channels?’ Right chart question: ‘What action did you take after discovering a product in a brand’s social media post?’ Never Bought / Other includes offline purchases made later. …Social Media Discovery Driving Purchases 44% 11% 45% 55% = Bought Product Online After Social Media Discovery Social Media Driving Product Discovery… 22% 34% 59% 59% 78% 0% 50% 100% Snap Twitter Pinterest Instagram Facebook % of Respondents, USA (18-65 Years Old) % of Respondents that Have Discovered Products on Platform, USA (18-34 Years Old) Bought Online Later Bought Online Immediately Never Bought / Other 72. 72 2% 6% 0% 2% 4% 6% 8% Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Social Media = Share of E-Commerce Referrals Rising @ 6% vs. 2% (2015) Social / Feed Referrals to E-Commerce Sites Share,USA 2015 2016 2017 2018 Source: Adobe Digital Insights (5/18). Note: Adobe Digital Insights based on 50B+ online USA page visits since 2015. Data is collected on a per-visit basis across all Internet connected devices and then aggregated by Adobe. Data reflects 5/1/18 measurements. 73. 73 Social Media = Helping Drive Growth for Emerging DTC Retailers / Brands $0 $20MM $40MM $60MM $80MM $100MM 0 1 2 3 4 5 6 7 AnnualRevenue,USA Years Since Inception Source: Internet Retailer 2017 Top 1,000 Guide. *Data only for E-Commerce sales and shown in 2017 dollars. Chart includes pure-play E-Commerce retailers and evolved pure-play retailers. The Top 1,000 Guide uses a combination of internal research staff and well-known e-commerce market measurement firms such as Compete, Compuware APM, comScore, ForeSee, Experian Marketing Services, StellaService and ROI Revolution to collect and verify information. Select USA Direct-to-Consumer (DTC) Brands – Revenue Ramp to $100MM Since Inception* 74. 74 Social Media = Ad Engagement Rising…Facebook E-Commerce CTRs Rising 1% 3% 0% 1% 2% 3% 4% Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 FacebookE-CommerceCTR,Global Facebook E-Commerce CTRs (Click-Through Rates) Source: Facebook, Nanigans Quarterly Facebook Benchmarking Data. Note: Click-Through Rate is defined as the percentage of people visiting a web page who access a hyperlink text from a particular advertisement. CTR figures based on $600MM+ of ad spend through Nannigan’s platform. 2016 2017 2018 75. 75 Return on Ad Spend = Cost Rising @ Faster Rate than Reach -40% 0% 40% 80% 120% Q1 Q2 Q3 Q4 Q1 Y/YGrowth,Global eCPM CTR Facebook E-Commerce eCPM vs. CTR Y/Y Growth 2017 2018 CTR = +61% Source: Booking Holdings Inc. (11/17), Nanigans Quarterly Facebook Benchmarking Data. Note: eCPMs are defined as the effective (blended across ad formats) cost per thousand ad impressions. Click-Through Rate is defined as the percentage of people visiting a web page who access a hyperlink text from a particular advertisement. CTR figures based on $600MM+ of ad spend through Nanigan’s platform. In 2017, Booking Holdings spent $4.1B on online performance advertising which is primarily focused on search engine marketing (SEM) channels. The quote on the left relates to historical long-term ad ROI Trends as competition across performance channels intensified. In performance-based [digital advertising] channels, competition for top placement has reduced ROIs over the years & been a source of margin pressure… - Glenn D. Fogel, CEO & President, Booking Holdings Q3:17 Earnings Call, (11/17) eCPM = +112% 76. 76 Source: Salesforce Digital Advertising 2020 Report (1/18). Note: n = 900 full-time advertisers, media buyers, and marketers with the title of manager and above. Respondents are from companies in North America (USA, Canada), Europe (France, Germany, Netherlands, UK, Ireland) and Asia Pacific (Japan, Australia, New Zealand) with each region having 300 participants. The survey was done online via FocusVision in 11/17. Customer Lifetime Value (LTV) = Importance Rising as... Customer Acquisition Cost (CAC) Increases What Do You Consider To Be Important Ad Spending Optimization Metrics? 8% 13% 15% 18% 19% 27% 0% 10% 20% 30% Multi-touch Attribution Last-Click Attribution Closed-Won Business Brand Recognition & Lift Impressions / Web Traffic Customer Lifetime Value % of Respondents, Global 77. 77 Lifetime Value / Customer Acquisition Cost (LTV / CAC) = Increasingly Important Metric for Retailers / Brands Source: Facebook (3/17). Facebook Ad Analytics Tools LTV Integration 78. 78 Data-Driven Personalization / Recommendations = Early Innings @ Scale 79. 79 Evolution of Commerce Drivers (1890s -> 2010s) = Demographic -> Brand -> Utility -> Data Source: Eric Feng @ Kleiner Perkins Wikimedia, eBay, Stitch Fix. Demographic Brand Utility Data Catalogs Limited product selection + shopping moments Department Stores / Malls Rising product selection + shopping moments E-Commerce – Transactional Massive product selection + 24x7 shopping moments E-Commerce – Personalized Curated product discovery + 24x7 recommendations • Sears Roebuck • Montgomery Ward • Macy’s • GAP • Nike • Amazon • eBay • Amazon • Facebook • Stitch Fix 1890s - 1940s 1940s - 1990s 1990s - 2010s 2010s - … 80. 80 Product Purchases = Many Evolving from Buying to Subscribing 81. 81 Subscription Service Growth = Driven by... Access / Selection / Price / Experience / Personalization Online Subscription Services Representative Companies Subscribers 2017 Growth Y/Y Netflix Video 118MM +25% Amazon Commerce / Media 100MM -- Spotify Music / Audio 71MM +48% Sony PlayStation Plus Gaming 34MM +30% Dropbox File Storage 11MM +25% The New York Times News / Media 3MM +43% Stitch Fix Fashion / Clothing 3MM +31% LegalZoom Legal Services 550K +16% Peloton Fitness 172K +173% Source: Netflix, Amazon, Spotify, Sony, Dropbox, The New York Times, Stitch Fix, LegalZoom, Peloton. Note: Netflix = global streaming memberships. The New York Times = digital subscribers. Sony PlayStation Plus figures reflect FY, which ends March 31. Stitch Fix figures reflect FY, which ends January 31. 82. 82 Free-to-Paid Conversion = Driven by User Experience... Spotify Subscribers @ 45% of MAUs vs. 0% @ 2008 Launch Source: Spotify (5/18). Note: MAU = Monthly Active Users. Spotify Subscribers % of MAU 0% 20% 40% 60% 0 25MM 50MM 75MM 2014 2015 2016 2017 Subscribers%ofMAU Subscribers,Global Subscribers Subscribers % of MAU 83. 83 Shopping = Entertainment… 84. 84 Mobile Shopping Usage = Sessions Growing Fast Mobile Shopping App Sessions – Growth Y/Y -40% -16% -8% -8% -8% 20% 20% 33% 43% 54% -60% -40% -20% 0% 20% 40% 60% Lifestyle Games Personalization Photography Sports News / Magazine Utilities / Productivity Business / Finance Music / Media / Entertainment Shopping Session Growth Y/Y (Global, 2017 vs. 2016) Source: Flurry Analytics State of Mobile 2017 (1/18). Note: n = 1MM applications across 2.6B devices globally. Sessions defined as when a user opens an app. Average = 6% Shopping 85. 85 Taobao 1.5MM+ Active Content Creators Product + Price Discovery = Often Video-Enabled… YouTube Many USA Consumers View YouTube Before Purchasing Products Source: YouTube (3/16, 5/18), Alibaba (3/18), Right image: South China Morning Post (2/18). Note: Many USA customers refers to data in a Report published by Google, based on Google / Ipsos Connect, YouTubeSports Viewers Study conducted on n = 1,500 18-54 year old consumers in the USA in 3/16. 86. 86 …Product + Price Discovery = Often Social + Gamified Source: Wish (5/18), Pinduoduo (1/18), Right image: Walkthechat (1/18). Note: Wish user figures are cumulative users, not MAU. Pinduoduo Refer Friends to Reduce Price Wish Hourly Deals 300MM+ Users 87. 87 Physical Retail Trending = Long-Term Growth Deceleration 88. 88 -6% -3% 0% 3% 6% $0 $1B $2B $3B $4B 2000 2002 2004 2006 2008 2010 2012 2014 2016 Volume Growth Y/Y Physical Retail = Long-Term Sales Growth Deceleration Trend Physical Retail Sales + Y/Y Growth, USA Source: St. Louis Federal Reserve FRED Database. Note: Physical Retail includes all retail sales excluding food services, motor vehicles / auto parts & fuel. PhysicalRetailSales,USA Y/YGrowth 89. 89 ‘New Retail’ = Alibaba View from China 90. 90 Alibaba = Building E-Commerce Ecosystem Born in China Source: Alibaba Investor Day (6/17). 91. 91 Alibaba & Amazon = Similar Focus Areas… Alibaba = Higher GMV…Amazon = Higher Revenue (2017) Source: Grace Chen (Alibaba) + Brian Nowak (Amazon) @ Morgan Stanley. *Alibaba has invested but does not have a majority ownership. **Alibaba Non- China revenue = Alibaba International Commerce revenue (AliExpress, Lazada, & Alibaba.com). Amazon Non-USA revenue = Retail sales of consumer products & subscriptions through internationally-focused websites outside of North America. Note: All figures reflect calendar year 2017. Alibaba GMV includes Non-China GMV estimates, Y/Y Growth is FX adjusted using 6.76 RMB / USD average exchange rate for 2017. All figures refer to calendar year. Market cap as of 5/29/18. Amazon GMV includes in-store GMV. FCF = Cash flow from operations - stock-based compensation - capital expenditures. Tmall / Taobao / AliExpress / Lazada / Alibaba.com / 1688.com / Juhuasuan / Daraz Alibaba Cloud Intime / Suning* / Hema Ant Financial* / Paytm* Youku / UCWeb / Alisports / Alibaba Music / Damai / Alibaba Pictures* Ele.Me (Local) / Koubei (Local) / Alimama / (Marketing) / Cainiao (Logistics) / Autonavi (Mapping) / Tmall Genie (IoT) Amazon.com Amazon Web Services (AWS) Whole Foods / Amazon Go / Amazonbooks Amazon Payments Amazon Video / Amazon Music / Twitch / Amazon Game Studios / Audible Alexa (IoT) / Ring (IoT) / Kindle + Fire Devices (Hardware) Amazon $783B = Market Capitalization $225B = GMV(E) +25% Y/Y $178B = Revenue +31% Y/Y 37% = Gross Margin $4B = Free Cash Flow 31% = Non-USA Revenue as % of Total** Alibaba $509B = Market Capitalization $701B = GMV(E) +29% Y/Y $34B = Revenue +31% Y/Y 60% = Gross Margin $14B = Free Cash Flow 8% = Non-China Revenue as % of Total** Cloud Platform Other Digital Entertainment Payments Online Marketplace Physical Retail 92. 92 …through technology & consumer insights, we [Alibaba] put the right products in front of right customers at the right time… our ‘New Retail’ initiatives are substantially growing Alibaba’s total addressable market in commerce… in this process of digitizing the entire retail operation, we are driving a massive transformation of the traditional retail industry. It is fair to say that our e-commerce platform is fast becoming the leading retail infrastructure of China. Since Jack Ma coined the term ‘New Retail’ in 2016, the term has been widely adopted in China by traditional retailers & Internet companies alike. New Retail has become the most talked about concept in business… Alibaba has three unique success factors that are enabling us to realize the New Retail vision. Alibaba = ‘New Retail’ Vision Starts in China… Alibaba CQ1:18 & CQ4:17 Earnings Calls, 5/4/18, 1/24/18 93. 93 …Alibaba’s marketplace platforms handle billions of transactions each month in shopping, daily services & payments. These transactions provide us with the best insights into consumer behavior & shifting consumption Trends. This puts us in the best position to enable our retail partners to grow their business. …Alibaba is a deep technology company. We contribute expertise in cloud, artificial intelligence, mobile transactions & enterprise systems to help our retail partners improve their businesses through digitization & operating efficiency. …Alibaba has the most comprehensive ecosystem of commerce platforms, logistics & payments to support the digital transformation of the retail sector. …Alibaba = ‘New Retail’ Vision Starts in China Alibaba CQ1:18 & CQ4:17 Earnings Calls, 5/4/18, 1/24/18. 94. 94 …Alibaba = Extending Platform Beyond China Source: Alibaba, Pitchbook. *Percentages represent international commerce revenue proportion of total revenue. Note: All figures are calendar year. Revenue figures translated using the USD / CNY = 6.76, the average rate for 2017. Grey indicates a majority control stake, all others are minority investments. Country based on headquarters, not countries of operation. Alibaba International Commerce revenue includes revenue generated from AliExpress, Lazada, and Alibaba.com. 0% 30% 60% 90% $0 $1B $2B $3B 2012 2013 2014 2015 2016 2017 International Commerce Revenue InternationalCommerceRevenue Y/YGrowth International Revenue = 8.4% vs. 7.9 Y/Y* Revenue Company Country Category Type Date Daraz.pk Pakistan Marketplace M&A 5/18 Tokopedia Indonesia Marketplace Equity 8/17 Paytm India Payments Equity 4/17 Lazada Singapore Marketplace M&A 4/16 Selected Investment Alibaba Non-China E-Commerce Highlights 95. 95 Internet ADVERTISING = GROWTH CONTINUING... ACCOUNTABILITY RISING 96. 96 Advertising $ = Shift to Usage (Mobile) Continues % of Time Spent in Media vs. % of Advertising Spending Source: Internet and Mobile advertising spend based on IAB and PwC data for full year 2017. Print advertising spend based on Magna Global estimates for full year 2017. Print includes newspaper and magazine. ~$7B opportunity calculated assuming Mobile (IAB) ad spend share equal its respective time spent share. Time spent share data based on eMarketer (9/17). Arrows denote Y/Y shift in percent share. Excludes out-of-home, video game & cinema advertising. 4% 13% 36% 18% 29% 9% 9% 36% 20% 26% 0% 10% 20% 30% 40% 50% Print Radio TV Desktop Mobile %ofMediaTimeinMedia/ AdvertisingSpending,2017,USA Time Spent Ad Spend ~$7B Opportunity 97. 97 Internet Advertising = +21% vs. +22% Y/Y Source: IAB / PWC Internet Advertising Report (5/18). Internet Advertising Spend $23 $26 $32 $37 $43 $50 $60 $73 $88 0% 10% 20% 30% 0 $30B $60B $90B 2009 2010 2011 2012 2013 2014 2015 2016 2017 Y/YGrowth InternetAdvertisingSpend,USA Desktop Advertising Mobile Advertising Y/Y Growth 98. 98 Advertisers / Users vs. Content Platforms = Accountability Rising... The Wall Street Journal, February 2018 Adweek, July 2017 Many Americans Believe Fake News Is Sowing Confusion Pew Research Center, December 2016 99. 99 Source: YouTube (5/18, 12/17), Facebook (Transparency Report: 5/18, 5/17, 2/18). Note: All Google content moderators represent full-time hires but Facebook content moderators are not all full-time. ...Advertisers / Users vs. Content Platforms = Accountability Rising Facebook (Q1:18)Google / YouTube Content Initiatives 8MM = Videos Removed (Q4:17)… 81% Flagged by Algorithms… 75% Removed Before First View 2MM = Videos De-Monetized For Misleading Content Tagging (2017) 10K = Content Moderators (2018 Goal) 583MM = Fake Accounts Removed… 99% Flagged Prior To User Reporting 21MM = Pieces of Lewd Content Removed… 96% Flagged by Algorithms 3.5MM = Pieces of Violent Content Removed… 86% Flagged by Algorithms 2.5MM = Pieces of Hate Speech Removed… 38% Flagged by Algorithms +7,500 = Content Moderators… 3,000 Hired (5/17–2/18) 100. 100 CONSUMER SPENDING = DYNAMICS EVOLVING… Internet CREATING OPPORTUNITIES 101. 101 Consumers… Making Ends Meet = Difficult 102. 102 Household Debt = Highest Level Ever & Rising… Change vs. Q3:08 = Student +126%...Auto +51%...Mortgage -4% 6% 4% 0% 5% 10% 15% $0 $3T $6T $9T $12T $15T 2003 2005 2007 2009 2011 2013 2015 2017 UnemploymentRate,USA HouseholdDebt,USA $13.1T$12.7T Household Debt & Unemployment Rate Source: Federal Reserve Bank of New York Consumer Credit Panel / Equifax, Quarterly Household Debt and Credit Report, Q4:17; St. Louis Federal Reserve FRED Database. Mortgage Student Loan Auto Credit Card Home Equity Revolving Other Unemployment Rate 103. 103 Personal Saving Rate = Falling @ 3% vs. 12% Fifty Years Ago… Debt-to-Annual-Income Ratio = Rising @ 22% vs. 15% Source: St. Louis Federal Reserve FRED Database, USA Federal Reserve Bank. *Consumer debt-to-annual-income ratio reflects outstanding credit extended to individuals for household, family, and other personal expenditures, excluding loans secured by real estate vs. average annual personal income. Personal saving rate is shown as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate.” (i.e. the annual share of disposable income dedicated to saving) Personal Saving Rate & Debt-to-Annual-Income* Ratio 0% 5% 10% 15% 20% 25% 1968 1978 1988 1998 2008 2018 Personal Saving Rate Debt-to-Annual-Income* Ratio Ratio,USA 104. 104 Relative Household Spending = Shifting Over Past Half-Century 105. 105 Relative Household Spending Rising Over Time = Shelter + Pensions / Insurance + Healthcare… Relative Household Spending 12% 7% 5% 15% 8% 5% 17% 10% 7% 0% 5% 10% 15% 20% AnnualSpend,USA 1972 1990 2017 $11K $31K $68KTotal Expenditure Source: USA Bureau of Labor Statistics (BLS), Consumer Expenditure Survey. *Pensions + Insurance includes deductions for private retirement accounts, social security, and life insurance. **Other Includes education and miscellaneous other expenses. Note: Results based on Surveys of American Urban & Rural Households (Families & Single Consumers). 1972 data reflects non-annual survey conducted by BLS + Census Bureau to adjust CPI. 1990 and 2017 Data Based on Annual Survey performed by BLS + Census Bureau. Healthcare costs include insurance, drugs, out-of-pocket medical expenses, etc. 2017 = mid-year figures. 106. 106 …Relative Household Spending Falling Over Time = Food + Entertainment + Apparel Relative Household Spending 15% 6% 5% 15% 5% 5% 12% 4% 3% 0% 5% 10% 15% 20% 1972 1990 2017 $11K $31K $68KTotal Expenditure AnnualSpend,USA Source: USA Bureau of Labor Statistics (BLS), Consumer Expenditure Survey. *Pensions + Insurance includes deductions for private retirement accounts, social security, and life insurance. **Other Includes education and miscellaneous other expenses. Note: Results based on Surveys of American Urban & Rural Households (Families & Single Consumers). 1972 data reflects non-annual survey conducted by BLS + Census Bureau to adjust CPI. 1990 and 2017 Data Based on Annual Survey performed by BLS + Census Bureau. Healthcare costs include insurance, drugs, out-of-pocket medical expenses, etc. 2017 = mid-year figures. 107. 107 Food = 12% vs. 15% of Household Spending 28 Years Ago... 108. 108 Grocery Price Growth = Declining Trend… Owing To Grocery Competition 0% 25% 50% 75% -2% 0% 2% 4% 6% 8% 10% 1990 1995 2000 2005 2010 2015 Grocery Price Change Y/Y & Market Share of Top 20 Grocers Top 20 Grocer Market Share Grocery* Price Y/Y Change PriceChangeY/Y,USA MarketShare,USA Source: USDA Research Services, using data from the USA Census Bureau’s Annual Retail Trade Survey + Company Reports, USA Bureau of Labor Statistics (BLS). *Grocery Price growth refers to the growth in prices for “Food at Home” as Reported by the USA Census Bureau. Note: Includes all food purchases in CPI, other than meals purchased away from home (e.g., Restaurants). Grocery @ 56% of Food Spend in 2017 vs. 58% in 1990 per BLS. 2017 109. 109 Walmart = Helped Reduce Grocery Prices via Technology + Scale... per Greg Melich @ MoffettNathanson 0% 5% 10% 15% 20% 1995 2000 2005 2010 2015 Walmart – Grocery Share 2017 By using technology to reduce inventory, expenses & shrinkage, we can create lower prices for our customers. - Walmart 1999 Annual Report Source: Greg Melich @ MoffettNathanson Note: Share reflects retail value of food for off-site consumption sold across all Walmart properties. GroceryShare,USA 110. 110 E-Commerce = Helping Reduce Prices for Consumers 111. 111 E-Commerce sales have risen rapidly over the past decade. Online prices are falling – absolutely & relative to – traditional inflation measures like the CPI. Inflation online is, literally, 200 basis points lower per year than what the CPI has been showing. To better understand the economy going forward, we will need to find better ways to measure prices & inflation. - Austan Goolsbee, Professor of Economics, University of Chicago Booth School of Business, 5/18 112. 112 Consumer Goods Prices = Have Fallen… -3% Online & -1% Offline Over 2 1/4 Years per Adobe DPI… Source: Adobe Digital Economy Project Note: Adobe Digital Economy Project measures prices and sales volume for 80% of online transactions at top 100 USA retailers (15B site visits & 2.2MM products) then calculates a Digital Price Index (DPI) using a Fisher Ideal model. CPI calculates USA prices using a basket of 83K goods, tracked monthly, & applied to a Laspeyeres model. DPI Excludes Apparel. Austan Goolsbee serves as strategic advisor to Adobe DPI project. $0.94 $0.96 $0.98 $1.00 $1.02 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Online Retail (DPI) Offline Retail Consumer Prices For Matching Products - Online vs. OfflinePrices(Indexedto1/1/16),USA Online = -3% Offline = -1% 2016 2017 2018 113. 113 …Online vs. Offline Price Decline Leaders = TVs / Furniture / Computers / Sporting Goods per Adobe DPI (30%) (20%) (10%) 0% 10% Price Change, Y/Y (DPI vs. CPI), USA, 3/17-3/18 DPI vs. CPI Difference (%) 5% 1% 1% 0% 0% -1% -1% -1% -2% -2% -3% -4% CPIDPI 0% 0% Source: Adobe Digital Economy Project Note: Adobe Digital Economy Project measures prices and sales volume for 80% of online transactions at top 100 USA retailers (15B site visits & 2.2MM products) then calculates a Digital Price Index (DPI) using a Fisher Ideal model. CPI calculates USA prices using a basket of 83K goods, tracked monthly, & applied to a Laspeyeres model. DPI Excludes Apparel. Austan Goolsbee serves as strategic advisor to Adobe DPI project. 114. 114 We've seen how technology can make online shopping more efficient, with lower prices, more selection & increased convenience. We are about to see the same thing happen to offline shopping. - Hal Varian, Chief Economist @ Google, 5/18 115. 115 Relative Household Spending = How Might it Evolve? Shelter Spend = Rising Transportation Spend = Flat Healthcare Spend = Rising 116. 116 Shelter as % of Household Spending = 17% vs. 12% (1972)... Largest Segment in % + $ Growth Relative Household Spending 12% 15% 17% 0% 5% 10% 15% 20% 1972 1990 2017 $11K $31K $68KTotal Expenditure AnnualSpend,USA Source: USA Bureau of Labor Statistics (BLS), Consumer Expenditure Survey. *Pensions + Insurance includes deductions for private retirement accounts, social security, and life insurance. **Other Includes education and miscellaneous other expenses. Note: Results based on Surveys of American Urban & Rural Households (Families & Single Consumers). 1972 data reflects non-annual survey conducted by BLS + Census Bureau to adjust CPI. 1990 and 2017 Data Based on Annual Survey performed by BLS + Census Bureau. Healthcare costs include insurance, drugs, out-of-pocket medical expenses, etc.. 2017 = mid-year figures. 117. 117 Shelter… 118. 118 USA Cities = Less Densely Populated vs. Developed World 0 1000 2000 3000 4000 South Korea Japan UK Italy Germany Spain France Australia USA CanadaUSA Population Density – Urban Areas* Top 10 ‘Advanced’ Economies**, 2014 Source: OECD, International Monetary Fund (IMF). *Urban areas defined as “Functional Urban Areas’ per OECD/EU with greater than 500K residents. **IMF determines ‘Advanced Economies’ designation using a combination of GDP per Capita, Export Diversity, and integration into the global financial system. ResidentsperKM2(UrbanAreas) 17x USA 6x ~2x 9x 5x ~3x ~3x ~2x 119. 119 USA Homes = Bigger vs. Developed World… Japan ~1,015 South Korea ~725 UK ~990 Source: Wikimedia, Japan Ministry of Internal Affairs, US Census Bureau, UK Office for National Statistics, Asian Development Bank Institute. *USA + Japan + UK = 2013. Korea = 2010, owing to lag in publication of government measured data. Note: Data reflects average occupied dwelling size across each nation. Average Home Size* (Square Feet) – Select Countries USA ~1,500 120. 120 …USA Homes = Getting Bigger...Residents Falling @ 2.5 vs. 3.0 (1972) 0 1 2 3 4 0 1K 2K 3K 4K 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 Average New Home Square Footage & ResidentsNewHomeSquareFootage,USA ResidentsperHome,USA New Home Square Footage Source: USA Census Bureau (6/17). Note: Data reflects newly built housing stock. Single Family homes includes newly built single family homes. Similar growth Trends are seen across all housing units, as single-family homes are the majority of new USA housing stock. Average size of multifamily new dwelling in USA = 1,095 square feet in 1999 (earliest data available), 1,207 square feet in 2016. Residents per household based on all households. Residents per Home 121. 121 USA Office Space = Steadily Getting Denser / More Efficient 0 50 100 150 200 250 1990 1995 2000 2005 2010 2015 Occupied Office Space per Employee – Square FeetSquareFootageperEmployee,USA 195 180 Source: CoStart Portfolio strategy Analysis of USA Leased office space & USA Employment Figures (2017). 2017 122. 122 …Shelter... To Contain Spending… Consumers May Aim to Increase Utility of Space 123. 123 Airbnb = Provides Income Opportunities for Hosts… Source: Airbnb, TechCrunch. Note: Airbnb disclosed in 2017 ~660K listings were in USA. A 2017 CBRE study of ~256K USA Airbnb listings + ~177K Airbnb hosts in Austin, Boston, Chicago, LA, Miami, Nashville, New Orleans, New York City, Oahu, Portland, San Francisco, Seattle, & Washington D.C. found that 83% of listings are made by single-listing hosts, or are listings for spaces within otherwise occupied dwellings. This implies that there >500K individuals listing spaces on Airbnb in USA as of 2018. 0 2MM 4MM 6MM 0 30MM 60MM 90MM 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 ActiveListings,Global GuestArrivals,Global Guest Arrivals Active Listings by Hosts Airbnb Guest Arrivals & Active Listings by Hosts 5MM Global Active Listings 124. 124 …Airbnb Consumer Benefits = Can Offer Lower Prices for Overnight Accommodations $306 $240 $220 $217 $193 $167 $118 $114 $187 $191 $93 $179 $114 $110 $65 $92 $0 $50 $100 $150 $200 $250 $300 $350 New York City Sydney Tokyo London Toronto Paris Moscow Berlin Hotel Airbnb Airbnb vs. Hotel – Average Room Price per Night Price,1/18 Source: AirDNA, HRS, Originally Compiled by Statista. Note: Hotel data based on HRS’s inventory of hotels. Euro prices converted to USD on 1/22/18. 125. 125 Relative Household Spending = How Might it Evolve? Shelter Spend = Rising Transportation Spend = Flat Healthcare Spend = Rising 126. 126 Transportation as % of Household Spending = 14% vs. 14% (1972)... #3 Segment of $ Spending Behind Shelter + Taxes Relative Household Spending 14% 16% 14% 0% 5% 10% 15% 20% 1972 1990 2017 $11K $31K $68KTotal Expenditure AnnualSpend,USA Source: USA Bureau of Labor Statistics (BLS), Consumer Expenditure Survey. *Pensions + Insurance includes deductions for private retirement accounts, social security, and life insurance. **Other Includes education and miscellaneous other expenses. Note: Results based on Surveys of American Urban & Rural Households (Families & Single Consumers). 1972 data reflects non-annual survey conducted by BLS + Census Bureau to adjust CPI. 1990 and 2017 Data Based on Annual Survey performed by BLS + Census Bureau. Healthcare costs include insurance, drugs, out-of-pocket medical expenses, etc.. 2017 = mid-year figures. 127. 127 Transportation… To Contain Spending… Consumers Reducing Relative Spend on Vehicles + Increasing Utility of Vehicles 128. 128 Transportation as % of Household Spending = Vehicle Purchase % Declining…Other Transportation % Rising 0% 20% 40% 60% 1972 1990 2017 Source: USA BLS Consumer Expenditure Survey. Vehicle Age = Bureau of Transportation Statistics + I.H.S. Public Transit Trips = American Public Transit Association Note: *Vehicle Operation + Maintenance includes Insurance, Repairs, Parking, and Other expenses. Other transportation includes all transportation outside of personal vehicles, including rise-sharing.. Results based on Surveys of American Urban and Rural Households (Families and Single Consumers). 1972 data reflects non-annual survey conducted by BLS + Census Bureau to adjust CPI. 1990 and 2017 Data Based on Annual Survey performed by BLS + Census Bureau. Cars refers to all light vehicles (i.e. passenger cars + light trucks). Includes all actively driven cars. Public transit trips reflect unlinked rides (i.e. one full journey). Note: Ride Share Statistics based on Q1:16 and Q1:17 Estimates from Hillhouse Capital. Relative Household Spending – Transportation RelativeTransportationSpend,USA Vehicle Purchases Gas + Oil Vehicle Operation + Maintenance* Other Transportation Relative Transportation Spending = Vehicles Stay On Road Longer... @ 12 vs. 8 Years (1995) Average Car Lifespan …Other Transportation Rising +30% vs. 1995 Public Transit Usage ~2x Y/Y (2017) Ride-Share Rides 129. 129 Uber = Can Provide Work Opportunities for Driver-Partners… 0 1MM 2MM 3MM $0 $15B $30B $45B 2012 2013 2014 2015 2016 2017 Driver-Partners,Global GrossBookings,Global Gross Bookings Driver-Partners Uber Gross Bookings & Driver-Partners 3MM Global Driver-Partners +50*% Source: Uber. *Approximately +50% Y/Y. Note: ~900K USA Driver-Partners. Note: As of Jan 2015, ~85% of Uber driver-partners drove for UberX – based on historical growth rates, it is estimated that >90% of USA Uber driver-partners drive for UberX. 130. 130 …Uber Consumer Benefits = Lower Commute Cost vs. Personal Cars – 4 of 5 Largest USA Cities Source: Nerdwallet Study, March 2017. Washington D.C. included in Top 5 due to including of Baltimore MSA population. *Car commute costs include Gas (OPIS), Maintenance (Edmunds.com), Insurance (NerdWallet), & Parking (parkme.com). Note: Commute distances are from 2015 Brookings analysis. Uber data is based on a suburbs-to-city-center trip mirroring average commute distance for a metro. Data collected at peak commute times in February 2017. Cheapest Option (UberX, UberPOOL, etc.) selected for Uber costs. $218 $116 $130 $89 $65 $142 $77 $96 $62 $181 $0 $50 $100 $150 $200 $250 New York City Chicago Washington D.C. Los Angeles Dallas Personal Car Uber UberX / POOL vs. Personal Car* – Weekly Commute Costs 5 Largest USA Cities, 2017 WeeklyCost 131. 131 Relative Household Spending = How Might it Evolve? Shelter Spend = Rising Transportation Spend = Flat Healthcare Spend = Rising CREATED BY NOAH KNAUF @ KLEINER PERKINS 132. 132 Healthcare as % of Household Spending = 7% vs. 5% (1972)... Fastest Relative % Grower Relative Household Spending 5%5% 7% 0% 5% 10% 15% 20% 1972 1990 2017 $11K $31K $68KTotal Expenditure AnnualSpend,USA Source: USA Bureau of Labor Statistics (BLS), Consumer Expenditure Survey. *Pensions + Insurance includes deductions for private retirement accounts, social security, and life insurance. **Other Includes education and miscellaneous other expenses. Note: Results based on Surveys of American Urban & Rural Households (Families & Single Consumers). 1972 data reflects non-annual survey conducted by BLS + Census Bureau to adjust CPI. 1990 and 2017 Data Based on Annual Survey performed by BLS + Census Bureau. Healthcare costs include insurance, drugs, out-of-pocket medical expenses, etc.. 2017 = mid-year figures. 133. 133 Healthcare Spending = Increasingly Shifting to Consumers… 134. 134 USA Healthcare Insurance Costs = Rising for All… Consumers Paying Higher Portion @ 18% vs. 14% (1999)… Annual Health Insurance Premiums vs. Employee Contribution Source: Kaiser Family Foundation Employer Health Benefits Survey (9/17). Note: n = 2,000 private, non-federal businesses with at least 3 employees. Employers are asked for full person costs of healthcare coverage and the employee contribution. 14% 18% 0% 5% 10% 15% 20% $0 $2K $4K $6K $8K 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 %EmployeeContribution AnnualHealthcareInsurancePremiumsfor EmployeeSponsoredSingleCoverage,USA Premiums % Employee Contribution 135. 135 …USA Healthcare Deductible Costs = Rising A Lot… Employees @ >$2K Deductible = 22% vs. 7% (2009) Annual Deductibles vs. % of Covered Employees with >$2K Deductibles 7% 22% 0% 10% 20% 30% $0 $500 $1,000 $1,500 2006 2008 2010 2012 2014 2016 %ofEmployeesEnrolledinaSingle CoveragePlanwith>$2KDeductible AnnualDeductibleAmongEmployeeswith SingleCoverage,USA Annual Deductible Among Covered Employees % of Employees Enrolled in a Plan with >$2K Deductible Source: Kaiser Family Foundation Employer Health Benefits Survey (9/17). Note: n = 2,000 private, non-federal businesses with at least 3 employees. Employers are asked for full person costs of healthcare coverage and the employee contribution. 136. 136 When Consumers Start Spending More They Tend To Pay More Attention to Value + Prices… Will Market Forces Finally Come to Healthcare & Drive Prices Lower for Consumers? 137. 137 Healthcare Patients Increasingly Developing Consumer Expectations… Modern Retail Experience Digital Engagement On-Demand Access Vertical Expertise Transparent Pricing Simple Payments 138. 138 Healthcare Consumerization… Source: One Medical, Web.Archive.org, Oscar, Capsule. Note: Oscar data as of the first month of each year based on enrollments timing. Office Locations Memberships Unique Conversations One Medical Modern Retail Experience 0 40 80 2014 2016 2018 Offices 0 150K 300K 2014 2015 2017 Memberships 0 15K 30K Unique Conversations 2016 2017 Digital Healthcare Management CapsuleOscar On-Demand Pharmacy 139. 139 …Healthcare Consumerization Source: Nurx, Dr. Consulta, Cedar. *Medical interactions include prescriptions, lab orders, & messages from MDs / RNs. **Cedar data represents the % of total collections using Cedar over time at a multispecialty group with 450 physicians and an ambulatory surgical center. Nurx Women’s Healthcare Specific Solutions Interactions Transparent Pricing CedarDr. Consulta Simplified Healthcare Billing 0 50K 100K 2016 2017 2018 0 500K 1,000K 2013 2015 2017 0% 50% 100% 0 31 60 91 Patients Medical Interactions* Patients % of Collections** Days %ofCollections 140. 140 Consumerization of Healthcare + Rising Data Availability = On Cusp of Reducing Consumer Healthcare Spending? 141. 141 WORK = CHANGING RAPIDLY… Internet HELPING, SO FAR… 142. 142 Technology Disruption = Not New...But Accelerating 143. 143 Technology Disruption = Not New… 0% 25% 50% 75% 100% 1900 1915 1930 1945 1960 1975 1990 2005 New Technology Proliferation Curves*Adoption,USA Grid Electricity Radio Refrigerator Automatic Transmission Color TV Shipping Containers Microwave Computer Cell Phone Internet Social Media Usage Smartphone Usage 2017 Source: ‘Our World In Data’ collection of published economics data including Isard (1942), Grubler (1990), Pew Research, USA Census Bureau, and others. *Proliferation defined by share of households using a particular technology. In the case of features (e.g., Automatic Transmission), adoption refers to share of feature in available models. 144. 144 …Technology Disruption = Accelerating…Internet > PC > TV > Telephone New Technology Adoption Curves Electricity Telephone Car Dishwasher Radio Air Conditioning Washer Refrigerator Television Microwave Personal Computer Mobile Phone Internet 0 15 30 45 60 75 90 1867 1887 1907 1927 1947 1967 1987 2007 YearsUntil25%Adoption,USA 2017 Source: The Economist (12/15), Pew Research Center (1/17), Asymco (11/13). Note: Starting years based on invention year of each consumer product. 145. 145 Technology Disruption Drivers = Rising & Cheaper Compute Power + Storage Capacity... 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 1.E+06 1.E+07 1.E+08 1.E+09 1.E+10 1900 1925 1950 1975 2000 2025 $1,000 of Computer Equipment Analytical Engine BINAC IBM 1130 Sun 1 Pentium II PC $0 $0 $1 $10 $100 $1,000 $10,000 $100,000 $1,000,000 $10,000,000 1956 1987 2017 PriceperGB 0GB 0GB 0GB 1GB 10GB 100GB 1000GB 10000GB HardDriveStorageCapacity Storage Price vs. Hard Drive Capacity 0.1GB 0.01GB 0.001GB $0.1 $0.01 CalculationsperSecond Price Per GB Capacity IBM Tabulator Source: John McCallum @ IDC, David Rosenthal @ LOCKSS Program – Stanford): Kryder’s Law. Time + Ray Kurzweil analysis of multiple sources, including Gwennap (1996), Kempt (1961) and others. Note: All figures shown on logarithmic scale. 146. 146 ...Technology Disruption Drivers = Rising & Cheaper Connectivity + Data Sharing 24% 49% 14% 33% 0% 10% 20% 30% 40% 50% 60% 2009 2010 2011 2012 2013 2014 2015 2016 2017 Penetration,Global Internet + Social Media – Global Penetration Internet Social Media Source: United Nations / International Telecommunications Union, USA Census Bureau. Internet user data is as of mid-year Internet user data: Pew Res
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