@DaveMcClure @500Startups http://500.co Khazanah Tech
Talk - San Francisco, March 2017 What’s New in Tech?

Dave McClure Founding Partner, 500
Startups 00’s & 10’s: • VC: Founders Fund, Facebook fbFund, 500 Startups • Angel: Mashery, Mint.com, SlideShare, Twilio, Wildfire, SendGrid • Marketing: PayPal, Simply Hired, Mint.com, O’Reilly 80’s & 90’s: • Entrepreneur: Aslan Computing (acq’d by Servinet/Panurgy) • Developer: Windows / SQL DB consultant (Intel, MSFT) • Engineer: Johns Hopkins‘88, BS Eng / Applied Math

• What is 500? –
$330M AUM / 4+ main funds / 10+ microfunds – 150 people / 25 languages / 20 countries – 1800+ Companies / 3000+ Founders / 200+ Mentors – Investment, Accelerator, BizDev, Marketing, Events, Education – Community + Content + Conferences • 1800+ Co’s / 60+ Countries – Twilio (NYSE: TWLO) – Credit Karma – Grab – Wildfire (acq GOOG, $350M) – MakerBot (acq SSYS, $400M) – Viki (acq Rakuten, $200M) – Behance (acq Adobe, $150M) – Simple (acq BBVA, $117M) – Sunrise (acq MSFT, $100M) – SendGrid – TalkDesk – Intercom – Udemy – Ipsy 500 Startups Global Seed Fund & Startup Platform

2017: What’s New in Tech?
• Startups: Cheaper, Faster, Bigger, Better • VCs: Lots of Little Funds, Lots of Little Bets • Corp: “How do we become VCs?” • Govt: “How do we create Silicon Valley?” • Old Tech: E-Commerce, Marketplaces, SaaS, Education, Healthcare, FinTech • New Tech: AI, AR, VR, Blockchain, etc

Dinosaurs vs. Cockroaches LEAN Startup:
Simpler, Faster, Cheaper, Smarter 1990-2000 ”Big, Fat, Dinosaur Startup” • Sun Servers • Oracle DB • Exodus Hosting • 12-24mo dev cycle • 6-18mo sales cycle • <100M people online • $5-10M Series A/B • Sand Hill Road crawl 2017 ”Lean, Little, Cockroach Startup” • AWS, Google, PayPal, FB, TW • Cloud + Open Source SW • Lean Startup; 3-90d dev cycle • SaaS / online sales • >3B people online • <$100K incub + <$1M seed • $1-3M Seed / Series A • Angel List global visibility

Startup Platforms: Search, Social, Mobile,
Pics, Video, Voice, Msgs

Startup Risk Reduction Concept Early
Customer Usage Scalable Customer Acquisition [about to be] Profitable Unit Economics Scalable Profitable Business Functional Prototype PRODUCT MARKET REVENUE Exit? When 500 Likes to Invest

2017: What’s New in Tech?
• Startups: Cheaper, Faster, Bigger, Better • VCs: Lots of Little Funds, Lots of Little Bets • Corp: “How do we become VCs?” • Govt: “How do we create Silicon Valley?” • Old Tech: E-Commerce, Marketplaces, SaaS, Education, Healthcare, FinTech • New Tech: AI, AR, VR, Blockchain, etc

Football “West Coast Offense” Baseball
“MoneyBall” Basketball “3-pt revolution” Venture Capital 500 Startups “Lots of little bets” 500 Strategy: MoneyBall for Startups Re-inventing a 50-year old sport

Q: How Many Series A
Startups Turn Into Unicorns? (~1%)

Data from ~600 companies from
500 Startups Funds I + II (2010 - 2013 cohorts) $1-10M Q: How Many Startups to Get 1 Unicorn? Unicorns 50:1 | Centaurs 20:1

The Lean Investor Make lots
of little bets: • Start with many small “experiments” • Filter out failures + small wins • Double-down on stuff that looks like it’s working • Incubation: $0-100K (“Build & Validate Product”) • Seed: $100K-$1M (“Test & Grow Marketing Channels””) • Venture: $1M-$10M (“Maximize Growth & Revenue”)

Investment Stage #1: Product
Validation + Customer Usage • Structure – 1-3 founders – $0-$100K investment – Incubator environment: multiple peers, mentors/advisors • Test Functional Prototype / “Minimum Viable Product” (MVP): – Prototype->Alpha, ~3-6 months – Develop Minimal Critical Feature Set => Get to “It Works! Someone Uses It.” – Improve Design & Usability, Setup Conversion Metrics – Test Small-Scale Customer Adoption (10-1000 users) • Demonstrate Concept, Reduce Product Risk, Test Functional Use • Develop Metrics & Filter for Possible Future Investment

Investment Stage #2: Market
Validation + Revenue Testing • Structure – 2-10 person team – $100K-$1M investment – Syndicate of Angel Investors / Small VC Funds • Improve Product, Expand Customers, Test Revenue: – Alpha->Beta, ~6-12 months – Scale Customer Adoption => “Many People Use It, & They Pay.” – Test Marketing Campaigns, Customer Acquisition Channels + Cost – Test Revenue Generation, Find Profitable Customer Segments • Prove Solution/Benefit, Assess Market Size • Test Channel Cost, Revenue Opportunity • Determine Org Structure, Key Hires

Investment Stage #3: Revenue
Validation + Growth • Structure – 5-25 person team – $1M-$10M investment – Seed & Venture Investors • Make Money (or Go Big), Get to Sustainability: – Beta->Production, 12-24 months – Revenue / Growth => “We Can Make (a lot of) Money!” – Mktg Plan => Predictable Channels / Campaigns + Budget – Scalability & Infrastructure, Customer Service & Operations – Connect with Distribution Partners, Expand Growth • Prove/Expand Market, Operationalize Business • Future Milestones: Profitable/Sustainable, Exit Options

2017: What’s New in Tech?
• Startups: Cheaper, Faster, Bigger, Better • VCs: Lots of Little Funds, Lots of Little Bets • Corp: “How do we become VCs?” • Govt: “How do we create Silicon Valley?” • Old Tech: E-Commerce, Marketplaces, SaaS, Education, Healthcare, FinTech • New Tech: AI, AR, VR, Blockchain, etc

The Unicorn “Hedge” https://500hats.com/welcome-to-the-unicorn-hedge-2fd3c6b50f89 TREND:
Public companies outsourcing research by investing, partnering in startups & funds, buying innovation (aka Unicorns) as a hedge against the value of their own stock.

Startups + Corporates 18 Startups:
• Speed • Talent (People) • Product / IP Corporations: • Customers • Budget / Money

Corporate/Startup Innovation Framework Partnerships Investments
M&A Outcomes Strategies People Product Customers Dealflow Accelerators PR & Sponsorships Competitions & Events Silicon Valley Outposts Investing in VC funds

2017: What’s New in Tech?
• Startups: Cheaper, Faster, Bigger, Better • VCs: Lots of Little Funds, Lots of Little Bets • Corp: “How do we become VCs?” • Govt: “How do we create Silicon Valley?” • Old Tech: E-Commerce, Marketplaces, SaaS, Education, Healthcare, FinTech • New Tech: AI, AR, VR, Blockchain, etc

Critical Ecosystem Factors • Optimism
& Belief (“Silicon Valley”) • Mentorship + Education (Knowledge) • Universities + Companies (People) • Capital, Legal, Finance (Infrastructure) • Engineering + Design / UX (Product) • Platforms + Distribution (Customers) • Online Payments (Monetization) • IPO / M&A Market (Exits)

Building Startup Ecosystems

Q: How many VC funds
needed to build a startup ecosystem? • USA: ~800 VC funds; 2.5 per 1M ppl • China: ~700 VC funds; 0.5 per 1M ppl • UK/EU: ~100 VC funds; 0.25 per 1M ppl • Other: <10-50 funds; <0.1 per 1M ppl

A Brief History of US
Venture Capital • first VC funds: ARDC, JH Whitney (1946) • SBICs / Small Business Investment Act (US, 1958) • Shockley -> “Traitorous Eight” -> Fairchild (1958) -> Intel (1968) • Sutter Hill (1964), Venrock (1969), Kleiner, Sequoia (1972) • ERISA laws + “prudent man rule” (1974, 1978) • Pension Funds in VCs: $39M (1977) -> $570M (1978) -> $4B (1989) • Tech Explosion: 80’s, 90’s, 00’s • Microsoft (1975), Apple (1976), Oracle (1977), Sun (1982), Cisco (1984), Amazon (1994), eBay (1995), Yahoo (1995), Google (1998), PayPal (1998), LinkedIn (2002), Facebook (2004), Twitter (2006)

2017: What’s New in Tech?
• Startups: Cheaper, Faster, Bigger, Better • VCs: Lots of Little Funds, Lots of Little Bets • Corp: “How do we become VCs?” • Govt: “How do we create Silicon Valley?” • Old Tech: E-Commerce, Marketplaces, SaaS, Education, Healthcare, FinTech • New Tech: AI, AR, VR, Blockchain, etc

500 Investment Themes Sectors CONTENT/CREATION
DATA SCIENCE/AI CLOUD/SAAS/B2B E-COMMERCE EDUCATION ERP/PRODUCTIVITY FINTECH HEALTH HR/RECRUITMENT IoT/HARDWARE MARKETING TECH/CRM REAL ESTATE/RETAIL SERVICES SOCIAL/COMMUNICATION TRAVEL * * *

Fintech still going strong; 19
Fintech Unicorns valued at $58.7B globally Source: CBInsights-

Over 220 unique investors in
fintech in 2010. Now, there are over 900. Over 70 strategics and corporates invested in blockchain startups. Source: CBInsights

2017: What’s New in Tech?
• Startups: Cheaper, Faster, Bigger, Better • VCs: Lots of Little Funds, Lots of Little Bets • Corp: “How do we become VCs?” • Govt: “How do we create Silicon Valley?” • Old Tech: E-Commerce, Marketplaces, SaaS, Education, Healthcare, FinTech • New Tech: AI, AR, VR, Blockchain, etc

500 Startups is one the
most active early-stage frontier technology Investors IoT - SecurityIoT - ToysIoT - Health IoT - HomeIoT – Enterprise 3D PrintingRobotics / AutoVR / AR ConnectivityAI IoT -Lifestyle Drones / Aero

>$2.2B invested in 156 VR
deals in 2016 Source: Digi-capital: http://www.digi-capital.com/news/2016/07/record-2-billion-arvr-investment-in-last-12-months/#.V9rRVD4rI9c Popular Investment categories: • VR/VR video • Hardware • Services and studios • Gaming • Apps • Advertising/marketing • Developer tools and distribution Top 10 most funded VR/AR startups 1. Magic Leap ($1.39 billion) 2. Razer ($125M) 3. NextVR ($115.5M) 4. OTOY ($101M) 5. Jaunt ($100M) 6. MindMaze ($118M) 7. Blippar ($99M) 8. Oculus ($93.55M) 9. LensAR ($91.1M) 10. Meta ($73M)

Apple, Google, Facebook acquiring VR/AR
startups Source: CBInsights https://www.cbinsights.com/blog/top-acquirers-ar-vr-ma-timeline/ Active VR/AR acquirers • Apple (3 acquisitions) • Google (2 acquisitions) • Facebook • Autodesk • GoPro Notable acquisitions • Facebook acquires Oculus (VR headset) for $2B • ALPHAEON acquires LensAR (laser cataract treatment) for $59M • Google acquires Skill & Hackett ((design studio) • Google acquires Thrive (VR Audio) • Apple acquires Flyby Media (mobile AR app developer) • Apple acquires PrimeSense (interactive device) • Apple acquires Metaio (AR) • Qualcomm acquires Kooaba (cloud base image recognition)

2017 VR Investment Focus Source:
Goldman Sachs Global Investment Research Development building blocks & tools • VR input • VR search • VR Social • VR payment Industries • Health • Gaming • Education • Real Estate • Retail • Live Events • Engineering • Military

Apple, Google, Intel, Microsoft, Salesforce,
Amazon acquired 18 AI companies in 2016 Source: CBInsights

2017 Investment Focus & Predictions
Artificial Intelligence for Verticals Source: CBInsights With the rise of big data & AI, startups applying machine learning algorithms to solve enterprise problems: • Health • Finance • IoT • Education • Commerce • Security In area of sales, marketing, CRM, customer service, legal, HR, etc.