The Quantified Self Market Overview and Proprietary Financial Intelligence Note: this is an adopted presentation of one given at the SVB Quantified Summit in Boston on April 3, 2014
Contents Quantified Self Defined Key Drivers Wearable Technology Software & Analytics Augmented Reality Summary #svbqs April 3, 2014
Quantified Self: Defined Products or services that use technology to extract and record data from everyday activities with the goal of providing information and insight that helps users to understand or improve personal behavior.
Quantified Self: Acceleration CONSUMER BEHAVIOR Focus on selfimprovement and general wellness TECHNOLOGY ADVANCES Sensors, smartphones, bluetooth low energy, smart watches, wearables The confluence of several key factors has driven the acceleration of this young, but rapidly growing sector MOBILE Tech-savvy, Mobile-centric population SOCIAL Connectivity to social networks, gamification
Quantified Self: Hype Curve Expectations Mass-Market Wearables Mass-Market Software Niche-Market Wearables Analytics Software Note: circle size indicates relative size of markets The Quantified Self shows great promise but is still in the early stages of maturity, adoption, and social application Technology Trigger Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Peak of Inflated Expectations Time
Quantified Self: Hype Curve Mass-Market Wearables Expectations Mass-market wearables have led the way in Quantified Self development and adoption Technology Trigger Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Peak of Inflated Expectations Time
Wearable: Acceleration Mobile Integration Metcalfe s Law Moore s Law Ubiquitous Computing Advances in cost and performance of technologies, network effects of mobile adoption, and other factors accelerate massmarket wearables Design Focus Battery/Sensor Technology
Wearable: Market Leadership 2013 Wearable Device Sales Jawbone 19% All Other 3% Nike 10% Fitbit 68% Mass wearables is a highly-saturated market, dominated by a few major players. Incumbents have a significant advantage over new startups with regard to sales, marketing, and distribution channels. In fact, since this presentation was first given, even Nike chose to wind-down its FuelBand.
Mobile Hardware: Replacement History of mobile devices provides a lesson for Quantified Self massmarket wearables namely that one device can do the job of many
160 Wearable: Cannibalization Risk ipod vs. iphone Device Sales Units Sold (mm) 120 80 40 0 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Release of the first-generation iphone marked the beginning of a stark turnaround in ipod sales
Garmin PND Sales (mm) Wearable: Replacement Risk Smartphone vs. Personal Navigation Device Sales 3 2.5 2 1.5 1 0.5 120 100 80 60 40 20 iphone Sales (mm) 0 2007 2008 2009 2010 2011 2012 2013 Advances in mobile device hardware enable mobile applications to replicate some functionality of a wearable using existing hardware. 0
Invested Capital Multiple 12x 10x 8x 6x 4x 2x x Wearable: Shifting Values Pre-2011 Median IC Multiple Pre-2011 Median IC 5.3x 2.6x 2.5x 9x Post-2011 Median IC Multiple Post-2011 Median IC 11.3x <$5M $5M-$20M $20M-$50M $50M+ Revenues (mm) As evidence of saturation, post-2011 wearable technologies required more investment to reach revenue thresholds and had lower valuations compared with previous years. 5.1x 120 100 80 60 40 20 0 Invested Capital (mm)
Quantified Self: Hype Curve Niche-Market Wearables Expectations Smartphone data collection isn t feasible in every situation (e.g. smart swim goggles), providing opportunity for niche wearables Technology Trigger Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Peak of Inflated Expectations Time
Mobile Hardware: Niche Catalyst Smartphones aren t a replacement, but rather a catalyst for acceleration in niche-wearables enabling the storage and analysis of personal data collected by niche-wearable devices
180 Niche Wearable: Stability iphone vs. Camera Device Sales 150 Unit Sales (mm) 120 90 60 30 0 2007 2008 2009 2010 2011 2012 2013 iphone adoption negatively impacted sales for point-and-shoot cameras, however the more niche DSLR camera sales remained stable.
Niche Wearable: Crowdfunding $500,000 Crowdfunding Campaigns (Q2-2013 to Q4-2013) Crowdfunding $ $400,000 $300,000 $200,000 $100,000 $- 0 500 1000 1500 2000 2500 3000 Number of Backers Quantified Self startups are flocking to crowdfunding platforms, particularly as a source of pre-order funding for new hardware applications, which also demonstrate consumer demand prior to potential venture investment.
Quantified Self: Hype Curve Mass-Market Software Expectations As hardware adoption increases data collection, software is there to store and analyze it Technology Trigger Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Peak of Inflated Expectations Time
Software: Acceleration Social Media Integration Device Agnostic Smartphone Hardware User model promotes Viral Growth Analytics Data recording and storage Growth in software has naturally followed the first wave of hardware development, but viral growth in socialization of information and gamification should be major accelerants of this segment
Software: Device Agnostic Mobile software is device agnostic applications can utilize data from any wearable, creating a cross-platform device for users
Invested Capital (mm) 45 40 35 30 25 20 15 10 5 0 Software: Value Accretion Total Invested Capital $2.77 Value per User $3.85 $4.00 < 5M 5M-10M 10M-50M Users(mm) When the community using a particular software grows, so does its value to investors (and users). This should accelerate as the adoption of Quantified Self technologies increases. $4.50 $4.00 $3.50 $3.00 $2.50 $2.00 $1.50 $1.00 $0.50 $0.00 Value Per User
Network Effect and Big Data Network effects occur when applications reach a critical mass of users, and social connectivity becomes a driver of engagement. Existing software solutions aggregate mass amounts of data, which creates opportunity for a new wave of health analytics companies.
Quantified Self: Hype Curve Analytics Software Expectations Though in the very early stages, the next major push will come from big data analytics Technology Trigger Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Peak of Inflated Expectations Time
Analytics: Next Accelerant Big data analytics represents a tremendous growth opportunity because the tools that will be used already exist and have been implemented in other sectors (e.g. digital advertising).
Augmented Reality: The Internet of Everything Data will eventually be collected on most everything, sent to, stored, and analyzed in the cloud, and have recommendations sent back to users to enhance real-time decision-making
Summary Mass-market wearables led the way in the development and early adoption of Quantified Self technologies, but shows limited opportunity for new startups moving forward because of market saturation and replacement/cannibalization risks that have already become evident. Because smartphones aren t able to collect data in every situation, we still see acceleration potential of niche wearables (e.g. smart swim goggles). Unlike with mass-wearables, smartphones will further enable not replace niche wearables devices. We are also optimistic about growth acceleration in software, due to the continual improvements in hardware enablement and the viral growth of socialization and gaming. As adoption of Quantified Self technologies spreads and data collection increases, we see the next big push coming from data analytics which has already been a major factor in other markets, such as digital advertising.
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