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Connected Living Rooms 2010.05.20

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A research study focusing on demand factors driving consumers to adopt connected tv devices in their living rooms. Research methods include interviews, primary and secondary research.

A research study focusing on demand factors driving consumers to adopt connected tv devices in their living rooms. Research methods include interviews, primary and secondary research.

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  • >Speaker: MS
  • >Speaker: MS
  • >Speaker: VH
  • >Speaker: VH
  • >Speaker: VHTechnology Maturation 2005: Windows Media Center 2005 (UR2)2006: XBMC 2.02007: Content Library: Hulu Founded Netflix Launches Watch Instantly2008: Netflix on Xbox – Ease of Installation2009: Processing Power:Yahoo! Connected TV, compels high end CE manufacturers to put more processing power into the TV2009: Blue-Ray Players below $1002009: Net-Enabled DevicesYoutube?Create the StandardHarvest the StandardThe Model is: create hardware to get out thereThen move to softwareAlignment of Device/Service.TC manufacturers sell devices consumersContent companies provide services to consumersLook at Chesbrough. 
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  • >Speaker: MSMatt says, I wanted to stop here and just remind us what companies we wanted to look at. We can go over some ohe analysis, but I think the primary research has some interesting tidbits.
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Connected Living Rooms 2010.05.20 Connected Living Rooms 2010.05.20 Presentation Transcript

  • Connected Living Rooms: Analysis of User Preferences and Market Trends
    Melody Akhtari
    Vincent Huang
    Matt Salazar
    May 19, 2010
    Faculty Advisor: Pablo Spiller
    UC Berkeley, Haas School of Business
  • 2
    Table of Contents
    • Executive Summary 3
    • Context, Definitions, and Objectives 4
    • Industry and User Trends 5
    • Industry Highlights 6
    • User Demographics & Trends 9
    • Analysis 13
    • Research Methodology 14
    • Competitive Landscape 15
    • SWOT Analysis 17
    • Primary Research 21
    • Industry Professionals 22
    • Connected Living Room User Interviews 23
    • Quantitative User Survey Analysis 24
    • Findings & Implications 29
    • Hypothesis Inventory 30
    • Hypothesis & Implications 31
    • Market and Users: Implications 44
    • Suggested Further Research/Steps 47
    • Inquiries, Contact Info 48
    • Appendix 49
    • A: Sample Survey 50
    • B: Regression Analysis 52
    • C: User Interview Guide 54
    UC Berkeley, Haas School of Business
  • Executive Summary
    Objectives:
    Map both demand and supply side of the connected living room landscape
    Identify the user preferences of lead users and predict trends in the mass market landscape
    Primary & Secondary Research:
    Mapping demand and supply-side:
    Qualitative interviews of industry leaders throughout the value chain: content producers, chip manufacturers, software, and hardware providers
    Identifying lead user preferences:
    Qualitative interviews of connected living room users
    Quantitative surveys of US lead users
    3
    UC Berkeley, Haas School of Business
  • Context, Definitions, and Objectives
    Context:
    Users are beginning to use devices and services to consume content from the Internet. There has been an explosion of companies vying for adoption of their device/service.
    Definitions:
    ACS Living Room: Content connected via Antenna, Cable, Satellite. Content is viewed in the living room.
    Connected Living Room: Content sourced from the Internet. Content is viewed in the living room.
    Content: Videos
    Production Value: User generated content (UGC), Independent, Mainstream (e.g. movies, TV shows)
    Length: Short-Form (<10 min), Episodic (10-60 min), Feature-length (60+ min)
    Content Acquisition: Recording, downloading, and streaming of content
    Content Platform: Content providers or content aggregators
    Devices: Companies whose core competencies are to create and sell physical products
    Devices include: Connected Blu-Ray players, connected TVs, game consoles, OTTB
    Services: Companies whose core competencies are to provide content from the Internet
    Services include: Content aggregators, content broadcasters, content platforms, content applications
    Our specific objectives include:
    Identify drivers and challenges for organizations within the content ecosystem
    Determine US lead user preferences for types of content consumed
    Provide predictions and recommendations for organizations in the content ecosystem
    4
    UC Berkeley, Haas School of Business
  • Industry and User Trends
    Industry Highlights
    User Demographics
    User Trends
    5
    UC Berkeley, Haas School of Business
  • Industry Highlights: A Complicated Value Chain
    UGC
    Indie Producer
    Broadcast Network
    Cable Network
    Antenna
    Cable
    Satellite
    Component Device
    STB
    OTTB
    Content Aggregator
    Content Platform
    Internet Broadcaster
    PC
    Consoles
    Internet Provider
    TV Manufacturer
    Product Co.
    Fred, Shay Carl
    hitRECord, Prom Queen, The Guild
    ABC, CBS, Fox, NBC
    Discovery, TBS, ESPN
    Comcast, CableVision, TimeWarner
    DirecTV, DISH
    DVD, Blu-Ray Player
    Scientific America, Motorola
    (Over The Top Box)
    AppleTV, Roku, TiVO
    Clickr.com, Boxee
    Hulu, Justin.TV, Netflix, Vudu
    Koldcast TV
    AT&T, Comcast, Verizon, CableVision, TimeWarner
    Samsung, LG, Vizio, SONY
    PS3, Wii, Xbox 360
    Roof, Rabbit Ears
    New Content and delivery channels have created multiple paths for consumption.
    20th Century Fox, ABC, Disney, Endemol
    Desktop, Laptop
    Traditional to Traditional
    Tradition to New
    New to Trad/New
    UC Berkeley, Haas School of Business
    6
  • Connected Living Rooms: On the Brink of Growth
    2004Content Connects to PCs
    Windows Media Center 2005
    2008Ease of Installation
    Netflix on Xbox
    2006PCs Connect to TVs
    XBMC 2.0
    Revenue
    2009Jump in Device Processing
    Yahoo! Connected TVs
    Blu-Ray Plays drops below $100
    2007New Content Platforms
    Hulu.com founded
    Netflix launches Watch Instantly
    2010Growth in Devices/Services
    Walmart.com buys Vudu
    Boxee gains 1M users
    Time
    Stage:
    Strategy:
    Growth:
    Gain Market Share
    Mature:
    Incremental
    Innovation
    Decline:
    Harvest Profits
    Emerging:
    Innovate and Disrupt
    7
    Source: Henry Chesbrough.
    Open Innovation Business Models
    UC Berkeley, Haas School of Business
  • Customer Demand and Implementation: Key Challenges and Obstacles
    There are many challenges and obstacles in creating the perfect connected experience.
    UC Berkeley, Haas School of Business
    8
    Challenges in Consumer Demand
    Industry
    Challenges
  • Online Video Has Arrived For All
    Online Video has become mainstream; 62% of online adults have used the Internet to watch or download video, nearly double since 2006.
    On a typical day, 36% of adult Internet users watched videos online,up from 30% in 2008.
    Source: RBC Capital Markets (September 2009)
    9
    UC Berkeley, Haas School of Business
    80%
    68%
    50%
  • User Trends: Increasing Demand forInternet Delivered Content on the Television
    Over a third of Netflix subscribers consume “Watch Instantly” content on something other than a computer monitor
    The increasing demand for Internet connectivity on the television is bolstered by consumers under 44.
    10
    UC Berkeley, Haas School of Business
  • User Trends: Internet Delivered Content is Both a Compliment and Substitute to Current Video Consumption
    Substitute: Upward trend of cord cutters (1.6M over 3 years)but still small to total market size (101M subscribers)
    Compliment: Upward trend in total video consumption
    11
    UC Berkeley, Haas School of Business
  • User Trends: Significant Questions Remain to Video Content Business Models and Economics
    44.2% of Baby Boomers say they’re most likely to give up paying a subscription fee for TV service over any other subscription-based service (RBC, September 2009)
    Advertising:Support amongst users but revenue has not materialized
    Payment: Only moderate support for online content purchases
    Source: eMarketer (February 2010)
    Source: eMarketer (April 2009)
    12
    UC Berkeley, Haas School of Business
  • Analysis
    Research Methodology
    Competitive Landscape
    SWOT Analysis
    13
    Haas School of Business
  • Research Methodology
    14
    UC Berkeley, Haas School of Business
  • Scoping: Identifying Key Players
    Competitive landscape analysis of all companies offering a “10-Foot” living room experience
    Narrowed list by focusing on:
    Recognizable and identifiable firms
    Firms recognized as industry leaders by users and industry experts
    Significant install base
    15
    UC Berkeley, Haas School of Business
  • Competitive Landscape: It’s Crowded at the Top
    16
    UC Berkeley, Haas School of Business
  • Analysis of Key Players: AppleTV
    17
    UC Berkeley, Haas School of Business
  • Analysis of Key Players: Boxee
    18
    UC Berkeley, Haas School of Business
  • Analysis of Key Players: Roku
    19
    UC Berkeley, Haas School of Business
  • Analysis of Key Players: WMC
    20
    UC Berkeley, Haas School of Business
  • Primary Research
    Industry Professionals Interview List
    Connected Living Room User Interviews
    Quantitative User Survey Analysis
    21
    UC Berkeley, Haas School of Business
  • Roku
    Brian Jacquet
    Director, Corporate Communications
    D-Link
    Dan Wong
    Director, Product Management
    Trident Microsystems
    Jackson Huang
    Sr. Director Marketing
    Industry Professional: Interview List
    Devices
    Netflix
    Richard Ezekiel
    Director, Partnerships
    Vudu
    Edward Licthy
    EVP, Strategy and Content
    Boxee
    Andrew Kippen
    VP, Marketing
    Services
    Endemol
    Jerry Kowal
    SVP Digital Media
    Koldcast TV
    Daniel Samuels
    CEO, Koldcast TV
    App Content Developer
    Rob Spectre
    Boxee A
    Content
    Providers
    22
    UC Berkeley, Haas School of Business
  • Users Interview Methodology
    Individuals obtained from additional closing question requesting a phone conversation to better explore users’ habits
    Questions formed around hypotheses: thoughts on downloading and streaming, high definition, obtaining content, consumption patterns
    20-30 minute phone conversations with eleven US-based individuals
    Interviewees included 44-year old female multi-solution user, a 25-year old male college student using Boxee, and a computer engineer using TivoHD with his wife and two young children, among many others.
    Conversations centered on in-depth insights based on users’ homeset-up, preferences and behavior, consumption patterns, and personal media libraries.
    23
    UC Berkeley, Haas School of Business
  • Survey Methodology
    Length: 10 Questions
    Time: Survey Ran from 4/22/10 to 5/6/10
    Forums Surveyed:
    AVSForum.com
    CNET.com
    TheGreenButton.com
    Mac-Rumors.com
    TivoCommunity.com
    Boxee Forums
    Results: 140 Valid Responses
    24
    UC Berkeley, Haas School of Business
  • Survey Topline
    Who are they?
    67% consider themselves early adopters
    55% describe themselves as technology experts
    What is their setup?
    85% have multiple computers in their household
    77% have connected a computer/laptop to their television
    70% have created or modified software/hardware to fit their technological needs
    25
    UC Berkeley, Haas School of Business
  • Demographics Chart
    26
    UC Berkeley, Haas School of Business
  • Time Spent Watching Chart
    27
    UC Berkeley Haas School of Business
  • Number of Devices Used
    48% of respondents use more than two solutions to consume digital content
    28
    UC Berkeley, Haas School of Business
  • Findings & Implications
    Hypothesis Inventory
    Hypothesis Testing & Implications
    Market Trends & Implications
    29
    UC Berkeley, Haas School of Business
  • Hypothesis Inventory
    User Behavior
    Users do not watch short-form content on their TVs
    Control over experience and setup is critical to power users
    Users predominantly like new and current content.
    Where Does Content Reside?
    People do not care whether content is streamed or downloaded.
    Users would rather build a digital library for their content
    Influencers Towards Connected Living Rooms
    HD Quality (720p or better) will drive users to connected living rooms
    The desire to watch content on the living room screen is positively correlated with length
    Users use one single device in the connected living room
    Content Discovery
    Users want social recommendations for content discovery
    Users want a content recommendation engine
    30
    UC Berkeley, Haas School of Business
  • Hypothesis 1: The (Un)importance of Short-Form
    Hypothesis: Users do not watch short-form content on their TVs
    Results: True
    • Less than 10% of users would like watch short-form content on their TVs.
    • The majority of users desire mainstream content.
    • “I'd rather watch the full movie. I don't really stream clips, but if it's something I really, really, really want to watch, then I'll watch a clip. I'll watch post-game interview/highlight clips. Value-added things that are in addition to the whole show.”
    • “Clips are worthless, I want to watch full episodes of things. It's like ‘Hey, here's a great scene from an episode I can't watch!’”
    Implications:
    • Most users do not find the offer of short-form video compelling. In few occasions where short-form is value-add, short-form video is not a strong selling point for connected devices. users feel that if they’re going to watch something on their television, it might as well be more significant than a short video.
    • Linkages to short-form content libraries, like YouTube, do not provide significant utility to the user.
    31
    UC Berkeley, Haas School of Business
  • Hypothesis 1: The (Un)importance of Short-Form
    32
    UC Berkeley, Haas School of Business
  • Hypothesis 2: Flexibility and Control of Experience
    Hypothesis: Control over experience and setup is critical to power users
    Results: True
    • “I have a large-screen TV in the living room, PCs in the office, and both wireless & wired networking at home for my own media library. Entertainment is consolidated in a hand-made console, with an HTPC and AV receiver with surround sound.”
    • “Any TV viewing is either from download or Netflix stream or in-mail DVD. That's the only way we watch anything. We have a TV with a WDTV Live box in the main living room downstairs with mostly cartoons for our younger two kids. We have a living room upstairs, where my husband and I watch Lost and network shows on the Xbox 360. We only watch the .avis up there because it won't play other formats like .mkvso we watch a lot of SD. Then in my ‘Me’ room I watch old movies from archive.org using a PC with WMC on it. It’s important to be able to access content off the network all over the house.”
    Implications:
    • Power users will invest more resources (time and money) to perfect their set-up. Most users believe that there is not a one-stop solution in the market; consequently, they will invest time and money to customize their experience through multiple platform efforts.
    • Given the fragmented preferences, a one-stop solution remains elusive and serves as a large barrier to mass-market adoption.
    33
    UC Berkeley, Haas School of Business
  • Hypothesis 3: Desire for Fresh Content
    Hypothesis: Users predominantly like new and current content
    Results: Uncertain
    • The type of content drives consumption of new versus cataloged content.
    • Users followed new episodic content and appreciate cataloged movie content.
    • “I prefer new TV shows, and movies I prefer to watch what I haven't seen. If it's an old movie I haven't seen that's fine. My wife wanted to watch Soylent Green the other day; since we haven't seen it, I don't mind watching it.”
    • It's a mixture. I've found that I'm watching shows that have been off the air for a long time that users have previously suggested to me. I'm watching Red Dwarf right now because it's on Netflix and someone suggested it to me. It's easy to find. It's a mixture, I watch half new shows and half old shows.
    Implications:
    • To consumers, movies are seen as timeless, while TV shows have a steeper half-life.
    • User profiles are complex as they carry over taste preferences from traditional media to online content. However, availability of content complicates what they can consume. Further research is recommended.
    34
    UC Berkeley, Haas School of Business
  • Hypothesis 4: Streaming Vs. Downloading
    Hypothesis: Users do not care whether content is streamed or downloaded.
    Results: True
    • While users exhibit preferences, the proportion of people preferring streams is not statistically different from the proportion preferring downloads (p=.254)
    • Streaming or downloading is a means to an end, and not an end unto itself. The preference for streaming/downloading is driven by other attributes such as content quality and content availability.
    • For Millenials, there is a significant preference for downloading over recording (p=.047) but not for streaming over recording (p=.187)
    • For Boomers, the preferences are reversed, where there is a significant preference for recording over downloading (p=.028)
    • “I just want to watch my show, it doesn't matter where it comes from.”
    Implications:
    • Given the indifference to streaming or downloading, organizations distributing content should message on performance.
    35
    UC Berkeley, Haas School of Business
  • Hypothesis 5: Building Digital Libraries
    Hypothesis: Users would rather build a digital library for their content
    Results: It depends on the content
    • Users prefer to digital libraries for content that are either favorited or consumed multiple times.
    • “We don't add any more drives to our media library. We keep all our kids' content because they want to watch it over and over, but for our current shows/movies, we download-watch-delete.”
    • "Yes there's a difference between streaming and downloading. Downloaded stuff is stuff I look forward to seeing and I can't find anywhere (like making a run to blockbuster, it's special). Streaming, to me, is more like flipping through channels; it's less choices but it's instant gratification. Streaming is for content that I have a bit of interest in, but I don't look forward to that content as much as I do to content that I have downloaded onto my computer, which I've gone out of my way to get.
    Implications:
    • We thought power users would want to own their shows and movies, but many people mostly want to watch their content, and then move on. They’ll only want to keep or own those shows/movies they highly value, their favorites.
    36
    UC Berkeley, Haas School of Business
  • Hypothesis 6: HD as a Driver
    Hypothesis: HD Quality (720p or better) will drive people to connected living rooms
    Results: False
    • HD content (p=.358) does not significantly raise the likelihood someone will stream content to their television.
    • "Yes, HD is very important to me. I would say I wouldn’t sacrifice quality for variety, but I do it now since Netflix's on demand isn't as high quality as I would like, so yes we sacrifice for the ease of instant playback. But I prefer quality, which is why we rent Blu-ray discs as well."
    • "I like HD, but only care a 'medium' amount for it. For TV shows, what I have right now is enough (480p and stereo surround on Hulu and PlayOn). But when I buy a movie, it should only be on Blu-Ray unless it's super rare or super cheap. If I'm buying something for my collection, it needs to be the best.”
    Implications:
    • While consumers show a strong preference towards higher quality content, content selection takes precedence. More succinctly, consumers are going to watch what they want to watch even if its not available in HD picture quality.
    37
    UC Berkeley, Haas School of Business
  • Hypothesis 6: HD as a Driver (Cont.)
    38
    UC Berkeley, Haas School of Business
  • Hypothesis 7: Correlation of Place and Length
    Hypothesis: The desire to watch content on the living room screen is positively correlated with length
    Results: False
    • On a whole, no significant correlation, no significant difference in likelihoodorwatching short form content over medium or long form content on the television.
    • Caveat: Boomers have a significantly stronger desire to watch Internet-delivered episodic content on their televisions (p=0.023) when compared to other generations.
    Implications:
    • Length and quality are not key drivers to whether users consume content via connected living rooms.
    • Overall consumption is the single largest driver to whether users consume via connected living room experiences.
    39
    UC Berkeley, Haas School of Business
  • Hypothesis 8: Single Solution Connected Experiences
    Hypothesis: Users have one single device in the connected living room.
    Results: False
    • 48% of respondents use more than 2 connected living room solutions to consume digital content (this is in addition to a computer/laptop), 14% of respondents use more than 3 connected living room solutions
    Implications:
    • No one-stop integrated solution to consume digital content current exists. To increase market share, companies will need to support multiple use-cases or convince users to change their behavior onto a consolidated platform.
    40
    UC Berkeley, Haas School of Business
  • Hypothesis 9: Social Discovery
    Hypothesis: Users want social recommendations for content discovery
    Results: False
    • Relative to other features, social discovery is significantly less important than most other features (p=.00) such as availability of mainstream content, HD picture quality content, and discovery from a recommendation engine.
    Implications:
    • Despite being in the Web 2.0 era where social discovery is becoming ubiquitous, connected living room platforms should not be distracted with these type of features that rank orders of magnitude lower than most desired feature.
    41
    UC Berkeley, Haas School of Business
  • Hypothesis 10: Recommendation Engines
    Hypothesis: Users want a content recommendation engine.
    Results: True
    • Preferences for a recommendation engine is larger than recommendations from friends (p=.00) but is significantly less important than mainstream content or HD picture quality (p=.00)
    Implications:
    • Algorithms and machine learning are crucial skills platform owners will need going forward. Recommendation engines should be used as tools to help users navigate expansive content libraries.
    • It is intriguing that in the current era of social and peer discovery, recommendation engines have a significantly higher preference ranking over other forms of discovery. Further research in this area is advised.
    42
    UC Berkeley, Haas School of Business
  • Hypothesis 10: Recommendation Engine
    43
    UC Berkeley, Haas School of Business
  • Market and User Trends: Findings & Implications
    The concept of a digital locker in the cloud is still very foreign. Social validation will be a key driver in helping users accept a digital locker.
    Implication: Companies will need to create user profiles to display content in “virtual shelves” when purchased from the cloud. These shelves are public and enable the user to broadcast their taste preferences and purchases to peers.
    Video streaming will supersede downloading only when HD (720p or higher) content is available for streaming.
    Implication: Content platform companies should significantly invest in optimization their distribution systems to deliver HD quality content without any initial buffering.
    There is little room for new content platforms.
    Implication: The content platform is crowded. New entrants have extremely high barriers of entry. Unless new entrants can deliver exclusive content or unparalleled user experience, new entrants should enter through acquisition. Existing companies should focus on a market share strategy.
    44
    UC Berkeley, Haas School of Business
  • Market and User Trends: Findings & Implications
    Physical device product lifecycles, while shortened, will continue to be much longer than software service lifecycles.
    Implication: Companies within the connected living room space will need to be extremely agile to keep up with its competitors. Moving to the cloud will enable companies to quickly iterate and innovate.
    Analytics will serve as the catalyst to incentivizing digital content distribution.
    Implication: Create infrastructure to collect, synthesize, and act upon data. Companies that can best serve analytics to content owners will be best positioned to find new models to monetize the content.
    While many players will build and provide an “apps” platform, in the long run, these platforms will be undifferentiated.
    Implication: Exclusive content and UI will be key differentiators for companies. Applications platforms will be will be a baseline requirement for connected living room devices.
    45
    UC Berkeley, Haas School of Business
  • Market and User Trends: Findings & Implications
    In the short term, connected Blu-Ray players are best positioned to have the best connected living room experiences.
    Implication: Blu-Ray devices contain both the necessary processing power and price point for consumers. Device manufacturers should seek strategic partnership with content platforms to deliver an integrated device/service.
    The connected living room will drive increased consumption of independent content
    Implication: While mainstream content will remain mainstream, connected living rooms encourage the long-tailed consumption of content. Given the initial explosion of options, UI will be a critical component of organization and discovery.
    46
    UC Berkeley, Haas School of Business
  • Suggested Further Research/ Future Steps
    47
    We chose to focus on intrinsic user behavior and preferences
    Potential next steps and opportunities for future research:
    Consumer tastes on “Ownership” and how these preferences will translate with cloud based streaming services.
    Further understanding of discovery preferences from recommendation engine and social network.
    Map user preferences along specific product features. This study focused on intrinsic user behaviors and did not seek to correlate user behaviors with specific product features.
    Examination of developing business models and economic trends for video content.
    Create quantitative analysis of findings from the Market & User Trends: Findings and Implications section. Trends were were derived qualitative interviews with industry professionals.
    Analyze consumer preferences for new versus cataloged content.
    Examination of developing business models and economic trends for video content. Monetization and understanding consumers willingness to pay was not within the scope. However, interviews indicate that many players throughout the value chain are deeply interested in this area.
    UC Berkeley, Haas School of Business
  • For Inquiries, Contact Us
    Melody Aktari, BS 2011
    melodyakhtari@berkeley.edu
    @iMelody
    Vincent Huang, MBA 2011
    vincent_huang@mba.berkeley.edu
    @huangv
    Matt Salazar, MBA 2011
    matt_salazar@mba.berkeley.edu
    @mattsalazar
    48
    UC Berkeley, Haas School of Business
  • 49
    Appendix
    A: Sample Survey
    B: Regression Analysis
    C: Sample User Interview Guide
    UC Berkeley, Haas School of Business
  • Appendix A: Sample Survey
    50
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  • Appendix A: Sample Survey
    51
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  • Appendix B: Regression Analysis
    52
    Haas School of Business
  • Appendix B: Regression Analysis
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  • Appendix C: User Interview Guide
    54
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