PS070 Digital Trends Presentation

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    PS070 Digital Trends Presentation - Presentation Transcript

      • Digital Trends
      • London, January 2009
      • www.ianjindal.com
      • www.internetretailing.net
      • Digital Trends
      • London, January 2009
      • www.ianjindal.com
      • www.internetretailing.net
      • Digital Trends
      • Context
      • Retail and Christmas
      • Social
      • Data
    1. 1. Context
    2. 1. Context
    3. 2. Christmas
      • £4.7bn online over Christmas: 14% YOY
      • November - highest YOY of 26%
      • Growth is slowing in ecommerce but still above offline
          • eCommerce - 16% for H2 (IMRG)
          • Offline - 0% for H2 (source: ONS)
        • Christmas Day: 3.8m (14% down), but sales 21% higher at £102m.
          • Customers bargain-hunting
        • Pre-Christmas sales and January started immediately after last posting date!
        • Boxing day busiest of year (down 5% YOY)
        • John Lewis Christmas day traffic - twelve times higher than 2007
        • PC World, Currys, Dixons - 30-40% increase (mainly large TVs)
      2. Christmas
      • Product. Price. Promise
      2. Christmas 118%
    4. 3. Social
      • Reviews becoming standard
      • User “stories”, not just ratings
      • 78%: “customer recommendations are the most credible form of advertising” (Nielsen)
      3. Social
      • Top style-setters become “Mavens”
      • Based on page views AND product clicks
      • Customers become sales-people
      • Social networks become retailers
      3. Social
      • Reviews becoming standardUser “stories”, not just ratings78%: “customer recommendations are the most credible form of advertising” (Nielsen)
      • Configure all panels, materials, colour
      • Preview your custom shoe
      • nikeid.nike.com
      3. Social
      • Configured option
      • Buy “your” show
      • Feedback to Nike on trends, colours
      • May put into production
      3. Social
    5. 4. Data
      • Data evolution
        • accurate
        • enriched
        • meta
        • actionable
        • mashed
        • semantic
        • autonomous & predictive
    6. 4. Data
      • Data evolution
        • accurate
        • enriched
        • meta
        • actionable
        • mashed
        • semantic
        • autonomous & predictive
    7. 4. Data
      • Metadata
        • Segmentation and metadata for increased relevance.“Behaviour” is useful metadata - if you can capture it - ‘ignore ratio’?Capture offline as well as online - warranties...
    8. 4. Data
      • Metadata
        • New services
        • Links to commerce
    9. 4. Data
      • “ Doing” not “viewing”
        • Making Social Networks “transactional”You can “do”, not just “view”From web to desktopWeb to web
    10. 4. Data
      • “ Doing” not “viewing”
        • Making Social Networks “transactional”You can “do”, not just “view”From web to desktopWeb to web
    11. 4. Data
        • Google - hCard format added to Search results.One click to add the result to your address book.Could do the same with calendar items, or recommentations
    12. 4. Data: personal and placeful and propagated
    13. 4. Data
        • More is More - the network effect
        • Network ‘knows’ more than any individual component or contributor
        • ‘ ambush’ marketing?
    14. 4. Data
        • Attention Profiling Markup Language - www.apml.org
        • Beyond ‘personal’: interchange and exchange value of behaviour
    15. 4. Data Show us some APML!!
    16. 4. Data Location, location, location (and mobile)
    17. 4. Data: epiphenomena and ESP
    18. 4. Data Number of freely connected nodes where exchange cost is near zero Business analysis Services Mashups Predictive Responsive and self-configuring ESP? Hyperdata Epidata Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+
    19. 4. Data Number of freely connected nodes where exchange cost is near zero Business analysis Services Mashups Predictive Responsive and self-configuring ESP? Business Web Social Web 1 Social Web 2 Networked Web Hyperdata Epidata Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+
    20. So?
      • Customers - cynical, savvy, disloyal, discriminating, demanding
      • Market - slowing, saturated, competitive
      • Insights - partial, expensive, temporary
      • CRM, VRM - just the start. Rounded behaviour generated rounded, multivariate, multi-co-ordinated, oddly-permissioned data
      So?
      • Proposition - value, clear, consistent - must “ring true”
      • Use don’t own - build on ‘free’
      • Invest in data - create, collect, exchange, borrow, give, sell, rent... combine
      • Time and place - every time, every place, everywhere: selling and serving by mobile in time and place
      • Look and learn - success is temporary: learn and respond to customers rather than ‘telling them’ to comply
      • Standout - good time to achieve distinctive and profitable position.
      So what?
      • Thank you
      • Digital Trends
      • London, January 2009
      • www.ianjindal.com
      • www.internetretailing.net

    + Ian JindalIan Jindal, 10 months ago

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