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PS070 Digital Trends Presentation

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"Digital Trends" presentation given to the first meeting of the eConsultancy.com 'Alumni' evening, with people from the eConsultancy MSc courses and the Graduate Academy and other guests.

"Digital Trends" presentation given to the first meeting of the eConsultancy.com 'Alumni' evening, with people from the eConsultancy MSc courses and the Graduate Academy and other guests.

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PS070 Digital Trends Presentation 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. Context
  • 1. Context
  • 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%
  • 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
  • 4. Data
    • Data evolution
      • accurate
      • enriched
      • meta
      • actionable
      • mashed
      • semantic
      • autonomous & predictive
  • 4. Data
    • Data evolution
      • accurate
      • enriched
      • meta
      • actionable
      • mashed
      • semantic
      • autonomous & predictive
  • 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...
  • 4. Data
    • Metadata
      • New services
      • Links to commerce
  • 4. Data
    • “ Doing” not “viewing”
      • Making Social Networks “transactional”You can “do”, not just “view”From web to desktopWeb to web
  • 4. Data
    • “ Doing” not “viewing”
      • Making Social Networks “transactional”You can “do”, not just “view”From web to desktopWeb to web
  • 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
  • 4. Data: personal and placeful and propagated
  • 4. Data
      • More is More - the network effect
      • Network ‘knows’ more than any individual component or contributor
      • ‘ ambush’ marketing?
  • 4. Data
      • Attention Profiling Markup Language - www.apml.org
      • Beyond ‘personal’: interchange and exchange value of behaviour
  • 4. Data Show us some APML!!
  • 4. Data Location, location, location (and mobile)
  • 4. Data: epiphenomena and ESP
  • 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+
  • 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+
  • 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