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Griffith - Information Architecture Overview

Griffith - Information Architecture Overview

Published in: Business, Technology

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  • 1. Info Architecture & Web 2.0 Design Standards
    Case Studies
  • 2. Design with Clear Intent
  • 3.
  • 4. Clear Layout
  • 5. Clear Layout
  • 6. De-cluttered Logical Flow
  • 7. De-cluttered Logical Flow
  • 8. Demonstrate clear Call to Action
  • 9. Clear Calls to Action
  • 10. Obvious Benefits
  • 11. Obvious Benefits
  • 12. Appropriate Channel Design
  • 13. Appropriate Channel Design
  • 14. Clear and Intuitive Messages
  • 15. Clear Intuitive Messages
  • 16. Sales Funnel Specifics
  • 17. Managing the Sales Funnel
    Methods of acquisition
    PPC Ads, SEO, Video, Email, LeagGen, Affiliate Marketing, Offer based, etc.
    Once there – what’s important?
    Prove you can Add Value
    Qualify Leads with intent
    You want users who are amenable to your message – Its ok for users to self-select opt out
    Monetise towards latter end of the Funnel
    After user sees value and expresses intent
    Push low-cost options in the middle of funnel
    High cost ones at the end of your funnel
  • 18. Customer Lifecycle
    Understand the customer lifecycle
    The various stages of a customer over a timer period
    Create indicators to track their intent
    As they begin to move lag – make sure you target them
    Identify high repeat behaviour
    Identify a common characteristic – and track this
    e.g. have visited more than 3 time and purchase
    Track rising and falling repeat rates
    Have early warning systems in place
    Track repeat rate by media source
    Search Engine, PPC, Banner Ad etc..
  • 19. Customer Lifetime Value
    Segment customers into acquisition channels
    Identify the potential lifetime value per channel
    Identify length of customer lifecycle per channel
    Low cost channels could have shortest lifecycle
    Compare the relative potential value
    Consider: length of lifecycle, potential revenue per Customer
    Allocate money towards higher potential value customers
    By corollary - away from lower potential value customers
  • 20. Understanding “Recency”
    Tracking Recency
    Time since a customer last engaged in a behaviour
    Recency is # 1 most powerful predictor of future behavior 
    Can predict likelihood of purchases, visits, game plays, or “other action-oriented” behaviour
    The more Recent a customer is, the higher their potential value is
    Segment Repeat segment into past and present (30 days)
    Apply a recency filter for real-time view
    Longer a customer has stopped engaging the less likely they are to repeat
    Take adjustive measures to increase in quality recency repeat customers
  • 21. Web 2.0 Design Model
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  • 34. Calls To Action