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Retail 2.0 - a New Paradigm for Location Analysts
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Retail 2.0 - a New Paradigm for Location Analysts


Presentation by Andy Thompson of Wendover Consulting Group and Steven Feldman of KnowWhere to the Society for Location Analysis.

Presentation by Andy Thompson of Wendover Consulting Group and Steven Feldman of KnowWhere to the Society for Location Analysis.

Published in Real Estate , Business , Technology
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  • 1. Retail 2.0 - A new paradigm for location specialists Steven Feldman KnowWhere
  • 2. Location still matters – or does it?
    • “ The dream of electronic commerce has become a reality in today’s wired world, where physical geography no longer presents a barrier to retailers or consumers – and shopping has never been easier.  ”
    • Nielsen
  • 3. Agenda
    • Web 2.0
    • Generations
    • Impact of online shopping
    • Bricks ‘n Clicks
    • New demographics
    • Impact on retail location strategies
    • How will we find our customers of the future?
    • Future data creation and analytical techniques
  • 4. Web 2.0
    • Rich user experience
    • User participation
    • Dynamic content 
    • Openness, freedom
    • Collective intelligence
    “ creating network effects through an " architecture of participation ," and going beyond the page metaphor of Web 1.0 to deliver rich user experience ” Tim O’Reilly
  • 5. Generations
  • 6. Why Web 2.0 matters to Retailers
    • 16m UK households have internet access
    • Online sales £55bn in last 12 months!
    • Sales growth 25-30%
    • 30-50 year olds lead online spending
    • Generation Y are the high value customers of the future
    • Main impact today is in comparison goods but tomorrow ……?
  • 7. Categories – who is buying online and where?
    • Books & music
      • Losing share to online
      • Higher in remote rural areas
    • Clothing & footwear
      • Catalogues go online and upmarket
      • Mix of rural areas and prosperous suburbs, urban professionals and areas of high ethnicity
    • PCs/Games consoles & software
      • Losing share rapidly
      • 15-30s boys
      • Asian Communities
    • Household Goods & Appliances
      • Frequently need delivery
      • Online winning where large retailer not close
      • Source CACI
  • 8. Where is hurting? Source CACI A mixture of affluent suburbs, some prosperous urban areas and an affluent rural hinterland
  • 9. OnLine vs InStore
    • OnLine
    • Price
    • Convenience
    • Wider Range
    • Comparison
    • Customer Reviews
    • Product information
    • InStore
    • Want to evaluate
    • Immediacy
    • No shipping costs or waiting at home for delivery
    • Trusted Brand
    • Knowledgeable Sales people
  • 10. OnLine vs InStore
  • 11. Bricks ‘n clicks can beat online only
    • Combining an online presence with physical outlets may offer the best option
      • Leverage core competencies
      • Supplier and distribution networks
      • Brand equity
      • Consumer trust
      • Economies of scale
  • 12. Bricks ‘n clicks can beat online only
  • 13. Finding the e-consumer
    • Target
      • 30-50s
      • May come from minority groups
      • E-literate
  • 14.  
  • 15. Location still matters
  • 16. RETAIL 2.0 A New Paradigm for Location Specialists
    • Andy Thompson
  • 17. The World of the Customer
  • 18. Impact on Retail Location Strategies
    • Here are three possible future states....
      • Retail catchment areas will be much smaller in size
      • Customers will reject brand loyalty in preference to price/convenience trade-off
      • Purchase behaviour will become more complex and transaction patterns less predictable
    • We need to find or create new data and analytical techniques to understand the customers and markets of the future
  • 19. WHERE 2.0
    • Electronic generation of mapping and location technology
    • Location enabled mobile devices will become the norm in the future
    • By 2012 at least 18% of phones will be smartphones .
  • 20. Crowd Sourced Data
    • Been around for centuries!
      • C19 th Oxford English Dictionary
    • WEB 2.0 provides the structure for collaboration
      • e.g.
    • Debate around coverage, currency and quality
    • What about crowd sourced retail data ?
  • 21. Pervasive Location
    • Path Intelligence
      • Tracking individuals using mobile phone signals
    • Footpath TM Technology
    • Retail applications
      • Rental valuations and tenancy mix
      • Shopper flow management
      • In centre marketing
      • Behaviour analysis
    Copyright 2007 Path Intelligence Ltd
  • 22.  
  • 23. Pervasive Location
    • Geo-location Services
      • Yahoo Fire Eagle
      • Mozilla Geode
      • Google Geolocation API
    • Don’t need a GPS service
    • Detection of “where” people are interacting with the web
    • Location intelligent Web 2.0 services
      • Sales and marketing offers.... not new anymore....
      • Security (location verification)
      • True “location-tailored” content
      • Intelligent Near Field Communication services
  • 24. Historical Data Analysis?
    • “ When you rely on historical data, its much harder to tease out causation”
    • Ian Ayres, Super Crunchers - “ How Anything Can Be Predicted”
    “ Marketing is concerned with recent past and near future.... and human beings are remarkably consistent in their behaviour over short periods” Sean Kelly, Customer Intelligence - “From Data to Dialogue”
  • 25. Random Sampling
    • Sir Ronald Fisher
    • Randomisation test
      • Study of errors in data with a non-normal distribution
    • Gold standard in medical research for testing success of treatments
    • Why aren’t we using randomisation?
      • We have the resources
      • We can create new data
  • 26. Randomisation in Action
    • Divide your customers randomly into groups, treat them differently and measure the responses
    • Sample size is key
      • If the sample is large enough we can assume they are statistically identical
      • Our intervention can then be measured purely - the “treatment effect”
    • Capital One – proactively intervenes in the market through randomised experiments
    • Today we have data which has random characteristics but are we treating it as random data?
  • 27. New Techniques in Predictive Modelling
  • 28. Generalised Linear Model
  • 29. Generalised Additive Model
  • 30. GAMs in Performance Modelling
  • 31. We need to act now!
    • “ Statistics are like a lamp-post to a drunken man.... more for leaning on than illumination”
    Lets make data analytics the currency of our organisations and the first activity of decision making not the last!
  • 32. Location still matters
  • 33. Thank You Steven Feldman [email_address] http:// GIScussions Slides at http:// Andy Thompson [email_address] Slides at