The location factor

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presentation for marketeers at a Datlinq event.How location and geography may provide insights and understanding of consumer behavior, how consumers are contributing themselves to better data, and how by analysing location we are able to make better decisions.

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  • From the ground it is really hard to see where you are(the piece of the puzzle is actually there)
  • Instead feedback on the planned actions of citizensWill this determine future behaviour of consumers?
  • Understanding (changed) behaviour
  • http://www.youtube.com/watch?v=1XBwjQsOEegWhat is it you see?
  • Location as a new lens
  • Location vs geography
  • How much something is soughtBy whomTo what degreeHow frequentlyWhereWhen
  • Where gives insight
  • Location gives you better inisight into changed behaviour
  • The role of the consumer
  • http://www.newscientist.com/article/dn19200-twitter-mood-maps-reveal-emotional-states-of-america.html
  • http://andsynchrony.net/projects/generating-utopia/
  • There is a need to deliver understanding by plugging the online experience andinteraction into offline data. To make sense of social interactive and mesh it with point of sale, customer loyalty and merchandize data. Location analysis and GIS provides a new lens on the search and social stream. A way to combine the new social analytics with traditional approaches to marketanalysis, demand planning, assortment and brand sentiment.GIS can be a platform to integrate social web information into business applicationsby more fully exploiting the value of local in location. It offers different ways to connect retailers with their customer and consumer across the spectrum of socialinteraction and help them make sense of it quickly.
  • Consumers contribute data
  • New insights with location analytics
  • How to wouwmarketeers
  • Great image from our friends at Esri UK
  • http://coolmaps.esri.com/Starbucks/
  • The location factor

    1. 1. The Location Factor Less is more, Datlinq 26 september 2013 Jan Willem van Eck Esri Nederland
    2. 2. Inzicht in (veranderend) gedrag
    3. 3. Combinatie van vele bronnen van data • big en small data • (on)gestructureerd • tijd & plaats • doel: inzicht krijgen, besluiten nemen, aanbod verbeteren Locatie als een nieuwe lens
    4. 4. Locatie: waar we zijn Geografie : context & begrip Ruimtelijke relaties tussen fenomenen Locatie en geografie
    5. 5. Locatie maakt inzicht mogelijk, maar eerst: • Verbinden • Verduidelijken • Informeren • In context plaatsen • Communiceren Locatie vs geografie
    6. 6. Want is a measure – What is sought – How much – By whom – To what degree – How frequently – Where – When Behoeften meetbaar maken
    7. 7. Voorkeuren en relaties in beeld brengen • Search • Potential • Opportunity • Gap • Aspiration Behoeften meetbaar maken
    8. 8. • Trends & Needs • Market Potential • Origins & Destinations • Frequency • Recency • Volume • Duration Waar zorgt voor inzicht
    9. 9. Behoeften matchen met andere marktdata • Demographics • Psychographics • Lifestage • Intents within, outside of and across organizations Waar zorgt voor inzicht
    10. 10. Inzicht in (veranderend) gedrag - door locatie
    11. 11. De rol van de consument
    12. 12. Space-Time Patterns - Annual Searches across a whole year - unfiltered Searches filtered by time of day (T.O.D.) Morning Afternoon Evening Night
    13. 13. Social Search Origins Search events, unfiltered for single day Highlights clusters, hotspots and spatial errors
    14. 14. Searches by Category Search categorized by category type Colors identify sentiments, trends and geographic patterns Comparative analysis highlights gaps, demand and opportunity
    15. 15. Search Intensity Comparative and overlay analysis can identify concentrations Grid colors represent demographics factored by frequency The heatmap expresses variations in search density and dynamics
    16. 16. One Input, Many Outputs Behavioral and sentiment effects generate different patterns Longitudinal analysis helps bring new understanding to SoLoMo data Consumer activity can seen in context of dynamics and trends
    17. 17. De rol van de consument - eigen bijdrage
    18. 18. Locaties analyseren, nieuwe inzichten
    19. 19. Analytics Lifecycle
    20. 20. Loyalty data Klant interactie Concurentie analyse Verzorgingsgebieden Eigenschappen outlet - Eigen data Combineren
    21. 21. Demografie Segmentatie Brand affiniteit Markt potentie Pyschographics Bestedingspatronen - Markt data Verrijken
    22. 22. Informeren
    23. 23. Locaties analyseren, nieuwe inzichten - en betere besluiten Inzicht in (veranderend) gedrag - door locatie De rol van de consument - eigen bijdrage
    24. 24. Final thoughts
    25. 25. How it’s made • Thinking, reading, research • Slides and guidance by Simon Thompson , Esri, Redlands • Feedback by Martin Kamphuis, Frits van der Schaaf, Esri, Nederland • Tools: Mindjet, Evernote, good old Powerpoint, Slideshark.

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