ENBIS Challenge 2009
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ENBIS Challenge 2009 Thomas Mühlenstädt Institut für Mathematische Statistik und PowerPoint PPT Presentation


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ENBIS Challenge 2009 Thomas Mühlenstädt Institut für Mathematische Statistik und industrielle Anwendungen. New Configurations: 4 GB RAM 2.4 GHz 17‘ Screen. Configuration:. Further comments on Configurations: No differences between stores

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ENBIS Challenge 2009 Thomas Mühlenstädt Institut für Mathematische Statistik und

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Enbis challenge 2009 thomas m hlenst dt institut f r mathematische statistik und

ENBIS Challenge 2009

Thomas Mühlenstädt

Institut für

Mathematische Statistik und

industrielle Anwendungen


Enbis challenge 2009 thomas m hlenst dt institut f r mathematische statistik und

New Configurations:

4 GB RAM 2.4 GHz 17‘ Screen

Configuration:

  • Further comments on Configurations:

  • No differences between stores

  • 864 possible combinations

  • No empty class

  • Costumers prefer „medium“ configurations


Enbis challenge 2009 thomas m hlenst dt institut f r mathematische statistik und

Price / Revenue:

Price minimum requirement:£300

15“, 4h Battery, 1 GB RAM, 1.5GHz, 40 GB HD

Promotional sales activities:

August / September:

Increase of daily sales volume: 100 %

Increase of daily revenue:86 %

December:

Increase of daily sales volume: 78 %

Increase of daily revenue:70 %

Store:No influence

Time:Decreasing trend,

depending on memory

Discount?:5 stores granted discount

of approx 30% during

March, June,

September, December

Second and Third Jump:

Marketing, Price?

New Configurations:

4 GB RAM 2.4 GHz 17‘ Screen


Enbis challenge 2009 thomas m hlenst dt institut f r mathematische statistik und

Spatial topics:

  • Map of London

  • Location of Stores:

  • „big“ stores

  • „medium“ stores

  • „small“ stores

  • population density plot

  • Conclusions:

  • Some stores might be better

  • Location not always good

Revenue per day in each store:

Big differences between stores


Enbis challenge 2009 thomas m hlenst dt institut f r mathematische statistik und

Conclusions:

  • Configurations:

    • Offer more hard ware

    • Also „smaller“ specifications

  • Price / Revenue:

    • Discounts not effective,

    • Revenue increased two times

  • Store locations:

    • Concentrate on „big“ shops

    • Some stores might perform better

    • Some stores are not located very good

  • Use of data:

    • More connotation


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