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Submitted By: Bhanu Pratap Singh 10609079 Bithika Bishesh 10609080 Chetna Kohli 10609081 Deepshikha Jain 10609082 Divya Bhatia 10609083 Garima Sharma 10609084 Gaurav Passy 10609085
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[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Tools & Measures  :     1. RFID (radio-frequency identification)   Identifies data and information  through radio signals on the tags  implanted on the products which helps to gather a regular information about the buying pattern of the customer.   2. Neural Networks using KDD (Knowledge Discovery in Databases) Identifies patterns and information in the past data to predict the future sales and requirements of weekly demand on  items in a supermarket.    
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
In the future the Swarm-Moves could be extended to answer many other questions that could also help retail stores in their decision making process: 1. What is the effect of products’ individual factors on impulse shopping? 2. What is the most prominent factor to increase impulse shopping in real-time? 3. Should we impose ’cross categorization’ to increase sales in a given time? Or should we impose ’uniform categorization’ to help the customer to find a product and to save time? 4. What is the most common path of customers? 5. What would be the effect of adding shelves and/or product in sales of supermarket?
 
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[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object]
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[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
 
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[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
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herd behavior consumer behavior

  • 1. Submitted By: Bhanu Pratap Singh 10609079 Bithika Bishesh 10609080 Chetna Kohli 10609081 Deepshikha Jain 10609082 Divya Bhatia 10609083 Garima Sharma 10609084 Gaurav Passy 10609085
  • 2.
  • 3.
  • 4.
  • 5. Tools & Measures :     1. RFID (radio-frequency identification)   Identifies data and information  through radio signals on the tags  implanted on the products which helps to gather a regular information about the buying pattern of the customer.   2. Neural Networks using KDD (Knowledge Discovery in Databases) Identifies patterns and information in the past data to predict the future sales and requirements of weekly demand on items in a supermarket.    
  • 6.
  • 7.
  • 8.
  • 9. In the future the Swarm-Moves could be extended to answer many other questions that could also help retail stores in their decision making process: 1. What is the effect of products’ individual factors on impulse shopping? 2. What is the most prominent factor to increase impulse shopping in real-time? 3. Should we impose ’cross categorization’ to increase sales in a given time? Or should we impose ’uniform categorization’ to help the customer to find a product and to save time? 4. What is the most common path of customers? 5. What would be the effect of adding shelves and/or product in sales of supermarket?
  • 10.  
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.  
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.  
  • 27.
  • 28.  
  • 29.  
  • 30.  
  • 31.
  • 32.
  • 33.
  • 34.
  • 35.  
  • 36.  

Notas del editor

  1. Even though the cheaters pattern of purchasing was increasing similarly there was a corresponding increase in purchases from list C