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CrowdAnalytix Ideation Challenge: Cracking the Code of Online Consumer


 
  
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This contest is for e-commerce lovers and here feature engineering will be a key focus. Your familiarity or experience with the retail industry will come in handy. This contest runs until Jan 18, 2013.


Online consumer CrowdAnalytix Ideation Challenge:
Cracking the Code of Online Consumer

This contest will run till 18 January 2013. Top 6 submissions will receive USD 400 each. Its a contest for e-commerce lovers and a first of its kind wherein feature engineering will be a key focus. Your familiarity or experience with the retail industry will come in handy in solving the problem. Looking forward to your participation.

Description
Online retailers face an uphill task of driving consumer loyalty. Catering to the needs of consumers in a proactive manner is never easy. But, it all starts with understanding how consumers make their purchase decision and what motivates them to buy product(s).

Client is an online retailer in the US operating across multiple product categories. For this contest, Client is interested in knowing how to use visit level data to understand consumer and visitor behavior. This will aid the client optimize their marketing decisions and enable them to target consumers better.

Skills Required:
Anyone can participate in this contest. But it requires knowledge of the e-commerce industry and consumer purchase behaviors. Any hands-on experience using widely used e-commerce tracking platforms like Google Analytics, Magento, Zencart, Virtuemart, Volusion etc. will also be handy in meeting the objectives.

Data includes

  • Customer demographics
  • Transactions (includes page visits, product clicks etc.)
  • Orders
  • Product information
Objective of the contest:
Objective of this contest is to answer specific questions on how to leverage data available through e-commerce platforms to help the client make effective marketing decisions for consumer targeting. In this contest you'll use your knowledge of e-commerce data and the one provided for illustration to identify and derive features that can be used in modeling visits and purchase behaviors.

Any raw data is of limited use unless data is converted in to features. Feature creation is a critical step in the modeling process and it brings to fore hidden intelligence in the raw data that may not be readily exposed unless derived

Learn more and participate at
www.crowdanalytix.com/contests/ideation-understanding-customer-purchase-behavior-for-an-online-retailer/



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