Recommendation in Retail

So you go to a shop you see that a specific brand of Deodorant and Bathing bar are bundled as a product and have been displayed with a specific discount and you hand pick it with immense happiness (??) and satisfaction of a good deal. How does the shop keepers come to know about this? Intuition, Analytics, Case Based Reasoning, Pattern matching, etc.,

It could be Walmart, Target, Macys, TESCO or even a small self-owned retail outlet its important that they understand the customer/consumer behavior correctly to make good profit end of the day. Lets not think that its particularly useful in retail industry its very much important for Services based organization also to understand the consumer behavior.

For the sake of ease of understanding and moving towards practical aspects of such implementation we will try and understand some of the factors which would or could influence recommendation.

  • Demography (City, Locality, Country,etc.,) (Transactions)
  • Culture(Transactions)
  • Product mix based past sales history(Transactions)
  • Social recommendations (Twitter, Facebook, posts) (Social Analytic/NoSQL/Semi Structured)
  • Product Reviews(Blog/Review/Semi Structured Data)
  • Post-Sales experience (Transactions)

The challenge would be to related these data and to make good recommendation through the system in a very short span of time to influence customer buying decisions. In my next post we will try to evaluate some of the data sets available in the internet for the further experiments on the same.

My aim would be to understand and implement a recommendation system or at least arrive at the right steps for making an recommendation system which would be reliable and can handle the complexity involved in data.

Keep waiting for next post.

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One thought on “Recommendation in Retail

  1. Pingback: Connecting to Mysql via SQOOP – List Tables | My exploration in data analytics

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