Organizing big data for boosting retail business

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With the unprecedented rise in the amount of internet data, and the subsequent rise of the online shopping industry, it is not unnatural that there has been a concerted effort towards the organization of data available over the internet. The success of a retail business depends largely on how well it presents itself to its customers. Presentation of data comprises a bunch of things ranging from easier user-navigation to useful user-information. While a photographer maybe searching for a backpack for a new camera and lenses, a student may well be searching for a similar item to keep stationery - the question is, "how would you identify the two from one another so as to make yourself more meaningful to each user". The secret lies in intelligent and efficient data organization.

The working model for the retail industry is quite simple: collection of as much internet data as possible and organizing it in an efficient manner, mining that data to extract what is useful to the industry, intelligent data analysis to develop user preferences, and a constant check on more incoming data to keep information as up-to-date as possible. Data organization is typically done by:

  • Organizing the users based on user activity, particularly what the users search for and what they eventually buy
  • Sampling users based on products, age, sex, region, etc. to derive relationships between different subsets
  • Maintaining relational tables between different products to give the users more and better product suggestions

Narrowing the focus allows the retail businesses to perform better since they can pinpoint specific areas that need improvement - this way the chances of getting more buyers becomes better. This shift in focus towards the organization of online data for retailing is a paradigm for medium and large scale companies, and the small scale retail businesses are making constant efforts to catch up to this technology. The importance of data organization is at its peak, and is rising even further with each day.

This article in particular talks about how video surveillance cameras are being used to analyze customer's gestures, behaviour when they come to a store, which part of the store they spend more time in , what do they end up buying and when. They also relate this to external factors like the weather outside, the location of the store etc.
Video surveillance has been there since a long time. Computer programs are designed to process this. Using it to analyze customer gestures and relating it their shopping decisions is a great example of using available information in an innovative manner to organize their business.