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A System and Approach to enhance E-commerce shopping experience using social media profiles Disclosure Number: IPCOM000247768D
Publication Date: 2016-Oct-06
Document File: 4 page(s) / 60K

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A System and Approach to enhance E-commerce shopping experience using social media profiles

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A System and Approach to enhance E -commerce shopping experience using social media profiles


E-commerce has become the prominent mode of shopping across the world

Lot of focus is given on techniques to improve customer buying experience in a E-commerce system Social media profiles have become one of the the most prominent ways to identify individuals Many mechanisms to link social media profiles and e-commerce shopping sites are already in place The proposed approach uses a combination of e-commerce sites and social media profiles of individuals to provide a enhanced shopping experience for people


Several options to link and extract information from social media profiles and use them in e-commerce sites are already in place
These options are used to enhance the shopping experience of the users which in turn will increase the popularity of e-commerce sites
The problem in this context would be add intelligence to the application to categorize the items where a virtual wearing experience can be provided.

Recommend alternate colors to the user based on the colors extracted from the social media profile pictures of individuals which have received maximum likes
It is assumed that the social media profiles of individuals should have their profile pictures.

More the number of photos of individual available in their social media profile, better will be shopping options that would be provided to the them


Analyzing the user's social account to determine certain parameters like e.g. most Likes/comments when user wears XXX colored T-shirt, Trousers, aviator, dress, locations, etc based on the posts by user and responses generated on those posts by social neighbors of the user.

   Ex: Pictures that you post are important to understand your taste. On top of it, social neighbors can influence which suited you the most of your taste
Deriving further intelligence by analyzing the above combinations with the group the user is associated with. For e.g. Parameters analyzing when with family, when with friends, when at home, in a selfie etc.

Based analyzed output, defining a algorithm based on predictive analysis theorem capitalizing on the data available on users social accounts to provide the user with information about the set of products available on a e-commerce sites which user interacts with to help him select correct products which...