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On Thursday, Amazon launched an exciting community-driven service ‘Spark’ to facilitate online shopping in our country. This feature is believed to have taken inspiration from Instagram and uses the customers’ browsing behavior to provide personalized feeds.

It allows one to post questions, stories, polls, and ideas with hashtags, images just like social networking platforms enabling the users to comment using emoticons (‘smiles’) and react to other posts.

It will enable customers to find content from brands along with community content from selected customers. The community has the ability to reward in the form of badges, smiles, and comments. The company would trend for the browsing and the true shopping behavior to the personalized feed which in return provides a grandeur enhancement for the product discovery offering a community experience.

The feature is also expected to gather different posts similar to Pinterest with the ability to tag different items with images and a commenting technique similar to Instagram. It also has the ability to revolve content around the products which is available through the online marketplace.

This feature will include two tabs, namely, Feed and Explore on the Spark page which will bring the content based on the interests and explore the tabs. This shall allow viewing content based on different categories like Technology and gadgets, women’s style, Food, Drink, DIY art and crafts.

There is a bag icon which is displayed on the Amazon Spark post to ensure the availability of the product on A click on the bag icon to view the list of the products. There is also the view of the products which is available just below the images shared to check on the number of times the images have been viewed.

This platform is made to make it more easy for the people by adding the fun element which will enable the community content and experience more ‘seamless shop-able – Kishore Thota, Director of Customer Engagement, Amazon India

The Spark button needs to be clicked from the Spark option from the left menu of the Amazon app which can be visited automatically from the spark page directly on the web.

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