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System and methods improvised to Analyze the Missed Hit Info for increasing hit ratio.

IP.com Disclosure Number: IPCOM000247544D
Publication Date: 2016-Sep-15
Document File: 3 page(s) / 31K

Publishing Venue

The IP.com Prior Art Database


System and methods improvised to Analyze the Missed Hit Info for increasing hit ratio and further improving hit to purchase ratio.

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System and methods improvised to Analyze the Missed Hit Info for increasing hit ratio .

We live and breathe in our business via customer care and relationships. There's been a natural gravitation to the Internet of Things/Internet of Everything, As a seller, I get the info about who browsed or added my product in the cart and is yet to purchase. However the seller does not have any information on number of internet users who hovered over the link and finally decided to access the website.

Moreover, such hovered data can be of the purchasers interest as well. Thus, this data can be stored in some fashion and used on users search requests or used via prompt mechanisms, etc
Proposal is pretty novel in terms of storing and analyzing the hovered information to extend and improvise on HIT ratio rather than a HOVER OVER action by the user. This hovered identification would be useful for the business as well as individual users.


Provision 1:

Record and store the internet crawling of users hovered components over the web pages.

Provision 2:

Manage and analyze the hovered details using business intelligence to increase component access mode. e.g. from hovered to hit / click.


Usecase 1:

A e-commerce site say ECOM1 has huge list of products on their site. These products have been listed by huge number of vendors who approach the site to host their product. As stated in the problem statement, today this site / vendor can easily determine which user has clicked on which product, (s) how many number of times, what user has selected as his WishList, what user added / removed from the cart, etc. To say it more straight, these sites today are capable of tracking all the users actions which user has opted via a CLICK mode. But, there are numerous sites which display information on HOVER. HOVER is another interesting area for a site user / surfers. Internet shopping spreading widely has increased number of users who like the product but instead of click on the the product, they hover over it and check the details which they wish, like, price, size, make, magnified picture, etc. When the user moves away after hovering (without clicking), this is a LOSS of business for the product owner in most of the cases. A click on the product increases the chance of the user to buy it as against a hover, its a universal acceptable method. But now what?

Solution is here: We propose a method by which our system would keep a track of all the hovered information by a user over a site. This hovered information would be tracked by the server as well as the client so as to benefit the users and the vendors. Once this hovered information is captured in the repository, the analysis would be performed based on numerous factors starting from the user who hovered, to why user didn't click. Lets take a example. User is surfing the ECOM1 site. User hovers over a Shoe (S1) and leaves page. Now this information would be captured ana analyzed. Analysis c...