Social media is expanding at a great rate. People could connect with their friends, families, live far away in just a few moments. They could share the important moments of their life with the people whom they love. But, the most important feature of social media is that people could communicate over a long distance easily.
Sometimes, people often recommend the products to others in social media. We often encounter many people’s status like a new iPhone purchase and experience. But, only these recommendations do not guarantee that the person will buy that product. There are many other factors like the influence of the person recommending that product, the area of interest of that person, etc.
To solve this problem Google has developed a new technology that provides a system and computer-implemented method for pricing product recommendations in a social network.
Why this technology?
The need for this technology arises from the fact that every company wants to increase its sales. Now, in order to do so, they promote the customers to recommend their products to other customers and in return, they offer some kind of discount coupons under referral programs.
But, the big problem arises that how would they know that a particular recommendation would force the other customer to buy the product. If they would offer the discount to every customer that recommend their product, then the company would suffer loss.
In order to solve this problem, Google has developed the technology that uses the computer to create a score of each recommendation on the basis of combining several factors. A computer implemented method include determining the level of influence the user (the one who recommends) has on the social network.
This determination is based on a responsiveness of other users to social activity generated by the user (the one who recommends) in the social network. It correlates the purchase decisions made by other users with social endorsements related to a particular product category.
It is then used to evaluate consumer responsiveness to that particular product category which generates a value for a recommendation of a product in that product category. It then provides that value to a vendor of the product.
How does this technology work?
This technology provides a mechanism to determine the value of a product recommendation provided by any user in the social network based on many factors that represent the likelihood of that recommendation-generating the purchase activity.
Now, a vendor could provide the discount or any gift equal to the determined value of the recommendation to the user who has a particular degree of influence in the social network in exchange for the recommendation of their product.
The system analyzes multiple factors within the social network to determine the value of a recommendation. These factors include the level of influence of the user that is recommending the product, the size of the user’s social graph, the authenticity of the user in making the recommendation, other consumer responsiveness to the product associated with the recommendation and general interest of the users who receive the recommendation in the product.
This technology could also assign some weight to each factor and then use these weight it could calculate the value.
The next challenge for Google would make sure that vendors believe that this system would give the accurate result. The authenticity of the result is the most important factors in the whole system. Google also have to ensure that this system takes all the factor into consideration.
But, there is some product for which the recommendation depends on certain factors more than the other factors. In this case, they would have to use the weight to each factor.