System and method providing business insights based on cluster success analytics for products based businesses

A system for recommending business factors to a merchant, said system comprising:

• a network trained to identify related merchant-vendor pairs by:
• embedding, by a first encoder, a plurality of merchant descriptions to a vector space to obtain a plurality of merchant vectors, each merchant description corresponding to a vendor;
• embedding, by a second encoder, each corresponding vendor to the vector space to obtain a plurality of vendor vectors;
• calculating a relation metric for each description-vendor pair;
• training a neural network with the description-vendor pairs and the corresponding relation metrics to predict whether a new vendor and a new merchant description are related;
• training the first encoder to embed related merchant descriptions to similar regions in the vector space;
• and
• training the second encoder to embed related vendors to the similar regions in the vector space;
• a computing device configured to:
• receive a request for recommended factors from a user device;
• receive merchant data associated with a merchant from the user device, the merchant data comprising vendor data associated with the merchant;
• embed the merchant data to a vector space to obtain a merchant vector, the vector space comprising a plurality of other vectors associated with other merchants;
• calculate, using the trained network, a relation metric between the merchant vector and a vector of the plurality of other vectors, the vector being associated with a second merchant, the relation metric representing a relation between the merchant and the second merchant;
• analyze the relation metric with a neural network trained to determine whether the merchant vector and the vector of the plurality of other vectors are related;
• and
• responsive to the determining, send merchant data associated with the second merchant to the user device, the merchant data associated with the second merchant comprising business factors data associated with the second business.

A computer-implemented method for recommending business factors to a merchant, said method comprising:

• training a network to identify related merchant-vendor pairs by:
• embedding, by a first encoder, a plurality of merchant descriptions to a vector space to obtain a plurality of merchant vectors, each merchant description corresponding to a vendor;
• embedding, by a second encoder, each corresponding vendor to the vector space to obtain a plurality of vendor vectors;
• calculating a relation metric for each description-vendor pair;
• training a neural network with the description-vendor pairs and the corresponding relation metrics to predict whether a new vendor and a new merchant description are related;
• training the first encoder to embed related merchant descriptions to similar regions in the vector space;
• and
• training the second encoder to embed related vendors to the similar regions in the vector space;
• receiving a request for recommended business factors from a device;
• receiving merchant data associated with a merchant from the device, the merchant data comprising vendor data associated with the merchant;
• embedding the merchant data to a vector space to obtain a merchant vector by:
• detecting stop words in the merchant data associated with the merchant from a pre-defined list of stop words,
• removing the detected stop words from the merchant data associated with the merchant,
• lemmatizing the merchant data associated with the merchant, and
• embedding the lemmatized merchant data to the vector space;
• the vector space comprising a plurality of other vectors associated with other merchants;
• calculating, using the trained network, a relation metric between the merchant vector and a vector of the plurality of other vectors, the vector being associated with a second merchant, the relation metric representing a degree of relation between the merchant and the second merchant;
• determining that the relation metric is above a pre-defined threshold value;
• and
• when it is determined that the relation metric is above the pre-defined threshold value, sending merchant data associated with the second merchant to the device, the merchant data associated with the second merchant comprising business factors associated with the second merchant.