Recommended content generation and distribution

A system comprising:

• one or more processors configured to:
• receive external data from one or more data sources;
• process the external data to generate processed data, wherein the processed data is stored at a server;
• determine available items of a first client, wherein each item has item attributes;
• retrieve user transactions associated with a targeted user having user attributes including a user identifier, wherein each user transaction comprises an item identifier and a user identifier, and wherein the user transactions comprises one or more transactions involving a second client different than the first client;
• pair each user attribute of the targeted user with each item attribute of the available items;
• determine a user mean purchasing frequency for each of the pairs of user attribute and item attribute;
• retrieve one or more user attribute values of the targeted user;
• for each of the one or more user attribute values, retrieve global transactions of a population of users that have a user attribute value that is equal to the each of the one or more user attribute values;
• for each of the global transactions, determine a standard deviation and a global mean purchasing frequency for each of the pairs of user attribute and item attribute from each of the global transactions;
• calculate a relevance score for each of the pairs of user attribute and item attribute based at least on the user mean purchasing frequency, the global mean purchasing frequency and the standard deviation;
• determine an item relevance score, for each available item, based upon one or more relevance scores that match an item attribute of the available item;
• and
• select one or more available items of the first client based upon relevance scores of the available items.

A non-transitory computer-readable medium having instructions stored thereon, wherein the instructions comprise:

• instructions to receive external data from one or more data sources;
• instructions to process the external data to generate processed data, wherein the processed data is stored at a server;
• instructions to determine available items of a first client, wherein each item has item attributes;
• instructions to retrieve user transactions associated with a targeted user having user attributes including a user identifier, wherein each user transaction comprises an item identifier and a user identifier, and wherein the user transactions comprises one or more transactions involving a second client different than the first client;
• instructions to pair each user attribute of the targeted user with each item attribute of the available items;
• instructions to determine a user mean purchasing frequency for each of the pairs of user attribute and item attribute;
• instructions to retrieve one or more user attribute values of the targeted user;
• instructions to for each of the one or more user attribute values, retrieve global transactions of a population of users that have a user attribute value that is equal to the each of the one or more user attribute values;
• instructions to for each of the global transactions, determine a standard deviation and a global mean purchasing frequency for each of the pairs of user attribute and item attribute from each of the global transactions;
• instructions to calculate a relevance score for each of the pairs of user attribute and item attribute based at least on the user mean purchasing frequency, the global mean purchasing frequency and the standard deviation;
• instructions to determine an item relevance score, for each available item, based upon one or more relevance scores that match an item attribute of the available item;
• and
• instructions to select one or more available items of the first client based upon relevance scores of the available items.