Methods and systems for ranking leads based on given characteristics

A computer-implemented method comprising:

• scanning, by a first processor of a computer comprising at least two processors, one or more social networking web documents associated with one or more leads within one or more databases and extracting lead information from the one or more social networking web documents, the lead information comprising one or more characteristic values;
• classifying, by the first processor of the computer, the lead information into categories of lead information based on the one or more characteristic values of the lead information;
• upon receiving from a computer of an agent, a selection of a first category of lead information and an attribute of the first category, filtering, by the first processor of the computer, the lead information to obtain a set of filtered lead information comprising only a subset of leads containing the attribute;
• assigning, by the first processor of the computer, a score to each attribute associated with each lead from the filtered lead information based on a measure of how each attribute satisfies a predetermined set of criteria;
• executing, by the first processor of the computer, a machine-learning algorithm technique to calculate a quality score for each lead, wherein the machine-learning algorithm technique is configured to calculate the quality score of each lead by computing a mean score for each lead based on a learning dataset comprising the each scored attribute;
• while the first processor of the computer is executing the machine-learning algorithm, iteratively updating, by a second processor of the computer, the learning dataset based on modified data associated with each lead having a score for each attribute greater than the predetermined set of criteria;
• periodically querying, by the second processor of the computer, the one or more databases to receive inputs on modified data associated with each lead and, in an event that the computer determines that the score of the attributes associated with each lead is changed, adjusting, by the second processor of the computer, the learning dataset;
• ranking, by the first processor of the computer, each lead based on their corresponding quality score, wherein the computer ranks each lead in order of their corresponding implied quality score and a propensity to close a transaction, wherein the computer determines the propensity to close the transaction for each lead based on the one or more characteristic values associated to each lead;
• and
• updating, by the first processor of the computer, a graphical user interface of the computer of the agent with auction information comprising the ranked leads and the quality score.