Systems and Methods for Data Mining of Historic Electronic Communication Exchanges to Identify Relationships, Patterns, and Correlations to Deal Outcomes

A method for using historic electronic communications in enhancing transactional metrics related to a transactional platform, the method comprising:

• accessing a time period of historic electronic communications data for an organization, the historic electronic communications data comprising a plurality of messages;
• filtering, by processing circuitry, the plurality of messages to remove a subset of irrelevant messages;
• after filtering, analyzing, by the processing circuitry, body text of the plurality of messages to identify a subset of business-related messages;
• matching, by the processing circuitry, contents of a plurality of the subset of business-related messages to transaction data, wherein matching comprises
• applying a machine learning model to classify each of the subset of business-related messages as being trade related or not trade related,
• for each of the subset of business-related messages identified as being trade related, parsing at least body text to identify trade data, wherein the trade data comprises trade-related terminology, and
• querying a transaction data store using the trade data to identify one or more matching transaction records to a portion of the subset of business-related messages identified as being trade related;
• and
• merging a portion of the trade data with matched transaction data obtained from the transaction data store to generate a plurality of enhanced transactional data records.