Systems and Methods for Data Mining of Historic Electronic Communication Exchanges to Identify Relationships, Patterns, and Correlations to Deal Outcomes
In an illustrative embodiment, systems and methods for generating data metrics and relationship analysis from an organization's electronic communications archives include pre-processing the electronic communications into a consistent, workable format, including filtering the data to remove irrelevant messages. Machine learning models may be applied to support automatic identification of relevant message content for data analytics. The systems and methods may link the electronic communications with transaction records of a transactional platform and analyze the communications traffic in view of transactional patterns and outcomes. Communications between parties may be analyzed to identify timings and patterns, plus correlations between electronic communication patterns and business outcomes.
1 . 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.