Abstract: Disclosed herein is a method of obtaining merchant sales information for marketing or sales teams. Including accessing transaction data from one or more financial institutions and extracting metadata associated with the transaction data in accordance with at least one rule. The metadata is then analyzed to identify transaction data associated with one or more merchants. The transaction data associated with the one or more merchants is provided to the marketing or sales teams.

Abstract: Disclosed herein is a method for providing users with saving opportunities of interest. The method includes developing a predictive model of user purchase behavior, evaluating a plurality of available savings opportunities from a savings opportunity data base using the model of user purchase behavior, selecting from the plurality of savings opportunities one with the highest likelihood of acceptance and communicating the selected savings opportunity to the user.

Abstract: Disclosed herein is a method of obtaining merchant sales information for marketing or sales teams. Including accessing transaction data from one or more financial institutions and extracting metadata associated with the transaction data in accordance with at least one rule. The metadata is then analyzed to identify transaction data associated with one or more merchants. The transaction data associated with the one or more merchants is provided to the marketing or sales teams.

Abstract: Disclosed herein is a method of classifying financial transactions by usage patterns of a user. The method includes analyzing metadata extracted from the information associated with financial transactions in accordance with at least one business rule. Where the analysis includes sequentially analyzing the metadata using a constant-time lookup data structure, a Radix tree, a Lucene tree and fuzzy logic methods, until a unique identifier is found that is associated with the metadata. The metadata with the unique identifier is then added to the constant-time lookup data structure to update the constant-time lookup data structure. The transaction data is then classified based on the unique identifier.