Abstract:
Disclosed herein is a method for identifying a member of a group with particular demographic characteristics. The method involves identifying purchasing behaviors of members of a group with particular demographic characteristics via market research, gathering transaction data from a financial account of a user at a financial institution for processing transactions of the user with the multiple of merchants, using the market research to set prior probabilities that a user is a member of the group in a Bayesian belief network, analyzing the transaction data of the user via a Bayesian belief network to determine whether the transaction data of the user indicates that the user is an individual member of the group with the particular demographic characteristics, and presenting to the user at least one of an offer and a savings opportunity from a merchant seeking to contact members of the group with the particular demographic characteristics.
Abstract:
Disclosed herein is a method of providing a user with one or more savings opportunities. The method comprising, gathering transaction data from a user's financial account, analyzing the transaction data for indications of savings opportunities, identifying savings opportunities from a database based on analysis and communicating the savings opportunities to the user.
Abstract:
Disclosed herein is a method for providing an offer which includes selecting at least one offer for presentation by applying at least one rule dictated by a merchant to a set of offers, applying at least one rule dictated by a financial institution to the offers, and applying a filter to identify offers with the highest likelihood of being accepted by the user. The selected offer is then presented to the user. An authorization request from a merchant for a user transaction is received by a remote computer and analyzed to determine one or more categories or sub-categories of the merchant or item in the transaction. The system then determines whether the selected offer is for a merchant or item in a related but different category from the one for which the authorization request was received, and if it is, the system reminds the user of the selected offer.
Abstract:
A method for providing a savings opportunity includes receiving an authorization request for a user transaction by a first remote computer. By analyzing, at the first remote computer, the authorization request, it can be determined if the currency being used during the transaction is different from the preferred currency (as indicated by a user profile). If there is a difference, a savings opportunity indication for the foreign transaction is generated. The savings opportunity indication may be transmitted to a second remote computer where a savings opportunity from a database of savings opportunities is matched to the user. Then, at least one of the user and the merchant is notified by the second remote computer of the savings opportunity. Alternatively, the matched savings opportunity is returned to the first remote computer for transmittal to at least one of the user and the merchant along with an authorization of the transaction.
Abstract:
Disclosed herein is a method for a merchant to gain information about the purchasing characteristics of a group with which the merchant wishes to interact. Merchants wishing to target group members are not able to specifically identify members of the group through depersonalized transaction data available from financial institutions. Group members are therefore identified through a traditional method: market research. The method also includes noting the purchasing behavior of group members, including providers of goods and services to group members, merchants not patronized by members of the group, and demographic characteristics of the group. An example of such a group is the so-called “millennials”. The identification of group members may be validated through test runs of financial data and fine-tuned to ensure correct identification of group members.
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.
Abstract:
A system and method of targeting users with a reward, offer, or incentive may include selecting at least one reward, offer, or incentive to present to a user by applying at least one rule, restriction, or filter dictated by a merchant to the set to be provided to the user, applying at least one rule, restriction, or filter dictated by a financial institution to the set, and applying a filter to the set to obtain those rewards, offers, or incentives with the highest likelihood of being accepted by the user. At least one parameter of the at least one reward, offer, or incentive is adjusted prior to presentation to the user based on a spending trajectory, user propensity model, user profile information or segmentation criteria, or campaign goal.
Abstract:
The present disclosure relates to comparison shopping and usage based service analysis for consumers, primarily for financial products. A consumer may not be aware of a provider's services, options, terms, conditions, costs, or how the service options change based on the consumer's particular usage characteristics. The disclosed comparison shopping method uses the consumer's actual or predicted service usage data. Service provider information is used to present the consumer with relevant alternative service offering options. Transaction data is gathered from a user's financial account and is analyzed for a savings opportunity indication. The analysis is used to match a savings opportunity from a database of savings opportunities, and the savings opportunity may be displayed in a statement of a user's financial account. Past responses to a savings opportunity indication may be gathered and analyzed. In one example, a savings opportunity is presented with a statement of the consumer's financial account.
Abstract:
Disclosed herein is a method is provided for managing campaign effectiveness by a merchant. The method comprising: initiating a campaign by one or more merchants, accessing transaction data from one or more financial institutions, extracting metadata associated with the transaction data in accordance with at least one rule, analyzing the metadata to identify transaction data associated with the campaign and the one or more merchants, analyzing the transaction data associated with the campaign and the one or more merchants and providing information associated with the campaign to the merchant.
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.