Abstract: Commercial size of spending wallet (“SoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“SoW”) is the portion of the spending wallet that is captured by a particular financial company. Commercial SoW is a modeling approach that utilizes various data sources to provide outputs that describe a company's spend capacity. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new account evaluation, and customer management across the lifecycle. Company financial statements are utilized to identify and calculate total business spend of a company that could be transacted using a commercial credit card. A spend-like regression model may then be developed to estimate annual commercial SoSW value for customers and prospects within a credit network.

Abstract: Disclosed herein are systems and methods of aggregating consumer data. The data may be acquired from numerous sources so that small portions of reliable data may be gathered into a single data set. Furthermore, by aggregating and analyzing such data, new insights and information about consumers may be discovered. Additionally disclosed are computer implemented arrangements for sharing of information that may provide incentives for data to be shared for purposes of aggregation and analysis. Some embodiments include a cooperative database system in which entities, such as marketers or communicators, may exchange data relating to consumers, such as email list activity data.

Abstract: Embodiments facilitate confidential and secure sharing of anonymous user profile data to improve the delivery of customized content. Embodiments of the invention provide a data appliance to an entity such as a business to convert profile data about the business's customers into anonymous identifiers. A similar data appliance is provided to a content provider in one embodiment to generate identifiers for its user profile data. Because the anonymous identifiers are generated with the same anonymization method, identical identifiers are likely generated from profile data of the same users. Therefore, the identifiers can be used to anonymously match the customers of the business to the users of the content provider. Therefore, data can be shared to improve customized content such as advertisements that the business wishes to place with the content provider without requiring the business to disclose customer data in an unencrypted form, and any non-matched data can remain confidential.

Abstract: Commercial size of spending wallet (“CSoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“CSoW”) is the portion of the spending wallet that is captured by a particular financial company. A modeling approach utilizes various data sources to provide outputs that describe a company's spend capacity. Research analysts can use CSoW/CSoSW to provide a comprehensive and robust indication of the business prospects of a rated company.

Abstract: Commercial size of spending wallet (“CSoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“CSoW”) is the portion of the spending wallet that is captured by a particular financial company. A modeling approach utilizes various data sources to provide outputs that describe a company's spend capacity. Marketing companies that sell lists compile those lists by searching one or more databases for names and/or businesses that match certain criteria. Those marketing companies can use the CSoW/CSoSW modeling approach to show predicted spend and/or revenues for each company on a list. This makes the list more valuable to list buyers.

Abstract: Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. The outputs can be used as attributes to consider in developing a credit bureau scorecard.

Abstract: A client transmits one or more lead records to a lead enhancement module that is configured to enhance the received lead records and return enhanced lead records to the client. The lead enhancement module may return a contactability score for each lead record, indicating a likelihood that the individual identified in the lead may be contacted using the contact information provided in the lead record and/or additional contract information located by the lead enhancement module. The lead enhancement module may also receive additional data items associated with leads from one or more data sources. Additionally, statistical models that may be customized for each client may be applied to information associated with lead records in order to determine one or more propensity scores for each of the lead records, where a propensity score indicates a likelihood that an individual will take a particular action, such as purchasing particular goods or services.

Abstract: The present invention provides a system, method, software and data structure for independently predicting attitudinal and message responsiveness, using a plurality of attitudinal or other identification classifications and a plurality of message content or version classifications, for a selected population of a plurality of entities, such as individuals or households, represented in a data repository. The plurality of predictive attitudinal (or identification) classifications and plurality of predictive message content (ore version) classifications have been determined using a plurality of predictive models developed from a sample population and applied to a reference population represented in the data repository, such as attitudinal, behavioral, or demographic models. For each predictive attitudinal (or identification) classification, at least one predominant predictive message content or version classification is independently determined.

Abstract: The present invention provides a system, method, software and data structure for independently predicting attitudinal and message responsiveness, using a plurality of attitudinal or other identification classifications and a plurality of message content or version classifications, for a selected population of a plurality of entities, such as individuals or households, represented in a data repository. The plurality of predictive attitudinal (or identification) classifications and plurality of predictive message content (ore version) classifications have been determined using a plurality of predictive models developed from a sample population and applied to a reference population represented in the data repository, such as attitudinal, behavioral, or demographic models. For each predictive attitudinal (or identification) classification, at least one predominant predictive message content or version classification is independently determined.

Abstract: A process and system for integrating information stored in at least two disparate databases. The stored information includes consumer transactional information. According to the process and system, at least one qualitative variable which is common to each database is identified, and then transformed into one or more quantitative variables. The consumer transactional information in each database is then converted into converted information in terms of the quantitative variables. Thereafter, an integrated database is formed for predicting consumer behavior by combining the converted information from the disparate databases.

Abstract: The present invention provides a system, method, software and data structure for independently predicting attitudinal and message responsiveness, using a plurality of attitudinal or other identification classifications and a plurality of message content or version classifications, for a selected population of a plurality of entities, such as individuals or households, represented in a data repository. The plurality of predictive attitudinal (or identification) classifications and plurality of predictive message content (ore version) classifications have been determined using a plurality of predictive models developed from a sample population and applied to a reference population represented in the data repository, such as attitudinal, behavioral, or demographic models. For each predictive attitudinal (or identification) classification, at least one predominant predictive message content or version classification is independently determined.

Abstract: A system is disclosed that maps user IDs (such as IP addresses) and geographic regions to particular categories or “segments” reflective of user profiles. The mappings may be based on behavioral data reflective of user browsing activities, offline data (e.g., survey data or demographic data), or a combination thereof. In one embodiment, the mappings are generated using data collected by a plurality of Internet Service Providers (ISPs) regarding their subscribers. The system also includes a query interface that enables content providers to retrieve segment data associated with particular user IDs.

Abstract: A media engagement system determines engagement scores for media vehicles across multiple media channels. The engagements scores for a media vehicle comprise multiple dimension scores indicating various aspects of engagement for that particular media vehicle. The dimension scores may be related to inspirational, trustworthy, life enhancing, social interaction, personal timeout, and ad attention/receptivity engagement dimensions, for example. The dimensions scores associated with respective engagement dimensions are based on responses to specific statements in engagement surveys completed by multiple media consumers. Thus, each statement in the engagement survey is associated with at least one engagement dimension and the engagement dimension score is then calculated based on media consumer responses to the statements associated with the respective engagement dimension.

Abstract: In some embodiments, systems and methods are disclosed for generating filters to determine whether a consumer is likely to have a scoreable credit record based on non-credit data, and to determine a potential risk level associated with an unscoreable credit record based on non-credit data. Existing scoreable and unscoreable records are compared to determine factors correlated with having an unscoreable record, and a multi-level filter is developed. Unscoreable records having at least one entry are compared to determine whether they are “good” or “bad” risks, factors correlated with either condition are determined, and a filter is developed. The filters can be applied to records comprising demographic data to determine consumers that are likely to have unscoreable records but represent good risks.

Abstract: The various embodiments of the invention provide a data processing system and method, for applications such as marketing campaign management, speech recognition and signal processing. An exemplary system embodiment includes a first data repository adapted to store a plurality of entity and attribute data; a second data repository adapted to store a plurality of entity linkage data; a metadata data repository adapted to store a plurality of metadata modules, with a first metadata module having a plurality of selectable parameters, received through a control interface, and having a plurality of metadata linkages to a first subset of metadata modules; and a multidimensional data structure. The control interface may modify the plurality of selectable parameters in response to received control information.

Abstract: The various exemplary embodiments provide a method for projecting survey information into a geographic region. The geographic region is divided into a plurality of geographic subregions, each of which are profiled using a plurality of profiling variables to form a selected geographic subregion profile. The profiling variables include both demographic and behavioral variables. A plurality of survey respondents are then randomly assigned into the selected geographic subregion to form a modeled population, with the random assignment weighted based on a representation probability of each of the corresponding plurality of survey respondents for the selected geographic subregion profile, with the representation probabilities having been determined using a sample balancing algorithm. Following such profiling and assignment for all subregions, survey information corresponding to the modeled population is projected into the geographic region.

Abstract: A process and system for integrating information stored in at least two disparate databases. The stored information includes consumer transactional information. According to the process and system, at least one qualitative variable which is common to each database is identified, and then transformed into one or more quantitative variables. The consumer transactional information in each database is then converted into converted information in terms of the quantitative variables. Thereafter, an integrated database is formed for predicting consumer behavior by combining the converted information from the disparate databases.

Abstract: A client transmits one or more lead records to a lead enhancement module that is configured to enhance the received lead records and return enhanced lead records to the client. The lead enhancement module may return a contactability score for each lead record, indicating a likelihood that the individual identified in the lead may be contacted using the contact information provided in the lead record and/or additional contract information located by the lead enhancement module. The lead enhancement module may also receive additional data items associated with leads from one or more data sources. Additionally, statistical models that may be customized for each client may be applied to information associated with lead records in order to determine one or more propensity scores for each of the lead records, where a propensity score indicates a likelihood that an individual will take a particular action, such as purchasing particular goods or services.

Abstract: The present invention provides a system, method, software and data structure for independently predicting attitudinal and message responsiveness, using a plurality of attitudinal or other identification classifications and a plurality of message content or version classifications, for a selected population of a plurality of entities, such as individuals or households, represented in a data repository. The plurality of predictive attitudinal (or identification) classifications and plurality of predictive message content (ore version) classifications have been determined using a plurality of predictive models developed from a sample population and applied to a reference population represented in the data repository, such as attitudinal, behavioral, or demographic models. For each predictive attitudinal (or identification) classification, at least one predominant predictive message content or version classification is independently determined.

Abstract: The various exemplary embodiments provide a method for projecting survey information into a geographic region. The geographic region is divided into a plurality of geographic subregions, each of which are profiled using a plurality of profiling variables to form a selected geographic subregion profile. The profiling variables include both demographic and behavioral variables. A plurality of survey respondents are then randomly assigned into the selected geographic subregion to form a modeled population, with the random assignment weighted based on a representation probability of each of the corresponding plurality of survey respondents for the selected geographic subregion profile, with the representation probabilities having been determined using a sample balancing algorithm. Following such profiling and assignment for all subregions, survey information corresponding to the modeled population is projected into the geographic region.