Abstract: A system and method for adaptive marketing using insight driven customer interaction. The invention uses a closed-loop process for developing insight that may be used to refine further customer interactions. Results of a first customer interaction such as a marketing campaign are stored in a database. The results may be used to retrain predictive models and gain new insights regarding how customers are responding to marketing campaigns. The insights may be used to refine the offers delivered to customers or to extend additional offers in an effort to increase the likelihood that customers will redeem the offers. After each marketing campaign, the results are stored in the database. New and/or modified offers are created based on insights provided by the results of past campaigns. This process may be repeated such that subsequent campaigns are based on insights generated by the predictive models. The insight enables businesses to better target customers with better offers.

Abstract: A system and method for adaptive marketing using insight driven customer interaction. The invention uses a closed-loop process for developing insight that may be used to refine further customer interactions. Results of a first customer interaction such as a marketing campaign are stored in a database. The results may be used to retrain predictive models and gain new insights regarding how customers are responding to marketing campaigns. The insights may be used to refine the offers delivered to customers or to extend additional offers in an effort to increase the likelihood that customers will redeem the offers. After each marketing campaign, the results are stored in the database. New and/or modified offers are created based on insights provided by the results of past campaigns. This process may be repeated such that subsequent campaigns are based on insights generated by the predictive models. The insight enables businesses to better target customers with better offers.

Abstract: A system and method for adaptive marketing using insight driven customer interaction. The invention uses a closed-loop process for developing insight that may be used to refine further customer interactions. Results of a first customer interaction such as a marketing campaign are stored in a database. The results may be used to retrain predictive models and gain new insights regarding how customers are responding to marketing campaigns. The insights may be used to refine the offers delivered to customers or to extend additional offers in an effort to increase the likelihood that customers will redeem the offers. After each marketing campaign, the results are stored in the database. New and/or modified offers are created based on insights provided by the results of past campaigns. This process may be repeated such that subsequent campaigns are based on insights generated by the predictive models. The insight enables businesses to better target customers with better offers.

Abstract: A system and method for segmenting customer data that represents a plurality of customers for use in a customer interaction. The segmentation process groups customers with similar characteristics into segments. The segments may be used to classify customers according to a likelihood of the customers to accept a particular marketing offer. The segments may also be used as an analytic framework for customer portfolio management, product development, marketing strategy, and customer interaction capabilities. A multi-dimensional segmentation approach may be used to cross-segment a plurality of customers so that the customers included in the crossed segments can be profiled for more precise targeting of marketing offers. Customers may be segmented according to one or more data types stored in a data warehouse. The multi-dimensional segmentation approach may be applied to relationships between and among the data types to obtain a holistic view of what drives customer value.

Abstract: A system and method for creating virtual flat customer records derived from database customer data that may be used as standardized input for analytical models. A Customer Analytic Record (“CAR”) application may be created as a database object to extract, transform, and format all of the customer data needed for customer segmentation and predictive modeling. The CAR may be a set of database views that are defined using virtual stored queries The CAR application may dynamically calculate additional variables using predetermined transformations, including custom transformations of an underlying behavior. The CAR is preferably a dynamic view of the customer record that changes whenever any update is made to the database. The definition of the CAR provides documentation of each data element available for use in models and analytics.

Abstract: A system and method for creating virtual “flat” customer records derived from database customer data that may be used as standardized input for analytical models. A Customer Analytic Record (“CAR”) application may be created as a database object to extract, transform, and format all of the customer data needed for customer segmentation and predictive modeling. The CAR may be a set of database “views” that are defined using virtual stored queries and enabled using capabilities of a data base management system and a structured query language. The CAR is preferably a virtual “flat” record of the customer data needed for customer analytics. The customer data may be extracted by running one or more SQL queries against the database view(s). The CAR application may dynamically calculate additional variables using predetermined transformations, including custom transformations of an underlying behavior. If additional variables are created, the CAR may be modified to include the additional variables.

Abstract: A system and method for adaptive marketing using insight driven customer interaction. The invention uses a closed-loop process for developing insight that may be used to refine further customer interactions. Results of a first customer interaction such as a marketing campaign are stored in a database. The results may be used to retrain predictive models and gain new insights regarding how customers are responding to marketing campaigns. The insights may be used to refine the offers delivered to customers or to extend additional offers in an effort to increase the likelihood that customers will redeem the offers. After each marketing campaign, the results are stored in the database. New and/or modified offers are created based on insights provided by the results of past campaigns. This process may be repeated such that subsequent campaigns are based on insights generated by the predictive models. The insight enables businesses to better target customers with better offers.

Abstract: A system and method for segmenting customer data that represents a plurality of customers for use in a customer interaction. The segmentation process groups customers with similar characteristics into segments. The segments may be used to classify customers according to a likelihood of the customers to accept a particular marketing offer. The segments may also be used as an analytic framework for customer portfolio management, product development, marketing strategy, and customer interaction capabilities. A multi-dimensional segmentation approach may be used to cross-segment a plurality of customers so that the customers included in the crossed segments can be profiled for more precise targeting of marketing offers. Customers may be segmented according to one or more data types stored in a data warehouse. The multi-dimensional segmentation approach may be applied to relationships between and among the data types to obtain a holistic view of what drives customer value.

Abstract: A system and method for creating virtual “flat” customer records derived from database customer data that may be used as standardized input for analytical models. A Customer Analytic Record (“CAR”) application may be created as a database object to extract, transform, and format all of the customer data needed for customer segmentation and predictive modeling. The CAR may be a set of database “views” that are defined using virtual stored queries and enabled using capabilities of a data base management system and a structured query language. The CAR is preferably a virtual “flat” record of the customer data needed for customer analytics. The customer data may be extracted by running one or more SQL queries against the database view(s). The CAR application may dynamically calculate additional variables using predetermined transformations, including custom transformations of an underlying behavior.

Abstract: A leak detector comprising a housing having an axis on first and second compartments spaced along the axis and hermetically separated by a partition, the first compartment being closed to comprise a pressure envelope which is in communication with an evacuated space to be monitored for leakage, an ionization cell in the first compartment providing an electrical current determined by gas in that compartment, hermetically sealed feed-through for enabling an electrical connection with the gauge, to the partition from the second compartment, an apparatus in the second compartment performing a control function in accordance with the current supplied by the cell.