Abstract: A facility for automatically prescribing, for a distinguished offering, an allocation of resources to a total marketing budget and/or individual marketing activities is described.

Abstract: A facility for automatically prescribing, for a distinguished offering, an allocation of resources to a total marketing budget and/or individual marketing activities is described.

Abstract: A facility for automatically prescribing, for a distinguished offering, an allocation of resources to a total marketing budget and/or individual marketing activities is described.

Abstract: In one embodiment a software facility that uses a qualitative description of a subject offering to automatically prescribe both (1) a total budget for marketing and sales resources for a subject offering and (2) an allocation of that total budget over multiple spending categories—also referred to as “activities”—in a manner intended to optimize a business outcome such as profit for the subject offering based on experimentally-obtained econometric data (“the facility”) is provided.

Abstract: In some embodiments, a software facility performs a method of automated specification of models, estimation of elasticities, and discovery of drivers using the framework(s) discussed elsewhere herein is provided. The facility first obtains the client, business, and/or brand goals in terms of profit optimization, volume or revenue goals, acquisition of new customers, retention of customers, share of wallet and upsell. In conjunction with these goals, the facility obtains cross-section meta-data related to the planning time horizon, markets, geographies, channels of trade and customer segments. In combination, the goals and meta-data define the structure of the data stack and the number of demand generation equations that are needed.

Abstract: In some embodiments, a software facility performs a method of automated specification of models, estimation of elasticities, and discovery of drivers using the framework(s) discussed elsewhere herein is provided. The facility first obtains the client, business, and/or brand goals in terms of profit optimization, volume or revenue goals, acquisition of new customers, retention of customers, share of wallet and upsell. In conjunction with these goals, the facility obtains cross-section meta-data related to the planning time horizon, markets, geographies, channels of trade and customer segments. In combination, the goals and meta-data define the structure of the data stack and the number of demand generation equations that are needed.

Abstract: A software facility that analyzes consumer interactions with one or more marketing campaigns and the results of those interactions to generate a cross-media or cross-channel attribution model representing the true impact of marketing resource allocation decisions is provided. The facility collects, from a plurality of sources, information representing consumer interactions with marketing campaigns and any results of those interactions. The facility aggregates the information to assess or determine the behavior of consumers with respect to different marketing campaigns and marketing channels. The facility analyzes the information according to varying depths or levels of channel granularity to generate models representative of the true impact of resources allocated to each channel or sub-channel on the performance or effectiveness of the marketing campaign. The facility or other processes may use the generated models to inform future marketing resource allocation decisions.

Abstract: In some embodiments, a software facility performs a method of automated specification of models, estimation of elasticities, and discovery of drivers using the framework(s) discussed elsewhere herein is provided. The facility first obtains the client, business, and/or brand goals in terms of profit optimization, volume or revenue goals, acquisition of new customers, retention of customers, share of wallet and upsell. In conjunction with these goals, the facility obtains cross-section meta-data related to the planning time horizon, markets, geographies, channels of trade and customer segments. In combination, the goals and meta-data define the structure of the data stack and the number of demand generation equations that are needed.

Abstract: In some embodiments, a software facility performs a method of automated specification of models, estimation of elasticities, and discovery of drivers using the framework(s) discussed elsewhere herein is provided. The facility first obtains the client, business, and/or brand goals in terms of profit optimization, volume or revenue goals, acquisition of new customers, retention of customers, share of wallet and upsell. In conjunction with these goals, the facility obtains cross-section meta-data related to the planning time horizon, markets, geographies, channels of trade and customer segments. In combination, the goals and meta-data define the structure of the data stack and the number of demand generation equations that are needed.

Abstract: In one embodiment, a computer-readable medium is provided for performing a method for automatically prescribing a budget for sales expenses including, determining lift factors for sales expenses and other promotion activities, establishing a relationship between the determined lift factors, budgets for the promotion activities to which the lift factors correspond, and a projected value of the distinguished business outcome; and using the established relationship to solve for a value of the sales expenses budget that tends to optimize the projected value of the distinguished business outcome in accordance with the selected optimization.

Abstract: In some embodiments, a software facility performs a method of automated specification of models, estimation of elasticities, and discovery of drivers using the framework(s) discussed elsewhere herein is provided. The facility first obtains the client, business, and/or brand goals in terms of profit optimization, volume or revenue goals, acquisition of new customers, retention of customers, share of wallet and upsell. In conjunction with these goals, the facility obtains cross-section meta-data related to the planning time horizon, markets, geographies, channels of trade and customer segments. In combination, the goals and meta-data define the structure of the data stack and the number of demand generation equations that are needed.

Abstract: A facility for automatically determining a recommended price for an entertainment event ticket is described. The facility determines a first group of attributes of the entertainment event ticket. For each of a second group of attributes selected from the determined first group of attributes, the facility applies to the attribute a lift factor determined for the attribute to obtain a quantitative measure of the effect of the attribute. The facility then combines the obtained quantitative measures of attribute effects to obtain a recommended price for the entertainment event ticket.

Abstract: A facility for automatically prescribing, for a distinguished offering, an allocation of resources to a total marketing budget and/or individual marketing activities is described.

Abstract: In one embodiment, a software facility is provided that uses a qualitative description of a subject offering to automatically prescribe both (1) a total budget for marketing and sales resources for a subject offering and (2) an allocation of that total budget over multiple spending categories—also referred to as “activities”—in a manner intended to optimize a business outcome such as profit for the subject offering based on experimentally-obtained econometric data.

Abstract: In one embodiment a software facility that uses a qualitative description of a subject offering to automatically prescribe both (1) a total budget for marketing and sales resources for a subject offering and (2) an allocation of that total budget over multiple spending categories—also referred to as “activities”—in a manner intended to optimize a business outcome such as profit for the subject offering based on experimentally-obtained econometric data (“the facility”) is provided.

Abstract: A facility for automatically prescribing, for a distinguished offering, an allocation of resources to a total marketing budget and/or individual marketing activities is described.

Abstract: A facility for automatically prescribing, for a distinguished offering, an allocation of resources to a total marketing budget and/or individual marketing activities is described.