Automated specification, estimation, discovery of causal drivers and market response elasticities or lift factors

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.

1 - 28 . (canceled) 
     
     
         29 . A computer-readable storage device storing instructions that, if executed by a computing system, cause the computing system to perform a method for prescribing a total budget and allocation of marketing resources for a subject offering, the instructions comprising:
 instructions for, collecting data relating to historical marketing efforts for a first offering other than the subject offering;   instructions for calculating, based on the collected data, an average elasticity measure indicating the impact on a business outcome of allocating resources to a total marketing budget for the first offering;   instructions for deriving an adjustment factor for the average elasticity measure that specifies how much the average elasticity measure is to be adjusted to reflect characteristics of the historical marketing efforts;   instructions for, for at least one of a plurality of spending categories, deriving an elasticity measure indicative of the effect of the spending category on the business outcome; and   instructions for determining a total marketing budget for the subject offering based on the calculated average elasticity measure and the derived adjustment factor.   
     
     
         30 . The computer-readable storage device of  claim 29  wherein the collected data comprises at least one of characteristics of the first offering, the total marketing budget for the first offering, an allocation of the total marketing budget for the first offering across spending categories, or a business outcome. 
     
     
         31 . The computer-readable storage device of  claim 29 , the instructions further comprising:
 instructions for collecting data relating to historical marketing efforts for a second offering other than the subject offering and other than the first offering;   instructions for calculating, based on the collected data relating to historical marketing efforts for the second offering, an average elasticity measure indicating the impact on the business outcome of allocating resources to a total marketing budget for the second offering;   instructions for deriving an adjustment factor for the average elasticity measure that specifies how much the average elasticity measure indicating the impact on the business outcome of allocating resources to the total marketing budget for the second offering is to be adjusted to reflect characteristics of the historical marketing efforts for the second offering; and   instructions for, for at least one of the plurality of spending categories, deriving an elasticity measure indicating the extent to which the marketing spending category impacted the business outcome,   wherein the instructions for determining the ideal total marketing budget is include instructions for determining the ideal total marketing budget based on the average elasticity measure indicating the impact on the business outcome of allocating resources to the total marketing budget for the second offering.   
     
     
         32 . The computer-readable storage device of  claim 29  wherein the plurality of spending categories include television, movie theatre, radio, and newspaper. 
     
     
         33 . The computer-readable storage device of  claim 32  wherein the plurality of spending categories include outdoor, home shopping TV, product placement, airport, public transportation, sponsorship of sports events, and sponsorship of non-sports events. 
     
     
         34 . The computer-readable storage device of  claim 33  wherein the plurality of spending categories include television, movie theatre, radio, newspapers, video game, streaming video, and interactive TV. 
     
     
         35 . The computer-readable storage device of  claim 34  wherein the plurality of spending categories include magazine, print article, loose insert, internet advertising, internet search, brand/company website, and email. 
     
     
         36 . The computer-readable storage device of  claim 35  wherein the plurality of spending categories include doctor's office, toll free lines, celebrity endorsement, in-store advertising, and promotion/special offer. 
     
     
         37 . A computing system, comprising a memory and a processor, for prescribing a total budget and allocation of marketing resources for a subject offering, the computing system comprising:
 a component configured to collect data relating to historical marketing efforts for a first offering other than the subject offering;   a component configured to calculate, based on the collected data, an average elasticity measure indicating the impact on a business outcome of allocating resources to a total marketing budget for the first offering;   a component configured to derive an adjustment factor for the average elasticity measure that specifies how much the average elasticity measure is to be adjusted to reflect characteristics of the historical marketing efforts;   a component configured to, for at least one of a plurality of spending categories, derive an elasticity measure indicative of the effect of the spending category on the business outcome; and   a component configured to determine a total marketing budget for the subject offering based on the calculated average elasticity measure and the derived adjustment factor.   
     
     
         38 . The computing system of  claim 37  wherein the collected data comprises at least one of characteristics of the first offering, the total marketing budget for the first offering, an allocation of the total marketing budget for the first offering across spending categories, or a business outcome. 
     
     
         39 . The computing system of  claim 37 , the instructions further comprising:
 a component configured to collect data relating to historical marketing efforts for a second offering other than the subject offering and other than the first offering;   a component configured to calculate, based on the collected data relating to historical marketing efforts for the second offering, an average elasticity measure indicating the impact on the business outcome of allocating resources to a total marketing budget for the second offering;   a component configured to derive an adjustment factor for the average elasticity measure that specifies how much the average elasticity measure indicating the impact on the business outcome of allocating resources to the total marketing budget for the second offering is to be adjusted to reflect characteristics of the historical marketing efforts for the second offering; and   a component configured to, for at least one of the plurality of spending categories, derive an elasticity measure indicating the extent to which the marketing spending category impacted the business outcome,   wherein the component configured to determine the ideal total marketing budget is configured to determine the ideal total marketing budget based further on the average elasticity measure indicating the impact on the business outcome of allocating resources to the total marketing budget for the second offering.   
     
     
         40 . The computing system of  claim 37  wherein the plurality of spending categories include television, movie theatre, radio, and newspaper. 
     
     
         41 . The computing system of  claim 40  wherein the plurality of spending categories include outdoor, home shopping TV, product placement, airport, public transportation, sponsorship of sports events, sponsorship of non-sports events, television, movie theatre, radio, newspapers, video game, streaming video, magazine, print article, loose insert, internet advertising, internet search, brand/company website, email, doctor's office, toll free lines, celebrity endorsement, in-store advertising, and promotion/special offer. 
     
     
         42 . A computer-readable memory storing instructions that, if executed by a computing system, cause the computing system to perform a method for automatically prescribing an allocation of resources to a total marketing budget for a distinguished offering from a distinguished business, the method comprising:
 receiving, by at least one of the one or more processors, qualitative attributes of a distinguished offering from a user;   for a plurality of data sources,   retrieving, by at least one of the one or more processors, an average total marketing budget lift factor from the data source based at least in part on a predefined template for the data source;   adjusting, by at least one of the one or more processors, the average total marketing budget lift factor based upon at least two of the received qualitative attributes of the distinguished offering; and   using, by at least one of the one or more processors, the adjusted average total marketing budget lift factor to determine an allocation of resources to a total marketing budget.   
     
     
         43 . The computer-readable memory of  claim 42 , wherein the qualitative attributes comprise at least one qualitative attribute selected from the group consisting of: information about the distinguished business, information about one or more current customers of the distinguished business, information about a product or service offered by the distinguished business in the distinguished offering, information about a current marketing method by the distinguished business, information about a brand strength of the distinguished business brand strength, and information about a current media allocation of the distinguished business. 
     
     
         44 . The computer-readable memory of  claim 42 , wherein the derived average total marketing budget lift factor is derived before receiving the qualitative attributes of the distinguished offering from the user. 
     
     
         45 . The computer-readable memory of  claim 42 , the method further comprising:
 collecting data relating to historical marketing efforts for a first offering other than the subject offering.   
     
     
         46 . A method in a computing system for automatically prescribing an allocation of resources to a total marketing budget for a distinguished offering, wherein the computing system performs one or more steps of the method, the method comprising:
 receiving qualitative attributes of the distinguished offering from a user;   for a plurality of data sources,   retrieving an average total marketing budget elasticity measure from the data source based at least in part on a predefined template for the data source;   adjusting the average total marketing budget elasticity measure based upon at least two of the received qualitative attributes of the distinguished offering; and   using the adjusted average total marketing budget elasticity measure to determine an allocation of resources to a total marketing budget that tends to optimize a distinguished business outcome.   
     
     
         47 . The method of  claim 46 , wherein the average total marketing budget elasticity measure is before receiving the qualitative attributes of the distinguished offering from the user. 
     
     
         48 . The method of  claim 46 , wherein the qualitative attributes comprise information about the distinguished business, information about one or more current customers of the distinguished business, information about a product or service offered by the distinguished business in the distinguished offering, information about a current marketing method by the distinguished business, information about a brand strength of the distinguished business brand strength, and information about a current media allocation of the distinguished business.