Accenture Global Services Gmbh

Andris Umblijs

Janmesh Srivastava

Stephen Denis Kirkby

Rahul Mahajan

Anatoly Roytman

Matthew Symons

Michael J Williams

Jeffrey Merrihue

Varun Rastogi

Chao Wang

James Walker

Prarthna Agarwal Goel

A method and system optimizes investments for each marketing channel of a multichannel marketing campaign. Past optimal investments are compared to current sales or profits for each marketing channel, and a new optimal investment is estimated for each marketing channel, which may be used as a marketing budget. A marketing dashboard is used to determine the new optimal investments for the marketing channels, and the new optimal investments are stored in a marketing database.

Multichannel digital marketing platform

A model optimization system is configured to determine quality of variables for model generation. A data storage stores input variables, quality metrics for the input variables, and weights for the quality metrics. The quality metrics describe sufficiency of data for the input variables and the data is provided for a plurality of regions. A scoring module determines a score for each region based on the input variables and the weighted quality metrics. An optimizer determines whether at least one of the input variables for a region is to be modified based on the scores, and determines whether the total score for the region is operable to be improved using a modified input variable.

Model optimization system using variable scoring

A hierarchal view preserving relationships between data is generated by storing information related to sales and investment. The information includes dimensions and each of the dimensions includes a level and each of the levels is described by variables. Relationships between the variables are also stored. A request for a hierarchy is received. The requested hierarchy includes a set of dimensions from the stored dimensions, a level for each dimension in the set, and a sequence of the dimensions or levels in the hierarchy. A computer system calculates values for the variables in the levels for the requested hierarchy using the stored relationships that are applicable to the variables in the levels. A view of the hierarchy is generated and includes the calculated values. The view also includes the dimensions or levels of the requested hierarchy in the sequence specified for the requested hierarchy.

Marketing investment optimizer with dynamic hierarchies

A method for automatically processing marketing and sales information. The method includes receiving data relating to one or more products, including data pertaining to marketing performance of the products and the marketing input drivers that influence the marketing performance. The method also includes analyzing the received data to determine response curves for the products, the response curves representing an optimal fit between a weighted combination of the input drivers of the products and their respective performance data. The method further includes adjusting the response curves based on feedback from one or more analysts to predict the future behavior of the response curves, determining an allocation of marketing resources based on the adjusted response curves, and presenting to a user the received data, the determined response curves, the adjusted response curves, and/or the marketing resources allocation.

Method and system for modeling marketing data

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Woking, United Kingdom

Andris Umblijs