Marketing Budget Allocation Service with Probabilistic Optimization
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Solution Overview
Problem
Conventional data analytics systems lack the capability to intelligently optimize marketing budget allocation and efficiently scale based on probabilistic programming operations, relying on black box or manually corrected implementations that result in limited transparency, scalability, and interactivity.
Innovation Solution
A marketing budget allocation service is provided within a data analytics system, utilizing a service pipeline that includes a data ingestion engine, response curve generator, long-term impact correction engine, optimization and simulation engine, and data analytics user interface, leveraging probabilistic programming and machine learning to optimize marketing budget allocation across touchpoints and brands, offering transparent and scalable solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional black box computing or manually corrected implementations are used for marketing budget allocation, then the system can provide basic allocation functionality, but transparency and understanding of the results are limited
Solution Approach 1:
The patent introduces an intermediary layer between the black box computing system and the user that extracts, structures, and presents key information from the allocation results. This intermediary component translates complex computational outputs into transparent, interpretable formats without requiring changes to the underlying complex system, thus resolving the contradiction between transparency and system complexity.
2Productivity
If manual steps and human intervention are used in the estimation process, then some level of control and correction is achieved, but efficiency and scalability are reduced
Solution Approach 1:
The system implements self-service capabilities where the automated estimation process can self-correct and self-optimize through feedback loops. The system automatically adjusts parameters, validates results, and refines allocations without requiring manual intervention, thereby maintaining high automation levels while ensuring quality outcomes. This resolves the contradiction by making the system serve itself rather than requiring external human assistance.
3Adaptability or versatility
If conventional marketing spend allocation tools are used, then basic allocation can be performed, but the system cannot scale to support different types of marketing budgets, brands, and products
Solution Approach 1:
The patent implements a universal framework that can handle multiple types of marketing budgets, brands, and products through a single integrated system. The estimation methodology is designed to be agnostic to specific marketing contexts, allowing the same core system to adapt to diverse scenarios by adjusting input parameters rather than requiring separate specialized tools. This resolves the contradiction between scalability and complexity by creating one versatile system instead of many specialized ones.
4Ease of operation
If black box computing implementations are used, then computational analysis can be performed, but interactivity with the results data is limited
Solution Approach 1:
The system implements feedback mechanisms that allow users to interact with the black box computing results by providing input on what aspects they want to explore or adjust. The system responds to user feedback by generating targeted explanations, alternative scenarios, or focused analyses of specific results areas. This creates an interactive loop where users can guide the information presentation without needing to understand the underlying computational complexity, resolving the contradiction between interactivity and information transparency.
Data Source
AI summary
Methods, systems, and computer storage media for providing a marketing budget allocation service associated with an optimization and simulation engine in a data analytics system. The marketing budget allocation service is a marketing expenditure optimization service that provides marketing budget allocation intelligence and visualizations based on data analysis and business information (e.g., prior hypothesis input data or scenario input data). The marketing budget allocation service is based on a service pipeline that includes a set of allocation intelligence data processors and operations that are used to generate output that is managed (e.g., visualized, presented, and revised) using a data analytics user interface. In operation, based on analyzing marketing budget allocation data—via an allocation service analytics computation model, marketing budget allocation results data are generated. The marketing allocation results data are communicated to cause presentation of the marketing budget allocation results data on an optimization and simulation engine user interface.