Promotional Demand Ranking System for Sales Resource Allocation
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Solution Overview
Problem
Existing methods for promotional demand management are ineffective in accurately ascertaining consumer demand for promotions and providers, leading to inefficiencies in sales resource allocation and promotion availability.
Innovation Solution
A method, apparatus, and computer program product that receive consumer requests for promotions or providers, generate aggregated lists, rank them based on promotion and provider scores, and distribute ranked lists to sales resources, providing an indication of demand through notifications and dynamic allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods for promotional demand management are used, then the system is simple to operate, but the accuracy of ascertaining consumer demand is poor
Solution Approach 1:
The patent segments consumer requests into individual items and aggregates them into demand lists, then further segments by ranking different promotions and providers separately. This segmentation enables precise measurement of demand for each item while maintaining a manageable system structure through modular processing.
Solution Approach 2:
The patent introduces an intermediary aggregation and ranking system that sits between raw consumer requests and sales resource allocation. This intermediary layer processes requests through scoring mechanisms and generates ranked demand lists, improving measurement accuracy while isolating the complexity from both data collection and resource allocation functions.
2Measurement precision
If consumer requests are aggregated and ranked comprehensively, then the demand indication is accurate, but the processing time and system complexity increase
Solution Approach 1:
The patent performs preliminary aggregation of consumer requests into demand lists and pre-calculates scoring metrics for promotions and providers before final allocation decisions. This preliminary processing organizes data in advance, enabling faster final ranking and reducing real-time processing time while maintaining comprehensive analysis.
Solution Approach 2:
The patent changes parameters by assigning numerical scores to promotions and providers based on multiple criteria, then uses these scored parameters for ranking. This parameter transformation converts complex qualitative assessments into quantifiable metrics that can be processed efficiently while maintaining measurement accuracy.
3Productivity
If sales resources are allocated based on ranked demand lists, then sales efficiency is improved, but the allocation system becomes more complex
Solution Approach 1:
The patent implements feedback by distributing ranked demand lists to sales resources and presumably tracking allocation outcomes. This feedback mechanism enables continuous optimization of sales efficiency while the structured ranking system provides clear guidance that simplifies the allocation decision-making process despite the underlying complexity.
Solution Approach 2:
The patent enables sales resources to autonomously access and utilize the ranked demand lists for their own allocation decisions. This self-service approach improves sales efficiency by empowering front-line resources while the centralized ranking system manages the complexity of demand analysis, separating computational complexity from operational simplicity.
Data Source
AI summary
A method, apparatus and computer program product are provided herein for ascertaining a demand of promotions. An example method comprises receiving, from one or more consumers, at least one consumer request for at least one of one or more requested promotions or one or more requested providers, generating an aggregated list of the at least one of the one or more requested promotions or the one or more requested providers, ranking the aggregated list of the at least one consumer request, and causing one or more ranked lists to be distributed to at least one sales resource.