Sales Pipeline Demand Forecasting via Travel Propensity
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Solution Overview
Problem
Current methods for managing a sales pipeline are inefficient and lack accuracy due to multiple manual steps, necessitating a solution that automates demand forecasting and supply identification to improve sales pipeline management.
Innovation Solution
A system and method that determine total demand for promotions by identifying a promotion area based on consumer travel probability, comparing it to a threshold, and adjusting demand accordingly, using a processor to identify satisfied demand and demand gaps, and assigning merchants to meet forecasted demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual steps are used in demand forecasting and supply identification, then the process can be easily understood and implemented, but the efficiency and accuracy of sales pipeline management deteriorate
Solution Approach 1:
The system enables self-service by automatically performing demand forecasting and supply identification without requiring manual intervention. The processor autonomously calculates travel probabilities, determines promotion areas, identifies satisfied demand, and detects demand gaps, allowing the sales pipeline management system to serve itself rather than relying on manual steps
Solution Approach 2:
The patent replaces manual mechanical processes with an automated computational system. The processor substitutes human analysts by executing algorithms that calculate travel probabilities, determine promotion areas based on geographic and temporal parameters, and automatically identify supply-demand mismatches, thereby improving efficiency while managing complexity through systematic automation
2Measurement precision
If travel probability calculations are performed to determine promotion areas, then demand forecasting accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The system applies partial action by calculating travel probabilities only for relevant consumer-promotion pairs within defined geographic and temporal parameters. Rather than computing all possible combinations, the processor focuses calculations on consumers within reasonable travel distance of promotions, achieving sufficient accuracy while reducing unnecessary computational overhead and processing time
Solution Approach 2:
The patent utilizes parameter changes by adjusting promotion area boundaries based on calculated travel probabilities. The system dynamically modifies geographic parameters (promotion areas) and temporal parameters (offer periods) according to probability thresholds, allowing flexible adaptation of forecasting models to balance accuracy requirements with computational efficiency
Data Source
AI summary
Provided herein are systems, methods and computer readable media for managing a sales pipeline, and in some embodiments, calculating supply based on travel propensity. An example method comprises identifying a total demand for a promotion tuple at a geographic location, determining, using a processor, a promotion area for the promotion tuple, the promotion tuple comprising at least a category, price information and a geographic area, identifying one or more promotions offered by a promotion and marketing service that comprise at least the category and the price information of the promotion tuple, determining whether the total demand for the promotion tuple at the geographic location is satisfied, wherein the total demand is satisfied in an instance in which the geographic location is within the promotion area for the one or more promotions, and identifying a demand gap in an instance in which the total demand for the promotion tuple at the geographic location is not satisfied.