Demand Forecasting via Virtual Promotions and Real-Time Signals
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Solution Overview
Problem
Current methods for managing a sales pipeline are inefficient and lack accuracy due to manual steps and inadequate data utilization, necessitating a more automated and data-driven approach for demand forecasting and supply identification.
Innovation Solution
A system and method for managing a sales pipeline that includes generating virtual promotions, calculating probabilities of consumer purchases based on historical data, determining real-time demand through user search data analysis, and distributing demand across price points and regions, while adjusting for external factors to forecast total demand and identify suitable merchants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual steps are used in demand forecasting, then the process is simpler to implement, but accuracy and efficiency deteriorate
Solution Approach 1:
The patent replaces manual mechanical processes with automated computational systems. Specifically, it substitutes manual data collection and analysis with automated web crawlers, databases, and algorithms that continuously gather and process demand signals, inventory data, and market information to generate forecasts without human intervention.
Solution Approach 2:
The system enables self-service through automated agents that independently perform demand forecasting, inventory optimization, and supply chain coordination. The algorithms autonomously analyze data patterns, generate predictions, and adjust parameters without requiring manual operation, allowing the system to serve itself in the forecasting process.
2Measurement precision
If more data is collected and processed, then forecasting accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by continuously collecting and pre-processing data in the background before it is needed for forecasting. Web crawlers constantly gather market data, and the system pre-computes baseline forecasts and trends, so when actual forecasting is required, the analysis can be completed quickly using pre-prepared data structures and models.
Solution Approach 2:
The patent implements continuous data collection and processing operations that run constantly rather than in discrete batches. The automated system maintains continuous monitoring of market conditions, inventory levels, and demand signals, enabling real-time forecasting updates without interrupting the flow of data processing and reducing overall processing time.
Data Source
AI summary
Provided herein are systems, methods and computer readable media for managing a sales pipeline, and in some embodiments, generating demand based on real time demand and predicted demand. An example method comprises generating a virtual promotion, wherein the virtual promotion comprises a combination of a category or sub-category, a location, and a price range, calculating a probability that a particular consumer would buy the virtual offer in a predetermined time period, wherein the probability is generated at least based on historical data related to the particular consumer and one or more related consumers, determining an estimated number of units to be sold for the virtual offer as a function of at least the probability, the estimated number of units representing a predicted demand, calculating a real time demand, wherein the real time demand is generated based on a plurality of generated identification pairs for the predetermined time period, and determining, using a processor, total demand by summing the predicted demand and the real time demand.