Retail Product Price Band Classification System
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Solution Overview
Problem
Existing methods for classifying retail products and services using price-based groupings are inefficient and time-consuming, especially when prices frequently change, as they require ad-hoc adjustments that are not convenient for reporting and analysis.
Innovation Solution
A system and method for classifying retail products and services using price level groups, where each group is defined with a price schema having multiple price levels associated with price band categories, allowing for efficient assignment and analysis of sales data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If ad-hoc price-based groupings are created to account for frequent price changes, then the classification can adapt to price variations, but the creation and maintenance of such groupings becomes inefficient and time consuming
Solution Approach 1:
The patent applies preliminary action by pre-defining price band categories (e.g., budget, mid-range, premium) and price level groups before actual classification is needed. When products need classification, the system automatically assigns them to predefined price bands based on current prices, eliminating the need for manual ad-hoc grouping. This resolves the contradiction by making the system adaptable to price changes through pre-established categories while maintaining high productivity through automated assignment.
Solution Approach 2:
The patent uses parameter changes by transforming the continuous price parameter into discrete price band categories. Instead of manually creating groupings for every price variation, the system automatically maps products to appropriate price bands based on price thresholds. This allows the classification to adapt to frequent price changes while maintaining efficiency through automated parameter transformation rather than manual intervention.
2Measurement precision
If manual ad-hoc price groupings are created for each price change, then accurate classification is maintained, but the time and effort required increases significantly
Solution Approach 1:
The patent applies self-service by enabling the classification system to automatically update and maintain price band assignments without manual intervention. When product prices change, the system automatically re-evaluates and reassigns products to appropriate price bands based on predefined criteria. This maintains accurate classification while eliminating the time loss associated with manual group creation, as the system serves itself by automatically adapting to price changes.
Solution Approach 2:
The system performs preliminary action by pre-establishing price band categories and assignment rules before classification is needed. This allows automated, accurate classification to occur without manual intervention when prices change, maintaining measurement precision through pre-defined criteria while eliminating the time required for manual group creation.
3Loss of information
If price-based classification is used for retail products, then sales data analysis becomes possible, but frequent price changes render the classification obsolete and require constant updates
Solution Approach 1:
The patent applies dynamics by making the price classification system dynamic rather than static. Instead of creating fixed price groupings that become obsolete when prices change, the system continuously monitors price changes and automatically reassigns products to appropriate price bands. This maintains the validity of classification over time despite frequent price changes, preserving the utility of sales data analysis without requiring constant manual updates.
Solution Approach 2:
The system uses self-service to automatically maintain valid classifications despite price changes. When prices change, the system automatically re-evaluates and updates price band assignments without external intervention. This extends the duration of action of the classification by making it self-updating, ensuring sales data remains useful without requiring manual maintenance.
Data Source
AI summary
A method of and system for classifying retail products and services. The method of classifying retail products and services includes defining a price level group in a computerized system, wherein the price level group includes a price schema having a plurality of price levels, and wherein each price level is associated with a price band category. The method also includes assigning the price level group to a grouping of at least one of services and retail products.