Product Configuration Menu with Distance-Based Recommendation
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Solution Overview
Problem
In e-commerce for original equipment manufacturers (OEMs), customers find it difficult to distinguish between pre-built and custom products, as well as custom and pre-built options, leading to challenges in selecting suitable products with short and predictable ship dates.
Innovation Solution
A computing system outputs a product configuration menu that allows users to select components, detects user input changes, and uses a product distance data structure to identify and display a candidate product with the smallest product distance score, ensuring the selected product is as similar as possible to the original, thereby facilitating customer choices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If OEMs offer both pre-built and custom products to satisfy all customer requirements, then customer requirements can be fully satisfied, but it becomes difficult for customers to distinguish between different product options
Solution Approach 1:
The patent segments the product catalog into pre-built and custom categories with distinct visual presentations. Pre-built products are displayed with inventory availability indicators, while custom products are presented with configuration options. This segmentation helps customers clearly distinguish between product types and make informed decisions.
Solution Approach 2:
The patent introduces a product recommendation system that acts as an intermediary between customer needs and product options. When a custom product is selected, the system automatically identifies and presents similar pre-built alternatives, facilitating easier comparison and decision-making without requiring customers to manually analyze all product differences.
2Loss of time
If OEMs maintain pre-built inventory to ensure short and predictable ship dates, then delivery predictability is improved, but the ability to meet all custom customer requirements is reduced
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors inventory levels, customer preferences, and order patterns. When custom products are configured, the system provides feedback about available pre-built alternatives with similar specifications and availability, enabling customers to make time-sensitive decisions while still meeting their requirements.
Solution Approach 2:
The patent performs preliminary actions by pre-calculating and storing similarity relationships between custom and pre-built products in advance. When a customer configures a custom product, the system can immediately retrieve and present relevant pre-built alternatives without requiring complex real-time analysis, thus maintaining both customizability and fast response times.
3Adaptability or versatility
If the system supports full custom builds to meet all customer requirements, then customer requirement satisfaction is improved, but ship dates become longer and unpredictable
Solution Approach 1:
The patent introduces an automated recommendation system that mediates between custom configuration desires and pre-built availability. When customers configure custom products, the system automatically identifies similar pre-built alternatives and presents them as options, enabling customers to potentially switch to faster-delivering pre-built products while still meeting their core requirements.
4Adaptability or versatility
If the system presents multiple product options to customers, then customer choice is increased, but customer decision-making complexity increases
Solution Approach 1:
The patent introduces a smart recommendation system that acts as an intermediary to filter and prioritize product options. Instead of presenting all possible products, the system analyzes customer configurations and preferences to present a curated subset of relevant alternatives, significantly reducing decision complexity while maintaining option variety.
Solution Approach 2:
The patent applies local quality by tailoring the information presentation to each customer's specific configuration and preferences. The system dynamically adjusts which product attributes and alternatives are highlighted based on the customer's needs, rather than presenting uniform information for all customers, thereby simplifying decision-making for each individual user.
Data Source
AI summary
A method for use in a computing system, comprising: outputting, by the computing system, a product configuration menu that specifies a first set of product components; outputting, by the computing system, information associated with a first product, the first product including the first set of product components; detecting, by the computing system, a user input that specifies a second set of product components, the user input being received via the product configuration menu; selecting, by the computing system, a second product that includes the second set of product components, the second product being selected by performing a search of a product distance data structure to identify a plurality of candidate products that include the second set of product components, obtaining a respective product distance score for the first product and each of the plurality of candidate products, and selecting one of the candidate products as the second product.