Service Estimation Engine for Pre-Transaction Product Recommendations
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Solution Overview
Problem
Conventional pre-transaction content provider systems cannot effectively provide information about complementary services related to products, leading to increased computational costs and user dissatisfaction due to unavailability of specific services, which hampers the transaction process and user experience.
Innovation Solution
A server system and method that integrates service recommendations with product recommendations during the pre-transaction phase, using a service estimation engine to provide lists of candidate products along with associated auxiliary services, based on historical data and statistical analysis, reducing the load on the transaction system and enhancing user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional pre-transaction content provider systems provide information about complementary services, then user experience and service availability improve, but computational cost and system load increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing service information in a service database before transaction processing. The service estimation engine pre-processes service data and makes it available for quick retrieval during pre-transaction phase, avoiding real-time computational overhead while maintaining service information availability.
Solution Approach 2:
The patent introduces a service estimation engine as an intermediary component between the user interface and the transaction system. This intermediary pre-fetches and estimates service information, filtering and preparing data before it reaches the main transaction processing system, thereby reducing the computational burden on the core system.
2Measurement precision
If the search engine processes each user request in real-time with up-to-date databases, then information accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary computation by pre-processing service information and storing it in the service database. During user requests, the service estimation engine retrieves pre-computed data instead of calculating everything in real-time, significantly reducing processing time while maintaining acceptable accuracy through periodic updates.
Solution Approach 2:
The service estimation engine performs partial computation by estimating service information based on available data without requiring complete real-time database queries. It provides sufficiently accurate service estimates using pre-computed data and statistical methods, avoiding the need for exhaustive real-time processing.
3Loss of information
If the system provides detailed service recommendations with product recommendations, then user decision-making improves, but system complexity and data processing requirements increase
Solution Approach 1:
The patent segments the information provision task into two parts: the transaction system handles product recommendations, while the service estimation engine separately handles service recommendations. This segmentation allows each component to specialize in its function without increasing overall system complexity, as the service estimation engine operates independently using its own database.
Solution Approach 2:
The service estimation engine serves multiple functions: it estimates service availability, predicts service demand, and provides service recommendations across different product types. This multi-functionality reduces the need for separate specialized systems for each service type, thereby managing complexity while providing comprehensive service information.
Data Source
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AI summary
There is provided a system (10) for determining a list of products in response to a client request received from a client device during a request/response session, the client request comprising one or more request parameters, the system comprising a product estimator configured to determine a list of main products, said list of main products comprising an estimation of the one or more main products matching said client request. The system further cooperates with an auxiliary product estimation database storing historical data related to sets of auxiliary products, the historical data being represented by a tree data structure (8) comprising nodes. The system further comprises an auxiliary product estimator (102) for determining, from the tree data structure, an occurrence frequency and an auxiliary product value information for each auxiliary product set in a list of auxiliary product sets, in response to the client request, the list of auxiliary product sets comprising at least one auxiliary product set. The system provides a list of candidate auxiliary products for each main product determined in response to the client request using the occurrence frequency and the auxiliary product information value determined for each auxiliary product set of said list of auxiliary product sets.