Cognitive Recommendation Engine for Personalized Cross-Selling
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Solution Overview
Problem
In the retail environment, cross-selling of complementary products between different stores has been limited, even when geographically close, due to a lack of technology that can effectively identify and recommend personalized complementary items to consumers based on their preferences and location.
Innovation Solution
A computer-implemented method using a cognitive recommendation engine that analyzes personal product-related information to produce a list of complementary items and identifies commercially available products, prioritizing them based on individual preferences and availability within a specified distance, allowing for cross-selling between different retailers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a cognitive recommendation engine analyzes personal product-related information to produce personalized complementary items list, then customer satisfaction and sales increase, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments the complex recommendation task into distinct modules: data collection module, analytics engine, product matching module, and recommendation generation module. Each module handles specific aspects of the recommendation process, making the overall system more manageable and maintainable while delivering personalized complementary product recommendations that increase sales
Solution Approach 2:
The cognitive recommendation engine acts as an intermediary between retail stores and consumers, processing personal product-related information and bridging the gap between consumer preferences and available products. This intermediary function enables cross-selling opportunities while managing the complexity of analyzing personal data through standardized interfaces and protocols
2Adaptability or versatility
If the cognitive recommendation engine identifies commercially available complementary products within a specified distance, then cross-selling between stores is enabled, but information processing and location analysis complexity increase
Solution Approach 1:
The recommendation engine is designed as a universal platform that can serve multiple retail stores simultaneously, analyzing location data, product inventory, and consumer preferences across different establishments. This multi-functional system enables cross-selling between stores by identifying complementary products within specified distances, handling diverse data types through standardized processing pipelines that manage information complexity
3Measurement precision
If the system prioritizes complementary products based on individual preferences and availability, then recommendation accuracy improves, but data analysis time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing consumer preference data, product information, and location data in structured formats before recommendation requests are made. Analytics results and product availability information are pre-cached, enabling the system to quickly generate accurate personalized recommendations without extensive real-time computation, thus reducing data analysis time while maintaining high recommendation accuracy
Data Source
AI summary
A process is provided for identifying by a cognitive recommendation engine one or more complementary products. The process includes obtaining an indication that an individual has selected a product, and based on obtaining the indication, performing by the cognitive recommendation engine analytics on prior products-related data for the individual to produce a complementary items list of one or more complementary items to the product that are personal to the individual. Further, the processing includes identifying, by the cognitive recommendation engine, one or more commercially available complementary products corresponding to one or more items within the complementary items list, and providing identifying information for at least one commercially available product of the one or more commercially available products to the individual.