Idea List Ranking Algorithm for Sales Knowledge Sharing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Sales personnel often generate product ideas in isolation, leading to missed opportunities for sharing successful suggestions and guiding customers in their purchasing decisions, as existing systems lack effective mechanisms for collaborative idea sharing and feedback.
Innovation Solution
A system and method for creating and sharing 'idea lists' with weighted attributes, popularity scores, and relevance-based ranking, where users can add products to lists, view and copy items, and earn points for list interactions, promoting the propagation of popular and relevant ideas across the sales platform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sales people generate product ideas in isolation, then individual creativity is maintained, but knowledge sharing and collaboration are lost
Solution Approach 1:
The patent merges isolated individual idea generation with collaborative knowledge sharing by creating a unified system where sales people's idea lists are aggregated into a shared database. This allows individual creativity to be preserved while simultaneously enabling team-wide access and collaboration through the central idea sharing platform.
Solution Approach 2:
The patent introduces an intermediary system - the idea sharing platform with its database and ranking mechanisms - that mediates between individual sales people and the organization. This intermediary captures, stores, and distributes product ideas while providing structured access through relevance ranking and popularity metrics, thus enabling knowledge transfer without direct interpersonal interaction.
2Measurement precision
If idea lists are ranked by relevance only, then search accuracy is improved, but popular successful ideas may be overlooked
Solution Approach 1:
The patent changes the ranking parameter from purely relevance-based to a hybrid model that incorporates both relevance metrics and popularity signals. This dual-parameter approach ensures that ideas are ranked not only by their semantic match to search queries but also by their proven effectiveness in generating sales, thus balancing search accuracy with commercial productivity.
Solution Approach 2:
The patent implements feedback loops where sales performance data and user interaction metrics continuously inform the ranking algorithm. Successful ideas that generate sales or receive engagement are fed back into the system to boost their visibility, creating a self-reinforcing mechanism that identifies and promotes high-performing product recommendations while maintaining relevance to customer needs.
3Loss of information
If all idea lists are displayed equally, then comprehensive information is provided, but user attention and engagement are reduced
Solution Approach 1:
The patent applies local quality by differentiating the visibility and prominence of individual idea lists based on their attributes such as relevance score and popularity metric. Rather than treating all ideas uniformly, the system selectively enhances the presentation of high-quality ideas through ranking and featured positioning, while still maintaining access to the full set of ideas for users who wish to explore comprehensively.
4Measurement precision
If the system tracks detailed user interactions to improve ranking accuracy, then recommendation quality is enhanced, but data processing complexity increases
Solution Approach 1:
The patent extracts and isolates the key interaction data elements needed for ranking - such as views, copies, and sales - from the broader user behavior dataset. By focusing only on these specific, high-value metrics rather than processing all possible user interactions, the system achieves accurate ranking while minimizing data processing complexity and computational overhead.
Data Source
AI summary
Methods and systems for identifying products and product idea lists. A method is provided which includes searching a product index for a result. The result is used to search an idea list index for idea lists related to the result wherein each idea list includes at least one product and has an associated popularity and relevance to the search. The method also includes outputting at least some of the idea lists based on the popularity and relevance of the idea lists. In one embodiment a method of identifying product idea lists is provided. The method includes searching a product index for keywords associated with products in a product idea list. The method also includes using the keywords to search a product idea index for other idea lists and outputting the other idea lists based on their popularities. In some embodiments, the popularities may be based on time-weighted events.