Dynamic Price Range Determination for Search Interfaces
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Solution Overview
Problem
Users face challenges in determining typical or popular price ranges for goods and services on electronic marketplaces, as they often lack specific price points or ranges in mind when searching, and current systems do not provide a straightforward way to find these ranges amidst a vast assortment of offerings.
Innovation Solution
A dynamic price range determination system that uses application servers to determine popular price ranges for items based on received search queries, leveraging data from listings, auctions, and external sources, and continuously updates pricing information to provide current and relevant pricing insights to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the publication system displays a wide variety of items or services for sale, then the user can access more options, but the user cannot quickly determine typical or popular price ranges for searched items
Solution Approach 1:
The system performs preliminary computation of price ranges and popular prices before the user needs to view search results. The server calculates price statistics in advance and stores them, so when a user searches for items, the price range information is already ready to be displayed immediately, eliminating the need for the user to manually determine prices from extensive listings.
Solution Approach 2:
The system introduces price range information as an intermediary element between the user's search query and the actual item listings. By displaying computed price ranges as a summary statistic before the user examines individual items, the system provides a quick reference point that mediates the user's understanding of typical prices without requiring them to analyze each listing individually.
2Measurement precision
If the publication system provides detailed search results, then the user can find relevant items, but the user cannot quickly determine pricing information without examining multiple listings
Solution Approach 1:
The system segments the pricing information from the individual item listings by computing aggregate price statistics separately. Instead of requiring users to examine multiple listings to determine price ranges, the system presents a summarized price range statistic that is calculated from the collective pricing data of relevant items, making price information easily accessible without sacrificing search result relevance.
Solution Approach 2:
The system automatically computes and displays price range information without requiring active user intervention to determine prices. The server self-services the price range calculation by aggregating pricing data from relevant listings and presenting the results automatically, eliminating the need for users to manually examine multiple items to understand typical pricing.
3Reliability
If the publication system updates pricing information continuously, then the pricing data remains current and relevant, but the system complexity increases
Solution Approach 1:
The system implements continuous feedback loops where pricing information is automatically updated based on current marketplace conditions. The server monitors changes in listing prices and dynamically recalculates price ranges and popular prices, ensuring that the displayed information remains current and relevant without requiring complex manual intervention or overly sophisticated processing systems.
Data Source
AI summary
Several systems, apparatuses, and methods are described. A data transmission that includes data indicating a first search query for an item of a publication system is received from a client machine. A first plurality of search results is determined from listed items based, at least in part, on the first search query, and the first plurality of search results are each associated with a price. A range of prices associated with a first subset of the search results is determined based on a price distribution range including a median price associated with the first search results, or a utility cost function using a plurality of price quantiles and a plurality of price values included in different price quantiles. The determined first search results and the range of prices associated with the first subset of the first search results are transmitted to the client machine for display.