Resource Pushing via Conversion Rate Segmentation
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Solution Overview
Problem
Existing resource pushing strategies lack accuracy in targeting users with high conversion rates, leading to inefficient resource utilization and reduced user engagement.
Innovation Solution
A method that divides users into groups based on predicted conversion rates and selects target users within each group based on real conversion rates, ensuring resources are accurately pushed to users with higher likelihoods of conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users are pushed resources using traditional strategies, then resource coverage is achieved, but conversion rate accuracy deteriorates
Solution Approach 1:
The patent segments users into different groups based on their predicted conversion rates. By dividing the user base into high-conversion and low-conversion groups, the system can apply different pushing strategies to each segment, thereby improving overall conversion rate accuracy while maintaining efficient resource utilization.
Solution Approach 2:
The patent changes the parameter of user selection by introducing predicted conversion rate as a key filtering criterion. Instead of pushing resources to all users or using simple demographic segmentation, the system dynamically adjusts user selection based on predicted conversion rate parameters, improving both accuracy and efficiency.
2Productivity
If resources are pushed to all users, then coverage is maximized, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent applies partial action by pushing resources only to the most promising user segments (those with high predicted conversion rates) rather than to all users. This selective approach maintains adequate user coverage while significantly improving resource utilization efficiency by concentrating resources on users most likely to convert.
3Measurement precision
If user segmentation is implemented, then conversion rate accuracy improves, but system complexity deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing predicted conversion rates for users before the resource pushing process. This advance preparation allows the system to quickly segment users during the actual pushing phase without adding significant real-time complexity, thereby improving targeting accuracy while keeping system complexity manageable.
Data Source
AI summary
A method for pushing a resource includes obtaining a collection of users to which a resource is to be pushed, in which the collection includes a plurality of users; obtaining respective predicted conversion rates of the resource for the plurality of users; obtaining user groups by dividing the plurality of users into groups based on respective predicted conversion rates for the plurality of users, in which the user groups correspond to different conversion rate ranges; and for each user group, selecting a target user from the user group based on a real conversion rate related to pushed users corresponding to the conversion rate range of the user group, and pushing the resource to the target user.