Dynamic Electronic Bid Adjustment via Time-Period Segmentation
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Solution Overview
Problem
Existing methods for determining electronic bid values for digital content objects in advertising struggle to dynamically adjust bid values based on varying interaction rates over different time periods, leading to inefficiencies such as wasted resources and improper allocation of storage and computing resources.
Innovation Solution
A system and method that programmatically generates conversion rates for different network time segments, calculates multiplier values based on these rates, and adjusts electronic bid values accordingly to optimize performance during day and night periods, using geolocation data to divide time periods and assess conversion performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electronic bid values are determined using static methods without considering time period variations, then the bidding process is simple and computationally efficient, but the conversion performance and resource allocation are suboptimal
Solution Approach 1:
The patent segments the bidding process by dividing network time periods into multiple time period segments (e.g., day time period and night time period), and further divides each segment into intervals. This segmentation allows the system to generate specific conversion rates for each segment and interval, enabling precise bid adjustments that improve conversion performance without requiring complete redesign of the bidding system.
Solution Approach 2:
The patent implements dynamic bid adjustment by continuously monitoring conversion rates across different time period segments and intervals, then programmatically adjusting electronic bid values based on performance metrics. The system dynamically generates multiplier values comparing actual conversion rates to baseline rates, allowing bids to adapt in real-time to varying performance conditions throughout the day and night periods.
2Productivity
If bid values are adjusted frequently based on real-time conversion rates, then conversion performance is optimized, but computational resources and processing time increase
Solution Approach 1:
The patent applies partial action by focusing computational efforts on specific high-value time period segments and intervals rather than uniformly processing all time periods. The system identifies and prioritizes segments with better conversion performance or higher business value, adjusting bids more aggressively during these periods while using fewer computational resources during lower-priority periods, thus optimizing the balance between performance and resource consumption.
Solution Approach 2:
The patent performs preliminary actions by pre-defining time period segments, intervals, and baseline conversion rates before the actual bidding process begins. Historical conversion data is analyzed in advance to establish baseline rates for different segments, allowing the system to quickly compare real-time performance against pre-established benchmarks without performing complex calculations during live bidding operations.
3Measurement precision
If the system divides time periods into multiple segments and generates conversion rates for each segment, then bid adjustment precision is improved, but the complexity of data processing and analysis increases
Solution Approach 1:
The patent segments the time periods into day time periods and night time periods, with each further divided into multiple intervals. This segmentation structure allows the system to generate specific conversion rates for each segment and interval, improving measurement precision by capturing temporal variations in user behavior and conversion patterns without overwhelming the processing system through excessive granularity.
Solution Approach 2:
The patent merges data processing by aggregating conversion signals and interaction signals across multiple intervals within each time period segment to generate segment-level conversion rates. This merging approach reduces the volume of individual data points that need to be processed while maintaining precision through the structured segmentation framework, as the system processes aggregated metrics rather than individual user interactions.
4Adaptability or versatility
If the system uses geolocation data to determine day and night time periods for different regions, then global ad placement performance is improved, but data processing requirements and system complexity increase
Solution Approach 1:
The patent applies local quality by tailoring time period definitions to specific geographic locations using geolocation data. Each region or market can have its own day time period and night time period definitions based on local time zones and regional user behavior patterns. This allows the system to optimize bid adjustments for local conditions while maintaining a unified global bidding framework, improving adaptability without requiring complete system redesign for each region.
Data Source
AI summary
Embodiments of the present disclosure provide methods, systems, and apparatuses for programmatically determining and adjusting electronic bid values for a digital content object based on different conversion rates during different network time periods.