Joint Conversion Rate and Latency Distribution Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional approaches for modeling conversion profiles in online advertising campaigns separately estimate conversion rates and latency distributions without considering their explicit correlation, leading to inaccurate and biased determinations, which can result in ineffective resource allocation and missed opportunities.
Innovation Solution
A computer-implemented method that simultaneously determines conversion rates and latency distributions by employing a constraint relationship between them, using maximum likelihood estimation and iterative methods like interior point or Newton-Raphson, and allows for any statistical distribution, such as a Pareto distribution, to accurately model the conversion profile.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conversion rates and latency distributions are estimated separately using conventional approaches, then the estimation process is simple and independent, but the determination becomes inaccurate and biased due to ignoring their explicit correlation
Solution Approach 1:
The patent combines the separate estimation processes of conversion rates and latency distributions into a unified joint estimation framework. By simultaneously estimating both parameters while accounting for their explicit correlation, the system resolves the technical contradiction by improving measurement precision through integration, accepting increased methodological complexity as necessary for accurate conversion profile determination.
Solution Approach 2:
The patent transforms the estimation approach by changing from independent parameter estimation to joint parameter estimation. This parameter change enables the system to capture the explicit correlation between conversion rates and latency distributions, thereby improving the accuracy of conversion profile determination while managing the complexity through structured mathematical modeling.
2Productivity
If separate estimation methods are used for conversion rates and latency distributions, then the computational process is faster and simpler, but resource allocation becomes ineffective due to biased results
Solution Approach 1:
The patent implements a feedback mechanism where the joint estimation of conversion rates and latency distributions provides more reliable inputs for resource allocation decisions. By capturing the explicit correlation between these parameters, the system generates feedback that improves the reliability of productivity and resource allocation outcomes, ensuring that faster processing does not compromise decision-making quality.
3Ease of manufacture
If conventional separate estimation approaches are applied, then the modeling process is easier to implement, but conversion opportunities are missed due to inaccurate conversion profiles
Solution Approach 1:
The patent merges the separate estimation processes into a unified joint estimation framework that simultaneously determines conversion rates and latency distributions while accounting for their explicit correlation. This integration improves measurement precision by capturing the interdependence between parameters, ensuring more accurate conversion profile determination despite increased implementation complexity.
Solution Approach 2:
The patent changes the estimation parameters from independent to jointly estimated variables. This parameter transformation enables the system to accurately capture the explicit correlation between conversion rates and latency distributions, improving the precision of conversion profile determination and preventing missed conversion opportunities.
Data Source
AI summary
Embodiments are directed at determining a conversion rate and a latency distribution for an online campaign. The conversion rate indicates a ratio of an overall number of converted impressions to the number of previously provided impressions. The converted impressions are a subset of the set of previously provided impressions. One method includes receiving conversions from the campaign and determining an observed latency for the conversions. Each conversion is uniquely associated with one of the converted impressions. The observed latencies are based on a temporal difference between the conversion and the associated converted impression. The method simultaneously determines each of the conversion rate and parameters of the latency distribution. The latency distribution indicates a temporal distribution of the observed latencies. Determining the conversion rate and parameters of the distribution is based on employing a constraint or relationship between the conversion rate and the distribution and an interior point or Newton-Raphson method.