A/B Testing Gain Correction via Hash Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
A/B testing experiments often suffer from overlapping issues between control and experiment groups, leading to inaccurate measurement of gains and conversion rates, making it difficult to estimate cumulative gains and precise gains for individual experiments, especially when running multiple experiments simultaneously or with smaller user bases.
Innovation Solution
A system and method that allocates users into control and experiment groups, tracks interactions, identifies overlapping users, calculates additional interactions, and adjusts interaction counts to isolate and correct overlapping effects, allowing for precise gain calculation and comparison against predefined thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple A/B testing experiments are run simultaneously, then productivity and efficiency are improved, but measurement precision of individual experiment gains deteriorates due to overlapping control and experiment groups
Solution Approach 1:
The patent segments the user base into distinct non-overlapping groups using advanced hashing techniques. Each experiment has its own dedicated control and treatment groups that are mutually exclusive, eliminating the measurement precision deterioration while maintaining the ability to run multiple experiments simultaneously. The segmentation is achieved through cryptographic hashing of user identifiers combined with experiment-specific parameters.
Solution Approach 2:
The patent introduces an intermediary layer of gain correction calculation that mediates between the overlapping experiment groups and the final gain measurement. This intermediary process computes correction factors based on the overlap between experiments and applies these corrections to isolate the true gain of each individual experiment, thereby restoring measurement precision.
2Measurement precision
If user groups are made mutually exclusive to avoid overlap, then measurement precision is improved, but the number of users required increases significantly
Solution Approach 1:
The patent changes the parameter of group allocation from simple random assignment to advanced cryptographic hashing with multiple parameters. By using hash functions that incorporate both user identifiers and experiment-specific parameters, the system can generate deterministic yet independent group assignments for multiple experiments, achieving measurement precision without requiring a proportionally larger user base.
Solution Approach 2:
The patent performs preliminary gain correction calculations that anticipate and compensate for potential overlaps before they affect the final measurements. By pre-calculating correction factors based on expected overlap patterns, the system maintains measurement precision with the existing user base size rather than requiring additional users.
3Measurement precision
If sequential execution of experiments is performed to avoid overlap, then measurement precision is improved, but productivity deteriorates due to time-consuming serial execution
Solution Approach 1:
The patent enables continuous parallel execution of multiple experiments by implementing gain correction calculations that can be performed concurrently. The useful action of running experiments continues uninterrupted for multiple experiments simultaneously, with the correction layer operating in parallel to maintain measurement precision without sacrificing productivity.
Solution Approach 2:
The gain correction mechanism serves as an intermediary that allows parallel experiment execution while maintaining measurement precision. Instead of requiring sequential execution, the intermediary correction layer processes overlapping results from parallel experiments and extracts accurate individual gains, thereby preserving both productivity and measurement precision.
4Quantity of substance
If experiments are extended beyond two months to accumulate sufficient users, then the required user quantity is achieved, but loss of time increases and experiment uniformity deteriorates
Solution Approach 1:
The patent changes the parameter of user allocation using cryptographic hashing techniques that can effectively utilize smaller sample sizes. By implementing advanced gain correction methods that account for statistical variations, the system achieves reliable measurements with smaller user quantities, thereby reducing the time required to complete experiments while maintaining result validity.
Data Source
AI summary
The present invention discloses a system and a method for correcting overlapping issues in A/B testing experiments. The system is configured to allocate a plurality of control versions of a webpage to a plurality of control groups and a plurality of experimental versions of a webpage to a plurality of experimental groups. The system is further configured to calculate a first experiment gain for each of the plurality of experimental versions of the webpage based on a number of users identified for carrying out an interaction in the each of the plurality of experimental versions of the webpage. The system is configured to calculate a second experiment gain for each of the plurality of experimental versions of the webpage using a modified number of interactions. Further, the system is configured to calculate a final gain based on the first experiment gain and the second experiment gain.