Custom Visitor Stitching via Data Science Notebooks

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing web analytics systems lack transparency and customization in the visitor stitching process, leading to inaccurate results and inefficient use of computational resources.

Innovation Solution

The use of data science notebooks to customize visitor stitching frameworks, allowing resource providers to modify and tailor the stitching process to their specific needs and data peculiarities.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If off-the-shelf stitching products are used, then implementation speed is improved, but transparency and customization are lost

Engineering Contradiction:

Improveimplementation speedVSAvoidcustomization capability

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The stitching process is divided into discrete, modular operations that can be independently selected and configured. Each stitching operation is a separate unit that can be customized through parameters and settings, allowing customers to build their own stitching pipeline from available operations rather than using a monolithic black-box solution.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The stitching framework allows dynamic configuration and adjustment of stitching operations based on customer-specific needs. Customers can modify stitching parameters, add or remove operations, and adapt the pipeline to their particular data characteristics and requirements, making the system flexible rather than static.

Inventive Principle:

Principle #15Dynamics

2Device complexity

If uniform stitching operations are applied to all customers, then system simplicity is maintained, but accuracy deteriorates due to customer-specific data peculiarities

Engineering Contradiction:

Improvesystem simplicityVSAvoidstitching accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The system enables customers to apply localized adjustments to the stitching process based on their specific data characteristics. For example, customers can configure different stitching operations for different data sources or adjust parameters to account for their particular calling conventions and data formats, ensuring accuracy without requiring complete system redesign.

Inventive Principle:

Principle #3Local quality

3Quantity of substance

If call center agent data is included in stitching, then data completeness is improved, but accuracy deteriorates due to agent-user conflation

Engineering Contradiction:

Improvedata completenessVSAvoidvisitor identification accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The system allows customers to extract and exclude specific data sources or operations that are known to cause problems. Customers can identify and remove stitching operations that conflate call center agents with actual users, while retaining other beneficial stitching operations. This selective extraction maintains data completeness from valid sources while eliminating harmful conflations.

Inventive Principle:

Principle #2Taking out (Extraction)

4Reliability

If unnecessary stitching operations are executed, then comprehensive processing is achieved, but computational efficiency deteriorates

Engineering Contradiction:

Improveprocessing completenessVSAvoidcomputational efficiency

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system implements a stitching framework where customers can select and execute only the necessary subset of stitching operations for their specific needs. Rather than forcing all possible operations to run on every dataset, customers can configure their pipeline to perform only the operations required for their particular use case, reducing unnecessary computational overhead while maintaining processing completeness for the selected operations.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12254360B2Visitor stitching with data science notebooks

Publication Date: 2025.03.18 ADOBE INC

AI summary

This disclosure involves using data science notebooks to customize and apply a visitor stitching framework. An event management system provides an initial visitor stitching framework via a data science notebook, wherein the data science notebook is an interactive environment for managing algorithms and data. The event management system receives, from a resource provider system via the data science notebook, a modification to the initial visitor stitching framework. The event management system applies the modification to the initial visitor stitching framework to generate a custom visitor stitching framework. The event management system processes a dataset associated with the resource provider system and a user using the custom visitor stitching framework to generate a stitched dataset associated with the user.