Automatic Behavior Collection Embedding in Mobile Apps
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Solution Overview
Problem
Current mobile device applications face challenges in efficiently collecting user behavior data, as developers must communicate with designers and market experts to embed data collection program codes, leading to increased complexity and time costs, especially when modifications are needed.
Innovation Solution
A system comprising a user interface module, recording module, marking module, and embedding module that allows for the automatic embedding of behavior collection components into mobile device applications, providing an easy-to-use interface for selecting tracking items and determining embedding positions, enabling non-technical personnel to integrate behavior collection components without requiring extensive programming knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If developers manually embed behavior collection component by communicating with designers and writing program codes, then data collection functionality is achieved, but the process becomes complicated and time-consuming
Solution Approach 1:
The system pre-processes the mobile device application to identify embedding positions before the actual embedding occurs. The marking module analyzes the application structure in advance, determines suitable locations for behavior collection components, and prepares embedding information, thereby simplifying the subsequent embedding process and reducing complexity.
Solution Approach 2:
The system enables automatic embedding of behavior collection components without requiring manual intervention from developers. The embedding module automatically integrates the components into identified positions based on pre-analyzed embedding information, making the process self-service and eliminating the need for developers to write program codes manually.
2Reliability
If developers manually write program codes for behavior collection, then data collection is implemented, but modification becomes inconvenient when APP changes are needed
Solution Approach 1:
The marking module performs preliminary analysis to generate embedding information that is separate from the application code. This embedding information serves as a configuration layer that can be modified independently when the application changes, without requiring changes to the application source code itself, thus improving ease of repair.
Solution Approach 2:
The system separates the behavior collection functionality into independent components that are embedded at specific positions. The embedding information is segmented and stored separately, allowing individual components to be modified or adjusted without affecting the entire application, thereby facilitating easier maintenance and updates.
3Adaptability or versatility
If designers or market developers directly set tracking items, then data collection requirements are met, but technical knowledge is required which they lack
Solution Approach 1:
The system introduces an intermediary layer between the non-technical users (designers or market developers) and the technical implementation. Users can configure tracking items through a simplified interface without needing to understand programming details. The system automatically translates these high-level configurations into the appropriate behavior collection components and embedding information, making the process accessible to non-technical personnel.
Solution Approach 2:
The system provides self-service capabilities that allow users to configure and embed behavior collection components through automated processes. The marking module and embedding module work automatically based on user selections, eliminating the need for users to manually write or modify program codes, thus enabling non-technical personnel to perform tasks that previously required programming knowledge.
Data Source
AI summary
A system for automatically embedding behavior collection components into a mobile device application; the system includes a user interface module, a recording module, a marking module, and an embedding module. The user interface module provides an operation interface which includes tracking items. The tracking items correspond to behavior collection components. The behavior collection components transmit operation information of the mobile device to a server. The recording module records relational information respectively corresponds to each of the behavior collection components, and each relational information is a relational function selected from of a plurality of relational functions of a library. The marking module determines and marks embedding positions of the behavior collection components in the mobile device application based on the behavior collection components of the selected tracking items and relational information thereof. The embedding module embeds the behavior collection components of the selected tracking items into the marked embedding positions.