Keyword Research Canvas with Drag-and-Drop Grouping
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Solution Overview
Problem
Current keyword research tools are inefficient and cumbersome for Internet marketers and SEO professionals, as they require manual and time-consuming processes to manipulate and display data, such as requiring users to click checkboxes and navigate through folders, making it difficult to identify and select the best keywords for driving internet traffic.
Innovation Solution
A computer-based system that allows users to import keywords from various sources, automatically groups them into hierarchical structures using 'grouping blocks' with drag-and-drop functionality, enabling manual override and visualization of data in a graphical user interface, with features like grouping blocks, tagging, and data aggregation to facilitate keyword selection and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If keyword research tools use traditional manual processes with checkboxes and folder navigation, then data manipulation is possible, but user efficiency and productivity are reduced
Solution Approach 1:
The patent replaces traditional mechanical UI interactions (checkboxes, folder navigation, click sequences) with a visual canvas-based drag-and-drop system. Keywords are represented as movable objects on an infinite canvas that can be directly manipulated by dragging, eliminating the need for checkbox selection and hierarchical folder navigation. This substitution of mechanical interaction patterns with direct visual manipulation resolves the contradiction by making data manipulation both easier and more productive.
Solution Approach 2:
The patent transitions from a traditional hierarchical folder structure (vertical/dimensional navigation) to an infinite canvas workspace (two-dimensional spatial arrangement). Keywords can be positioned freely on the canvas and organized into groups visually, allowing users to manipulate data in a two-dimensional space rather than navigating through multiple hierarchical levels. This dimensional change enables more efficient keyword research by allowing simultaneous visualization and manipulation of multiple keywords in a single view.
2Loss of time
If keyword research tools require multiple clicks and navigation steps, then data can be accessed, but time consumption increases
Solution Approach 1:
The patent extracts keywords from their traditional confined locations (search results pages, spreadsheets, documents) and places them directly onto an infinite canvas workspace. This extraction eliminates the need to navigate between multiple applications or pages, allowing users to import keywords from various sources and immediately manipulate them in a single unified interface. By taking keywords out of their original contexts and consolidating them in one workspace, the system reduces time consumption and interface complexity.
Solution Approach 2:
The patent performs preliminary organization and visualization of keywords on the canvas before the user begins analysis. Keywords can be imported and automatically displayed on the canvas in a ready-to-manipulate state, with options for automatic grouping or individual placement. This preliminary arrangement eliminates the need for users to spend time setting up their workspace or navigating through multiple steps to access keywords, allowing them to immediately begin keyword research and selection tasks.
Data Source
AI summary
The various implementations of the present invention are provided as a computer-based system for manipulating and displaying data. The system can be deployed as a keyword research tool configured pull keywords into the system from a variety of sources such as through various application programming interfaces (“API”), allow the user to copy and paste, import via a file format such as CSV, etc. or enter seed keywords that our system uses to find related keyword phrases from an internal database or external database via an application programming interface (“API”). The keywords are displayed to the user in groups with associated grouping blocks that will most often include blocks in the shape of an “inverted L” configuration to provide maximum utility. In the most preferred embodiments of the present invention, each keyword also comprises a plurality of associated metrics such as search volume, cost per click, competition level, etc. The grouping block is a general purpose invention that can be utilized in a variety of areas where grouping hierarchical information is required.