Design Requirements
Creating Design Requirements for Data-Heavy Interfaces
This prompt helps product managers draft design requirements for data-heavy interfaces, such as dashboards or reporting tools. It focuses on defining user needs, functionality, and visual hierarchy to ensure clarity and usability.
Responsible:
Product Management
Accountable, Informed or Consulted:
Product, Design
THE PREP
Creating effective prompts involves tailoring them with detailed, relevant information and uploading documents that provide the best context. Prompts act as a framework to guide the response, but specificity and customization ensure the most accurate and helpful results. Use these prep tips to get the most out of this prompt:
Define the goals and target audience for the data-heavy interface.
Identify key data points and their sources.
Collaborate with stakeholders to understand user needs and technical constraints.
THE PROMPT
Help write detailed design requirements for wireframes of a data-heavy interface in [specific product or feature]. Focus on:
Purpose of the Interface: Explaining what the data is meant to accomplish for users, such as monitoring, analyzing trends, or making decisions.
Key Data Elements: Listing the most critical pieces of information to display, along with their priority and relationships.
Visual Hierarchy: Specifying how to organize and present data for easy scanning, comparison, and interpretation.
Interactions: Documenting required user actions, such as filtering, sorting, or drilling down into data points.
Error and Edge Cases: Highlighting how to handle scenarios like missing data, loading states, or incorrect inputs.
Provide recommendations for structuring the requirements, including references to best practices for data visualization and tools for collaboration (e.g., Figma, Tableau). If additional details about the data sources or user goals are needed, ask clarifying questions to refine the requirements.
Bonus Add-On Prompts
Propose techniques for documenting and prioritizing data visualization types in the design requirements.
Suggest methods for validating the usability of data-heavy wireframes with end users.
Highlight ways to integrate performance considerations for loading and rendering large datasets.
Use AI responsibly by verifying its outputs, as it may occasionally generate inaccurate or incomplete information. Treat AI as a tool to support your decision-making, ensuring human oversight and professional judgment for critical or sensitive use cases.
SUGGESTIONS TO IMPROVE
Focus on specific types of data-heavy interfaces, such as financial dashboards or health monitoring tools.
Include methods for documenting responsive behavior in the design requirements.
Propose strategies for handling sensitive or private data in the interface design.
Highlight tools for creating prototypes of data-heavy interfaces for validation.
Add recommendations for incorporating accessibility standards into data visualization.
WHEN TO USE
During the planning phase of dashboards, analytics tools, or other data-driven interfaces.
To align product and design teams on key data presentation and functionality goals.
When improving the usability of existing data-heavy features.
WHEN NOT TO USE
If the interface is not data-focused or requires minimal information display.
When data sources or user needs are unclear or undefined.