Introduction
To improve Tiger Analytics' data visualization tools for non-technical users, we need to focus on simplifying complex data insights while maintaining depth and accuracy. I'll outline a strategic approach to enhance accessibility, usability, and value for our target audience.
Framework overview
I'll start by asking clarifying questions, then analyze user segments and pain points. From there, I'll generate and evaluate solutions, prioritize them, and propose metrics for measuring success.
Step 1
Clarifying Questions (5 mins)
Why it matters: Determines the level of simplification needed and specific features to prioritize Expected answer: Mid-level managers and executives across various departments Impact on approach: Would focus on high-level insights and executive-friendly visualizations
Why it matters: Helps identify areas of friction and opportunities for improvement Expected answer: Weekly usage, primarily for report generation and basic data exploration Impact on approach: Would prioritize streamlining report creation and enhancing data exploration capabilities
Why it matters: Identifies areas where we can differentiate and improve Expected answer: We excel in data processing but lag in user-friendly interfaces Impact on approach: Would focus on UI/UX improvements while leveraging our data processing strengths
Why it matters: Ensures our solution aligns with overall company goals Expected answer: Expanding market share in non-technical segments and increasing user engagement Impact on approach: Would balance feature accessibility with potential for upselling advanced capabilities
Tip
At this point, I'd like to take a 1-minute break to organize my thoughts before diving into the next step.
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