Introduction
The recent 25% decrease in GoodData's data modeling feature usage among mid-market clients is a concerning trend that requires immediate attention. To address this issue, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term and long-term implications for our product strategy.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Changes in pricing or features could directly impact usage patterns. Expected answer: No major changes in pricing or features for mid-market clients. Impact on approach: If there were changes, we'd focus on their impact; if not, we'll look elsewhere.
Why it matters: New features or UI changes could affect user behavior and adoption. Expected answer: A minor update was released 2 months ago. Impact on approach: If yes, we'd investigate the update's impact; if no, we'd look at other factors.
Why it matters: Changes in user education could affect feature adoption and usage. Expected answer: No significant changes to onboarding or support. Impact on approach: If changes occurred, we'd examine their effect; if not, we'd explore other areas.
Why it matters: Competitive pressures could drive users to alternative solutions. Expected answer: A new competitor entered the market last quarter with aggressive pricing. Impact on approach: If yes, we'd analyze competitive impact; if no, we'd focus more on internal factors.
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