Introduction
DataRobot's AutoML feature has experienced a 15% drop in usage among enterprise customers over the past quarter, raising concerns about its performance and value proposition. This analysis will systematically investigate potential root causes, generate hypotheses, and propose solutions to address this decline in usage.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Seasonal variations could explain temporary usage fluctuations. Expected answer: No significant seasonal pattern observed. Impact on approach: If seasonal, we'd focus on cyclical strategies; if not, we'll investigate other factors.
Why it matters: Helps identify if the issue is widespread or specific to certain user groups. Expected answer: The decline is more pronounced in mid-sized enterprises in the finance sector. Impact on approach: We'd tailor our investigation and solutions to the most affected segments.
Why it matters: Product changes often impact usage patterns. Expected answer: A minor UI update was implemented, but no major feature or pricing changes. Impact on approach: If changes occurred, we'd focus on their impact; if not, we'll look at other factors.
Why it matters: Competitive pressures can influence customer behavior and product usage. Expected answer: A new competitor launched an aggressive marketing campaign last month. Impact on approach: If competition is a factor, we'd analyze our market positioning and differentiation strategies.
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