Introduction
The sudden 25% decline in client satisfaction scores for TransPerfect's website localization services over the past two weeks is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our product and business.
I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into our product, metrics, and potential internal causes. We'll generate data-driven hypotheses, conduct root cause analysis, and develop a comprehensive plan to resolve the issue and prevent future occurrences.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, a new machine learning algorithm was implemented. Impact on approach: If true, we'd focus on the new algorithm's performance and integration.
Why it matters: Ensures the data is statistically significant and consistently measured. Expected answer: Scores from 500+ clients, no change in measurement. Impact on approach: If sample size is small or inconsistent, we'd need to validate the data first.
Why it matters: Helps isolate whether this is a service-specific or company-wide issue. Expected answer: Other services' scores are stable. Impact on approach: If true, we'd focus exclusively on website localization processes.
Why it matters: Changes in client base or project complexity could affect satisfaction scores. Expected answer: No significant changes noted. Impact on approach: If changes exist, we'd analyze how they might impact satisfaction scores.
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