When faced with conflicting customer data, I first verify data sources for accuracy and potential biases. I use **A/B testing** and audience segmentation to validate insights and adapt strategies. Engaging with customers through **surveys and feedback** helps add context. By continuously optimizing campaigns and making data-driven adjustments, I turn inconsistencies into opportunities for better decision-making.

When faced with conflicting data on customer behavior, I take a structured approach to uncover the root cause and make informed decisions: 1. Validate Data Sources: Ensure accuracy by checking for tracking errors or biases with multiple tools available 2. Segment the Data: Break it down by cohorts and traffic sources to pinpoint discrepancies 3. Run Experiments: Use A/B testing to validate assumptions and uncover real-time customer preferences 4. Leverage Qualitative Insights: Analyze heatmaps and customer feedback to complement quantitative data 5. Align with Business Goals: Prioritize decisions that drive revenue, retention, and long-term growth This structured approach helps me make data-driven decisions with confidence

When faced with conflicting data on customer behavior, start by analyzing the sources—identify which data is more reliable and relevant. Cross-check with historical trends, market research, and customer feedback. Engage directly with key customers to validate assumptions and uncover insights. Stay flexible and open-minded, adjusting strategies based on emerging patterns rather than clinging to outdated assumptions. Collaborate with your team to brainstorm solutions and align on a revised approach. Use A/B testing or pilot programs to test new strategies before full implementation. Ultimately, let the most credible data guide your decisions while remaining adaptable to ongoing changes.

En una ocasión, datos de uso del cliente contradijeron las preferencias declaradas en encuestas. En lugar de asumir cuál era correcto, realizamos pruebas A/B para validar hipótesis y organizamos sesiones de retroalimentación directa con los usuarios. El resultado nos permitió identificar una necesidad oculta y ajustar la oferta, logrando una mejora significativa en la adopción del servicio