Customer Data Analyst
Role summary
Seeking a detail-oriented Customer Data Analyst to analyze customer data, identify trends, and provide actionable insights. Responsibilities include data collection, cleaning, and analysis; developing dashboards and reports; measuring customer metrics; and collaborating with cross-functional teams. Requires proficiency in SQL, experience with data visualization tools (Power BI, Tableau, Looker), and knowledge of CRM systems (Salesforce, HubSpot). Preferred skills include Python/R, customer segmentation, and A/B testing.
We are seeking a detail-oriented Customer Data Analyst to analyze customer data, identify trends, and provide actionable insights that support business decisions. The ideal candidate has strong analytical skills, experience with data visualization tools, and the ability to communicate findings to both technical and non-technical stakeholders.
Key Responsibilities:
- Collect, clean, and analyze customer data from multiple sources.
- Identify customer behavior patterns, trends, and segmentation opportunities.
- Develop dashboards and reports to monitor key customer metrics.
- Measure customer satisfaction, retention, churn, and lifetime value.
- Collaborate with marketing, sales, and customer service teams to optimize customer engagement strategies.
- Perform statistical analysis to support business decisions.
- Ensure data accuracy, integrity, and compliance with data privacy regulations.
- Present insights and recommendations to stakeholders.
- Monitor campaign performance and customer journey metrics.
- Automate recurring reports and improve data processes where possible.
Required Qualifications:
- Bachelor's degree in Data Analytics, Statistics, Mathematics, Business, Computer Science, or a related field.
- 2+ years of experience in data analysis or business intelligence.
- Proficiency in SQL for data extraction and analysis.
- Experience with Excel, Power BI, Tableau, or Looker.
- Knowledge of Python or R for data analysis is preferred.
- Understanding of CRM systems such as Salesforce or HubSpot.
- Strong analytical, problem-solving, and communication skills.
Preferred Skills:
- Customer segmentation and predictive analytics.
- Data visualization and storytelling.
- Knowledge of A/B testing methodologies.
- Experience working with large datasets.
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
- Understanding of customer lifecycle management and marketing analytics.
Key Performance Indicators (KPIs):
- Customer retention rate
- Customer churn rate
- Customer Lifetime Value (CLV)
- Customer Acquisition Cost (CAC)
- Net Promoter Score (NPS)
- Data accuracy and report delivery timeliness
- Dashboard adoption and stakeholder satisfaction
