Product Performance Data Analyst
Budget: $15 – $25 USD
Data Analysis: Collect, analyze, and interpret data to identify trends, opportunities, and challenges in the product performance.
Market Research: Conduct competitive and market research to understand customer needs, market trends, and industry best practices.
Product Strategy Support: Collaborate with product managers to develop and refine product strategies based on data and market insights.
Reporting and Dashboards: Create regular reports, dashboards, and visualizations to track product performance and key metrics.
Customer Insights: Work closely with customer-facing teams to gather and analyze feedback from customers, and turn this into actionable product improvements.
A/B Testing & Experimentation: Design and analyze A/B tests to optimize product features, user experience, and conversion rates.
Cross-Functional Collaboration: Work with engineering, design, marketing, and sales teams to support product launches, monitor performance, and gather feedback.
Data-Driven Decision Making: Assist in prioritizing product features and improvements based on data, and help define success metrics for each feature.
Documentation & Reporting: Maintain clear documentation of analyses, results, and insights for internal stakeholders.
Market Research: Conduct competitive and market research to understand customer needs, market trends, and industry best practices.
Product Strategy Support: Collaborate with product managers to develop and refine product strategies based on data and market insights.
Reporting and Dashboards: Create regular reports, dashboards, and visualizations to track product performance and key metrics.
Customer Insights: Work closely with customer-facing teams to gather and analyze feedback from customers, and turn this into actionable product improvements.
A/B Testing & Experimentation: Design and analyze A/B tests to optimize product features, user experience, and conversion rates.
Cross-Functional Collaboration: Work with engineering, design, marketing, and sales teams to support product launches, monitor performance, and gather feedback.
Data-Driven Decision Making: Assist in prioritizing product features and improvements based on data, and help define success metrics for each feature.
Documentation & Reporting: Maintain clear documentation of analyses, results, and insights for internal stakeholders.