Key Responsibilities- Design A/B and longitudinal test plans taking into account control groups, statistical significance, audience size, incrementality, etc.
- Write custom queries or deep-dive analysis across multiple data sources to answer ad-hoc business questions that enhance CRM marketing strategies, create insight, or troubleshoot performance issues.
- Support team in building comprehensive reports and dashboards of all relevant CRM KPIs to track and socialize performance across individual and evergreen/lifecycle campaigns.
- Employ data-driven insights and an iterative approach to optimize campaign builds, content modules, segmentation and testing constructs.
- Leverage data to provide insights and identify opportunities to further develop segmentation and targeting initiatives.
- Define & building sales and performance attribution models.
- Manage CRM data architecture and partner cross-functionally to build, maintain and optimize all CRM data pipelines.
- Continuously monitor CRM data hygiene inputs from data warehouse/data sharing tools and outputs to end users, ensuring fluctuations do not fall outside of standard deviations.
- Own data activation roadmap and requirements to advance real-time, cross-channel and personalization use-cases.
- Partner with Data Science team to help define data inputs and logic within one-to-one customer modeling.
- Work cross functionally to develop an in-depth understanding of the customer journey and identify churn behaviors that allow for us to implement strategies to maximize customer retention.
- Regular, dependable attendance and punctuality.
- Strong analytics skills and working knowledge of data visualization/reporting tools, preferably Tableau.
- Comfortable using SQL to structure queries from scratch to extract and manipulate data.
- Able to work with little SQL oversight, needs to be advanced enough self-sufficient.
- Ability to review large amounts of data and provide strategic and actionable inferences and recommendations based on patterns and trends.
- Interest and knowledge of experimental design, A/B testing, and conversion rate optimization.
- Understanding of statistical modeling and quantitative analysis techniques.
- Experience using standard web analytics tools (e.g. Adobe Analytics, Google Analytics) is a plus.
- Must be proficient in Excel.
- Self-motivated, results driven, have strong attention to detail & comfortable with ambiguity.
- Flexible and adaptive, enjoys an ever-changing, dynamic work environment.
- Intellectual curiosity and willingness to accept feedback.
- Not afraid to fail, gain insights and apply to future.
