Customer Data Analyst (Customer Segmentation) (all genders)

at  Zalando

THE ROLE & THE TEAM

You work for the Customer Analytics team in Zalando’s Markets organization, which enables data driven business strategies for 20+ countries. Through our customer focussed analytics and segmentations we put our customers at the center of every marketing and retail decision. As a (Senior) Customer Data Analyst in our Customer Segmentation Team you are the closest link to our customer: You build a deep understanding of our customer base by developing and analyzing different customer segments based on their purchasing behavior, interests, customer value and onsite activities. You will transform data and segmentations into actionable insights and recommendations that drive strategic decisions and customer retention.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

• Develop and analyze customer segmentations and audiences, support targeting and steering initiatives to drive customer value and retention. Collaborate with data scientists and engineers to optimize and productionalize your segmentations and audience selections.
• Design, conduct and evaluate A/B tests to optimize your segmentations and audiences according to their use case. Recommend testing strategies to optimize targeted campaigns, campaign efficiency and ultimately customer value and retention. Translate complex questions into sound analytical tasks, autonomously planning large scale projects.
• Collaborate with business stakeholders to identify new strategic opportunities and recommend actions supporting the customer strategy. Present your findings and work closely with business stakeholders and product owners to operationalize your recommendations.
• Drive data mindset in the team and provide senior guidance to your team members in terms of methodology & technology to raise the bar within the department. Collaborate with other analysts, data scientists, engineers and commercial colleagues to untap new sources of data and know-how.
• Independently manage analytical projects, identifying efficiency opportunities and supporting decision-making with insights from descriptive and inferential analysis.
• Conduct knowledge-sharing sessions, support junior colleagues, and contribute to internal events and the hiring process.